High resolution thin multi-aperture imaging systems

- Corephotonics Ltd.

A multi-aperture imaging system comprising a first camera with a first sensor that captures a first image and a second camera with a second sensor that captures a second image, the two cameras having either identical or different FOVs. The first sensor may have a standard color filter array (CFA) covering one sensor section and a non-standard color CFA covering another. The second sensor may have either Clear or standard CFA covered sections. Either image may be chosen to be a primary or an auxiliary image, based on a zoom factor. An output image with a point of view determined by the primary image is obtained by registering the auxiliary image to the primary image.

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Description
CROSS REFERENCE TO RELATED APPLICATIONS

This application is a Continuation application of U.S. patent application Ser. No. 14/386,823 (now allowed), which was a National Phase application from PCT patent application PCT/IB2013/060356 which claimed priority from U.S. Provisional Patent Application No. 61/730,570 having the same title and filed Nov. 28, 2012, the latter incorporated herein by reference in its entirety.

This broadening reissue application is a continuation of U.S. patent application Ser. No. 16/383,618, filed Apr. 14, 2019, which is a reissue application of U.S. patent application Ser. No. 15/375,090, filed Dec. 11, 2016, now U.S. Pat. No. 9,876,952, which is a continuation of U.S. patent application Ser. No. 14/386,823, filed Apr. 22, 2014, now U.S. Pat. No. 9,538,152, which was a National Phase application from PCT application PCT/IB2013/060356 which claimed priority from U.S. Provisional Patent Application No. 61/730,570 having the same title and filed Nov. 28, 2012, the latter incorporated herein by reference in its entirety. The following three co-pending applications are also continuation reissue applications of U.S. patent application Ser. No. 16/383,618, filed Apr. 14, 2019; U.S. patent application Ser. No. 16/384,140, filed Apr. 15, 2019, U.S. patent application Ser. No. 16/384,197, filed Apr. 15, 2019, and U.S. patent application Ser. No. 16/419,604, filed May 22, 2019.

FIELD

Embodiments disclosed herein relate in general to multi-aperture imaging (“MAI”) systems (where “multi” refers to two or more apertures) and more specifically to thin MAI systems with high color resolution and/or optical zoom.

BACKGROUND

Small digital cameras integrated into mobile (cell) phones, personal digital assistants and music players are becoming ubiquitous. Each year, mobile phone manufacturers add more imaging features to their handsets, causing these mobile imaging devices to converge towards feature sets and image quality that customers expect from stand-alone digital still cameras. Concurrently, the size of these handsets is shrinking, making it necessary to reduce the total size of the camera accordingly while adding more imaging features. Optical Zoom is a primary feature of many digital still cameras but one that mobile phone cameras usually lack, mainly due to camera height constraints in mobile imaging devices, cost and mechanical reliability.

Mechanical zoom solutions are common in digital still cameras but are typically too thick for most camera phones. Furthermore, the F/# (“F number) in such systems typically increases with the zoom factor (ZF) resulting in poor light sensitivity and higher noise (especially in low-light scenarios). In mobile cameras, this also results in resolution compromise, due to the small pixel size of their image sensors and the diffraction limit optics associated with the F/#.

One way of implementing zoom in mobile cameras is by over-sampling the image and cropping and interpolating it in accordance with the desired ZF. While this method is mechanically reliable, it results in thick optics and in an expensive image sensor due to the large number of pixels associated therewith. As an example, if one is interested in implementing a 12 Megapixel camera with X3 ZF, one needs a sensor of 108 Megapixels.

Another way of implementing zoom, as well as increasing the output resolution, is by using a dual-aperture imaging (“DAI”) system. In its basic form, a DAI system includes two optical apertures which may be formed by one or two optical modules, and one or two image sensors (e.g., CMOS or CCD) that grab the optical image or images and convert the data into the electronic domain, where the image can be processed and stored.

The design of a thin MAI system with improved resolution requires a careful choice of parameters coupled with advanced signal processing algorithms to support the output of a high quality image. Known MAI systems, in particular ones with short optical paths, often trade-off functionalities and properties, for example zoom and color resolution, or image resolution and quality for camera module height. Therefore, there is a need for, and it would be advantageous to have thin MAI systems that produce an image with high resolution (and specifically high color resolution) together with zoom functionality.

Moreover, known signal processing algorithms used together with existing MAI systems often further degrade the output image quality by introducing artifacts when combining information from different apertures. A primary source of these artifacts is the image registration process, which has to find correspondences between the different images that are often captured by different sensors with different color filter arrays (CFAs). There is therefore a need for, and it would be advantageous to have an image registration algorithm that is more robust to the type of CFA used by the cameras and which can produce better correspondence between images captured by a multi-aperture system.

SUMMARY

Embodiments disclosed herein teach the use of multi-aperture imaging systems to implement thin cameras (with short optical paths of less than about 9 mm) and/or to realize optical zoom systems in such thin cameras. Embodiments disclosed herein further teach new color filter arrays that optimize the color information which may be achieved in a multi-aperture imaging system with or without zoom. In various embodiments, a MAI system disclosed herein includes at least two sensors or a single sensor divided into at least two areas. Hereinafter, the description refers to “two sensors”, with the understanding that they may represent sections of a single physical sensor (imager chip). Exemplarily, in a dual-aperture imaging system, a left sensor (or left side of a single sensor) captures an image coming from a first aperture while a right sensor (or right side of a single sensor) captures an image coming from a second aperture. In various embodiments disclosed herein, one sensor is a “Wide” sensor while another sensor is a “Tele” sensor, see e.g. FIG. 1A. The Wide sensor includes either a single standard CFA or two different CFAs: a non-standard CFA with higher color sampling rate positioned in an “overlap area” of the sensor (see below description of FIG. 1B) and a standard CFA with a lower color sampling rate surrounding the overlap area. When including a single standard CFA, the CFA may cover the entire Wide sensor area. A “standard CFA” may include a RGB (Bayer) pattern or a non-Bayer pattern such as RGBE, CYYM, CYGM, RGBW#1, RGBW#2 or RGBW#3. Thus, reference may be made to “standard Bayer” or “standard non-Bayer” patterns or filters. As used herein, “non-standard CFA” refers to a CFA that is different in its pattern that CFAs listed above as “standard”. Exemplary non-standard CFA patterns may include repetitions of a 2×2 micro-cell in which the color filter order is RR-BB, RB-BR or YC-CY where Y=Yellow=Green+Red, C=Cyan=Green+Blue; repetitions of a 3×3 micro-cell in which the color filter order is GBR-RGB-BRG; and repetitions of a 6×6 micro-cell in which the color filter order is RBBRRB-RWRBWB-BBRBRR-RRBRBB-BWBRWR-BRRBBR, or BBGRRG-RGRBGB-GBRGRB-RRGBBG-BGBRGR-GRBGBR, or RBBRRB-RGRBGB-BBRBRR-RRBRBB-BGBRGR-BRRBBR, or, RBRBRB-BGBRGR-RBRBRB-BRBRBR-RGRBGB-BRBRBR.

The Tele sensor may be a Clear sensor (i.e. a sensor without color filters) or a standard CFA sensor. This arrangement of the two (or more than two) sensors and of two (or more than two) Wide and Tele “subset cameras” (or simply “subsets”) related to the two Wide and Tele subsets. Each sensor provides a separate image (referred to respectively as a Wide image and a Tele image), except for the case of a single sensor, where two images are captured (grabbed) by the single sensor (example above). In some embodiments, zoom is achieved by fusing the two images, resulting in higher color resolution that approaches that of a high quality dual-aperture zoom camera. Some thin MAI systems disclosed herein therefore provide zoom, super-resolution, high dynamic range and enhanced user experience.

