Abstract: The invention relates to a method for determining a localization error (?) of a point (P0) of a raw image, comprising the following steps: estimating the value of a statistical magnitude (G) characteristic of a probability law (D(X, Y, Z)) of at least one terrain coordinate (X, Y, Z) associated with the point (P0) of the raw image, using a probability law (D(?1, . . . , ?n)) with magnitudes (?1, . . . , ?n) depending on the exposure conditions of the raw image and a localization function, deduced from an exposure function and a terrain model and applied for the image coordinate point (P0) of the raw image; and deducing the localization error (?) of the point (P0) of the raw image from the statistical magnitude (G).

Abstract: An image capturing apparatus performs focus detection based on a pair of image signals obtained from an image sensor including pixels each having a pair of photoelectric conversion units capable of outputting the pair of image signals obtained by independently receiving a pair of light beams that have passed through different exit pupil regions of an imaging optical system. In the focus detection, an f-number of the imaging optical system is acquired, the pair of image signals undergo filtering using a first filter formed from an summation filter when the f-number is less than a predetermined threshold, or using a second filter formed from the summation filter and a differential filter when the f-number is not less than the threshold, and focus detection is performed by a phase difference method based on the pair of filtered image signals.

Abstract: A method and apparatus for image processing a lens-distorted image (e.g., a fisheye image) is provided. The method includes partitioning coordinate points in a selected output image into tiles. The output image is an undistorted rendition of a subset of the lens-distorted image. Coordinate points on a border of the tiles in the output image are selected. For each tile, coordinate points in the lens-distorted image corresponding to each selected coordinate point in the output image are calculated. In addition, for each tile, a bounding box on the lens-distorted image is selected. The bounding box includes the calculated coordinates in the lens-distorted image. The bounding boxes are expanded so that they encompass all coordinate points in the lens-distorted image that map to all coordinate points in their respective corresponding tiles. Output pixel values are generated for each tile from pixel values in their corresponding expanded bounding boxes.

Abstract: The invention relates to a method for processing video images comprising the steps for acquiring a plurality of video images during a time interval comprising a reference time t; associating a weighting factor with each of the video images, at least two of the video images having different weighting factors; memorising the video images; weighting each of the video images memorised with the associated weighting factor; generating an image called the reference image associated with the reference time t by averaging weighted video images. According to the invention, each video image is memorised with a resolution proportional to the weighting factor associated with said video image in order to reduce the memory space necessary for the storage of images and reduce the access time to the memorised images.

Abstract: A Digital Image Stabilization method including selecting a principal transform representing a stationary/background object in the scene of a video frame, based on scoring each of a plurality of transforms of tile motion vector (Tile MV) groups and of feature point motion vector (FP MV) groups, and excluding large moving objects based on the history of the stationary (background) group and the history of each of the plurality motion vector groups.

Abstract: An image processing circuit and a ringing artefact removing method thereof are provided. The image processing circuit includes a deRing detection unit and a deRing filtering unit. The deRing detection unit receives a plurality of display data of an input frame and calculates a regulating reference value corresponding to each display data according to the display data and the display data at adjacent display positions. The deRing filtering unit is coupled to the deRing detection unit. The deRing filtering unit receives the display data and regulates the display data according the regulating reference values respectively corresponding to the display data to output a plurality of regulated display data.

Abstract: According to an embodiment, a high dynamic range synthesizing circuit includes an interpolation processing unit, a blur detection unit and a mix processing unit. The interpolation processing unit generates an interpolation signal. The blur detection unit uses a first image signal and a second image signal a signal level of which is adjusted for detecting the amount of blur. The mix processing unit performs processing of mixing the second image signal into the interpolation signal. The mix processing unit applies a weight of the second image signal depending on the amount of blur to the interpolation signal by the mix processing.

Abstract: An image processing device includes: a first band limiting unit that reduces noise included in an input image; and a restoring unit, wherein the restoring unit has a difference calculating unit that calculates a difference between the input image and a noise-reduced image, a predicted noise obtaining unit that obtains a predicted noise amount to be included in the input image, a correction signal generating unit that generates a correction signal for correcting the noise-reduced image and controlling an absolute value of the difference between the input image and the noise-reduced image within a range of the predicted noise amount, and an image synthesizing unit that corrects the noise-reduced image based on the correction signal.

