Abstract: A corresponding region movement amount calculation unit calculates the amount of movement of each of a plurality of corresponding characteristic regions between a reference image and a base image. A clustering processing unit groups one or more characteristic regions exhibiting a substantially identical tendency in the calculated amounts of movement as belonging to a plane group located on the same plane, and classifies the plurality of characteristic regions in one or more plane groups. A projection transform matrix calculation unit calculates one or more projection transform matrices, by using the amounts of movement of the characteristic regions and the result of the grouping performed by the clustering processing unit.

Abstract: A method and system for protecting video and image files processes from original files to detect skin tones of persons appearing in the media. Pixels determined to contain skin tones are blurred or blacked out, and the pixel locations and their original color values are stored in a metadata file. The metadata file is encrypted and stored with the redacted video file. Thereafter, when an authorized person wants to see an unredacted version of the video, the system decrypts the metadata and reconstituted the video, replacing the redacted pixels with their original color values, and inserting a unique watermark into the video that identifies the requesting person. The watermarked video is then provided to the requesting person.

Abstract: An image processing apparatus for obtaining an output image by performing a filter processing of an input image, includes a setting unit configured to set a plurality of local regions in the input image, a deriving unit configured to derive a plurality of coefficients corresponding to each of the plurality of local regions based on statistics indicating variations in pixel values in the plurality of local regions, and a filter processing unit configured to obtain an output pixel value by performing a liner transformation of the input image based on the plurality of the coefficients, wherein the plurality of local regions include a region that is partitioned diagonally to a raster scan direction; wherein the filter processing unit performs the liner transformation of the input image based on a coefficient adaptively selected from the plurality of coefficients.

Abstract: A noise reduction unit reduces color noise of an input image to generate a noise-reduced image. A first generation unit generates a color difference signal from the noise-reduced image. A reduction processing unit generates hierarchical images including at least two or more reduced images from the noise-reduced image. A second generation unit generates coloring-suppressed color difference signals from the reduced images. A combining unit combines the color difference signal generated by the first generation unit with each of the color difference signals generated by the second generation unit. The second generation unit selects one of the color difference signals of the reduced images for each pixel based on magnitude of each of the color difference signals of the reduced images, to generate the coloring-suppressed color difference signals.

Abstract: An “Adaptive Exposure Corrector” performs automated real-time exposure correction of individual images or image sequences of arbitrary length. “Exposure correction” is defined herein as automated adjustments or corrections to any combination of shadows, highlights, high-frequency features, and color saturation of images. The Adaptive Exposure Corrector outputs perceptually improved images based on image ISO and camera ISO capabilities in combination with camera noise characteristics via exposure corrections by a variety of noise-aware image processing functions. An initial calibration process adapts these noise aware image processing functions to noise characteristics of particular camera models and types in combination with particular camera ISO settings. More specifically, this calibration process precomputes a Noise Aware Scaling Function (NASF) and a Color Scalar Function (CSF).

Abstract: Embodiments relate to biasing an image noise filter to reduce edge and texture blurring of image data. Pixel values used to determine photometric coefficients for a bilateral filter are modified by offset values. The offset value for a pixel value is determined by applying a high pass filter to the pixel (referred to as the center pixel) and neighboring pixels of the center pixel. By adding the offset value to the center pixel value, the pixel value difference between the neighboring pixels and the center pixel becomes smaller for pixels on the same side of an edge as the center pixel. Thus, pixels on the same side of the edge get more weight in the bilateral noise filter. Conversely, pixels on the opposite side of the edge as the center pixel get less weight in the bilateral filter. As a result, the biased bilateral filter reduces blurring of edges and increases preservation of texture in the image data.

