Abstract: Systems and methods described herein relate, among other things, to unmixing more than three stains, while preserving the biological constraints of the biomarkers. Unlimited numbers of markers may be unmixed from a limited-channel image, such as an RGB image, without adding any mathematical complicity to the model. Known co-localization information of different biomarkers within the same tissue section enables defining fixed upper bounds for the number of stains at one pixel. A group sparsity model may be leveraged to explicitly model the fractions of stain contributions from the co-localized biomarkers into one group to yield a least squares solution within the group. A sparse solution may be obtained among the groups to ensure that only a small number of groups with a total number of stains being less than the upper bound are activated.

Abstract: This document relates to hybrid eye center localization using machine learning, namely cascaded regression and hand-crafted model fitting to improve a computer. There are proposed systems and methods of eye center (iris) detection using a cascade regressor (cascade of regression forests) as well as systems and methods for training a cascaded regressor. For detection, the eyes are detected using a facial feature alignment method. The robustness of localization is improved by using both advanced features and powerful regression machinery. Localization is made more accurate by adding a robust circle fitting post-processing step. Finally, using a simple hand-crafted method for eye center localization, there is provided a method to train the cascaded regressor without the need for manually annotated training data. Evaluation of the approach shows that it achieves state-of-the-art performance.

Abstract: Systems and methods are disclosed for non-linear color correction. The method including receiving an input image from an image sensor, converting the input image from a red, green, blue (RGB) color space format to an alternate color space format, determining localized hue correction parameters for a selected color in the alternate color space, determining localized saturation correction parameters for a selected hue in the alternate color space, applying the localized hue correction parameters and the localized saturation correction parameters to the input image to generate an output image and storing, displaying, or transmitting the output image based on at least the localized hue correction parameters and the localized saturation correction parameters.

Abstract: An imaging method of a fluorescent image performs image processing before generating colored-fluorescent images, including steps: respectively imaging the red, green and blue lights of the white light on three monochromatic sensors under the precondition that the software processing speed is not affected; imaging the near infrared fluorescent light on one of the monochromatic sensors; determining whether the sensor used to receive the near infrared fluorescent light receives the fluorescent signal; calculating the light intensity received by the sensor receiving the fluorescent signal and the light intensities received by the other two sensors; automatically adjusting the projection intensity of the white light source and/or the excitation light source according to the difference of the intensities of the two types of light signals, whereby a closed-loop system is formed to simultaneously present the colored-florescent images on a picture with the best contrast.

Abstract: A care area is determined in an image of a semiconductor wafer. The care area is divided into sub-care areas based on the shapes of polygons in a design file associated with the care area. A noise scan of a histogram for the sub-care areas is then performed. The sub-care areas are clustered into groups based on the noise scan of the histogram.

Abstract: A method and system for imaging thermodynamic phase of clouds includes obtaining a spatially-resolved polarimetric image of a region of the sky containing a cloud using a multipixel image sensor having multiple channels corresponding to different wavelength bands, determining a value of the Stokes S1 polarization parameter of incident light on each pixel corresponding to a portion of the image containing the cloud for multiple channels corresponding to different wavelength bands, and determining the thermodynamic phase of the cloud within the image based on the values of the Stokes S1 polarization parameter. The Stokes S1 polarization parameter values determined for a first channel corresponding to a first wavelength band is used to determine a liquid thermodynamic phase, and the Stokes S1 polarization parameter values determined for a second channel corresponding to a second, shorter wavelength band is used to determine an ice thermodynamic phase.

Abstract: In a case where a user manually selects an image to be converted into a monochrome image with distinguishability, the user is to take labor and may select an image unsuitable for conversion into a monochrome image with distinguishability. An attribute in a page of print data is analyzed for each page, and based on the attribute of the page, a distinguishability improvement method that performs conversion into gray data by using density difference or outline emphasis is switched.

Abstract: Predicting patch displacement maps using a neural network is described. Initially, a digital image on which an image editing operation is to be performed is provided as input to a patch matcher having an offset prediction neural network. From this image and based on the image editing operation for which this network is trained, the offset prediction neural network generates an offset prediction formed as a displacement map, which has offset vectors that represent a displacement of pixels of the digital image to different locations for performing the image editing operation. Pixel values of the digital image are copied to the image pixels affected by the operation.