In some embodiments, in order to reach optical zoom capabilities, a different magnification image of the same scene is grabbed by each subset, resulting in field of view (FOV) overlap between the two subsets. In some embodiments, the two subsets have the same zoom (i.e. same FOV). In some embodiments, the Tele subset is the higher zoom subset and the Wide subset is the lower zoom subset. Post processing is applied on the two images grabbed by the MAI system to fuse and output one fused (combined) output zoom image processed according to a user ZF input request. In some embodiments, the resolution of the fused image may be higher than the resolution of the Wide/Tele sensors. As part of the fusion procedure, up-sampling may be applied on the Wide image to scale it to the Tele image.

In an embodiment there is provided a multi-aperture imaging system comprising a first camera subset that provides a first image, the first camera subset having a first sensor with a first plurality of sensor pixels covered at least in part with a non-standard CFA, the non-standard CFA used to increase a specific color sampling rate relative to a same color sampling rate in a standard CFA; a second camera subset that provides a second image, the second camera subset having a second sensor with a second plurality of sensor pixels either Clear or covered with a standard CFA; and a processor configured to process the first and second images into a combined output image.

In some embodiments, the first and the second camera subsets have identical FOVs and the non-standard CFA may cover an overlap area that includes all the pixels of first sensor, thereby providing increased color resolution. In some such embodiments, the processor is further configured to, during the processing of the first and second images into a combined output image, register respective first and second Luma images obtained from the first and second images, the registered first and second Luma images used together with color information to form the combined output image. In an embodiment, the registration includes finding a corresponding pixel in the second Luma image for each pixel in the first Luma image, whereby the output image is formed by transferring information from the second image to the first image. In another embodiment, the registration includes finding a corresponding pixel in the first Luma image for each pixel in the second Luma image, whereby the output image is formed by transferring information from the first image to the second image.

In some embodiments, the first camera subset has a first FOV, the second camera subset has a second, smaller FOV than the first FOV, and the non-standard CFA covers an overlap area on the first sensor that captures the second FOV, thereby providing both optical zoom and increased color resolution. In some such embodiments, the processor is further configured to, during the processing of the first and second images into a combined output image and based on a ZF input, register respective first and second Luma images obtained from the first and second images, the registered first and second Luma images used together with color information to form the combined output image. For a ZF input that defines an FOV greater than the second FOV, the registration includes finding a corresponding pixel in the second Luma image for each pixel in the first Luma image and the processing includes forming the output image by transferring information from the second image to the first image. For a ZF input that defines an FOV smaller than or equal to the second FOV, the registration includes finding a corresponding pixel in the first Luma image for each pixel in the second Luma image, and the processing includes forming the output image by transferring information from the first image to the second image.

In an embodiment there is provided a multi-aperture imaging system comprising a first camera subset that provides a first image, the first camera subset having a first sensor with a first plurality of sensor pixels covered at least in part with a standard CFA; a second camera subset that provides a second image, the second camera subset having a second sensor with a second plurality of sensor pixels either Clear or covered with a standard CFA; and a processor configured to register first and second Luma images obtained respectively from the first and second images and to process the registered first and second Luma images together with color information into a combined output image.

In some embodiments, the first and the second camera subsets have identical first and second FOVs. In some such embodiments, the registration includes finding a corresponding pixel in the second Luma image for each pixel in the first Luma image and the processing includes forming the output image by transferring information from the second image to the first image. In other such embodiments, the registration includes finding a corresponding pixel in the first Luma image for each pixel in the second Luma image and the processing includes forming the output image by transferring information from the first image to the second image.

In some embodiments, the first camera subset has a first FOV, the second camera subset has a second, smaller FOV than the first FOV, and the processor is further configured to register the first and second Luma images based on a ZF input. For a ZF input that defines an FOV greater than the second FOV, the registration includes finding a corresponding pixel in the second Luma image for each pixel in the first Luma image and the processing includes forming the output image by transferring information from the second image to the first image. For a ZF input that defines an FOV smaller than or equal to the second FOV, the registration includes finding a corresponding pixel in the first Luma image for each pixel in the second Luma image, and the processing includes forming the output image by transferring information from the first image to the second image.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting examples of embodiments disclosed herein are described below with reference to figures attached hereto that are listed following this paragraph. The drawings and descriptions are meant to illuminate and clarify embodiments disclosed herein, and should not be considered limiting in any way.

FIG. 1A shows schematically a block diagram illustrating a dual-aperture zoom imaging system disclosed herein;

FIG. 1B shows an example of an image captured by the Wide sensor and the Tele sensor while illustrating the overlap area on the Wide sensor;

FIG. 2 shows schematically an embodiment of a Wide sensor that may be implemented in a dual-aperture zoom imaging system disclosed herein;

FIG. 3 shows schematically another embodiment of a Wide camera sensor that may be implemented in a dual-aperture zoom imaging system disclosed herein;

FIG. 4 shows schematically yet another embodiment of a Wide camera sensor that may be implemented in a dual-aperture zoom imaging system disclosed herein;

FIG. 5 shows schematically yet another embodiment of a Wide camera sensor that may be implemented in a dual-aperture zoom imaging system disclosed herein;

FIG. 6 shows schematically yet another embodiment of a Wide camera sensor that may be implemented in a dual-aperture zoom imaging system disclosed herein;

FIG. 7 shows schematically yet another embodiment of a Wide camera sensor that may be implemented in a dual-aperture zoom imaging system disclosed herein;

FIG. 8 shows schematically yet another embodiment of a Wide camera sensor that may be implemented in a dual-aperture zoom imaging system disclosed herein;

FIG. 9 shows schematically yet another embodiment of a Wide camera sensor that may be implemented in a dual-aperture zoom imaging system disclosed herein;

FIG. 10 shows a schematically in a flow chart an embodiment of a method disclosed herein for acquiring and outputting a zoom image;

FIG. 11A shows exemplary images captured by a triple aperture zoom imaging system disclosed herein;

FIG. 11B illustrates schematically the three sensors of the triple aperture imaging system of FIG. 11A.

 DETAILED DESCRIPTION

Embodiments disclosed herein relate to multi-aperture imaging systems that include at least one Wide sensor with a single CFA or with two different CFAs and at least one Tele sensor. The description continues with particular reference to dual-aperture imaging systems that include two (Wide and Tele) subsets with respective sensors. A three-aperture imaging system is described later with reference to FIGS. 11A-11B.

The Wide sensor includes an overlap area (see description of FIG. 1B) that captures the Tele FOV. The overlap area may cover the entire Wide sensor or only part of the sensor. The overlap area may include a standard CFA or a non-standard CFA. Since the Tele image is optically magnified compared to the Wide image, the effective sampling rate of the Tele image is higher than that of the Wide image. Thus, the effective color sampling rate in the Wide sensor is much lower than the Clear sampling rate in the Tele sensor. In addition, the Tele and Wide images fusion procedure (see below) requires up-scaling of the color data from the Wide sensor. Up-scaling will not improve color resolution. In some applications, it is therefore advantageous to use a non-standard CFA in the Wide overlap area that increases color resolution for cases in which the Tele sensor includes only Clear pixels. In some embodiments in which the Tele sensor includes a Bayer CFA, the Wide sensor may have a Bayer CFA in the overlap area. In such embodiments, color resolution improvement depends on using color information from the Tele sensor in the fused output image.

