Abstract: An apparatus captures an image of an ID tag displaying printed ID information specific to a patient to acquire an ID-tag image, and acquires a color correction value from the ID-tag image. The color correction value is used to correct an image to be captured. The apparatus corrects a captured image of an affected area by using the color correction value.

Abstract: Systems and methods for a six-primary color system for display. A six-primary color system increases the number of primary colors available in a color system and color system equipment. Increasing the number of primary colors reduces metameric errors from viewer to viewer. The six-primary color system includes Red, Green, Blue, Cyan, Yellow, and Magenta primaries. The systems of the present invention maintain compatibility with existing color systems and equipment and provide systems for backwards compatibility with older color systems.

Abstract: A method of performing image-adaptive tone mapping includes: determining a tone mapping curve based on a data signal corresponding to an image frame to be displayed on a display panel; determining whether a scene-change occurs between the image frame and a previous image frame by comparing the data signal with a previous data signal corresponding to the previous image frame; generating, in response to a determination that the scene-change does not occur, a final tone mapping curve based on the tone mapping curve and a previous tone mapping curve, which is applied to the previous image frame; determining, in response to a determination that the scene change occurs, the tone mapping curve as the final tone mapping curve; and performing a tone mapping by applying the final tone mapping curve to the image frame.

Abstract: The current document is directed to digital-image-normalization methods and systems that generate accurate intensity mappings between the intensities in two digital images. The intensity mapping generated from two digital images is used to normalize or adjust the intensities in one image in order to produce a pair of normalized digital images to which various types of change-detection methodologies can be applied in order to extract differential data. Accurate intensity mappings facilitate accurate and robust normalization of sets of multiple digital images which, in turn, facilitates many additional types of operations carried out on sets of multiple normalized digital images, including change detection, quantitative enhancement, synthetic enhancement, and additional types of digital-image processing, including processing to remove artifacts and noise from digital images.

Abstract: Provided is an optical apparatus using reflection geometry. The optical apparatus includes a lens element disposed to face an object to be measured, a light source generating an incident beam that passes through the lens element to be incident on the object, and a photodetector receiving light that is scattered by the object. The incident beam is obliquely incident on the object off an optical center axis of the lens element, without passing through the optical center axis. The scattered light is transmitted to the photodetector by passing through the optical center axis of the focusing lens element and a region therearound.

Abstract: Systems, methods, and non-transitory computer-readable media can obtain a media item. The media item is positioned in a content item. A plurality of histograms are generated based on colors of a first portion and a second portion of the media item. A custom background for the media item in the content item is generated based on the plurality of histograms.

Abstract: A method and a digital video camera for reducing intensity variations in a video stream depicting a scene comprising capturing, using a first sensor setting, a first frame; detecting a change in intensity in a portion of the first frame, the portion represents a first area of the scene; determining a second sensor setting based on the first frame; capturing, using the second sensor setting, a second frame; creating a local tone mapping mask, wherein a local tone mapping in the first area of the scene is different from a local tone mapping in an area outside the first area, and wherein the local tone mapping in the area outside the first area is based on a relation between the first sensor setting and the second sensor setting; and applying the local tone mapping mask to the second frame.

Abstract: A handheld imaging device has a data receiver that is configured to receive reference encoded image data. The data includes reference code values, which are encoded by an external coding system. The reference code values represent reference gray levels, which are being selected using a reference grayscale display function that is based on perceptual non-linearity of human vision adapted at different light levels to spatial frequencies. The imaging device also has a data converter that is configured to access a code mapping between the reference code values and device-specific code values of the imaging device. The device-specific code values are configured to produce gray levels that are specific to the imaging device. Based on the code mapping, the data converter is configured to transcode the reference encoded image data into device-specific image data, which is encoded with the device-specific code values.