Abstract: A mobile device comprising a processor configured to merge a plurality of images each having a distinct focus position in a scene to generate a focus-stacked image that encompasses all focus positions of the plurality of images. Also, an apparatus comprising a camera configured to capture a plurality of color images for one scene each with a distinct focus distance and a processor configured to register the plurality of color images to generate a plurality of registered color images, generate a plurality of luminance (Y) channels from the plurality of registered color images, and stack the plurality of Y channels to generate a focus-stacked Y channel.

Abstract: A method and an apparatus for deblurring an image from a sequence of images are described. The image comprises pixels. A motion estimation stage estimates motion of the pixels of the image. A point spread function modeling stage models point spread functions for the pixels of the image using the motion estimates. A deconvolution stage determines a deblurred estimate of the image using the modeled point spread functions. A feedback loop allows iteratively improving the motion estimates for the pixels until the modeled point spread functions converge.

Abstract: In embodiments of optical flow accounting for image haze, digital images may include objects that are at least partially obscured by a haze that is visible in the digital images, and an estimate of light that is contributed by the haze in the digital images can be determined The haze can be cleared from the digital images based on the estimate of the light that is contributed by the haze, and clearer digital images can be generated. An optical flow between the clearer digital images can then be computed, and the clearer digital images refined based on the optical flow to further clear the haze from the images in an iterative process to improve visibility of the objects in the digital images.

Abstract: The present invention has an object to provide an image processing apparatus and an image processing method capable of, when reducing a blur in an input image, (i) reducing noise included in the input image and (ii) restraining degradation of the image caused by noise processing from being emphasized by image restoration processing. An image processing apparatus (100) for reducing a blur in an input image includes: a noise processing unit (10) which performs noise processing that reduces noise to the input image, to generate a noise-processed image; and a restoration processing unit (20) which performs image restoration processing that reduces a blur to the noise-processed image, the noise processing unit (10) performing the noise processing based on a characteristic of the image restoration processing.

Abstract: At each of mutually different multiple focal positions, focal adjustment parameter values are obtained from images of standard particles made of the same substance. Each focal adjustment parameter value is figured out as any one of the ratio between the density value around the center of the standard particle image and the density value around the outline, the difference therebetween, and the density value around the center. The in-focus position is adjusted on the basis of the relationship between the obtained focal adjustment parameter values and the focal positions. Moreover, on the basis of the relationship between the focal adjustment parameter values and the focal positions, the parameter values are converted into focal positions, and the focal positions and dispersion thereof are used to check the displacement of the in-focus position and the thickness of the sample liquid.

Abstract: Methods and apparatus for providing simultaneous, non-destructive blur patterns in an interactive environment. A blur module may render physically-realistic, spatially-varying blurs in digital images while at the same time giving users the flexibility to produce creative blur effects. The blur module may provide different types of blur patterns, including field blur, iris blur, and tilt-shift blur, all of which are available in a given session. Each different blur pattern can be combined with one or more of the other blur patterns non-destructively. Each blur pattern has a corresponding on-canvas user interface element or elements that can be manipulated for a live preview. A bokeh technique may be provided to create bokeh effects in digital images by simulating bokeh in the resultant blurred image. A selection bleed technique may be provided that allows the user to control bleeding at the edges of selections for any of the blur patterns.

Abstract: An image processing device is provided that includes a subject image designator and an image processor. The subject image designator designates a main subject in an image. The image processor subjects an image to image processing that depends on the distance to the main subject.

Abstract: Systems and methods can be configured to perform operations related to determining a phase transfer function of a digital imaging system. A digital image that includes at least one edge is received, the at least one edge includes a plurality of pixels with disparate pixel values. The at least one edge from the digital image is identified and an edge spread function is generated based on the identified edge. The edge spread function can be generated by taking at least one slice across the identified at least one edge. A line spread function is generated based on the edge spread function. An optical transfer function is generated based on a Fourier transform of the line spread function. A phase error is also identified. The phase transfer function of the digital image is identified based on the phase of the generated optical transfer function and the identified phase error.

Abstract: A mobile terminal and a method of controlling the same are provided. The mobile terminal detects an object in which a ghost may appear through a preview image of an image acquired using a dual camera. The mobile terminal may display an indicator for identifying the detected object. Accordingly, a higher quality high dynamic range (HDR) image can be more efficiently acquired.