FIG. 1A shows schematically a block diagram illustrating a dual-aperture zoom imaging (“DAZI”) system 100 disclosed herein. System 100 includes a dual-aperture camera 102 with a Wide subset 104 and a Tele subset 106 (each subset having a respective sensor), and a processor 108 that fuses two images, a Wide image obtained with the Wide subset and a Tele image obtained with the Tele subset, into a single fused output image according to a user-defined “applied” ZF input or request. The ZF is input to processor 108. The Wide sensor may include a non-standard CFA in an overlap area illustrated by 110 in FIG. 1B. Overlap area 110 is surrounded by a non-overlap area 112 with a standard CFA (for example a Bayer pattern). FIG. 1B also shows an example of an image captured by both Wide and Tele sensors. Note that “overlap” and “non-overlap” areas refer to parts of the Wide image as well as to the CFA arrangements of the Wide sensor. The overlap area may cover different portions of a Wide sensor, for example half the sensor area, a third of the sensor area, a quarter of the sensor area, etc. A number of such Wide sensor CFA arrangements are described in more detail with reference to FIGS. 2-9. The non-standard CFA pattern increases the color resolution of the DAZI system.

The Tele sensor may be Clear (providing a Tele Clear image scaled relative to the Wide image) or may include a standard (Bayer or non-Bayer) CFA. It in the latter case, it is desirable to define primary and auxiliary sensors based on the applied ZF. If the ZF is such that the output FOV is larger than the Tele FOV, the primary sensor is the Wide sensor and the auxiliary sensor is the Tele sensor. If the ZF is such that the output FOV is equal to, or smaller than the Tele FOV, the primary sensor is the Tele sensor and the auxiliary sensor is the Wide sensor. The point of view defined by the output image is that of the primary sensor.

FIG. 2 shows schematically an embodiment of a Wide sensor 200 that may be implemented in a DAZI system such as system 100. Sensor 200 has a non-overlap area 202 with a Bayer CFA and an overlap area 204 covered by a non-standard CFA with a repetition of a 4×4 micro-cell in which the color filter order is BBRR-RBBR-RRBB-BRRB. In this figure, as well as in FIGS. 3-9, “Width 1” and “Height 1” refer to the full Wide sensor dimension. “Width 2” and “Height 2” refer to the dimensions of the Wide sensor overlap area. Note that in FIG. 2 (as in following FIGS. 3-5 and 7, 8) the empty row and column to the left and top of the overlap area are for clarity purposes only, and that the sensor pixels follow there the pattern of the non-overlap area (as shown in FIG. 6). In overlap area 204, R and B are sampled at ½0.5 Nyquist frequency in the diagonal (left to right) direction with 2 pixel intervals instead of at ½ Nyquist frequency in a standard Bayer pattern.

FIG. 3 shows schematically an embodiment of a Wide sensor 300 that may be implemented in a DAZI system such as system 100. Sensor 300 has a non-overlap area 302 with a Bayer CFA and an overlap area 304 covered by a non-standard CFA with a repetition of a 2×2 micro-cell in which the color filter order is BR-RB. In the overlap area, R and B are sampled at ½0.5 Nyquist frequency in both diagonal directions.

FIG. 4 shows schematically an embodiment of a Wide sensor 400 that may be implemented in a DAZI system such as system 100. Sensor 400 has a non-overlap area 402 with a Bayer CFA and an overlap area 404 covered by a non-standard CFA with a repetition of a 2×2 micro-cell in which the color filter order is YC-CY, where Y=Yellow=Green+Red, C=Cyan=Green+Blue. As a result, in the overlap area, R and B are sampled at ½0.5 Nyquist frequency in a diagonal direction. The non-standard CFA includes green information for registration purposes. This allows for example registration between the two images where the object is green, since there is green information in both sensor images.

FIG. 5 shows schematically an embodiment of a Wide sensor 500 that may be implemented in a DAZI system such as system 100. Sensor 500 has a non-overlap area 502 with a Bayer CFA and an overlap area 504 covered by a non-standard CFA with a repetition of a 6×6 micro-cell in which the color filter order is RBBRRB-RWRBWB-BBRBRR-RRBRBB-BWBRWR-BRRBBR, where “W” represents White or Clear pixels. In the overlap area, R and B are sampled at a higher frequency than in a standard CFA. For example, in a Bayer pixel order, the Red average sampling rate (“Rs”) is 0.25 (sampled once for every 4 pixels). In the overlap area pattern, Rs is 0.44.

FIG. 6 shows schematically an embodiment of a Wide sensor 600 that may be implemented in a DAZI system such as system 100. Sensor 600 has a non-overlap area 602 with a Bayer CFA and an overlap area 604 covered by a non-standard CFA with a repetition of a 6×6 micro-cell in which the color filter order is BBGRRG-RGRBGB-GBRGRB-RRGBBG-BGBRGR-GRBGBR. In the overlap area, R and B are sampled at a higher frequency than in a standard CFA. For example, in the overlap area pattern, Rs is 0.33 vs. 0.25 in a Bayer pixel order.

FIG. 7 shows schematically an embodiment of a Wide sensor 700 that may be implemented in a DAZI system such as system 100. Sensor 700 has a non-overlap area 702 with a Bayer CFA and an overlap area 704 covered by a non-standard CFA with a repetition of a 3×3 micro-cell in which the color filter order is GBR-RGB-BRG. In the overlap area, R and B are sampled at a higher frequency than in a standard CFA. For example, in the overlap area pattern, Rs is 0.33 vs. 0.25 in a Bayer pixel order.

FIG. 8 shows schematically an embodiment of a Wide sensor 800 that may be implemented in a DAZI system such as system 100. Sensor 800 has a non-overlap area 802 with a Bayer CFA and an overlap area 804 covered by a non-standard CFA with a repetition of a 6×6 micro-cell in which the color filter order is RBBRRB-RGRBGB-BBRBRR-RRBRBB-BGBRGR-BRRBBR. In the overlap area, R and B are sampled at a higher frequency than in a standard CFA. For example, in the overlap area pattern, Rs is 0.44 vs. 0.25 in a Bayer pixel order.

FIG. 9 shows schematically an embodiment of a Wide sensor 900 that may be implemented in a DAZI system such as system 100. Sensor 900 has a non-overlap area 902 with a Bayer CFA and an overlap area 904 covered by a non-standard CFA with a repetition of a 6×6 micro-cell in which the color filter order is RBRBRB-BGBRGR-RBRBRB-BRBRBR-RGRBGB-BRBRBR. In the overlap area, R and B are sampled at a higher frequency than in a standard CFA. For example, in the overlap area pattern, Rs is 0.44 vs. 0.25 in a Bayer pixel order.

Processing Flow

In use, an image is acquired with imaging system 100 and is processed according to steps illustrated in a flowchart shown in FIG. 10. In step 1000, demosaicing is performed on the Wide overlap area pixels (which refer to the Tele image FOV) according to the specific CFA pattern. If the CFA in the Wide overlap area is a standard CFA, a standard demosaicing process may be applied to it. If the CFA in the Wide overlap area is non-standard CFA, the overlap and non-overlap subsets of pixels may need different demosaicing processes. That is, the Wide overlap area may need a non-standard demosaicing process and the Wide non-overlap area may need a standard demosaicing process. Exemplary and non-limiting non-standard demosaicing interpolations for the overlap area of each of the Wide sensors shown in FIGS. 2-9 are given in detail below. The aim of the demosaicing is to reconstruct missing colors in each pixel. Demosaicing is applied also to the Tele sensor pixels if the Tele sensor is not a Clear only sensor. This will result in a Wide subset color image where the colors (in the overlap area) hold higher resolution than those of a standard CFA pattern. In step 1002, the Tele image is registered (mapped) into the Wide image. The mapping includes finding correspondences between pixels in the two images. In step 1002, actual registration is performed on luminance Tele and Wide images (respectively LumaTele and Lumawide) calculated from the pixel information of the Tele and Wide cameras. These luminance images are estimates for the scene luminance as captured by each camera and do not include any color information. If the Wide or Tele sensors have CFAs, the calculation of the luminance images is performed on the respective demosaiced images. The calculation of the Wide luminance image varies according to the type of non-standard CFA used in the Wide overlap area. If the CFA permits calculation of a full RGB demosaiced image, the luminance image calculation is straightforward. If the CFA is such that it does not permit calculation of a full RGB demosaiced image, the luminance image is estimated from the available color channels. If the Tele sensor is a Clear sensor, the Tele luminance image is just the pixel information. Performing the registration on luminance images has the advantage of enabling registration between images captured by sensors with different CFAs or between images captured by a standard CFA or non-standard CFA sensor and a standard CFA or Clear sensor and avoiding color artifacts that may arise from erroneous registration.