Abstract: A printing system includes a terminal device, a plurality of printers, a first server, and a second server. The first server calculates a round-trip accuracy of each printer using a color conversion profile supplied from the second server with respect to target color information included in a printing command provided from the terminal device, and selects one or more printers among the plurality of printers according to the round-trip accuracy to cause the printers to execute printing.

Abstract: There is provided a microscope device comprising a microscope objective (12), a first light source (18) for transmitted light illumination of the sample (16) with light within a first spectral range and a second light source (20) for transmitted light illumination of the sample with light within a second spectral range different from the first spectral range, a tube lens (22) for forming a sample-image from the light collected by the microscope objective, a first camera detector (32) for detecting light within the first spectral range, a second camera detector (34) for detecting light within the second spectral range, a dichroic beam splitter (24) in the image beam path (26) between the tube lens and the detectors, and an analyzer unit (44), The beam splitter reflects light within the first spectral range onto the first detector and transmits light within the second spectral range onto the second detector, and wherein the analyzer unit is configured to combine a first image of the sample recorded by the first

Abstract: Approaches are described for ranking images against image effects. An image effect is identified from a plurality of image effects. Each image effect includes instructions defining steps of modifying visual data of an input image to produce an output image. Preview images are generated, where for each data object of a plurality of data objects the instructions of the image effect are applied to a respective image corresponding to the data object to generate a preview image of the data object. Ranking scores are determined, where for each data object visual data of the respective image is analyzed using a set of evaluation criteria associated with the image effect to determine a ranking score of the image effect for the data object. Data is transmitted which causes at least one of the preview images to be presented on a user device based on the ranking scores.

Abstract: In various examples, image data may be received that represents an image. Corner detection may be used to identify pixels that may be candidate corner points. The image data may be converted from a higher dimensional color space to a converted image in a lower dimensional color space, and boundaries may be identified within the converted image. A set of the candidate corner points may be determined that are within a threshold distance to one of the boundaries, and the set of the candidate corner points may be analyzed to determine a subset of the candidate corner points representative of corners of polygons. Using the subset of the candidate corner points, one or more polygons may be identified, and a filter may be applied to the polygons to identify a polygon as corresponding to a fiducial marker boundary of a fiducial marker.

Abstract: A point cloud compression approach that exploits HEVC for compression of both the geometry and color data is described herein. Although both the geometry and color could be compressed in a lossy fashion, the point cloud compression approach is suggested for the scenario of lossless geometry and lossy color coding. Both geometry and color data are first mapped into 2D images and then compressed by HEVC. A sorting technique is used to sort the geometry data to make it as correlated as possible when it is mapped to a 2D image. For color coding, clustering is used to put similar colors in a point cloud into spatial neighbors in the mapped 2D image. This significantly avoids color leaking due to quantization errors to neighbor points in 3D. The results show that much better compression is achieved compared to the Anchor when it is configured for lossless geometry coding.

Abstract: One or more computing devices, systems, and/or methods for selective content insertion into areas of media objects are provided. For example, a media object (e.g., an image or video), is selected for composition with content, such as where a message, interactive content, a hyperlink, or other types of content is overlaid or embedded into the media object to create a composite media object. The content is added into an area of the media object that is selectively identified to reduce occlusion and/or improve visual cohesiveness between the content and the media object (e.g., added to an area with a similar or complimentary color, having an adequate size with spare amounts of visual features such as a soccer player, a ball, or other entity, etc.). In this way, the content may be add into the area of the media object to create a composite media object to provide to users.

Abstract: Provided is an image processing apparatus that includes a component obtainer configured to obtain diffusive reflection components and specular reflection components for pixels of an input image, a filter processor configured to perform filter-processing on a diffusive reflection component image, a specular reflection component image, and the input image, a component combiner configured to combine the filter-processed diffusive reflection component image and the filter-processed specular reflection component image to generate a combined image, and an evaluator configured to evaluate a separation accuracy of the diffusive reflection components or the specular reflection components based on the combined image and the filter-processed input image.