Abstract: The invention provides a camera system. In one embodiment, the camera system comprises a camera module and a processor. The camera module photographs a target object according to a focal length to generate an image. The processor comprises an extending-lens-depth-of-filed (EDOF) module and an auto focus module. The EDOF module processes the image according to an EDOF process to generate an EDOF image. The auto focus module adjusts the focal length of the camera module according to an auto focus process.

Abstract: Provided is an imaging apparatus including an imaging unit that performs imaging with an image sensor having pixels of first, second, and third colors, a luminance ratio calculation unit that integrates luminance of each of the first, second, and third colors within a focus determination region of an imaging signal output by the imaging unit and calculates a ratio of the luminance between the integrated values of the colors, a luminance normalization unit that normalizes the integrated value of the luminance of the first color within the focus determination region of the imaging signal output by the imaging unit at the ratio of the luminance between the integrated values calculated by the luminance ratio calculation unit, and a display processing unit that performs display corresponding to the integrated value of the luminance normalized by the luminance normalization unit.

Abstract: A computer-implemented method for viewing images on an interactive computing device comprises displaying an image from a stack comprising a display image and at least one compressed sub-image of nominally the same scene, each of the sub-images of the stack having been acquired at respective focal distances. Responsive to a user selecting a portion of the displayed image, the selected portion is mapped to a corresponding mapped portion of a sub-image within the stack according to the difference in focal distances between the displayed image and the sub-image. At least one row of compressed image blocks of the at least one sub-image extending across the mapped portion; and a reference value for a point in the compressed image stream of the sub-image preceding the row of compressed image blocks is determined.

Abstract: Systems and methods for assessing and optimizing virtual microscope slide image quality are provided. In order to determine whether any of multiple virtual slide images has an out of focus area and is therefore a candidate for manual inspection or rescanning, various focus points used to scan each virtual slide image are used to calculate a best fit surface for each virtual slide image. The best fit surface is then used to determine whether any of the various focus points are outliers. If it is determined that a virtual slide image is associated with outlying focus points, it is identified as a candidate for manual inspection or rescanning.

Abstract: Mobile phones and other portable devices are equipped with a variety of technologies by which existing functionality can be improved, and new functionality can be provided. Some aspects relate to visual search capabilities, and determining appropriate actions responsive to different image inputs. Others relate to processing of image data. Still others concern metadata generation, processing, and representation. Yet others concern user interface improvements. Other aspects relate to imaging architectures, in which a mobile phone's image sensor is one in a chain of stages that successively act on packetized instructions/data, to capture and later process imagery. Still other aspects relate to distribution of processing tasks between the mobile device and remote resources (“the cloud”). Elemental image processing (e.g., simple filtering and edge detection) can be performed on the mobile phone, while other operations can be referred out to remote service providers.

Abstract: In accordance with an example embodiment a method, apparatus and computer program product are provided. The method comprises determining a plurality of first pixels having resemblance with a second pixel associated with an image based on a depth information of the image. The method further comprises replacing the second pixel by at least one first pixel of the plurality of first pixels based on a determination that the at least one first pixel is not associated with the at least one image defect.

Abstract: An image processing apparatus comprises a captured image data acquisition unit configured to acquire captured image data, an information acquisition unit configured to acquire information of object distances of objects, a refocus image generation unit configured to generate a refocus image at a predetermined focus position in the captured image data, a display unit configured to display the refocus image on a display medium, a designation unit configured to designate an address in the refocus image displayed by the display unit, and a distance calculation unit configured to calculate distances between the designated address and positions of the objects in the refocus image, wherein the refocus image generation unit generates a refocus image using, as a focus position, an object distance of one of the objects based on the distances.

Abstract: A smart-focusing technique includes identifying an object of interest, such as a face, in a digital image. A focus-generic classifier chain is applied that is trained to match both focused and unfocused faces and/or data from a face tracking module is accepted. Multiple focus-specific classifier chains are applied, including a first chain trained to match substantially out of focus faces, and a second chain trained to match slightly out of focus faces. Focus position is rapidly adjusted using a MEMS component.