In step 1004, the data from the Wide and Tele images is processed together with the registration information from step 1002 to form a high quality output zoom image. In cases where the Tele sensor is a Clear only sensor, the high resolution luminance component is taken from the Tele sensor and color resolution is taken from the Wide sensor. In cases where the Tele sensor includes a CFA, both color and luminance data are taken from the Tele subset to form the high quality zoom image. In addition, color and luminance data is taken from the Wide subset.

Exemplary Process for Fusing a Zoom Image

1. Special Demosaicing

In this step, the Wide image is interpolated to reconstruct the missing pixel values. Standard demosaicing is applied in the non-overlap area. If the overlap area includes a standard CFA, standard demosaicing is applied there as well. If the overlap area includes a non-standard CFA, a special demosaicing algorithm is applied, depending on the CFA pattern used. In addition, in case the Tele sensor has a CFA, standard demosaicing is applied to reconstruct the missing pixel values in each pixel location and to generate a full RGB color image.

2. Registration Preparation

    • Tele image: a luminance image LumaTele is calculated from the Tele sensor pixels. If the Tele subset has a Clear sensor, LumaTele is simply the sensor pixels data. If the Tele subset has a standard CFA, LumaTeleis calculated from the demosaiced Tele image.
    • Wide image: as a first step, in case the Wide overlap CFA permits estimating the luminance component of the image, the luminance component is calculated from the demosaiced Wide image, LumaWide. If the CFA is one of those depicted in FIGS. 4-9, a luminance image is calculated first. If the CFA is one of the CFAs depicted in FIG. 2 or FIG. 3, a luminance image is not calculated. Instead, the following registration step is performed between a weighted average of the demosaiced channels of the Wide image and LumaTele. For convenience, this weighted average image is also denoted LumaWide. For example, if the Wide sensor CFA in the overlap region is as shown in FIG. 2, the demosaiced channels RWide and BWide are averaged to create LumaWide according to LumaWide=(f1*RWide+f2*BWide/(f1+f2), where f1 may be f1=1 and f2 may be f2=1.
    • Low-pass filtering is applied on the Tele luminance image in order to match its spatial frequency content to that of the LumaWide image. This improves the registration performance, as after low-pass filtering the luminance images become more similar. The calculation is LumaTele→Low pass filter→LumaTeleLP, where “LP” denotes an image after low pass filtering.
      3. Registration of LumaWide and LumaTeleLP

This step of the algorithm calculates the mapping between the overlap areas in the two luminance images. The registration step does not depend on the type of CFA used (or the lack thereof), as it is applied on luminance images. The same registration step can therefore be applied on Wide and Tele images captured by standard CFA sensors, as well as by any combination of CFAs or Clear sensor pixels disclosed herein. The registration process chooses either the Wide image or the Tele image to be a primary image. The other image is defined as an auxiliary image. The registration process considers the primary image as the baseline image and registers the overlap area in the auxiliary image to it, by finding for each pixel in the overlap area of the primary image its corresponding pixel in the auxiliary image. The output image point of view is determined according to the primary image point of view (camera angle). Various correspondence metrics could be used for this purpose, among which are a sum of absolute differences and correlation.

In an embodiment, the choice of the Wide image or the Tele image as the primary and auxiliary images is based on the ZF chosen for the output image. If the chosen ZF is larger than the ratio between the focal-lengths of the Tele and Wide cameras, the Tele image is set to be the primary image and the Wide image is set to be the auxiliary image. If the chosen ZF is smaller than or equal to the ratio between the focal-lengths of the Tele and Wide cameras, the Wide image is set to be the primary image and the Tele image is set to be the auxiliary image. In another embodiment independent of a zoom factor, the Wide image is always the primary image and the Tele image is always the auxiliary image. The output of the registration stage is a map relating Wide image pixels indices to matching Tele image pixels indices.

4. Combination into a High Resolution Image

In this final step, the primary and auxiliary images are used to produce a high resolution image. One can distinguish between several cases:

a. If the Wide image is the primary image, and the Tele image was generated from a Clear sensor, LumaWide is calculated and replaced or averaged with LumaTele in the overlap area between the two images to create a luminance output image, matching corresponding pixels according to the registration map LumaOut=c1*LumaWide+c2*LumaTele. The values of c1 and c2 may change between different pixels in the image. Then, RGB values of the output are calculated from LumaOut and RWide, GWide, and BWide.

b. If the Wide image is the primary image and the Tele image was generated from a CFA sensor, LumaTele is calculated and is combined with LumaWide in the overlap area between the two images, according to the flow described in 4a.

c. If the Tele image is the primary image generated from a Clear sensor, the RGB values of the output are calculated from the LumaTele image and RWide, GWide, and BWide (matching pixels according to the registration map).

d. If the Tele image is the primary image generated from a CFA sensor, the RGB values of the output (matching pixels according to the registration map) are calculated either by using only the Tele image data, or by also combining data from the Wide image. The choice depends on the zoom factor.

Certain portions of the registered Wide and Tele images are used to generate the output image based on the ZF of the output image. In an embodiment, if the ZF of the output image defines a FOV smaller than the Tele FOV, the fused high resolution image is cropped to the required field of view and digital interpolation is applied to scale up the image to the required output image resolution.

Exemplary and Non-Limiting Pixel Interpolations Specifications for the Overlap Area

FIG. 2

B11 B12 R13 R21 B22 B23 R31 R32 B33

In order to reconstruct the missing R22 pixel, we perform R22=(R31+R13)/2. The same operation is performed for all missing Blue pixels.
FIG. 3

R11 B12 R13 B21 R22 B23 R31 B32 R33

In order to reconstruct the missing B22 pixel, we perform B22=(B12+B21+B32+B23)/4. The same operation is performed for all missing Red pixels.
FIG. 4

Y11 C12 Y13 C21 Y22 C23 Y31 C32 Y33

In order to reconstruct the missing C22 pixel, we perform C22=(C12+C21+C32+C23)/4. The same operation is performed for all missing Yellow pixels.
FIG. 5
Case 1: W is Center Pixel

R11 B12 B13 R21 W22 R23 B31 B32 R33

In order to reconstruct the missing 22 pixels, we perform the following:

B22=(B12+B32)/2

R22=(R21+R23)/2

G22=(W22−R22−B22) (assuming that W includes the same amount of R, G and B colors).

Case 2: R22 is Center Pixel

B11 B12 R13 R14 W21 R22 B23 W24 B31 R32 B33 R34

B22=(B11 +R33)/2

In order to reconstruct the missing 22 pixels, we perform the following:

W22=(2*W21+W24)/3

G22=(W22−R22−B22) (assuming that W contains the same amount of R, G and B colors). The same operation is performed for Blue as the center pixel.

FIG. 6

B11 B12 G13 R14 R21 G22 R23 B24 G31 B32 R33 G34 R41 R42 G43 B44

In order to reconstruct the missing 22 pixels, we perform the following:

B22=(B12+B32)/2

R22=(R21+R23)/2.

In order to reconstruct the missing 32 pixels, we perform the following:

G32=(2*G31+2*G22+G43)/5

R32=(R41+2*R42+2*R33+R23+R21)/7.

FIG. 7

G11 B12 R13 G14 R21 G22 B23 R24 B31 R32 G33 B34 G41 B42 R43 G44

In order to reconstruct the missing 22 pixels, we perform the following:

B22=(2*B12+2*B23+B31)/5

R22=(2*R21+2*R32+R13)/5

and similarly for all other missing pixels.

