Abstract: A method to denoise low dose CT images without introducing blurriness is shown using cross directional bilateral filtering. Techniques are provided that (1) enhance low-radiation dosage images, beyond just reducing noise, and (2) may be combined with other approaches, such as adaptive exposure techniques and iterative reconstruction, for radiation dose reduction.

Abstract: A method for controlling a terminal is provided. The terminal includes a capturing apparatus and at least one processor. An image is acquired by the capturing apparatus. A motion parameter of the terminal is obtained. Image processing on the acquired image is controlled to be performed based on the motion parameter being equal to or less than a preset parameter threshold, and skipped based on the motion parameter being greater than the preset parameter threshold.

Abstract: An image processing device is provided that includes: an acquisition unit that acquires a plurality of viewpoint images which are captured at a plurality of different viewpoints by an imaging unit; a detection unit that detects viewpoint-relevant information between the plurality of viewpoint images; a determination unit that determines a second imaging condition in which image change between before and after predetermined image processing is greater than that in a first imaging condition in which the plurality of viewpoint images are captured on the basis of the first imaging condition and the viewpoint-relevant information; and an output unit that outputs the second imaging condition determined by the determination unit.

Abstract: A method for restoring images in a sequence of images, including, when it is applied to a first image in the image sequence: estimating an item of information representing a global motion of a background of the first image with respect to a second image; compensating for said global motion of the background in the second image in order to obtain an adjusted version of the second image, referred to as the adjusted second image; obtaining a contour of an object of the first image by applying a segmentation method using the adjusted second image; using the contour of the object thus obtained in order to estimate an item of information representing a global motion of the object; and applying to the first image an image restoration method using the information representing the estimated global motion of the background and the estimated global motion of the object.

Abstract: The disclosure features systems and methods for providing information to a user about the user's environment. The systems feature a detection apparatus configured to obtain image information about the environment, where the image information corresponds to information at multiple distances relative to a position of the user within the environment, and an electronic processor configured to obtain focal plane distance information defining a set of one or more distance values relative to the position of the user within the environment, construct one or more confocal images of the environment from the image information and the set of one or more distance values, wherein each of the one or more confocal images corresponds to a different distance value and includes a set of pixels, and transform the one or more confocal images to form one or more representative images having fewer pixels and a lower dynamic range.

Abstract: In an image processing apparatus of the present invention, multiple subjects are selected in an image signal, and subject distances for focusing on each of the selected subjects are specified. A subject distance range defined by the specified subject distances is then set. Then, based on the image signal, the image processing apparatus generates a reconstructed image that is focused on each of the subjects that are to be focused on in the set subject distance range.

Abstract: Techniques of generating depth-of-field blur effects on digital images by digital effect generation system of a computing device are described. The digital effect generation system is configured to generate depth-of-field blur effects on objects based on focal depth value that defines a depth plane in the digital image and a aperture value that defines an intensity of blur effect applied to the digital image. The digital effect generation system is also configured to improve the accuracy with which depth-of-field blur effects are generated by performing up-sampling operations and implementing a unique focal loss algorithm that minimizes the focal loss within digital images effectively.

Abstract: A system and method for improving a video characteristic of a video stream is described. According to various implementations of the invention, a changed region between a later-in-time image frame and an earlier-in-time image frame and an unchanged region between such two image frames are determined. A new improvement to the video characteristic is determined and applied to the changed region of the later-in-time image frame. A prior improvement to the video characteristic that was determined for the earlier-in-time image frame is applied to the unchanged region of the later-in-time image frame.

Abstract: A computing system can receive an image including foreground pixels. The foreground pixels can be determined based on determining eccentricity ?k based on a sequence of images acquired by a stationary sensor. The vehicle can determine moving objects in the image based on the foreground pixels. The vehicle can be operated based on the moving objects in the image.