Abstract: A system and method for analyzing images using a non-transitory programmable device is disclosed. A user interface generator operating on the non-transitory programmable device receives specifications of a first image of a biological sample and a first image analysis step. A sequencer operating on the non-transitory programmable device applies the first image analysis step to the first image to develop annotated training data, and a machine learning system trainer operating on the non-transitory programmable device trains an untrained machine learning system to develop a trained machine learning system. When the trained machine learning system is presented with the first image as an input, the trained machine learning system develops a prediction of the annotated training data.

Abstract: A gradient calculation unit calculates an image gradient on a pixel-by-pixel basis in each of a plurality of images. A scale search unit calculates a scale score based on degree of spatial frequency components for each pixel in each of the images. A gradient score calculation unit calculates, for each pixel, a gradient score on the basis of the image gradient and the scale score. A gradient finalization unit calculates, using the gradient score and, as a target gradient, an image gradient of each pixel in a combined image. On the basis of the target gradient, a coefficient calculation unit calculates, for each pixel of the combined image, a coefficient of base vectors constituting a preset base vector group in the combined image. A combining unit generates the combined image through linear combination of the base vectors based on the calculated coefficients.

Abstract: An image processing method includes obtaining a difference map of an original image, obtaining an edge feature parameter of a first pixel in an intermediate image based on a pixel value of a pixel in the difference map, obtaining an edge feature parameter of a second pixel in a target image based on the edge feature parameter, and obtaining the target image based on the edge feature parameter of the second pixel.

Abstract: Systems and methods relating to fault detection and diagnosis. Signals received from sensors are first filtered to remove noise and are then analyzed using wavelet packet transform (WPT) based PCA. The results of the PCA analysis are then automatically classified to thereby quickly and easily determine what issues there may be in a finished product or in a machine being monitored.

Abstract: Techniques related to detecting texture content in an input image are discussed. Such techniques include accumulating pixel-wise directional gradient counts for positive and negative gradients for a first direction and positive and negative gradients for a second direction for pixels in a pixel window. A texture value for the target pixel of the window is determined based on a sum of a minimum of the positive and negative gradients for a first direction and a minimum of the positive and negative gradients for a second direction.

Abstract: Embodiments relate to enhancing local contrast in an image. A bilateral high pass filter generates a high frequency value for each pixel of an input image, based on a convolution using photometric kernel coefficients associated with other pixels around the pixel. A noise control circuit generates a modulated high frequency value for the pixel based on a noise model for the image defining a noise threshold value for modifying the high frequency value. The modulated high frequency value for the pixel is then combined with a pixel value of the pixel to generate an enhanced value for the pixel. Enhanced values for pixels of the image may be generated to provide the local contrast enhancement for the input image.

Abstract: An image processing apparatus includes an input unit for inputting an image, a division unit for dividing the inputted image into a plurality of divided regions, an obtaining unit for obtaining a feature amount of the image for each of the divided regions, a generation unit for generating a compression curve for each divided region, and a compression unit for generating an output image by performing compression of a dynamic range using the compression curve for each of the divided regions. The generation unit generates the compression curve for each of the divided regions so that a slope of the compression curve for each of the divided regions matches in a range from a luminance of a dark region of the image to a luminance of a predetermined brightness.

Abstract: An electronic device is provided. The electronic device includes a camera, a display, a memory, a communication module, and a processor configured to identify a plurality of parameter sets related to image capturing from an external device using the communication module, provide, in a first preview, at least part of one or more images using the display during at least part of obtaining the one or more images using the camera, generate one or more first corrected images to which a first parameter set among the plurality of parameter sets is applied, using the one or more images, generate one or more second corrected images to which a second parameter set among the plurality of parameter sets is applied, using the one or more images, identify priority for the plurality of parameter sets, and provide, in a second preview, one or more among the one or more first corrected images and the one or more second corrected images according to the priority during at least part of providing the first preview.