Abstract: A method for rendering an image, called a final image, from at least one image acquired by a camera array, is provided. According to such a method, the determination of a color value for at least one pixel of the final image, called a current pixel, comprises: for at least one initial image acquired by the camera array, obtaining a color value of a pixel associated with said current pixel within said at least one initial image, acquiring at least one color value called a real color value; computing at least one interpolated color value, from said at least one real color value; determining the color value for said current pixel, as a function of said at least one real color value and said at least one interpolated color value.

Abstract: An image processing apparatus includes an acquirer configured to acquire a captured image generated through imaging by an optical system, a reconstruction processor configured to reconstruct a discretized point spread function of the optical system using coefficient data used to approximate the point spread function, and a sharpening processor configured to perform unsharp mask processing for the captured image based on information on the reconstructed point spread function. A discretization interval of the reconstructed point spread function is different according to an image height.

Abstract: An apparatus for combining multiple images to form a blended image, configured to identify regions of overlap: (i) in a first image and in a second image, corresponding to where those first and second images will overlap each other in the blended image; and (ii) in the first image and in a third image, corresponding to where those first and third images will overlap each other in the blended image, identify an image quality associated with each region of overlap, determine a gain for each image that, when applied to the image as a whole, will minimise a sum of: (i) a difference between the image qualities associated with the regions of overlap in the first and second images; and (ii) a difference between the image qualities associated with the regions of overlap in the first and third images and apply the respective gains to the first, second and third images.

Abstract: One embodiment can provide a system for detecting outlines of objects in images. During operation, the system receives an image that includes at least one object, generates a random noise signal, and provides the received image and the random noise signal to a shape-regressor module, which applies a shape-regression model to predict a shape outline of an object within the received image.

Abstract: An image processing apparatus of the disclosure includes: a blocking unit configured to divide image information into blocks; a map information acquisition unit configured to acquire at least one piece of map information in which pieces of reference pixel information and pieces of positional information are associated with a target pixel in each of the blocks, the pieces of reference pixel information denoting at least one reference pixel referenced by the target pixel, each of the pieces of positional information denoting a positional relationship between the target pixel and the at least one reference pixel; and a reference pixel information selecting unit configured to select one piece of reference pixel information of the pieces of reference pixel information included in the at least one piece of map information based on a pixel value of the target pixel and a pixel value of the at least one reference pixel.

Abstract: A histogram statistics circuit and a multimedia processing system, where the multimedia processing system includes a memory, a histogram statistics circuit, and a processor. The memory is configured to store multimedia data. The histogram statistics circuit is configured to obtain the multimedia data from the memory and perform histogram statistics on the multimedia data, to generate a statistical result. The processor is configured to process the multimedia data based on the statistical result and a histogram application algorithm.

Abstract: In an image processing apparatus, a face detection unit detects a face area from an input image, and an image processing unit extracts a high luminance area from the face area to generate a correction amount of the high luminance area and corrects the high luminance area using the correction amount. Then, in a case where a plurality of face areas is detected, the image processing unit adjusts the correction amount based on feature information of the plurality of face areas.

Abstract: A computer-aided design system enables physical articles to be customized via printing or embroidering and enables digital content to be customized and electronically shared. A user interface may be generated that includes an image of a model of an article of manufacture and user customizable design areas. Customization permissions associated with a selected design area are accessed. User provided content to be used in customizing a design area may be analyzed in real time or in batch mode using a trained engine to determine if it complies with one or more rules. If the user provided content satisfies a corresponding rule, manufacturing instructions and a design file may be transmitted to a printing system.

Abstract: Various techniques are disclosed for reducing noise and enhancing sharpness of an input image. For example, a method includes performing an initial collaborative filtering and sharpening on the input image to generate a pilot image, using the pilot image to derive coefficients that are used to perform a second collaborative filtering on the input image to generate a filtered image. In some embodiments, the collaborative filtering and sharpening is performed using parameters that boost or enhance the differences in pixel values for the same spatial locations of the matched image blocks extracted during the collaborative filtering and sharpening process. Accordingly, the method according to various embodiments performs especially well for images that have weak spatial correlations among mutually similar blocks.