Abstract: A pulsed laser may illuminate a scene that is obscured by dense, dynamic and heterogeneous fog. Light may reflect back to a time-resolved camera. Each pixel of the camera may detect a single photon during each frame. The imaging system may accurately determine reflectance and depth of the fog-obscured target, without any calibration or prior knowledge of the scene depth. The imaging system may perform a probabilistic algorithm that exploits the fact that times of arrival of photons reflected from fog have a Gamma distribution that is different than the Gaussian distribution of times of arrival of photons reflected from the target. The probabilistic algorithm may take into account times of arrival of all types of measured photons, including scattered and un-scattered photons.

Abstract: A method for determining a local contrast value for a digital image captured by an image sensor in a camera comprising: applying an edge detection algorithm to image data of the digital image, thereby obtaining a data set pertaining to edges in the digital image; calculating, based on said data set, an edge occurrence value for the digital image; estimating, based on image data of the digital image and a noise model of the image sensor, an estimated image sensor noise for the digital image; and computing the local contrast value as a relationship between the edge occurrence value of the digital image and the expected edge occurrence value for the digital image. A method for adjusting a focus setting of a camera using the local contrast value for images captured by the camera.

Abstract: An electronic device may include noise statistics circuitry to receive input image data corresponding to an image displayable on an electronic display. The input image data may include one or more channels of pixel data. The noise statistics circuitry may also determine a subset of pixel data of a channel of pixel data that qualifies for statistics gathering according to qualification criteria. Additionally, the noise statistics circuitry may determine noise statistics based on the subset of pixel data, and identify image features within the subset of pixel data based on the noise statistics. The image features may include frequency signatures, differentiated from noise, that correspond to features of content of the image. The electronic device may also include enhancement circuitry to enhance the input image data based on the noise statistics and the identified image features. Such enhancement circuitry may substantially preserve the image features within the input image data.

Abstract: There is provided an image processing apparatus. A focal position determining unit determines, for each of a plurality of captured image data, a focal position in a depth direction at a target position. The focal position determining unit determines a position at which a subject at the target position is in focus as the focal position if a first focus mode has been selected by a selecting unit, and determines the focal position for each of the plurality of captured image data such that the focal positions track a position at which a subject at the target position is in focus at a speed that is less than or equal to a threshold value, in an order of generation of the plurality of captured image data, if a second focus mode has been selected by the selecting unit.

Abstract: A device and algorithm for allowing a customer to choose a photo book cover template that is compatible with a photo having faces. The photo is compared with a set of templates arranged in a first order to determine how compatible the photo is to each of the templates, and a score indicative of compatibility is assigned. A re-sorted set of compatible templates combined with the photo is presented to the customer for consideration.

Abstract: An anisotropic filtering method for deblurring complex seismic images from seismic data acquired from anisotropic earth formation. The algorithm is tested using synthetic data. Results demonstrate its effectiveness.

Abstract: An image processing apparatus includes: a memory configured to acquire a plurality of visual point images; a visual point change processing unit configured to perform image processing on image data based on the plurality of visual point images to generate a combination image; an area designation unit configured to designate an area subjected to the image processing using the visual point change processing unit; and an adjustment unit configured to set an adjustable range of the image processing for each area designated by the area designation unit.

Abstract: A digital photographing method and apparatus include determining a motion vector of an object in a preview image, determining whether the motion vector meets a predetermined condition and, when it does, generating an image capturing signal to photograph a scene desired by a user.

Abstract: Embodiments described herein provide for a distributed antenna system (DAS) including a host unit and a plurality of active antenna units (AAUs). The host unit is configured to send management information to the one or more RAN nodes. The one or more RAN nodes are configured to manage the RF signals based on the management information.

Abstract: Systems and methods for detecting image anomalies include extracting one or more detected images from a submission file received from at least one computing device and generating an image identification (ID) for each of the one or more images. One or more image quality indices are determined for the submission file based on at least one of predetermined image features, an image type of the one or more images, and submission file attributes, and one or more image anomalies associated with the one or more images of the submission file are detected based on at least one of the image ID and the one or more image quality indices.