Abstract: A self-contained, low-cost, low-weight guidance system for vehicles is provided. The guidance system can include an optical camera, a case, a processor, a connection between the processor and an on-board control system, and computer algorithms running on the processor. The guidance system can be integrated with a vehicle control system through “plug and play” functionality or a more open Software Development Kit. The computer algorithms re-create 3D structures as the vehicle travels and continuously updates a 3D model of the environment. The guidance system continuously identifies and tracks terrain, static objects, and dynamic objects through real-time camera images. The guidance system can receive inputs from the camera and the onboard control system. The guidance system can be used to assist vehicle navigation and to avoid possible collisions. The guidance system can communicate with the control system and provide navigational direction to the control system.

Abstract: The present application discloses a vehicle monitoring method and apparatus, processor, and image acquisition device. The method includes: identifying a vehicle window area image in a vehicle image obtained through monitoring; performing feature identification on the vehicle window area image to obtain an identification result of a target feature; performing human eye sensory processing on the vehicle image and the vehicle window area image respectively, and stitching the processed vehicle image and the processed vehicle window area image to obtain a processed image; and outputting the identification result of the target feature and the processed image. The present application solves the technical problem of relatively low identification rate in vehicle monitoring by image detection.

Abstract: Image blurring methods and apparatuses, storage media, and electronic devices. The method can be carried out by the apparatuses, media and devices, and includes: generating a second image having second pixel points corresponding to first pixel points of a first image; determining, according to blurring desired data of the first pixel points, respective initial blurring weight values of the corresponding second pixel points; performing at least one update on at least one of the second pixel points, the update including: updating, based on a first pixel value of the first pixel point and a current blurring weight value of the second pixel point corresponding to the based first pixel point, a current pixel value and a current blurring weight value of at least one neighboring second pixel point of the based corresponding second pixel point; and obtaining a blurring result of the first image according to the updated second image.

Abstract: In some embodiments, noise data may be used to train a neural network (or other prediction model). In some embodiments, input noise data may be obtained and provided to a prediction model to obtain an output related to the input noise data (e.g., the output being a prediction related to the input noise data). One or more target output indications may be provided as reference feedback to the prediction model to update one or more portions of the prediction model, wherein the one or more portions of the prediction model are updated based on the related output and the target indications. Subsequent to the portions of the prediction model being updated, a data item may be provided to the prediction model to obtain a prediction related to the data item (e.g., a different version of the data item, a location of an aspect in the data item, etc.).

Abstract: A method of generating an image from multiple cameras having different focal lengths is described. The method comprising receiving a wide image and a tele image; aligning the wide image and the tele image to overlap a common field of view; correcting for photometric differences between the wide image and the tele image; selecting a stitching seam for the wide image and the tele image; and joining the wide image and the tele image to generate a composite image, wherein a first portion of the composite image on one side of the stitching seam is from the wide image and a second portion of the composite image on the other side of the stitching seam is from the tele image. An electronic device for generating an image is also described.

Abstract: A method for rendering a computer image includes, for each pixel of a plurality of N×M pixels forming a tile, determining a plurality of masks for the pixel, wherein N and M denote integers larger than 1, and wherein each mask identifies a respective subset of the pixels that are equidistant from the pixel and located at a respective distance from the pixel. The method further includes: determining an active mask for the tile, the active mask identifying active pixels of the pixels, each of the active pixels being determined as having color information; based on the active mask, identifying an empty pixel of the pixels, the empty pixel lacking color information; and determining at least a first nearest active pixel that is nearest to the empty pixel. The determining includes comparing the active mask with at least one mask of the masks for the empty pixel.

Abstract: A system and method for calibrating sensors may include one or more processors, a first sensor configured to obtain a two-dimensional image, a second sensor configured to obtain three-dimensional point cloud data, and a memory device. The memory device stores a data collection module and a calibration module. The data collection module has instructions that configure the one or more processors to obtain the two-dimensional image and the three-dimensional point cloud data. The calibration module has instructions that configure the one or more processors to determine and project a three-dimensional point cloud edge of the three-dimensional point cloud data onto the two-dimensional image edge, apply a branch-and-bound optimization algorithm to a plurality of rigid body transforms, determine a lowest cost transform of the plurality of rigid body transforms using the branch-and-bound optimization algorithm, and calibrate the first sensor with the second sensor using the lowest cost transform.