Abstract: A method generates images based on context-aware imaging. The method includes acquiring a first image of a patient using first image acquisition parameters. The method includes determining, within the first image, an area as a function of first data associated with the patient. The method includes determining modification data as a function of at least one of (a) second data corresponding to the determined area and (b) the first data. The method includes determining second image acquisition parameters as a function of the modification data and the first image acquisition parameters. The method includes acquiring a second image of the patient using the second image acquisition parameters.

Abstract: A computing device is provided, including a display and a processor. The processor may, for each frame of a plurality of frames included in a video, determine a brightness characterization for a region of interest of the frame. The processor may determine one or more additional brightness characterizations for the region of interest of one or more additional frames of the plurality of frames. The processor may determine that a high brightness condition is present in the region of interest. The processor may generate a filter for the frame based on the brightness characterization and the one or more additional brightness characterizations. The processor may apply the filter to the region of interest of the frame to generate a filtered frame. The high brightness condition is not present in the region of interest of the filtered frame. The processor may output the filtered frame for display at the display.

Abstract: Implementations disclosed herein include an image capture device, a system, and a method for performing multiscale denoising of an image. An image processor of the image capture device obtains a first image. The first image may be in any format and may include noise artifacts. The image processor decomposes the first image into one or more sub-images. The sub-images may range from a coarse scale to a fine scale. In some implementations, the image processor iteratively denoises each of the one or more sub-images from the coarse scale to the fine scale. The image processor reconstructs the one or more denoised sub-images to produce a denoised image. A memory of the image capture device may be configured to store the denoised image.

Abstract: The present disclosure provides a driving method and apparatus for a display apparatus. The driving method includes: selecting one of at least two partitions divided in a display interface, marking the one as a selected partition; calculating a chroma and a hue value of the selected partition; adjusting initial gray scale parameters of sub-pixel units of each of the pixel units according to the chroma and the hue value, acquiring an initial input signal of the selected partition, and adjusting the gray scale parameters corresponding to the initial input signal according to the initial input signal and the initial gray scale parameters of the sub-pixel units.

Abstract: A method for filtering noise for imaging includes receiving an image frame having position and range data. A filter size divides the frame into filter windows for processing each of the filter windows. For the first pixel, a space to the center pixel and a range difference between this pixel and the center pixel is determined and used for choosing a selected weight from weights in a 2D weight LUT including weighting for space and range difference, a filtered range value is calculated by applying the selected 2D weight to the pixel, and the range, filtered range value and selected 2D weight are summed. The determining, choosing, calculating and summing are repeated for at least the second pixel. A total sum of contributions from the first and second pixel are divided by the sum of selected 2D weights to generate a final filtered range value for the center pixel.

Abstract: An automatic teeth whitening system analyzes digital content and detects at least one teeth region in the digital content. A teeth region refers to a region or portion of the digital content that includes teeth (e.g., human teeth), and the teeth region detection includes identifying each pixel that displays part of the teeth using instance segmentation. The automatic teeth whitening system also finds the visual structure of each tooth in the teeth region using instance contours specific to the tooth. After finding the teeth region and the visual structure of each tooth in the teeth region, a whitening process is applied to the teeth to whiten them. The whitening of the teeth is performed automatically—manual steps by the user of selecting teeth regions and coloring the teeth in those regions are avoided.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include accessing an image from an image sensor; detecting an object area on the image; classifying the object area on the image; applying a filter to an object area of the image to obtain a low-frequency component image and a high-frequency component image; determining a first enhanced image based on a weighted sum of the low-frequency component image and the high-frequency component image, where the high-frequency component image is weighted more than the low-frequency component image; determining a second enhanced image based on the first enhanced image and a tone mapping; and storing, displaying, or transmitting an output image based on the second enhanced image.

Abstract: The present disclosure proposes an image adjustment method, including: determining a distance between a user and a display apparatus; determining, according to a relationship between the distance and a foreground image or a background image displayed on the display apparatus, a target image to which action information of the user is directed, wherein the target image comprises at least one of the foreground image and the background image; determining an adjustment manner corresponding to the action information of the user; and adjusting the target image according to the adjustment manner.

