Abstract: Apparatus, method, and computer program code for producing composite image. A method comprises: obtaining (150) a first image (130) with first depth information; obtaining (152) a second image (132) with second depth information; detecting (154) regions of interest in the first image (130); segmenting (156) the regions of interest into individual layers; performing (158) image compensation for the individual layers according to the first depth information so that in image compensated individual layers a perspective and/or a viewpoint of the first image (130) is modified to be more similar with the second image (132); and rendering (160) the image compensated individual layers with the second image (132) utilizing the first depth information and the second depth information in order to produce a composite image (134).

Abstract: Provided is an image display apparatus that displays a page image including a plurality of objects on a screen, determines an amount of movement of the end of the object to be displayed from the end of the screen by detecting a user operation on a touch panel, and sets the end position of the object based on the determined amount of movement when the object to be displayed is larger than the screen.

Abstract: Environmental map generation techniques and systems are described. A digital image is scaled to achieve a target aspect ratio using a content aware scaling technique. A canvas is generated that is dimensionally larger than the scaled digital image and the scaled digital image is inserted within the canvas thereby resulting in an unfilled portion of the canvas. An initially filled canvas is then generated by filling the unfilled portion using a content aware fill technique based on the inserted digital image. A plurality of polar coordinate canvases is formed by transforming original coordinates of the canvas into polar coordinates. The unfilled portions of the polar coordinate canvases are filled using a content-aware fill technique that is initialized based on the initially filled canvas. An environmental map of the digital image is generated by combining a plurality of original coordinate canvas portions formed from the polar coordinate canvases.

Abstract: An image scale device for up-scaling an input image by generating data signals for a plurality of additional pixels, the additional pixels added to the input image to generate an up-scaled image, the device comprising an RGB interpolator configured to generate red (R), green (G), and blue (B) data signals for each of the additional pixels on the basis of the R, G, and B data signals of an arbitrary pixel among pixels of the input image that are adjacent to the respective additional pixel, and a W interpolator configured to generate a white (W) data signal for each of the additional pixels on the basis of W data signals of the pixels of the input image that are adjacent to the respective additional pixel.

Abstract: A method and an apparatus for generating an image are provided. A specific embodiment of the method comprises: acquiring a to-be-processed facial image, the image resolution of the to-be-processed facial image being lower than a preset first resolution threshold; and inputting the to-be-processed facial image into a pre-trained generativemodel to generate a processed facial image. The generative model updates a model parameter using a loss function in a training process, and the loss function is determined based on a probability of an image group being positive sample data, the image group composed of a facial sample image and a facial generative image. According to this embodiment, authenticity of the generated facial image is enhanced.

Abstract: An edge image generating unit detects edge pixels in an original image and generates an edge image that includes the detected edge pixels. A reduction processing unit sets a reduction direction as a horizontal or a vertical direction, and reduces the edge image along the reduction direction by a predetermined reduction ratio without reducing the original image along a direction perpendicular to the reduction direction and thereby generates a reduced image. A connecting pixel group detecting unit detects, in the reduced image, a connecting pixel group continuously extending along the reduction direction. A ruled line determining unit associates two connecting pixel groups with each other as a connecting pixel group pair among the detected connecting pixel groups, and determines a position of a ruled line in the original image from a position of the connecting pixel group pair on the basis of the reduction ratio.

Abstract: An image stitching method and an image stitching device for stitching a first image and a second image are presented. The image stitching method includes: calculating, according to pixel values of the first image and the second image in an overlapping area, a plurality of costs respectively corresponding to a plurality of positions in the overlapping area; calculating, according to the plurality of costs and relative distances between the plurality of positions, a plurality of forward regularized cumulative costs respectively corresponding to the plurality of positions in the overlapping area; determining a seam in the overlapping area according to the plurality of forward regularized cumulative costs, wherein the seam includes a plurality of stitching positions; and stitching the first image and the second image on the basis of the seam to generate a stitched image.

Abstract: High resolution style transfer techniques and systems are described that overcome the challenges of transferring high resolution style features from one image to another image, and of the limited availability of training data to perform high resolution style transfer. In an example, a neural network is trained using high resolution style features which are extracted from a style image and are used in conjunction with an input image to apply the style features to the input image to generate a version of the input image transformed using the high resolution style features.

Abstract: Systems and methods are provided for image scaling with efficient pixel resolution conversion. One embodiment is an image scaling system that includes a processor that receives an instruction to scale an input image having a first resolution by a scaling ratio to create an output image having a second resolution, and determines a rational fraction approximation of the scaling ratio to obtain a numerator integer representing a first block of consecutive pixels in the output image and a denominator integer representing a second block of consecutive pixels in the input image. The processor also calculates pixel values of the first block of pixels by: bit shifting pixel values of the second block of pixels, obtaining a sum of bit shifting operations of neighboring pixel values of the second block of pixels, and correcting the sum with a correction value to compensate for rounding errors in the bit shifting.