Abstract: An image processing system includes: a determining unit configured to determine whether or not a region is a stationary region in an image frame at the time of processing, based on a first image generated from each image frame captured in a first time period from the time of the processing and a second image generated from each image frame captured in a second time period from the time of the processing, the second time period being longer than the first time period; and a generation unit for configured to generate reliability information about determination as to whether or not each region in an image frame being processed is the stationary region.

Abstract: A pixel position to be mapped to each pixel position on an output image by deformation is obtained as an input pixel position. A filter coefficient group to be used for pixel interpolation at the time of deformation is adjusted by using the pixel values of pixels positioned around an input pixel position on the input image. A pixel value at the pixel position on the output image which corresponds to the input pixel position is calculated by using the pixel values of the pixels positioned around the input pixel position on the input image and the filter coefficient group after adjustment.

Abstract: An image processing apparatus includes a first determination unit to determine an attribute of an area included in an input image obtained by reading a document, a second determination unit to determine saturation of an area determined to be a halftone dot area by the first determination unit, and a background removal unit to remove a background included in the input image. The background removal unit converts for an area determined to be a halftone dot area by the first determination unit and whose value indicating saturation is determined to be less than a predetermined value by the second determination unit, a color of a pixel of pixels making up the area, which has a pixel value greater than a first level, into white.

Abstract: A color reproduction analyzing apparatus includes: a specific area extractor that extracts a specific area on which an error is supposed to occur as an error factor area when image data for image forming for forming an image on paper and read image data generated by reading the image on the paper are received and compared; and a color reproduction analyzer that obtains pixel values of a desired color in a position corresponding to the image data for image forming and the read image data, excludes the error factor area, and compares pixel values of the image data for image forming and the read image data to analyze a color reproduction.

Abstract: An image processing device includes an edge strength calculation unit, and a mixing unit. The edge strength calculation unit calculates an edge strength of a pixel of interest in an input image from a stairs tone strength of the pixel of interest and a gradient of the pixel of interest, wherein the gradient is calculated from pixel values of the pixel of interest and pixels adjacent to the pixel of interest, and the stairs tone strength is indicative of differences between the gradient and a variance of the pixel of interest calculated from the pixel values of the pixel of interest and the adjacent pixels. The mixing unit calculates an illumination light component of the pixel of interest of the input image from an average value of the pixel of interest and pixel values adjacent to the pixel of interest, and a mixing ratio calculated from the edge strength.

Abstract: An image processing apparatus comprises an image acquiring unit configured to acquire a face image including a face of a person; a lip extracting unit configured to extract a lip region from the face image; a color determining unit configured to determine a representative color of the lip based on pixels included in the lip region; a value acquiring unit configured to acquire a first value representing a proximity to the lip region and a second value correlated to similarity of a color to the representative color; a generating unit configured to generate, based on distributions of the first and second values, a lip correction map representing a distribution of weights used in correcting a color of the lip included in the face image; and an image correcting unit configured to correct the color of the lip using the lip correction map.

Abstract: A method and apparatus for generating a grayscale image. The method and apparatus receive a single value. From the single value, the method and apparatus generate a set of grayscale weighting values. The method and apparatus generate the grayscale based on a color image and the set of grayscale weighting values. By limiting the number of values to a single value, the method and apparatus prevents a user from arbitrarily selecting a number of possible weighting values which could result in a grayscale image that is too dim or too bright. This single control method and apparatus quickly and efficiently produces a grayscale image that is neither too bright nor too dim.

Abstract: Systems and methods for processing YCC image data provided. In one example, an electronic device includes memory to store image data in RGB or YCC format and a YCC image processing pipeline to process the image data. The YCC image processing pipeline may include receiving logic configured to receive the image data in RGB or YCC format and color space conversion logic configured to, when the image data is received in RGB format, convert the image data into YCC format. The YCC image processing logic may also include luma sharpening and chroma suppression logic; brightness, contrast, and color adjustment logic; gamma logic; chroma decimation logic; scaling logic; and chroma noise reduction logic.

Abstract: An image processing apparatus includes a definition reducing section, a color region extracting section, a concealing image generating section and an image combining section. The definition reducing section, based on a received image, generates an image having a lower definition than the received image. The color region extracting section extracts a color region from the low definition image generated by the definition reducing section. The concealing image generating section, based on the color region extracted by the color region extracting section, converts the color region into a concealing region for concealing a part of the received image and, generates a concealing image including the concealing region. The image combining section combines the received image with the concealing image generated by the concealing image generating section.