Abstract: An image comprising a set of pixels is obtained and a dominant hue is determined. A color value of individual pixels in a subset of the set of pixels that fall within the hue range is modified to produce a first transformed image. A filter is applied to the first transformed image or an image derived from the first transformed image to reduce spatial high frequency noise and derive a low frequency image. A high frequency image is generated based on the first transformed image and the low frequency image. Whether the high frequency image depicts the object at a target image frequency is determined based on specified criteria for an object, and if the high frequency image corresponds to the target image frequency, the high frequency image is stored.

Abstract: The present application relates to a detection method, belonging to the technical field of anti-fake detection. The detection method comprises steps of: acquiring reference imaging spectral data and imaging spectral data of a surface of an object to be detected; obtaining spectral reflectance of the surface of the object to be detected according to the reference imaging spectral data and the imaging spectral data of the surface of the object to be detected; matching the spectral reflectance of the object to be detected with spectral reflectance, stored in a calibration library, of an original object corresponding to the object to be detected; determining that the object to be detected is consistent with the original object if the matching of spectral reflectance is successful; and determining that the object to be detected is not consistent with the original object if the matching of spectral reflectance is failed.

Abstract: A vehicle device includes a video acquisition unit configured to acquire videos captured by cameras configured to capture surroundings of a vehicle; a light emission controller configured to control light emission of a light beam pattern which is emitted by light emitting devices and with which the ground is irradiated at certain positions with respect to the vehicle; an image processing unit 24 configured to generate, using the videos acquired, a bird's-eye view video including the light beam pattern; a superimposing image generation unit configured to generate a superimposing image at a position corresponding to the light beam pattern included in the bird's-eye view video; and an image determination processing unit 27 configured to detect, in the bird's-eye view video, an overlapping portion of the superimposing image and an image of the light beam pattern and determine whether camera parameters for generating the bird's-eye view video are accurately calibrated.

Abstract: Disclosed herein are methods and apparatus for making measurements using a single image capture device.

Abstract: Systems and methods for controlling camera settings of a camera to improve detection of faces in an uncontrolled environment are described. A first image is received from the camera, where the first image is captured by the camera at a first set of camera settings. A face is detected in the first image. The camera is adjusted to a second set of camera settings based on the detected face, where the second set of camera settings different from the first set of camera settings. A second image is received from the camera, where the second image is captured by the camera at the second set of camera settings. The face is detected in the second image. A quality metric of the face in the second image is determined where the quality metric is indicative of an image quality of the face in the second image.

Abstract: Embodiments relate to generation of hue maps for highlight recovery of an input image. An image having a plurality of color channels is obtained at a first resolution lower than a resolution of the input image. A hue for each color channel for each pixel is determined, using a pixel value for that color channel and pixel values for the plurality of color channels in the first image. Weights are determined for each pixel for each color channel, based on hues for the pixel and pixel values for the pixel in the first image. A plurality of candidate hue maps are generated, based on the weights and pixel values in the first image in a patch surrounding the pixel for the plurality of color channels.

Abstract: An image processing apparatus (100) includes a synthetic image acquirer (24) for acquiring a plurality of smoothed images different from each other, in which noise components have been smoothed on an image to be processed, and that is operable to perform weighted synthesis of the smoothed images based on pixel value differences between a pixel value of a pixel of the image to be processed and pixel values of pixels of the acquired smoothed images, in which a positive and a negative have been taken into consideration.

Abstract: The present disclosure discloses a method and apparatus for determining a pupil position. The method includes that: at least one first parameter of a pupil in an image, an initial edge region of the pupil and at least one second parameter of at least one light spot in the image are acquired; the initial edge region is corrected according to the at least one first parameter and the at least one second parameter to obtain a first edge region; a pupil edge region is determined according to an edge section in the first edge region, and the edge section is a region formed by a point set meeting a first preset condition in the first edge region; and fitting processing is performed on the pupil edge region to obtain a position of the pupil.