FIG. 8

R11 B12 B13 R14 R21 G22 R23 B24 B31 B32 R33 B34 R41 R42 B43 R44 B51 G52 B53 R54

In order to reconstruct the missing 22 pixels, we perform the following:

B22=(2*B12+2*B32+B13)/5

R22=(2*R21+2*R23+R11)/5.

In order to reconstruct the missing 32 pixels, we perform the following:

G32=(2*G22+G52)/3

R32=(2*R33+2*R42+R41+R21+R23)/7.

FIG. 9

R11 B12 R13 B14 B21 G22 B23 R24 R31 B32 R33 B34 B41 R42 B43 R44 R51 G52 R53 B54

In order to reconstruct the missing 22 pixels, we perform the following:

B22=(B12+B32+B23+B21)/4

R22=(R11+R13+R31+R33)/4.

In order to reconstruct the missing 32 pixels, we perform the following:

G32=(2*G22+G52)/3

R32=(R42+R31+R33)/3.

Triple-Aperture Zoom Imaging System with Improved Color Resolution

As mentioned, a multi-aperture zoom or non-zoom imaging system disclosed herein may include more than two apertures. A non-limiting and exemplary embodiment 1100 of a triple-aperture imaging system is shown in FIGS. 11A-11B. System 1100 includes a first Wide subset camera 1102 (with exemplarily X1), a second Wide subset camera (with exemplarily X1.5, and referred to as a “Wide-Tele” subset) and a Tele subset camera (with exemplarily X2). FIG. 11A shows exemplary images captured by imaging system 1100, while FIG. 11B illustrates schematically three sensors marked 1102, 1104 and 1106, which belong respectively to the Wide, Wide-Tele and Tele subsets. FIG. 11B also shows the CFA arrangements in each sensor: sensors 1102 and 1104 are similar to Wide sensors described above with reference to any of FIGS. 2-9, in the sense that they include an overlap area and a non-overlap area. The overlap area includes a non-standard CFA. In both Wide sensors, the non-overlap area may have a Clear pattern or a standard CFA. Thus, neither Wide subset is solely a Clear channel camera. The Tele sensor may be Clear or have a standard Bayer CFA or a standard non-Bayer CFA. In use, an image is acquired with imaging system 1100 and processed as follows: demosaicing is performed on the overlap area pixels of the Wide and Wide-Tele sensors according to the specific CFA pattern in each overlap area. The overlap and non-overlap subsets of pixels in each of these sensors may need different demos aicing. Exemplary and non-limiting demosaicing specifications for the overlap area for Wide sensors shown in FIGS. 2-9 are given above. The aim is to reconstruct the missing colors in each and every pixel. In cases in which the Tele subset sensor is not Clear only, demosaicing is performed as well. The Wide and Wide-Tele subset color images acquired this way will have colors (in the overlap area) holding higher resolution than that of a standard CFA pattern. Then, the Tele image acquired with the Tele sensor is registered (mapped) into the respective Wide image. The data from the Wide, Wide-Tele and Tele images is then processed to form a high quality zoom image. In cases where the Tele subset is Clear only, high Luma resolution is taken from the Tele sensor and color resolution is taken from the Wide sensor. In cases where the Tele subset includes a CFA, both color and Luma resolution is taken from the Tele subset. In addition, color resolution is taken from the Wide sensor. The resolution of the fused image may be higher than the resolution of both sensors.

While this disclosure has been described in terms of certain embodiments and generally associated methods, alterations and permutations of the embodiments and methods will be apparent to those skilled in the art. For example, multi-aperture imaging systems with more than two Wide or Wide-Tele subsets (and sensors) or with more than one Tele subset (and sensor) may be constructed and used according to principles set forth herein. Similarly, non-zoom multi-aperture imaging systems with more than two sensors, at least one of which has a non-standard CFA, may be constructed and used according to principles set forth herein. The disclosure is to be understood as not limited by the specific embodiments described herein, but only by the scope of the appended claims.

Claims

1. A multi-aperture imaging system comprising: a) a first camera that provides a first camera image, the first camera having a first sensor with a first plurality of sensor pixels covered at least in part with a non-standard color filter array (CFA) used to increase a specific color sampling rate relative to a same color sampling rate in a standard CFA, wherein the nonstandard CFA includes a repetition of a n×n micro-cell where n=4 and wherein each micro-cell includes a BBRR-RBBR-RRBB-BRRB color filter order; b) a second camera that provides a second camera image, the second camera having a second sensor with a second plurality of sensor pixels, the second plurality of sensor pixels being either Clear or covered with a standard CFA, wherein the second camera image has an overlap area with the first camera image; and c) a processor configured to process the first and second camera images into a fused output image, wherein in the overlap area pixels of the second camera image are registered with corresponding pixels of the first camera image.

2. A multi-aperture imaging system comprising: a) a first camera that provides a first camera image, the first camera having a first sensor with a first plurality of sensor pixels covered at least in part with a non-standard color filter array (CFA) used to increase a specific color sampling rate relative to a same color sampling rate in a standard CFA. wherein the non-standard CFA includes a repetition of a n×n micro-cell where n=6 and wherein each micro-cell includes a color filter order selected from the group consisting of RBBRRB-RWRBWB-BBRBRR-RRBRBB-BWBRWR-BRRBBR, BBGRRG-RGRBGB-GBRGRB-RRGBBG-BGBRGR-GRBGBR, RBBRRB-RGRBGB-BBRBRR-RRBRBB-BGBRGR-BRRBBR and RBRBRB-BGBRGR-RBRBRB-BRBRBR-RGRBGB-BRBRBR; b) a second camera that provides a second camera image, the second camera having a second sensor with a second plurality of sensor pixels, the second plurality of sensor pixels being either Clear or covered with a standard CFA, wherein the second camera image has an overlap area with the first camera image; and c) a processor configured to process the first and second camera images into a fused output image, wherein in the overlap area pixels of the second camera image are registered with corresponding pixels of the first camera image.

3. The multi-aperture imaging system of claim 1, wherein the first camera is a Wide camera with a field of view FOVW and wherein the second camera is a Tele camera with a field of view FOVT smaller than FOVW.

4. A method of acquiring images by a multi-aperture imaging system, the method comprising:

a) providing a first image generated by a first camera of the imaging system, the first camera having a first field of view (F0V1);
b) providing a second image generated by a second camera of the imaging system, the second camera having a second field of view (FOV2) such that FOV2<FOV1, the second image having an overlap area with the first image; and
c) fusing the first and second images into a fused image, wherein the fusing includes applying a registration process between the first and second images, the registration process including: i. extracting a first Luma image from the first image ii. extracting a second Luma image from the second image, iii. applying low-pass filtering on the second Luma image in order to match its spatial frequency content to that of the first Luma image and to generate a low-pass second Luma image, and iv. applying registration on the low-pass second Luma image and the first Luma image,
wherein the non-standard CFA includes a repetition of a n×n micro-cell where n=4 and
wherein each micro-cell includes a BBRR-RBBR-RRBB-BRRB color filter order.

5. The method of claim 4, wherein n=6 instead of n=4 and wherein instead of each micro-cell including a BBRR-RBBR-RRBB-BRRB color filter order, each micro-cell includes a color filter order selected from the group consisting of RBBRRB-RWRBWB-BBRBRR-RRBRBB-BWBRWR-BRRBBR, BBGRRG-RGRBGB-GBRGRB-RRGBBG-BGBRGR-GRBGBR, RBBRRB-RGRBGB-BBRBRR-RRBRBB-BGBRGR-BRRBBR and RBRBRB-BGBRGR-RBRBRB-BRBRBR-RGRBGB-BRBRBR.