Abstract: An image pickup apparatus capable of reducing camera-shake blur and rolling-caused distortion of image data obtained by shooting without including invalid data. An object obtained by shooting is stored in a memory area as first image data, and data having a smaller data size than the first image data is acquired as second image data by clipping from the memory area. A clipping position which enables correction of camera-shake blur is calculated according to an amount of movement due to a camera shake. Range information indicative of a range in the memory area and shift amounts used for correcting rolling-caused distortion are calculated. Rolling-caused distortion of the second image data is corrected based on the calculated shift amounts.

Abstract: A focal plane staring sensor is provided that includes an M×N sensor, where M is a number of rows of sensor pixels in the sensor and N is a number of columns of sensor pixels in the sensor, where M and N are integers greater than one. A control circuit samples a sensor pixel value for each sensor pixel of the M×N sensor at a plurality of different integration times corresponding to an amount of time that a photonic charge can be acquired in each sensor pixel of the M×N sensor, wherein the control circuit selects one sample from a set of samples to generate a scaled value to facilitate an equalization of a signal to noise ratio between the sensor pixels.

Abstract: Described are techniques for image deconvolution to deblur an image given a blur kernel. Localized color statistics derived from the image to be deblurred serve as a prior constraint during deconvolution. A pixel's color is formulated as a linear combination of the two most prevalent colors within a neighborhood of the pixel. This may be repeated for many or all pixels in an image. The linear combinations of the pixels serve as a two-color prior for deconvolving the blurred image. The two-color prior is responsive to the content of the image and it may decouple edge sharpness from edge strength.

Abstract: A method for correcting overfocus of a digital image created from coherent imaging using centered fractional Fourier transforms or mathematical equivalents is described. A received image is presented to a numerical processor, and a first numerical value for an imaginary power variable is selected and used in an iterative algorithm, numerical procedure, system architecture, etc. A centered discrete fractional Fourier transform of an imaginary power and a phase restore operator associated are applied to the image file to produce a modified image. A change in mis-focused is determined and used in adjusting the specified imaginary power for a next iteration.

Abstract: Method for applying super-resolution to images captured by a camera device of a vehicle includes receiving a plurality of image frames captured by the camera device. For each image frame, a region of interest is identified within the image frame requiring resolution related to detail per pixel to be increased. Spatially-implemented super-resolution is applied to the region of interest within each image to enhance image sharpness within the region of interest.

Abstract: Methods are provided to perform area summation of various subsections of data values in a regular input array of one or several dimensions and varying sizes. The summation is achieved by adding up values from a ripmap of partial sums, where the partial sums are computed from the input array using a binary reduction method. According to such embodiments, the generation of the ripmap of partial sums will employ several binary reduction stages. Within each stage, a reduction operator is used that adds two elements along the respective direction. This is repeated until the output is only one element wide in the respective direction. The addresses of partial sums in the ripmap may subsequently be computed using a binary analysis of the target subsections in order to choose those partial sum values for a desired area that results in the desired area sum using an optimal number of data fetches.

Abstract: The spatial resolution of captured plenoptic images is enhanced. In one aspect, the plenoptic imaging process is modeled by a pupil image function (PIF), and a PIF inversion process is applied to the captured plenoptic image to produce a better resolution estimate of the object.

Abstract: The present invention operates in connection with refocusable video data, information, images and/or frames, which may be light field video data, information, images and/or frames, that may be focused and/or refocused after acquisition or recording. A video acquisition device acquires first refocusable light field video data of a scene, stores first refocusable video data representative of the first refocusable light field video data, acquires second refocusable light field video data of the scene after acquiring the first refocusable light field video data, determines a first virtual focus parameter (such as a virtual focus depth) using the second refocusable light field video data, generates first video data using the stored first refocusable video data and the first virtual focus parameter, wherein the first video data includes a focus depth that is different from an optical focus depth of the first refocusable light field video data, and outputs the first video data.

Abstract: Disclosed is an image registration device which includes an image input unit which receives an image; an image information generating unit which generates a homography matrix from the input image; and a warping unit which registers an image based on the homography matrix. The registration information generating unit comprises a distance information generator which generates distance information on subjects of the input image; a distance information modeler which approximates the generated distance information; an overlap information generator which generates overlap information from the approximated distance information; a matching pair determiner which determines a matching pair from the overlap information; and a homography matrix generator which generates a homography matrix from the matching pair.