Abstract: The invention relates to a method for encoding HDR images, of the type wherein the HDR image is encoded in a first data stream containing a LDR image with colour range lower than that of the HDR image, and in a second data stream containing a residual image obtained from the HDR image and from the LDR image.

Abstract: Image data stored in a spool memory and respectively corresponding to a plurality of colors is read and sequentially decompressed, and image forming processing is performed based on the decompressed image data. In the decompression, the image data respectively corresponding to the plurality of colors is sequentially decompressed, switching between decompression target data in units of bands.

Abstract: Encoding and decoding systems disclosed enhance the AV1/VPX codecs in the context of 8-bit SDR video and 10-bit HDR video content, for applications including streaming and high quality coding for content contribution editing. For SDR content, lapped biorthogonal transforms for near lossless applications and used and optimized resampling filter pairs for adaptive resolution coding in streaming applications are used. For HDR content, a data adaptive grading technique in conjunction with the VP9/VP10 encoder may be used. The encoding/decoding system provides substantial value in the coding of HDR content, and provides backward compatibility with SDR.

Abstract: The disclosure concerns a method for filtering spurious pixels in a depth-map. It is important to filter a depth-map to remove the spurious pixels. One issue when filtering spurious pixels, is to remove them while preserving the boundaries of the real details of the depth-map. A known approach to filter spurious pixels is to use a bi-lateral filter. However, the bi-lateral filter is not efficient to remove the spurious pixels. The proposed solution enables to remove spurious pixels in a depth-map while preserving the sharp edges of the depth-map and smoothing faint details or noise.

Abstract: The adjustment method includes: acquiring a first component, a second component, and a third component of each of the pixel units in the pixel area in a first color space; acquiring a tone angle value and a saturation in a second color space according to an average value of the first component, an average value of the second component, and an average value of the third component of the pixel unit in the pixel area; acquiring specified lightness of a blue backlight module and a green backlight module in the backlight module area according to the tone angle value and the saturation; and performing at least one of the following two steps: adjusting lightness of the blue backlight module according to the specified lightness of the blue backlight module; and adjusting lightness of the green backlight module according to the specified lightness of the green backlight module.

Abstract: Embodiments of the present disclosure provide a maximum connected domain marking method, a target tracking method and an AR (Augmented Reality)/VR (Virtual Reality) apparatus, and relate to the field of image processing technology, and can obtain the maximum connected domain. A maximum connected domain marking method comprises: marking connected domains of pixels of a binary image and recording equivalent relationships; merging the equivalent connected domains according to the equivalent relationships, for pixels with the equivalent relationships in the marked results; counting the number of pixels in each merged connected domain; determining a connected domain label for the maximum connected domain according to the counted number of pixels in each connected domain; and determining coordinates of boundary pixels in the maximum connected domain based on the connected domain label.

Abstract: An apparatus for classifying a defect generated in a substrate, includes: a first storage part for storing a first image data for defect classification determination, which includes a defect region in which the defect is generated and a surrounding region of the defect region; a first estimation part for estimating a first type of defect by using a deep learning system, based on the first image data; a second storage part for storing a second image data for defect classification estimation, which is obtained by expressing the defect region and the surrounding region by a binarized data; a second estimation part for estimating a second type of defect by using a rule-based system, based on an attribute of the defect region extracted from the second image data; and a comprehensive determination part for comprehensively determining a type of defect based on the first and second types of defects.

Abstract: A content analyzer determines whether various types of modification have been made to images. The content analyzer computes JPEG ghosts from the images that are concatenated with the image channels to generate a feature vector. The feature vector is provided as input to a neural network that determines whether the types of modification have been made to the image. The neural network may include a constrained convolution layer and several unconstrained convolution layers. An image fake model may also be applied to determine whether the image was generated using a computer model or algorithm.

Abstract: A detection system including a light source, an image sensor and a processor is provided. The light source is configured to illuminate an object. The image sensor is configured to output a picture. The processor is configured to generate an IR picture and a color picture according to the picture captured by the image sensor, identify a skin-color object in the color picture and determine an object image in the IR picture according to the skin-color object.