6. A multi-aperture imaging system comprising:

a) a first camera having a first field of view (FOV1), a first zoom factor (X1) and a first sensor with a first filter array (FA);
b) a second camera having a second field of view (FOV2), a second zoom factor (X2) and a second sensor with a second filter array, the first sensor having a first overlap area with the second sensor and a first non-overlap area; and
c) a third camera having a third field of view (FOV3), a third zoom factor (X3) and a third sensor with a third filter array, the second sensor having a second overlap area with the third sensor and a second non-overlap area, wherein X1 is different from X3 and X2 wherein a FA pattern of the first FA in the first overlap area differs from a FA pattern of the first FA in the first non-overlap area or the second FA in the second non-overlap area, wherein an FA pattern of the second FA in the second overlap area differs from the FA pattern of the first FA in the first non-overlap area or the second FA in the second non-overlap area.

7. The multi-aperture imaging system of claim 6, wherein the third filter array is one of an RGB (Bayer), RGBE, CYYM, CYGM, RGBW#1, RGBW#2 or RGBW#3 color filter array.

8. The multi-aperture imaging system of claim 6, wherein X3 is greater than X1.

9. The multi-aperture imaging system of claim 6, wherein X3 is greater than X2.

10. The multi-aperture imaging system of claim 6, wherein X2 is greater than X1.

11. The multi-aperture imaging system of claim 6, wherein the second non-overlap area filter array is one of an RGB (Bayer), RGBE, CYYM, CYGM, RGBW#1, RGBW#2 or RGBW#3 color filter array.

12. The multi-aperture imaging system of claim 9, wherein the third filter array is a clear filter array.

13. The multi-aperture imaging system of claim of claim 9, wherein the second non-overlap area filter array is a clear filter array.

14. The multi-aperture imaging system of claim of claim 13, wherein the third color filter array is a Bayer color filter array.

15. The multi-aperture imaging system of claim 9, wherein the first non-overlap area filter array is one of an RGB (Bayer), RGBE, CYYM, CYGM, RGBW#1, RGBW#2 or RGBW#3 color filter array.

16. The multi-aperture imaging system of claim 9, wherein the first non-overlap area color filter array is a Bayer color filter array.

17. A multi-aperture imaging system comprising:

a) a first camera having a first field of view (FOV1) and a first sensor;
b) a second camera having a second field of view (FOV2) and a second sensor with a color filter array (CFA) that includes a red color filter, a green color filter and a blue color filter, the first sensor having a first non-overlap area with the second sensor and a first overlap area with the second sensor; and
c) a third camera having a third field of view (FOV3) and a third sensor with a Bayer color filter array, the second sensor having a second overlap area with the third sensor and a second non-overlap area, wherein FOV1>FOV2>FOV3 wherein the first sensor comprises a Bayer CFA in the first non-overlap area, wherein a CFA pattern of the first sensor in the first overlap area differs from the Bayer CFA of the first sensor in the first non-overlap area or a second CFA pattern of the second sensor in the second non-overlap area, wherein a CFA pattern of the second sensor in the second overlap area differs from the Bayer CFA of the first sensor in the first non-overlap area or the CFA pattern of the second sensor in the second non-overlap area.