Abstract: An image processing apparatus capable of acquiring images with high visibility is provided. A system control circuit of an image processing apparatus acquires the turning speed of the image capturing device capable of being turned, determines a first intensity as the intensity of noise reduction processing when the turning speed is higher than a speed in a predetermined speed range, and determines a second intensity lower than the first intensity as the intensity of the noise reduction processing when the turning speed is within the predetermined speed range. An image processing circuit of the image processing apparatus performs the noise reduction processing on an image of a target frame, which is one of a plurality of images of frames captured by the image capturing device, at the determined intensity, based on the image of the target frame and an image of a frame preceding the target frame.

Abstract: An imaging device including a pixel matrix and a processor is provided. The pixel matrix includes a plurality of phase detection pixels and a plurality of regular pixels. The processor performs autofocusing according to pixel data of the phase detection pixels, and determines an operating resolution of the regular pixels according to autofocused pixel data of the phase detection pixels, wherein the phase detection pixels are always-on pixels and the regular pixels are selectively turned on after the autofocusing is accomplished.

Abstract: An image combining device, comprising a memory that stores a plurality of images for different focus positions, and focus positions when the plurality of images were acquired, a plurality of image processing circuits that combine the plurality of images for different focus positions to generate a combined image, and a processor that sets assignment for distributing the plurality of images for different focus positions to the plurality of image processing circuits, wherein the processor makes images for at least one focus position, among the plurality of images for different focus positions, a plural distribution image and distributes this plural distribution image to the plurality of image processing circuits, and sets assignment so that images other than the plural distribution image are distributed to any one of the plurality of image processing circuits.

Abstract: Systems, methods, and media for providing interactive refocusing are provided, the systems comprising: a lens; an image sensor; and a processor that: causes the image sensor to capture a plurality of images over a predetermined period of time, wherein each of the plurality of images represents a scene at a different point in time; changes a depth of field between at least a pair of the plurality of images; concatenates the plurality of images to create a duration focal volume in the order in which the images were captured; computes a space-time in-focus image that represents in-focus portions from each of the plurality of images based on the duration focal volume; and computes a space-time index map that identifies an in-focus image for each location of the scene from among the plurality of images based on the duration focal volume and the space-time in-focus image.

Abstract: An imaging apparatus and method enables an automated extended depth of field capability that automates and simplifies the process of creating extended depth of field images. An embodiment automates the acquisition of an image “stack” or sequence and stores metadata at the time of image acquisition that facilitates production of a composite image having an extended depth of field from at least a portion of the images in the acquired sequence. An embodiment allows a user to specify, either at the time of image capture or at the time the composite image is created, a range of distances that the user wishes to have in focus within the composite image. An embodiment provides an on-board capability to produce a composite, extended depth of field image from the image stack. One embodiment allows the user to import the image stack into an image-processing software application that produces the composite image.

Abstract: An information processing device acquiring to the present invention includes: a CPU; and a memory storing a program, wherein the CPU, by the program, configures: a variation-amount calculating unit that, for an input image, calculates a variation amount between a value of a predetermined pixel of the input image and values of peripheral pixels of the predetermined pixel; an attribute reliability unit that, based on an attribute that is a property of pixels within a specified area in the input image and the variation amount, calculates attribute reliability of the pixel; a regularization strength estimating unit that, based on image quality information about image quality for the attribute and the attribute reliability, estimates a regularization strength of the pixel; and an image reconstructing unit generates a reconstructed image that is an image acquired by reconstructing the input image by using the regularization strength.

Abstract: Methods and apparatus for estimating a depth of unfocused plenoptic data are suggested. The method includes: determining a level of homogeneity of micro-lens images of unfocused plenoptic data; determining pixels of the micro-lens images of the unfocused plenoptic unfocused plenoptic data which either have disparities equal to zero or belong to homogeneous areas as a function of the calculated level of homogeneity of the micro-lens images of the unfocused plenoptic data; and estimating the depth of the unfocused plenoptic data by a disparity estimation without considering the determined pixels. With the disclosure, by pre-processing the raw data, it can prevent any disparity estimation method to spend time on estimating disparities for: (i) pixels that are in focus, (ii) pixels that belong to homogenous areas of the scene.