Abstract: Systems and methods for imaging a target object are provided. In one example, a multispectral imager includes an objective lens configured to disperse light from a target object with a high degree of longitudinal chromatic aberrations along an optical axis of the objective lens. The multispectral imager also includes a sensor configured to capture a whole image of the target object at each of a plurality of wavelengths when at least one of the objective lens and the sensor is moved along the optical axis. Furthermore, the multispectral imager includes a processor configured to analyze intensities of different additive primary colors of each pixel of each whole image to determine which pixels have a correct wavelength.

Abstract: A method of gamut mapping and color gamut mapping apparatus comprises: acquiring the Lab value of the color point in the original color gamut; and determining the color point in the original color gamut relative to the coordinate location in a hue plane based on the Lab value; and determining the mapping target gamut of the color point based on the coordinate location; If a color point is located outside the mapping target area, it determining the first intersection point of the line connecting the color point and the maximum brightness and the borderline of the mapping target color gamut and the second intersection point of the color point relative to the borderline of the mapping target gamut, and finally according to the preset adjustment parameter, the mapping point being determined on the borderline of the mapping target color gamut relative to the color point.

Abstract: A change of a color tone of an image to be displayed is suppressed. A liquid crystal display device (1) displays an original image having a first dynamic range in a second dynamic range narrower than the first dynamic range. The liquid crystal display device includes a display control circuit (50) that lowers luminance of a dominant color having luminance higher than predetermined luminance to the predetermined luminance or less and lowers luminance of a non-dominant color.

Abstract: Image signal processing may include desaturation control, which may include adaptive desaturation control. Image signal processing with desaturation control may include obtaining, by an image signal processor, from an image sensor, an input image signal representing an input image, obtaining, by the image signal processor, color correction information for the input image, obtaining a color corrected image based on the input image using color correction with desaturation control such that inaccurate colorization of the color corrected image is minimized, and outputting the color corrected image.

Abstract: Techniques for authentication and authorization of a user, an application, or a user device for access to web resources are described. For example, a machine identifies an access request to access a remote resource associated with a web service. The access request may be received from an application executing at a user device. The machine retrieves at least one user artifact from a security manager identifier received from the web service. The machine performs fingerprinting of the user device based on the at least one user artifact. The machine transmits the access request to the web service based on the performing of the fingerprinting of the user device. The machine, in response to the transmitting of the access request to the web service, receives a resource access authorization from the web service for the application executing at the user device.

Abstract: The present invention discloses a false color removal method comprising: receiving a current pixel including a first color value, a second color value and a third color value, in which the three color values are composed of a maximum value, a medium value and a minimum value; performing permutation to the maximum value, the medium value and the minimum value to obtain six permutation results; calculating six weighting values, in which a kth weighting value is calculated according to at least a kth permutation result of the six permutation results and the three color values, and the k stands for an integer-variable between one and six; calculating six products, in which a kth product is obtained by multiplying the kth weighting value by the kth permutation result; and using the sum of the six products to update the first, second and third color values.

Abstract: A color gamut mapping method and a color gamut mapping device is provided, the method includes: determining a mapping target color gamut; obtaining a Lab value of a color point in the original color gamut, and determining a coordinate position of the color point in a corresponding tone plane of the original color gamut; judging the color point position; determining an intersection of a horizontal line the color point located and a boundary of the original color gamut, and a boundary of the mapping target color gamut; and determining a mapping point of the color point on the boundary of the map target color gamut by a ratio of an area of a pattern formed by the intersection, and an intersection of the original color gamut and a coordinate axis, and a difference between the area of the original color gamut and the area of the mapping target color gamut.

Abstract: An auto white balance method is disclosed. The auto white balance method includes receiving image data to divide the image data into a plurality of partition cells, calculating an estimation value of a skin tone included in the image data, and selecting outliers for detection of a white point of the image data, based on at least some of the plurality of partition cells and the estimation value.