18. A multi-aperture imaging system comprising:

a) a first camera having a first field of view (FOV1) and a first sensor with a first color filter array (CFA) that includes a red color filter, a green color filter and a blue color filter;
b) a second camera having a second field of view (FOV2) and a second sensor with a second CFA that includes a red color filter, a green color filter and a blue color filter, the first sensor having a first overlap area with the second sensor and a first non-overlap area; and
c) a third camera having a third field of view (FOV3) and a third sensor with a third color filter array that includes a red color filter, a green color filter and a blue color filter, the second sensor having a second overlap area with the third sensor and a second non-overlap area, wherein FOV1>FOV2>FOV3 wherein a CFA pattern of the first sensor in the first overlap area differs from a CFA pattern of the first sensor in the first non-overlap area or a second CFA pattern of the second sensor in the second non-overlap area, wherein a CFA pattern of the second sensor in the second overlap area differs from the CFA pattern of the first sensor in the first non-overlap area or the CFA pattern of the second sensor in the second non-overlap area.
Referenced Cited
U.S. Patent Documents
4199785 April 22, 1980 McCullough et al.
5005083 April 2, 1991 Grage et al.
5032917 July 16, 1991 Aschwanden
5041852 August 20, 1991 Misawa et al.
5051830 September 24, 1991 von Hoessle
5099263 March 24, 1992 Matsumoto et al.
5248971 September 28, 1993 Mandl
5287093 February 15, 1994 Amano et al.
5394520 February 28, 1995 Hall
5436660 July 25, 1995 Sakamoto
5444478 August 22, 1995 Lelong et al.
5459520 October 17, 1995 Sasaki
5657402 August 12, 1997 Bender et al.
5682198 October 28, 1997 Katayama et al.
5768443 June 16, 1998 Michael et al.
5926190 July 20, 1999 Turkowski et al.
5940641 August 17, 1999 McIntyre et al.
5982951 November 9, 1999 Katayama et al.
6101334 August 8, 2000 Fantone
6128416 October 3, 2000 Oura
6148120 November 14, 2000 Sussman
6208765 March 27, 2001 Bergen
6268611 July 31, 2001 Pettersson et al.
6549215 April 15, 2003 Jouppi
6611289 August 26, 2003 Yu et al.
6643416 November 4, 2003 Daniels et al.
6650368 November 18, 2003 Doron
6680748 January 20, 2004 Monti
6714665 March 30, 2004 Hanna et al.
6724421 April 20, 2004 Glatt
6738073 May 18, 2004 Park et al.
6741250 May 25, 2004 Furlan et al.
6750903 June 15, 2004 Miyatake et al.
6778207 August 17, 2004 Lee et al.
7002583 February 21, 2006 Rabb, III
7015954 March 21, 2006 Foote et al.
7038716 May 2, 2006 Klein et al.
7199348 April 3, 2007 Olsen et al.
7206136 April 17, 2007 Labaziewicz et al.
7248294 July 24, 2007 Slatter
7256944 August 14, 2007 Labaziewicz et al.
7305180 December 4, 2007 Labaziewicz et al.
7339621 March 4, 2008 Fortier
7346217 March 18, 2008 Gold, Jr.
7365793 April 29, 2008 Cheatle et al.
7411610 August 12, 2008 Doyle
7424218 September 9, 2008 Baudisch et al.
7509041 March 24, 2009 Hosono
7533819 May 19, 2009 Barkan et al.
7561191 July 14, 2009 May et al.
7619683 November 17, 2009 Davis
7676146 March 9, 2010 Border et al.
7738016 June 15, 2010 Toyofuku
7773121 August 10, 2010 Huntsberger et al.
7809256 October 5, 2010 Kuroda et al.
7880776 February 1, 2011 LeGall et al.
7918398 April 5, 2011 Li et al.
7964835 June 21, 2011 Olsen et al.
7978239 July 12, 2011 Deever et al.
8094208 January 10, 2012 Myhrvold
8115825 February 14, 2012 Culbert et al.
8134115 March 13, 2012 Koskinen et al.
8149327 April 3, 2012 Lin et al.
8154610 April 10, 2012 Jo et al.
8179457 May 15, 2012 Koskinen et al.
8238695 August 7, 2012 Davey et al.
8274552 September 25, 2012 Dahi et al.
8390729 March 5, 2013 Long et al.
8391697 March 5, 2013 Cho et al.
8400555 March 19, 2013 Georgiev et al.
8439265 May 14, 2013 Ferren et al.
8446484 May 21, 2013 Muukki et al.
8483452 July 9, 2013 Ueda et al.
8514491 August 20, 2013 Duparre
8542287 September 24, 2013 Griffith et al.
8547389 October 1, 2013 Hoppe et al.
8553106 October 8, 2013 Scarff
8587691 November 19, 2013 Takane
8619148 December 31, 2013 Watts et al.
8660420 February 25, 2014 Chang
8803990 August 12, 2014 Smith
8896655 November 25, 2014 Mauchly et al.
8976255 March 10, 2015 Matsuoto et al.
9019387 April 28, 2015 Nakano
9025073 May 5, 2015 Attar et al.
9025077 May 5, 2015 Attar et al.
9041835 May 26, 2015 Honda
9137447 September 15, 2015 Shibuno
9185291 November 10, 2015 Shabtay et al.
9215377 December 15, 2015 Sokeila et al.
9215385 December 15, 2015 Luo
9270875 February 23, 2016 Brisedoux et al.
9286680 March 15, 2016 Jiang et al.
9344626 May 17, 2016 Silverstein et al.
9360671 June 7, 2016 Zhou
9369621 June 14, 2016 Malone et al.
9413930 August 9, 2016 Geerds
9413984 August 9, 2016 Attar et al.
9420180 August 16, 2016 Jin
9438792 September 6, 2016 Nakada et al.
9485432 November 1, 2016 Medasani et al.
9578257 February 21, 2017 Attar et al.
9618748 April 11, 2017 Munger et al.
9681057 June 13, 2017 Attar et al.
9723220 August 1, 2017 Sugie
9736365 August 15, 2017 Laroia
9736391 August 15, 2017 Du et al.
9768310 September 19, 2017 Ahn et al.
9800798 October 24, 2017 Ravirala et al.
9851803 December 26, 2017 Fisher et al.
9894287 February 13, 2018 Qian et al.
9900522 February 20, 2018 Lu
9927600 March 27, 2018 Goldenberg et al.
20020005902 January 17, 2002 Yuen
20020030163 March 14, 2002 Zhang
20020063711 May 30, 2002 Park et al.
20020075258 June 20, 2002 Park et al.
20020122113 September 5, 2002 Foote
20020167741 November 14, 2002 Koiwai et al.
20030030729 February 13, 2003 Prentice et al.
20030093805 May 15, 2003 Gin
20030160886 August 28, 2003 Misawa et al.
20030202113 October 30, 2003 Yoshikawa
20040008773 January 15, 2004 Itokawa
20040012683 January 22, 2004 Yamasaki et al.
20040017386 January 29, 2004 Liu et al.
20040027367 February 12, 2004 Pilu
20040061788 April 1, 2004 Bateman
20040141065 July 22, 2004 Hara et al.
20040141086 July 22, 2004 Mihara
20040240052 December 2, 2004 Minefuji et al.
20050013509 January 20, 2005 Samadani
20050046740 March 3, 2005 Davis
20050157184 July 21, 2005 Nakanishi et al.
20050168834 August 4, 2005 Matsumoto et al.
20050185049 August 25, 2005 Iwai et al.
20050200718 September 15, 2005 Lee
20060054782 March 16, 2006 Olsen et al.
20060056056 March 16, 2006 Ahiska et al.
20060067672 March 30, 2006 Washisu et al.
20060102907 May 18, 2006 Lee et al.
20060125937 June 15, 2006 LeGall et al.
20060170793 August 3, 2006 Pasquarette et al.
20060175549 August 10, 2006 Miller et al.
20060187310 August 24, 2006 Janson et al.
20060187322 August 24, 2006 Janson et al.
20060187338 August 24, 2006 May et al.
20060227236 October 12, 2006 Pak
20070024737 February 1, 2007 Nakamura et al.
20070126911 June 7, 2007 Nanjo
20070177025 August 2, 2007 Kopet et al.
20070188653 August 16, 2007 Pollock et al.
20070189386 August 16, 2007 Imagawa et al.
20070257184 November 8, 2007 Olsen et al.
20070285550 December 13, 2007 Son
20080017557 January 24, 2008 Witdouck
20080024614 January 31, 2008 Li et al.
20080025634 January 31, 2008 Border et al.
20080030592 February 7, 2008 Border et al.
20080030611 February 7, 2008 Jenkins
20080084484 April 10, 2008 Ochi et al.
20080106629 May 8, 2008 Kurtz et al.
20080117316 May 22, 2008 Orimoto
20080129831 June 5, 2008 Cho et al.
20080218611 September 11, 2008 Parulski et al.
20080218612 September 11, 2008 Border et al.
20080218613 September 11, 2008 Janson et al.
20080219654 September 11, 2008 Border et al.
20090086074 April 2, 2009 Li et al.
20090109556 April 30, 2009 Shimizu et al.
20090122195 May 14, 2009 Van Baar et al.
20090122406 May 14, 2009 Rouvinen et al.
20090128644 May 21, 2009 Camp et al.
20090219547 September 3, 2009 Kauhanen et al.
20090252484 October 8, 2009 Hasuda et al.
20090295949 December 3, 2009 Ojala
20090324135 December 31, 2009 Kondo et al.
20100013906 January 21, 2010 Border et al.
20100020221 January 28, 2010 Tupman et al.
20100060746 March 11, 2010 Olsen et al.
20100097444 April 22, 2010 Lablans
20100103194 April 29, 2010 Chen et al.
20100165131 July 1, 2010 Makimoto et al.
20100196001 August 5, 2010 Ryynänen et al.
20100238327 September 23, 2010 Griffith et al.
20100259836 October 14, 2010 Kang et al.
20100277619 November 4, 2010 Scarff