Abstract: Aspects vary object illumination values within a digital photograph in response to relocating light-emitting objects. Embodiments generate a three-dimensional model of a digital photograph defined by pixel data that plots a representation of a light source at a first location in a three-dimensional physical space relative to plotted locations of remaining other digital photograph pixels; relocate the representation of the light source within the three-dimensional model to a different, second location within the model three-dimensional physical space; revise a brightness value of a first pixel in proportion to an amount of a change in distance from the first pixel to the second location, relative to a distance to the first, plotted light source location; and generate a revised version of the photograph from the pixel data inclusive of the revised brightness value of the first pixel.

Abstract: Embodiments of the disclosure provide methods, apparatus and computer programs for adaptive loop filtering in an encoder and in a decoder. One method, performed in an encoder, comprises: determining filter parameters for a plurality of filters to be used in encoding a frame or slice; determining respective activity values for each of a plurality of blocks in the frame or slice, wherein each block comprises a plurality of pixels; determining respective quantization parameters for each of the plurality of blocks; selecting, for each of the plurality of blocks, a filter from the plurality of determined filters based on the respective activity value and the respective quantization parameter; and applying the filter parameters for the respective selected filters to the plurality of blocks.

Abstract: Implementations set forth herein relate to a camera calibration system for generating various types of calibration data by maneuvering a camera through a variety of different calibration test systems. The calibration data generated by the camera calibration system can be transmitted to the camera, which can locally store the calibration data. The calibration data can include spatial frequency response value data, which can be generated according to a spatial frequency response test that is performed by the camera calibration system. The calibration data can also include field of view values and distortion values that are generated according to a distortion test that is also performed by the camera calibration system. The camera calibration system can maneuver the camera through a variety of different calibration tests, as well as transmit any resulting calibration data to the camera for storage.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model. In one aspect, a method includes receiving training data for training the machine learning model on a plurality of tasks, where each task includes multiple batches of training data. A task is selected in accordance with a current task selection policy. A batch of training data is selected from the selected task. The machine learning model is trained on the selected batch of training data to determine updated values of the model parameters. A learning progress measure that represents a progress of the training of the machine learning model as a result of training the machine learning model on the selected batch of training data is determined. The current task selection policy is updated using the learning progress measure.

Abstract: A system, components, and methodologies are provided for image data processing and subsequent use to detect and/or identify objects and object movement in such image data to enable assistance, automation, control and/or documentation regarding transportation vehicle movement. An affine contour filter provides the ability to extract precise sub-pixel roots of contours that represent boundaries of blobs in an image that undergoes small affine changes such as translation, rotation and scale. Thereby lateral contour tracking may be performed wherein movement of an object may be tracked within the field of view of a camera by aligning the contours associated with the object in space-time. As a result, the size and shape of the object to be tracked need not be specified ahead of time.

Abstract: A machine learning based image processing architecture and associated applications are disclosed herein. In some embodiments, a machine learning framework is trained to learn low level image attributes such as object/scene types, geometries, placements, materials and textures, camera characteristics, lighting characteristics, contrast, noise statistics, etc. Thereafter, the machine learning framework may be employed to detect such attributes in other images and process the images at the attribute level.

Abstract: A method to improve the efficiency of coding high-dynamic range (HDR) signals in a dual-layer system is presented. A piece-wise linear, two-segment, inter-layer predictor is designed where base-layer codewords larger than a highlights threshold (Sh) are all mapped to a constant value. Given a target bit rate for the enhancement layer, which can be expressed as a percentage (?) of the bit rate of the base layer, an optimal highlights threshold is derived by computing estimated bit rates for the base and enhancement layers based on pixel complexity measures of pixels in the input HDR signal and the threshold value, and by minimizing an optimization criterion.