Abstract: The present image blurring correction device includes light field information generating portion, angle blurring amount detecting portion and correcting portion. The light field information generating portion generates a series of light field information corresponding to consecutive shooting images shot by a digital camera. The angle blurring amount detecting portion detects a blurring amount of the digital camera based on variation in the series of light field information. The correcting portion corrects the series of light field information in accordance with the blurring amount so as to suppress variation in the series of light field information.

Abstract: An image processing apparatus includes a distance calculating unit that calculates a distance between first and second distributions, wherein the first distribution is a distribution of pixel values of pixels surrounding a focus pixel included in an image, the second distribution is a distribution of pixel values of pixels surrounding a pixel included in a window that includes the focus pixel at the center, and the second distribution is obtained for each pixel included in the window; a coefficient calculating unit that calculates, using the distance between the first and second distributions, a filter coefficient for each pixel included in the window; and a filter processing unit that calculates a correction value for the focus pixel by performing a filter process on each pixel included in the window using the filter coefficient.

Abstract: A blurred barcode image is processed by providing an image representation thereof comprising grayscale values. The image representation is deconvoluted using a candidate motion kernel to get a deconvoluted representation. A barcode similarity measure is calculated for the deconvoluted representation to indicate how close the distribution of the grayscale values of the deconvoluted representation is to an optimal distribution for a barcode image. The kernel provision, deconvolution and measure calculation are repeated for different candidate kernels and the candidate kernel resulting in a deconvoluted representation that is closest to a barcode image as determined based on the barcode similarity measures is selected. The selected kernel is used for deconvoluting the blurred barcode image to get a deblurred barcode image that can be read and decoded.

Abstract: A method for correcting a rolling shutter effect is provided. The method includes: obtaining feature point pairs in images, wherein each of the feature point pairs corresponds to a motion vector; obtaining sampling points between two consecutive images in time; setting a moving velocity and an angular velocity of an image capturing unit at each of the sampling points as variables; obtaining estimating motion vectors according to the variables, a focal length of the image capturing unit, and row locations where the feature point pairs are located; executing an optimization algorithm according to a difference between the motion vectors and the estimating motion vectors, to calculate the moving velocity and the angular velocity corresponding to the variables; varying locations of pixels in an image according to the moving velocity and the angular velocity, to generate a first corrected image. Thereby, the rolling shutter effect in an image is removed.

Abstract: An image processing method includes the steps of obtaining an input image that is an image in which information of an object space is obtained from a plurality of points of view using an image pickup apparatus that includes an image pickup element having a plurality of pixels and an imaging optical system, calculating a first position of a virtual imaging plane that corresponds to a specified focus position, setting the virtual imaging plane to a second position that is in a range of a depth of focus of the imaging optical system with reference to the first position so that a maximum value of an apparent pixel pitch that is formed by reconstructing the input image is decreased, and generating an output image in a state where the virtual imaging plane is set to the second position.

Abstract: A depth expansion apparatus includes an image-pickup-optical-system and an image-pickup-device (hereinafter, IPS) configured to form and pick up images A and B in different focus positions, and a depth-expanded-image forming section configured to generate, based on the images A and B, a depth-expanded-image that maintains a relation between a distance from an object point to the image-pickup-optical-system and luminance. When an image side NA of the image A is represented as NA?, a resolution determined by the IPS, as R, an optical path interval between image forming surfaces for the images A and B, as d, NA of an image at a near photographing distance among the images A and B, as NAn, and NA of an image at a far photographing distance among the images A and B, as NAf, the IPS satisfy the following conditional expressions (1) and (2): R×NA?/2?d??(1) 0.05?(NAf/NAn)2?0.9??(2).

Abstract: A method and apparatus for providing image processing. For one embodiment of the invention, an image processing apparatus is arranged to process a first relatively underexposed and sharp image of a scene, and a second relatively well exposed and blurred image, nominally of the same scene, the first and second images being derived from respective image sources. The apparatus provides a portion of the relatively first underexposed image as an input signal to an adaptive filter; and a corresponding portion of the second relatively well exposed image as a desired signal to the adaptive filter. The adaptive filter produces an output signal from the input signal and the desired signal; and an image generator constructs a first filtered image from the output signal, relatively less blurred than the second image.