20100283842 November 11, 2010 Guissin et al.
20100321494 December 23, 2010 Peterson et al.
20110058320 March 10, 2011 Kim et al.
20110063417 March 17, 2011 Peters et al.
20110063446 March 17, 2011 McMordie et al.
20110064327 March 17, 2011 Dagher
20110080487 April 7, 2011 Venkataraman et al.
20110121421 May 26, 2011 Charbon et al.
20110128288 June 2, 2011 Petrou et al.
20110164172 July 7, 2011 Shintani et al.
20110216228 September 8, 2011 Kawamura
20110229054 September 22, 2011 Weston et al.
20110234798 September 29, 2011 Chou
20110234853 September 29, 2011 Hayashi et al.
20110234881 September 29, 2011 Wakabayashi et al.
20110242286 October 6, 2011 Pace et al.
20110242355 October 6, 2011 Goma et al.
20110285730 November 24, 2011 Lai et al.
20110292258 December 1, 2011 Adler et al.
20110298966 December 8, 2011 Kirschstein et al.
20120026366 February 2, 2012 Golan et al.
20120044372 February 23, 2012 Cote et al.
20120062780 March 15, 2012 Morihisa
20120069235 March 22, 2012 Imai
20120075489 March 29, 2012 Nishihara
20120081566 April 5, 2012 Cote
20120105579 May 3, 2012 Jeon et al.
20120124525 May 17, 2012 Kang
20120154547 June 21, 2012 Aizawa
20120154614 June 21, 2012 Moriya et al.
20120196648 August 2, 2012 Havens et al.
20120229663 September 13, 2012 Nelson et al.
20120249815 October 4, 2012 Bohn et al.
20120287315 November 15, 2012 Huang et al.
20120320467 December 20, 2012 Baik et al.
20130002928 January 3, 2013 Imai
20130016427 January 17, 2013 Sugawara
20130063629 March 14, 2013 Webster et al.
20130076922 March 28, 2013 Shihoh et al.
20130093842 April 18, 2013 Yahata
20130094126 April 18, 2013 Rappoport et al.
20130113894 May 9, 2013 Mirlay
20130135445 May 30, 2013 Dahi et al.
20130136355 May 30, 2013 Demandolx
20130155176 June 20, 2013 Paripally et al.
20130182150 July 18, 2013 Asakura
20130201360 August 8, 2013 Song
20130202273 August 8, 2013 Ouedraogo et al.
20130235224 September 12, 2013 Park et al.
20130250150 September 26, 2013 Malone et al.
20130258044 October 3, 2013 Betts-LaCroix
20130270419 October 17, 2013 Singh et al.
20130278785 October 24, 2013 Nomura et al.
20130321668 December 5, 2013 Kamath
20140009631 January 9, 2014 Topliss
20140049615 February 20, 2014 Uwagawa
20140118584 May 1, 2014 Lee et al.
20140192238 July 10, 2014 Attar et al.
20140192253 July 10, 2014 Laroia
20140218587 August 7, 2014 Shah
20140313316 October 23, 2014 Olsson et al.
20140362242 December 11, 2014 Takizawa
20150002683 January 1, 2015 Hu et al.
20150042870 February 12, 2015 Chan et al.
20150070781 March 12, 2015 Cheng et al.
20150092066 April 2, 2015 Geiss et al.
20150103147 April 16, 2015 Ho et al.
20150138381 May 21, 2015 Ahn
20150154776 June 4, 2015 Zhang et al.
20150162048 June 11, 2015 Hirata et al.
20150195458 July 9, 2015 Nakayama et al.
20150215516 July 30, 2015 Dolgin
20150237280 August 20, 2015 Choi et al.
20150242994 August 27, 2015 Shen
20150244906 August 27, 2015 Wu et al.
20150253543 September 10, 2015 Mercado
20150253647 September 10, 2015 Mercado
20150261299 September 17, 2015 Wajs
20150271471 September 24, 2015 Hsieh et al.
20150281678 October 1, 2015 Park et al.
20150286033 October 8, 2015 Osborne
20150316744 November 5, 2015 Chen
20150334309 November 19, 2015 Peng et al.
20160044250 February 11, 2016 Shabtay et al.
20160070088 March 10, 2016 Koguchi
20160154202 June 2, 2016 Wippermann et al.
20160154204 June 2, 2016 Lim et al.
20160212358 July 21, 2016 Shikata
20160212418 July 21, 2016 Demirdjian et al.
20160241751 August 18, 2016 Park
20160291295 October 6, 2016 Shabtay et al.
20160295112 October 6, 2016 Georgiev et al.
20160301840 October 13, 2016 Du et al.
20160353008 December 1, 2016 Osborne
20160353012 December 1, 2016 Kao et al.
20170019616 January 19, 2017 Zhu et al.
20170070731 March 9, 2017 Darling et al.
20170187962 June 29, 2017 Lee et al.
20170214846 July 27, 2017 Du et al.
20170214866 July 27, 2017 Zhu et al.
20170242225 August 24, 2017 Fiske
20170289458 October 5, 2017 Song et al.
20180013944 January 11, 2018 Evans, V et al.
20180017844 January 18, 2018 Yu et al.
20180024329 January 25, 2018 Goldenberg et al.
20180059379 March 1, 2018 Chou
20180120674 May 3, 2018 Avivi et al.
20180150973 May 31, 2018 Tang et al.
20180176426 June 21, 2018 Wei et al.
20180198897 July 12, 2018 Tang et al.
20180241922 August 23, 2018 Baldwin et al.
20180295292 October 11, 2018 Lee et al.
20180300901 October 18, 2018 Inakai et al.
20190121103 April 25, 2019 Bachar et al.
Foreign Patent Documents
101276415 October 2008 CN
201514511 June 2010 CN
102739949 October 2012 CN
103024272 April 2013 CN
103841404 June 2014 CN
1536633 June 2005 EP
1780567 May 2007 EP
2523450 November 2012 EP
S59191146A October 1984 JP
04211230 August 1992 JP
H107318864 December 1995 JP
08271976 October 1996 JP
2002010276 January 2002 JP
2003298920 October 2003 JP
2004133054 April 2004 JP
2004245982 September 2004 JP
2005099265 April 2005 JP
2006238325 September 2006 JP
2007228006 September 2007 JP
2007306282 November 2007 JP
2008076485 April 2008 JP
2010204341 September 2010 JP
2011085666 April 2011 JP
2013106289 May 2013 JP
20070005946 January 2007 KR
20090058229 June 2009 KR
20100008936 January 2010 KR
20140014787 February 2014 KR
101477178 December 2014 KR
20140144126 December 2014 KR
20150118012 October 2015 KR
2000027131 May 2000 WO
2004084542 September 2004 WO
2006008805 January 2006 WO
2009097552 August 2009 WO
2010122841 October 2010 WO
2014072818 May 2014 WO
2017025822 February 2017 WO
2017037688 March 2017 WO
2018130898 July 2018 WO
Other references
  • Statistical Modeling and Performance Characterization of a Real-Time Dual Camera Surveillance System, Greienhagen et al., Publisher: IEEE, 2000, 8 pages.
  • A 3MPixel Multi-Aperture Image Sensor with 0.7μm Pixels in 0.11μm CMOS, Fife et al., Stanford University, 2008, 3 pages.
  • Dual camera intelligent sensor for high definition 360 degrees surveillance, Scotti et al., Publisher: IET, May 9, 2000, 8 pages.
  • Dual-sensor foveated imaging system, Hua et al., Publisher: Optical Society of America, Jan. 14, 2008, 11 pages.
  • Defocus Video Matting, McGuire et al., Publisher: ACM SIGGRAPH, Jul. 31, 2005, 11 pages.
  • Compact multi-aperture imaging with high angular resolution, Santacana et al., Publisher: Optical Society of America, 2015, 10 pages.
  • Multi-Aperture Photography, Green et al., Publisher: Mitsubishi Electric Research Laboratories, Inc., Jul. 2007, 10 pages.
  • Multispectral Bilateral Video Fusion, Bennett et al., Publisher: IEEE, May 2007, 10 pages.
  • Super-resolution imaging using a camera array, Santacana et al., Publisher: Optical Society of America, 2014, 6 pages.
  • Optical Splitting Trees for High-Precision Monocular Imaging, McGuire et al., Publisher: IEEE, 2007, 11 pages.
  • High Performance Imaging Using Large Camera Arrays, Wilburn et al., Publisher: Association for Computing Machinery, Inc., 2005, 12 pages.
  • Real-time Edge-Aware Image Processing with the Bilateral Grid, Chen et al., Publisher: ACM SIGGRAPH, 2007, 9 pages.
  • Superimposed multi-resolution imaging, Caries et al., Publisher: Optical Society of America, 2017, 13 pages.
  • Viewfinder Alignment, Adams et al., Publisher: Eurographics, 2008, 10 pages.
  • Dual-Camera System for Multi-Level Activity Recognition, Bodor et al., Publisher: IEEE, Oct. 2014, 6 pages.
  • Engineered to the task: Why camera-phone cameras are different, Giles Humpston, Publisher: Solid State Technology Jun. 2009, 3 pages.
  • International Search Report and Written Opinion issued in related PCT patent application PCT/IB2013/060356, dated Apr. 17, 2014, 15 pages.
Patent History
Patent number: RE48697
Type: Grant
Filed: Apr 15, 2019
Date of Patent: Aug 17, 2021
Assignee: Corephotonics Ltd. (Tel Aviv)
Inventors: Gal Shabtay (Tel-Aviv), Noy Cohen (Tel-Aviv), Oded Gigushinski (Herzlia), Ephraim Goldenberg (Ashdod)
Primary Examiner: Mark Sager
Application Number: 16/384,244
Classifications
Current U.S. Class: Combined Image Signal Generator And General Image Signal Processing (348/222.1)
International Classification: H04N 5/232 (20060101); H04N 9/04 (20060101); G06T 11/60 (20060101); G06T 7/00 (20170101); H04N 9/09 (20060101); H04N 5/225 (20060101); G06T 5/20 (20060101);