Abstract: Embodiments of the present invention provide a novel solution that uses subjective end-user input to generate optimal image quality settings for an application. Embodiments of the present invention enable end-users to rank and/or select various adjustable application parameter settings in a manner that allows them to specify which application parameters and/or settings are most desirable to them for a given application. Based on the feedback received from end-users, embodiments of the present invention may generate optimal settings for whatever performance level the end-user desires. Furthermore, embodiments of the present invention may generate optimal settings that may be benchmarked either on a server farm or on an end-user's client device.

Abstract: A system includes a borescope and at least one processor. The borescope includes a camera configured to acquire an acquisition series of frames of at least one target component. The at least one processor is operably coupled to the camera, and is configured to acquire the acquisition series of frames from the camera; determine a blurriness metric value for each of the frames; select frames that satisfy a threshold for the blurriness metric value to form an inspection series of frames; and perform an inspection analysis for the at least one target component using the inspection series of frames.

Abstract: A device that includes an input interface that receives a correlithm object at a first time. The device further includes a memory operable to store the received correlithm object and a plurality of correlithm object values. The device further includes a processor operable to determine a Hamming distance between the correlithm object received at the input interface and each of the correlithm object values stored in the memory. The process is further operable to store the correlithm object received at the input interface in the memory if any of the determined Hamming distances are within a predetermined threshold and an output interface communicates the correlithm object at a second time later than the first time.

Abstract: An object region identifying apparatus according to an embodiment identifies to which one of a plurality of predetermined object classes each pixel of an image belongs to label the pixel with an object type. The object region identifying apparatus includes following units. A base cost calculating unit calculates base costs of the respective object classes in each of the pixels. A transition cost estimating unit estimates a transition cost accrued when a transition between the object classes occurs between adjacent pixels in the image. A cumulative cost calculating unit calculates cumulative costs of the respective object classes in each of the pixels by accumulating the base cost and the transition cost for the respective object classes along a scanning direction set on the image. A class determining unit determines the object class of each of the pixels based on the corresponding cumulative cost.

Abstract: A system and method for processing a plurality of channels, for example audio channels, in parallel is provided. For example, a plurality of telephony channels are processed in order to detect and respond to call progress tones. The channels may be processed according to a common transform algorithm. Advantageously, a massively parallel architecture is employed, in which operations on many channels are synchronized, to achieve a high efficiency parallel processing environment. The parallel processor may be situated on a data bus, separate from a main general purpose processor, or integrated with the processor in a common board or integrated device. All, or a portion of a speech processing algorithm may also be performed in a massively parallel manner.

Abstract: Embodiments of the present disclosure disclose an image data processing method performed at a computing device, including: obtaining target image data, and creating grid information on a target display region corresponding to the target image data; obtaining a sliding operation track corresponding to a touch screen, and extracting a touch point in the sliding operation track, as a target touch point; creating position coordinates of the target touch point, and calculating, according to the grid information and the position coordinates of the target touch point, a cleaning number corresponding to the target touch point; adding a grid number same as the cleaning number to a preset number set, and deleting subimage data covered by the target touch point; and completely deleting, when the quantity of grid numbers in the number set meets a cleaning condition, the target image data from which a plurality of pieces of subimage data has been deleted.

Abstract: First, second, and third line reading processing is processing of emitting light of each color to first, second, and third line of an original document in first, second, and third lighting order, respectively, and reading reflection light of the emitted light. A color that is first in the first lighting order, a color that is first in the second lighting order, and a color that is first in the third lighting order are different from each other. A color that is second in the first lighting order, a color that is second in the second lighting order, and a color that is second in the third lighting order is different from each other. A color that is third in the first lighting order, a color that is third in the second lighting order, and a color that is third in the third lighting order is different from each other.