Abstract: A device and algorithm for allowing a customer to choose a photo book cover template that is compatible with a photo having faces. The photo is compared with a set of templates arranged in a first order to determine how compatible the photo is to each of the templates, and a score indicative of compatibility is assigned. A re-sorted set of compatible templates combined with the photo is presented to the customer for consideration.

Abstract: According to one implementation, a video processing system includes a computing platform having a hardware processor and a system memory storing a sample-based video sharpening software code. The sample-based video sharpening software code receives a video sequence, and classifies frames of the video sequence as sharp or unsharp. For each pixel of an unsharp frame, the sample-based video sharpening software code determines a mapping of the pixel to another pixel in some or all of the sharp frames, determines a reverse mapping of each of the other pixels to the pixel, identifies a first confidence value corresponding to each of the other pixels based on the mapping, identifies a second confidence value corresponding to each of the other pixels based on the mapping and the reverse mapping, and sharpens the pixel based on a weighted combination of the other pixels determined using the first and second confidence values.

Abstract: The disclosure extends to methods, systems, and apparatuses for automated fixation generation and more particularly relates to generation of synthetic saliency maps. A method for generating saliency information includes receiving a first image and an indication of one or more sub-regions within the first image corresponding to one or more objects of interest. The method includes generating and storing a label image by creating an intermediate image having one or more random points. The random points have a first color in regions corresponding to the sub-regions and a remainder of the intermediate image having a second color. Generating and storing the label image further includes applying a Gaussian blur to the intermediate image.

Abstract: A vehicle includes a camera and processor(s) configured to: record images via the camera; combine the recorded images; identify edges in the combined image by comparing each pixel of the combined image to a threshold; update dimensions of the vehicle based on the identified edges; execute an automatic parking routine based on the updated dimensions.

Abstract: A method of generating, by means of a processing device, a depth map and/or a fully focused image of a scene, from a series of images of the scene taken under a same viewing angle but with a different focusing, the method including the steps of: a) for each position of a pixel in the series of images, searching for an extremum of the pixel value in the series of images; and b1) assigning to said pixel position a depth value which is a function of the rank, in the series of images, of the image where the extremum has been identified at step a) to construct a depth map of the scene, and/or b2) assigning to said pixel position the value of the extremum identified at step a) to construct a fully focused image of the scene.

Abstract: A method is provided. The method includes activating an anti-shake mode for an electronic display. The method includes, in response to activating the anti-shake mode, identifying movement of a user relative to the electronic display at least based on processing of a plurality of captured images of at least part of the user, and transforming an image displayed on the electronic display based on the identified movement of the user. A computing device is also provided.

Abstract: Methods and apparatus for displaying information from a three dimensional imaging data cube, having particular application in ophthalmology, are disclosed. The method of the present invention slices 3D imaging data along curved surfaces that match anatomical layers, and comprising four steps: a locating step in which anatomical layers are located; a selecting step in which a slicing surface is selected based on the locations of the anatomical layers; an extracting step, wherein the user extracts data values that fall on the slicing surface selected; and a displaying step in which the data values extracted are displayed as a three dimensional image. The apparatus of the subject invention comprises hardware and software that employ the method of the subject invention to display improved anatomical 3D images.

Abstract: A system, device, and method for controlling a remotely-controlled device are disclosed. The remotely-controlled device control system could include one or more remotely-controlled devices; a controller comprised of a data collection module, at least one active module, at least one module description file (MDF), a robot description file (RDF) for each remotely-controlled device, and a processing unit (PU); at least one data source, and a marketplace. The PU may be configured to receive at least one active module; receive, for each received active module, input data of its associated MDF provided by the data collection module; generate, for each received active module, output data as a function of to the input data received by the processing unit, and provide the output data to a destination system.