Abstract: An image processing apparatus includes a reduction unit and a compression unit. The reduction unit is configured to execute color-number reduction processing for each block configured by a plurality of pixels included in a processing target image expressed by processing target image data, the color-number reduction processing including reducing the number of colors expressed by the plurality of pixels in the block to generate image data having the reduced number of colors from the processing target image data, a gradation-number of each color value included in the image data having the reduced number of colors being the same as a gradation-number of each color value included in the processing target image data. The compression unit is configured to execute compression processing using the image data having the reduced number of colors to generate compressed image data.

Abstract: The present invention relates to an image processing apparatus and method, and a program that are capable of displaying images more easily and effectively. A degree-of-blur detecting unit 21 detects the degree of blur of an input image. The selecting unit 22 selects an image processing operation to be performed on the input image on the basis of a detection result of the degree of blur, and supplies the input image to a block that performs the selected image processing operation among a comic-style conversion unit 23 to a sharpness processing unit 28. The block supplied with the input image among the comic-style conversion unit 23 to the sharpness processing unit 28 performs the image processing operation on the input image and outputs it to an output unit 29. The present invention can be applied to an image processing apparatus.

Abstract: An image enhancement method for improving color perception of colorblind viewers has an image input step, an image difference area analyzing step, an image color distribution adjusting step, and an image output step. In such method, a normal image and a colorblindness-simulative image are input and calculated to produce a colorblindness-optimized image. Color vision obtained by a colorblind person from the colorblindness-optimized image is substantially identical to that obtained by a person with normal color perception from the normal image.

Abstract: A method and apparatus for generating a grayscale image. The method and apparatus receive a single value. From the single value, the method and apparatus generate a set of grayscale weighting values. The method and apparatus generate the grayscale based on a color image and the set of grayscale weighting values. By limiting the number of values to a single value, the method and apparatus prevents a user from arbitrarily selecting a number of possible weighting values which could result in a grayscale image that is too dim or too bright. This single control method and apparatus quickly and efficiently produces a grayscale image that is neither too bright nor too dim.

Abstract: A VDP workflow system and method are disclosed. The system includes an image memory to store a photograph image. The system also includes a VDP document tool to access the photograph image from the image memory and to generate a VDP document comprising the photograph image. The system further includes a red-eye removal tool to process the VDP document to discover red-eye artifacts and to remove the red-eye artifacts from the photograph image on the VDP document based on a programmable red-eye sensitivity value.

Abstract: A video is segmented to produce volumetric video regions. Descriptors are created for the video regions. A region graph is created for the video, where the region graph has weighted edges incident to video regions and the weight of an edge is calculated responsive to the descriptors of the video regions incident to the edge. The region graph is segmented responsive to the weights of the edges incident to the video regions to produce a new region graph having new volumetric video regions comprised of merged video regions of the first region graph. The descriptions of the region graphs are stored in a data storage.

Abstract: Apparatus, methods and systems of object recognition are disclosed. Embodiments of the inventive subject matter generates map-altered image data according to an object-specific metric map, derives a metric-based descriptor set by executing an image analysis algorithm on the map-altered image data, and retrieves digital content associated with a target object as a function of the metric-based descriptor set.

Abstract: Implementations relate to estimating noise in images. In some implementations, a method includes extracting a plurality of sample blocks of pixels from a received image, where each sample block includes a subset of pixels of the image. One or more of the sample blocks are examined for texture content based on whether the sample blocks include one or more edges based on a predetermined threshold. At least one sample block determined to include texture content is removed. The method determines one or more average color variances based on the remaining sample blocks that have not been removed, where noise estimations for the image are based on the average color variances.

Abstract: An image comprising color pixels with varying illumination is selected. Instances of a repeating pattern in the image are determined. Illumination values for illuminated pixels at locations within instances of the repeating pattern are calculated based on pixel intensities of non-illuminated pixels at corresponding locations in other instances of the repeating pattern. The illumination variation is removed from the illuminated pixels based on the calculated illumination values to produce enhanced pixels. Color from the non-illuminated pixels at the corresponding locations in other instances of the repeating pattern is propagated to the enhanced pixels.