Abstract: Embodiments of the present disclosure relate to a configurable convolution engine that receives configuration information to perform convolution or its variant operations on streaming input data of various formats. To process streaming input data, input data of multiple channels are received and stored in an input buffer circuit in an interleaved manner. Data values of the interleaved input data are retrieved and forwarded to multiplier circuits where multiplication with a corresponding filter element of a kernel is performed. Varying number of kernels with different sizes and sparsity can also be used for the convolution operations.

Abstract: The imaging support device includes: a distance information-acquisition unit (20) that acquires distance information on a distance between an imaging device (200) and the surface to be imaged of a structure; an inclination angle information-acquisition unit (22) that acquires inclination angle information on an inclination angle of the surface to be imaged of the structure; an actual pixel density-calculation unit (24) that calculates actual pixel density of the surface to be imaged of the structure on the basis of imaging performance information of the imaging device (200) (including information on the number of pixels of an imaging element, size information of the imaging element, and information on a focal length), distance information, and inclination angle information; and a pixel density-determination unit (26) that determines whether or not the calculated actual pixel density matches required pixel density information.

Abstract: A method for transforming an image descriptor, based on a gradient histogram (h) having a plurality of histogram bins (hi), into a transformed gradient histogram descriptor (v) including a set of values (vj), wherein it is provided the step of applying at least one criterium for calculating the set of values (vj), at least one criterium having a location criterium of the histogram bins (hi). The invention also relates to an image processing device suitable for carrying out the method.

Abstract: Techniques and systems are described for style-aware patching of a digital image in a digital medium environment. For example, a digital image creation system generates style data for a portion to be filled of a digital image, indicating a style of an area surrounding the portion. The digital image creation system also generates content data for the portion indicating content of the digital image of the area surrounding the portion. The digital image creation system selects a source digital image based on similarity of both style and content of the source digital image at a location of the patch to the style data and content data. The digital image creation system transforms the style of the source digital image based on the style data and generates the patch from the source digital image in the transformed style for incorporation into the portion to be filled of the digital image.

Abstract: A method and system for real-time noise removal and image enhancement of high-dynamic range (HDR) images. The method includes receiving an HDR input image I and operating processing circuitry for (i) applying a first edge-preserving filter (e.g. guided filter) to the input image I, thereby generating a first image component B1 and a first set of linear coefficients ?i,1; (ii) applying a second edge-preserving filter (e.g. guided filter) to the input image I, thereby generating a second image component B2 and a second set of linear coefficients ?i,2; (iii) generating a plausibility mask P from a combination of the first set of linear coefficients ?i,1 and the second set of linear coefficients ?i,2, the plausibility mask P indicating spatial detail within the input image I; and (iv) generating an output image O based on first image component B1, the second image component B2 and the plausibility mask P.

Abstract: The invention relates to an apparatus (100) for processing a medical image (IM) of a structure of interest (SOI). The apparatus comprises a first unit (101) configured for decomposing the medical image (IM) into at least one band pass image (Bdl) and a low pass image (L); a user interface (102) arranged for enabling a user to specify an enhancement curve (EC) for the radiographic image (IM) based on at least one of (i) a metric structure length (l), (ii) a structure selectivity (s) and (iii) a structure enhancement strength (a); a second unit (103) configured for applying the enhancement curve (EC) to the at least one band pass image (Bdl) for generating at least one enhanced band pass image EBdl; and a third unit (105) configured for composing an enhanced medical image (EIM) based on the at least one enhanced band pass image (EBdl) and the low pass image (L). The invention also relates to a corresponding method of processing a medical image (IM).

Abstract: Sub-pixel compensation is described. In at least some implementations, a computing device includes a plurality of sub-pixels within a pixel which may generate an alternating display to approximate the display of a single sub-pixel. In other implementations, a voltage is applied to sub-pixels of a color such that a voltage across a first sub-pixel is proportional to a voltage across one or more additional sub-pixels. In other implementations, a change in a voltage drop across a sub-pixel is detected, and the change is compensated for by altering a voltage of a second sub-pixel within the pixel.