Abstract: This disclosure relates to techniques for synthesizing out of focus effects in digital images. Digital single-lens reflex (DSLR) cameras and other cameras having wide aperture lenses typically capture images with a shallow depth of field (SDOF). SDOF photography is often used in portrait photography, since it emphasizes the subject, while deemphasizing the background via blurring. Simulating this kind of blurring using a large depth of field (LDOF) camera may require a large amount of computational resources, i.e., in order to simulate the physical effects of using a wide aperture lens while constructing a synthetic SDOF image. However, cameras having smaller lens apertures, such as mobile phones, may not have the processing power to simulate the spreading of all background light sources in a reasonable amount of time. Thus, described herein are techniques to synthesize out-of-focus background blurring effects in a computationally-efficient manner for images captured by LDOF cameras.

Abstract: Techniques are disclosed for estimating quality of images in an automated fashion. According to these techniques, a source image may be downsampled to generate at least two downsampled images at different levels of downsampling. Blurriness of the images may be estimated starting with a most-heavily downsampled image. Blocks of a given image may be evaluated for blurriness and, when a block of a given image is estimated to be blurry, the block of the image and co-located blocks of higher resolution image(s) may be designated as blurry. Thereafter, a blurriness score may be calculated for the source image from the number of blocks of the source image designated as blurry.

Abstract: A method for obtaining a refocused image from a 4D raw light field data for a given focus (zfocus) is described. The method is remarkable in that it comprises applying a shift correction parameter on shifted and summed images from said 4D raw light field data, the shifted and summed images being defined as a function of the given focus (zfocus), and the shift correction parameter (?) including, for at least a part of pixels of at least two sub-aperture images derived from at least one 4D light field data of a test-chart image, determined shifts for pixels belonging to the part of pixels between the at least two sub-aperture images, the test-chart image comprising patterns adequate to compute disparities between the sub-apertures images.

Abstract: A method for image de-blurring includes estimating an intermediate image L by marking and constraining an edge region and a smooth region in an input image; estimating a blur kernel k by extracting salient edges from the intermediate image L, wherein the salient edges have scales greater than those of the blur kernel k; and restoring the input image to a clear image by performing non-blind deconvolution on the input image and the estimated blur kernel k. Imposing constraints on the edge region and the smooth region allows the intermediate image to maintain the edge while effectively removing noise and ringing artifacts in the smooth region. The use of the salient edges in the intermediate image L enables more accurate blur kernel estimation. Performing non-blind deconvolution on the input image and the estimated blur kernel k restores the input image to a clear image achieving desired de-blurring effect.

Abstract: Systems and methods for the manipulation of captured light fields and captured light field image data in accordance with embodiments of the invention are disclosed. In one embodiment of the invention, a system for manipulating captured light field image data includes a processor, a display, a user input device, and a memory, wherein a depth map includes depth information for one or more pixels in the image data, and wherein an image manipulation application configures the processor to display a first synthesized image, receive user input data identifying a region within the first synthesized image, determine boundary data for the identified region using the depth map, receive user input data identifying at least one action, and perform the received action using the boundary data and the captured light field image data.

Abstract: An image processing apparatus that performs inspection or measurement of an object included in an image, the image processing apparatus receiving operation from a user, selecting second image processing information, which is information indicating second image processing configured by a plurality of kinds of first image processing, on the basis of the received operation, and performing editing of the plurality of kinds of first image processing configuring the second image processing indicated by the second image processing information.

Abstract: Systems, methods, and computer readable media for adaptively selecting what portion (aka slice) of a first image (aka frame) is selected to overlap and blend with a second frame during frame capture operations are disclosed. In general, for every new frame captured in a sequence the overlap between it and the slice selected from a prior frame may be determined based, at least in part, on sensor output. If the overlap so determined is below a desired threshold, the position of the current frame's slice may be adjusted so as to provide the desired overlap.

Abstract: A method for deblurring a blurry image (400) includes the steps of: performing a first phase of deconvolution (202) with a first phase regularization spatial mask (300) to reconstruct the main edges and generate a first phase latent sharp image (404) having reconstructed main edges; and performing a second phase of deconvolution (204) with a second phase regularization spatial mask (304) to reconstruct the texture and generate a second phase latent sharp image (406). The second phase regularization spatial mask (304) can be different from the first phase regularization spatial mask (300).