Abstract: A method for restoring and enhancing a space based image of point or spot objects. The method includes: 1) dividing a space-variable degraded image into multiple space-invariant image sub-blocks, and constructing a point spread function for each of the image sub-blocks; 2) correcting each of the image sub-blocks via a space-invariant image correction method whereby obtaining a corrected image {circumflex over (f)}i for each of the image sub-blocks; and 3) stitching the corrected image sub-blocks {circumflex over (f)}i altogether via a stitching algorithm whereby obtaining a complete corrected image {circumflex over (f)}.

Abstract: An imaging system includes a positionable device configured to axially shift an image plane, wherein the image plane is generated from photons emanating from an object and passing through a lens, a detector plane positioned to receive the photons of the object that pass through the lens, and a computer programmed to characterize the lens as a mathematical function, acquire two or more elemental images of the object with the image plane of each elemental image at different axial positions with respect to the detector plane, determine a focused distance of the object from the lens, based on the characterization of the lens and based on the two or more elemental images acquired, and generate a depth map of the object based on the determined distance.

Abstract: An image de-blurring system obtains a blurred input image and generates, based on the blurred input image, a blur kernel. The blur kernel is an indication of how the image capture device was moved and/or how the subject captured in the image moved during image capture, resulting in blur. Based on the blur kernel and the blurred input image, a de-blurred image is generated. The blur kernel is generated based on sharp versions of the blurred input image predicted using a data-driven approach based on a collection of prior edges.

Abstract: An image processing device (36) which performs blur correction on an input picture captured through a follow shot of a subject, and includes: a blur estimation unit (32) which estimates a direction and size of a blur in each of a plurality of regions in the input picture; a clustering unit (33) which performs clustering of the regions based on a similarity of the regions in at least one of the estimated direction and size of the blur; a subject region identification unit (34) which identifies at least one cluster corresponding to the subject, from among a plurality of clusters obtained through the clustering; and a blur correction unit (35) which performs blur correction on a region belonging to the identified cluster, based on the estimated direction and size of the blur.

Abstract: The image pickup apparatus includes a first detector detecting a first in-focus position by a phase difference detection method using paired image signals, a controller controlling position of a focus lens a basis of the first in-focus position to perform focusing, a second detector detecting a second in-focus position by a contrast detection method, a calculating part calculating a correction value for correcting the first in-focus position in image capturing on a basis of difference between the first and second in-focus positions, and a determining part determining a level of reliability of the first in-focus position. The controller calculates the correction value when the level of reliability is a first level, and to restrict the calculation of the correction value when the level of reliability is a second level lower than the first level.

Abstract: An auto focus image system that includes a pixel array coupled to a focus signal generator. The pixel array captures an image that has at least one edge with a width. The focus signal generator may generate a focus signal that is a function of the edge width and/or statistics of edge widths. A processor receives the focus signal and/or the statistics of edge widths and adjust a focus position of a focus lens. The edge width can be determined by various techniques including the use of gradients. A histogram of edge widths may be used to determine whether a particular image is focused or unfocused. A histogram with a large population of thin edge widths is indicative of a focused image. Edge corruption/partial corruption may be detected. Partially corrupted edge may have edge width calculated by relying more on the side that is not corrupted and less on the side that is corrupted. Edge or edge side corruption may be detected by detecting a presence of an adjacent edge of the opposite sign.

Abstract: A system and method for generating a focused image of an object is provided. The method comprises obtaining a plurality of images of an object, estimating an initial depth profile of the object, estimating a parallax parameter and a blur parameter for each pixel in the plurality of images and generating a focused image and a corrected depth profile of the object using a posterior energy function. The posterior energy function is based on the estimated parallax parameter and the blur parameter of each pixel in the plurality of images.

Abstract: An urban scenes reconstruction method includes: acquiring digital data of a three-dimensional subject, the digital data comprising a 2D photograph and a 3D scan; fusing the 3D scan and the 2D photograph to create a depth-augmented photograph; decomposing the depth-augmented photograph into a plurality of constant-depth layers; detecting repetition patterns of each constant-depth layer; and using the repetitions to enhance the 3D scan to generate a polygon-level 3D reconstruction.

Abstract: An exemplary system includes at least one detector configured to provide an output based on a detected input. A plurality of input control elements control the input detected by the detector. A processor is configured to determine at least one point spread function based on a condition of the detector, a condition of the input control elements and a selected distance associated with the output.