Abstract: Systems, methods, and non-transitory computer-readable media can capture media content including an original set of frames. A plurality of subsets of frames can be identified, based on a subset selection input, out of the original set of frames. An orientation-based image stabilization process can be applied to each subset in the plurality of subsets of frames to produce a plurality of stabilized subsets of frames. Multiple frames within each stabilized subset in the plurality of stabilized subsets of frames can be combined to produce a plurality of combined frames. Each stabilized subset of frames can be utilized to produce a respective combined frame in the plurality of combined frames. A time-lapse media content item can be provided based on the plurality of combined frames.

Abstract: A method for using a GNSS device to determine a position of an unknown point includes determining positions of a first point, a second point, and a third point using the GNSS device. A first image is captured of the first point using an image sensor, the image includes the unknown point and at least one of the second point or the third point. A second image is captured from the second point; the second image includes the unknown point and at least one of the second point or the third point. A third image is captured from the third point; the third image includes the unknown point and at least one of the second point or the first point. A position of the unknown point is calculated based on the first, second, and third images and the first, second, and third positions.

Abstract: A generative network is used for lung lobe segmentation or lung fissure localization, or for training a machine network for lobar segmentation or localization. For segmentation, deep learning is used to better deal with a sparse sampling of training data. To increase the amount of training data available, an image-to-image or generative network localizes fissures in at least some of the samples. The deep-learnt network, fissure localization, or other segmentation may benefit from generative localization of fissures.

Abstract: Embodiments of the present disclosure relate to a configurable convolution engine that receives configuration information to perform convolution or its variant operations on streaming input data of various formats. To process streaming input data, input data of multiple channels are received and stored in an input buffer circuit in an interleaved manner. Data values of the interleaved input data are retrieved and forwarded to multiplier circuits where multiplication with a corresponding filter element of a kernel is performed. Varying number of kernels with different sizes and sparsity can also be used for the convolution operations.

Abstract: An image processing apparatus operable to perform development processing by performing at least a tone conversion on RAW image data that is inputted image data, the image processing apparatus comprising: a setting unit configured to set a first tone conversion curve corresponding to a dynamic range of the image data; an adjusting unit configured to generate a second tone conversion curve by adjusting the first tone conversion curve so that luminance changes of a bright portion and a dark portion of the image data are visually equivalent; and a tone conversion unit configured to perform a tone conversion of the image data by using the second tone conversion curve.

Abstract: An image processing apparatus including a selection section which, by selecting an electricity consumption minimum value where electricity consumption of a display section, which performs a display based on a value out of a plurality of values which are present within a predetermined distance from a pixel value of an image in a uniform color space, is a minimum as a pixel value of the image after color conversion, generates an image after the color conversion.

Abstract: A display apparatus is provided. The display apparatus includes a display panel comprising a plurality of pixels, a panel driver configured to drive the display panel, a storage configured to store information regarding a color gamut of each of the plurality of pixels, and a processor configured to determine a target color gamut of each of the plurality of pixels so that a difference in color gamut from at least one adjacent pixel is equal to or less than a predetermined threshold value, and to drive the panel driver for each of the plurality of pixels to have a grayscale value based on the target color gamut.

Abstract: An inspection apparatus and method comprising a unit for acquiring an optical image of an object to be inspected by irradiating the object with light, wherein the unit includes a line sensor comprising a plurality of sensors linearly arranged in a row, a generating unit for generating a reference image from design data of the object to be inspected, a comparing unit for comparing the optical image with the reference image, a unit for storing data of three lines acquired by the line sensor, and calculating differences between a gradation value of a pixel on a center line and each gradation value of the eight pixels adjacent to the pixel determining if the pixel is a defect if all of the eight differences of the adjacent pixels are more than a predetermined threshold.