Abstract: A method for identifying a set of key video frames from a video sequence comprising extracting feature vectors for each video frame and applying a group sparsity algorithm to represent the feature vector for a particular video frame as a group sparse combination of the feature vectors for the other video frames. Weighting coefficients associated with the group sparse combination are analyzed to determine video frame clusters of temporally-contiguous, similar video frames. A set of key video frames are selected based on the determined video frame clusters.

Abstract: Systems and methods are provided for correcting red-eye in a digital image. an identification of pixels in a color image where red-eye is to be corrected is accessed. At least a portion of the color image is converted from a color representation to generate a grayscale representation. The color image is adjusted by replacing identified pixels in the color image with corresponding pixels from the grayscale representation to generate an adjusted color image, and the adjusted color image is saved in a computer-readable medium.

Abstract: Implementations relate to estimating noise in images. In some implementations, a method includes extracting a plurality of sample blocks of pixels from a received image, where each sample block includes a subset of pixels of the image. One or more of the sample blocks are examined for texture content based on whether the sample blocks include one or more edges based on a predetermined threshold. At least one sample block determined to include texture content is removed. The method determines one or more average color variances based on the remaining sample blocks that have not been removed, where noise estimations for the image are based on the average color variances.

Abstract: According to one embodiment, an decoloring apparatus includes: an decoloring processing unit configured to apply decoloring processing decoloring a color of an decolorable colorant; a sheet conveying unit configured to convey the sheet and cause the sheet to pass through the decoloring processing unit; an image reading unit arranged further on an upstream side than the decoloring processing unit in a sheet conveying direction by the sheet conveying unit and configured to read the image formed on the sheet conveyed by the sheet conveying unit; a thickness sensor arranged further on the upstream side than the decoloring processing unit in the sheet conveying direction by the sheet conveying unit and configured to detect thickness of the sheet conveyed by the sheet conveying unit; an decolorability determining unit configured to determine, on the basis of a detection result in at least one of the image reading unit and the thickness sensor, executability of the decoloring processing in the decoloring processing

Abstract: This disclosure pertains to apparatuses, methods, and computer readable media for red-eye removal techniques using multiple recognition channels. In the following examples, red, golden, and white recognition channels are used. A recognition channel is the monochrome extraction from a color photograph in a manner designed to make one kind of red-eye artifact glow with maximum contrast. Once the red-eye artifact has been characterized by, e.g., size and location, the techniques disclosed herein may then discern whether the red-eye artifact is, for example, a red-, golden-, or white-eye case by examining the configuration and characteristics of pro prominence bitmasks created for the various recognition channels. Once the type of red-eye case has been discerned, the techniques disclosed herein may then replace the artifact with a photographically reasonable result based on the type of red-eye case being repaired. Specular reflection may also be re-added to the photograph.

Abstract: A method of generation, by a digital processing device, of a first high dynamic range digital image from second and third digital images of a same scene, including, for at least one point of the first image: determining a brightness index; comparing this index with at least one of first, second, third, and fourth decreasing thresholds stored in a memory; and determining the value of the point by taking into account the value of the index.

Abstract: A device and method of removing chromatic aberration which occurs in an image generated by capturing a target subject. The chromatic aberration removing device includes a chromatic aberration region detecting unit which detects a chromatic aberration occurrence region in an input image, a coefficient calculating unit which calculates a minimizing pixel value which minimizes a difference between sizes, numbers of pixels or intensities of edges of red, green, and blue (RGB) channels of the chromatic aberration occurrence region, a chroma signal processing unit which removes chromatic aberration in the chromatic aberration occurrence region, and a purple fringing removing unit which removes purple fringing.

Abstract: A color processing apparatus includes an obtaining unit that obtains a first color signal from outside, a converting unit that converts the first color signal obtained by the obtaining unit into a second color signal based on a viewing condition, and a generating unit that generates a third color signal on the basis of the first color signal obtained by the obtaining unit and the second color signal obtained through conversion performed by the converting unit, the third color signal being an input signal that is used for a color gamut mapping process of performing mapping to a color gamut of an output device.

Abstract: A method of processing digital images by transforming a set of pixels from a three-dimensional space to a normalized two-dimensional space, determining a membership class and membership class level of each pixel in the set of pixels, and selectively modifying colors of pixels in the set of pixels based on the determined membership classes and membership class levels.