Abstract: Exemplary embodiments of the invention as described herein generally provide for detecting the displacement of feature(s) within a visual image in cases where pattern matching fails due to the existence of aperture(s) caused for example by external condition(s) encountered in recording such an image over time. Technique(s) are disclosed for detecting the difference between displacement of a geometric feature of an object appearing within an image (e.g., an edge or smooth surface) that has an aperture and another feature (e.g., a corner) that does not since it is not symmetrically invariant.

Abstract: Systems, methods, and devices for training models or algorithms for classifying or detecting particles or materials in microscopy images are disclosed. A method includes receiving a plurality of microscopy images of a specimen and a classification for the specimen. The plurality of microscopy images includes a first image captured at a first magnification and a second image captured at the first magnification with a different focus than the first image. The method includes training a machine learning model or algorithm using the plurality of images, wherein the first image and the second image are provided with one or more labels indicating the classification.

Abstract: Provided is a method of controlling an electronic apparatus. The method includes: generating a focus map that indicates focus values of a plurality of blocks defined by splitting a field; continuously capturing a plurality of images corresponding to the focus values in the focus map; and storing the plurality of images, focus value information of each of the plurality of images, and focus value information of the field.

Abstract: A method including receiving input data representing an input frame of a video. Transformation data representing at least one transformation for applying to an image to adjust a geometric distortion of the image is received. A first and second plurality of input tiles, each including a respective portion of the input frame, is processed with at least part of the transformation data, thereby generating first and second sub-window data representing a first and second sub-window of an output frame of the video, respectively.

Abstract: A gaze contingent display technique for providing a human viewer with an enhanced three-dimensional experience not requiring stereoscopic viewing aids. Methods are shown which allow users to view plenoptic still images or plenoptic videos incorporating gaze-contingent refocusing operations in order to enhance spatial perception. Methods are also shown which allow the use of embedded markers in a plenoptic video feed signifying a change of scene incorporating initial depth plane settings for each such scene. Methods are also introduced which allow a novel mode of transitioning between different depth planes wherein the user's experience is optimized in such a way that these transitions trick the human eye into perceiving enhanced depth. This disclosure also introduces a system of a display device which comprises gaze-contingent refocusing capability in such a way that depth perception by the user is significantly enhanced compared to prior art.

Abstract: A multi-depth-interval refocusing method, apparatus and electronic device are provided. The method includes displaying an image on a display device; acquiring user input, and determining, in the displayed image according to the user input, a refocus area including at least two discontinuous depth intervals, where each depth interval in the at least two discontinuous depth intervals is constituted by at least one depth plane, each depth plane contains at least one focus pixel, and depths of object points corresponding to focus pixels contained on a same depth plane are the same; performing refocusing processing on an image within the refocus area to display a refocused image on the display device, where the refocused image has a visually distinguishable definition difference relative to an area, except the refocus area, in the displayed image; and displaying the refocused image on the display device. Therefore, multi-depth-interval refocusing is implemented.

Abstract: Near-eye display systems in accordance with embodiments of the invention enable accommodation-invariant display control. One embodiment includes a near-eye display; a processor; a memory containing a target image and an accommodation-invariant display application; where the processor is configured by the accommodation-invariant display application to calculate an impulse response of the near-eye display; calculate a compensation image by generating a deconvolved color channel of the target image using a ratio of the target image and the impulse response, where the compensation image is a representation of the target image that remains in focus at a plurality of distances from the near-eye display; and display the compensation image on the near-eye display.

Abstract: An image processing method is provided. The image sensor is controlled to output the merged image. The depth-of-field area is identified based on the merged image. The image sensor is controlled to output the color-block image. A first part of the color-block image within the depth-of-field area is converted into a first simulation image using a first interpolation algorithm. The second part of the color-block image outside the depth-of-field area is converted into a second simulation image using a second interpolation algorithm. The first simulation image and the second simulation image are merged to generate a simulation image corresponding to the color-block image.