Abstract: Systems and methods for detecting chroma dropout errors in one or more fields associated with various video frames are provided. Pixels associated with a current field are divided into a set of pixel pairs. Co-occurrences matrices are calculated for previous and subsequent fields. A first pixel pair associated with the current field is selected. First and second set of entries are selected from the co-occurrence matrices corresponding to the previous and subsequent fields. The first pixel pair is searched in the first and second set of entries. An absence of the first pixel pair in the first and second set of entries satisfies a first criterion of chroma dropout error. Other criteria in addition to the first criterion are evaluated to label the first pixel pair as erroneous.

Abstract: The embodiments discussed herein involve flood filling a region with anti-aliasing. In forming a fill region, a candidate pixel can be included in the region based on a color of the pixel and also a color of a neighbor of the point. The inclusion basis may be a color distance between a seed color and the points, and a color distance between the seed color and the point's neighbor. Points in the region may be weighted according to their color distance relative to the seed color, where the color distance can also take into account alpha values. Flood filling may be anti-aliased by assigning alpha values to pixels in gaps between corners of the fill region, where an alpha value may be proportional to a point's contribution to the gap. Dimples in a fill region may be tested for and used to determine which of two flood fill algorithms to use.

Abstract: An input image is denoised by first constructing a pixel-wise noise variance map from the input image. The noise has spatially varying variances. The input image is partitioned into patches using the noise variance map. An intermediate image is determined from the patches. Collaborative filtering is applied to each patch in the intermediate image using the noise variance map to produce filtered patches. Then, the filtered patches are projected to an output image.

Abstract: A method for converting a full color image to a monochrome image is provided, wherein the color values of pixels are decomposed in a luminance and a chrominance component. Both components are converted to a grayscale value representing an intensity of a pixel. The luminance grayscale value is in a limited range close to a light end of the available grayscale. The chrominance grayscale value is closer to the dark end of the available grayscale when the chrominance component of the color value is larger. The darkest value of the two converted values is selected for a corresponding pixel. The effect of this conversion is that colored pixels are darker than colorless pixels, which is useful to highlight parts of a monochrome image that stand out because of their color in a full color image. It is particularly useful to help color blind people recognize colored parts of an image.

Abstract: The present disclosure relates to a method and an apparatus for image processing. The method includes: setting a block including at least one pixel and a window including the at least one block, with a center pixel as a reference; converting an input image in a YCbCr format to a monochrome image; determining a magnitude of an edge component and an edge direction in the window; determining a weight of the block in consideration of the magnitude of the edge component and the edge direction; and determining a color signal value of the center pixel by reflecting the weight of the block in the monochrome-converted window.

Abstract: An image processing apparatus of the present invention includes: a blank document determination section determining whether or not input image data is image data of a blank document, regardless of a process mode set for setting a process with respect to the input image data; a storage device storing the input image data in association with a determination result made by the blank document determination section; and a control section (i) reading out the input image data from the storage device and (ii) excluding the input image data determined as image data of a blank document by the blank document determination section, from images to be displayed by the image display device, when the image display device carries out a preview display of the input image data. This configuration makes it possible to carry out a preview display in which a blank document (blank page document) is skipped, without reading the document again.

Abstract: In a case where a background removal level is a level for removing a background, monochrome image data is generated based on color image data and then background removal processing is applied to the generated monochrome image data. In a case where the background removal level is a level for not removing the background, the background removal processing is applied to color image data and then monochrome image data is generated based on the image data having underdone the background removal processing.

Abstract: A color separating unit separates a color image into plural color components to generate images of respective colors. A periodicity determining unit determines, for each of the color images, whether an image region including a target pixel whose pixel value is to be interpolated is a periodic region in which pixel values vary periodically. A first generating unit generates pixel values of the respective colors of a pixel using a first interpolation method. A second generating unit generates pixel values of the respective colors of a pixel using a second interpolation method. A control unit determines which one of the first and second generating units is to be used for generating pixel values of the respective colors of the target pixel. A pixel value combining unit combines candidate pixel values which are the pixel values of the respective colors of the target pixel to calculate a combined pixel value.