Abstract: Disclosed are a method and device for transmitting and displaying an image, a storage medium, and a processor. The method includes: segmenting a target image into multiple regions to obtain multiple regional images, where the multiple regions to which the regional images belong include a first region and a second region, the first region is a region on which a gaze point falls, and the second region is a region other than the first region in the target image; assigning resolutions to the respective regional images of the target image, where the respective regional images have different resolutions; and transmitting, one by one, the respective regional images have different resolutions.

Abstract: An image processing system includes a storage device, and a processor coupled to the storage device and configured to extract, from an input image, an aerosol spectrum across a plurality of wavelength bands of the input image. The storage device contains therein a database storing a plurality of predetermined aerosol spectra, and a plurality of corresponding values associated with an aerosol optical property at the plurality of wavelength bands. The processor is further configured to retrieve, from the database, values associated with the aerosol optical property at the plurality of wavelength bands, the retrieved values corresponding to the extracted aerosol spectrum. The processor is further configured to correct the input image, by using the retrieved values associated with the aerosol optical property at the plurality of wavelength bands, to generate a corrected image.

Abstract: A memory device receives an original input image having at least one horizontal reticle or at least one vertical reticle. The memory device also receives a horizontal reticle mask image for horizontal reticles and/or a vertical reticle mask image for vertical reticles. A processor inpaints three regions: (1) vertical reticles with a horizontal filter, (2) horizontal reticles with a vertical filter, and (3) an intersection of the horizontal and vertical reticles with a two dimensional filter. A single inpainted image is produced. The processor determines whether a maximum change in any one of the first inpainted region, the second inpainted region or the third inpainted region equals or exceeds a predetermined threshold, and if so, repeating the inpainting steps. Once the maximum change in pixel intensity is less than the predetermined threshold the processing stops.

Abstract: An image local contrast enhancement method includes: obtaining a first block where a pixel is located and a second block adjacent to the first block, and a gray scale source of a third block; obtaining a source gray scale of a fourth block opposite to the first block; respectively calculating a linear interpolation value according to the source gray scale and a distance between the pixel and the first block, the second block, the third block, and the fourth block; calculating a nonlinear interpolation value of the linear interpolation value by a nonlinear function; performing weighted calculation on the nonlinear interpolation value to obtain a target gray scale. The disclosure increases the diagonal blocks in the local gray scale adjustment, reflects the diagonal direction of the image, enhances the display effect of the local contrast in the smoothing process, enhances the edge image display effect, and improves the user experience.

Abstract: To encode High Dynamic Range (HDR) images, the HDR images can be converted to Low Dynamic Range (LDR) images through tone mapping operation, and the LDR images can be encoded with an LDR encoder. The present principles formulates a rate distortion minimization problem when designing the tone mapping curve. In particular, the tone mapping curve is formulated as a function of the probability distribution function of the HDR images to be encoded and a Lagrangian multiplier that depends on encoding parameters. At the decoder, based on the parameters indicative of the tone mapping function, an inverse tone mapping function can be derived to reconstruct HDR images from decoded LDR images.

Abstract: An image processing method and apparatus, and a storage medium are provided in the technical field of display. The method may include: acquiring pixel data of an image to be processed; acquiring a histogram of the image according to the pixel data, the histogram indicating a pixel number under each grey scale; obtaining a target grey scale set by using in the histogram a grey scale whose pixel number exceeds a preset pixel number; selecting, from the image, a target pixel whose grey scale belongs to the target grey scale set from the image; and performing a color inversion operation to the target pixel. The color inversion operation is performed to the background pixels and character pixels. Thus, the image grey scales may be reduced while maintaining the contrast of the image, and influence to the image definition by the grey scales is reduced.

Abstract: An image processing apparatus obtains distance information indicating a distance to each of one or more objects of an image, performs grouping of the one or more objects in accordance with the distance to each object, extracts a plurality of object regions of the image in accordance with the grouping, and determines, in accordance with a number of the plurality of object regions extracted by the extraction unit, whether to perform tone conversion by applying a same tone characteristic to the image as a whole or to perform tone conversion by applying different tone characteristics for respective regions of the image.

Abstract: An apparatus includes a first brightness value acquisition unit configured to obtain a first absolute brightness value by converting a representative brightness value of an image obtained using an image pickup unit, into absolute brightness, a first determination unit configured to determine an output value based on an input-output characteristic of an output device, the output value corresponding to the first absolute brightness value obtained by the first brightness value acquisition unit, and a second determination unit configured to determine information about exposure corresponding to the output value.

Abstract: This disclosure relates generally to image processing, and more particularly to generate a high resolution image from multiple low resolution images. In an embodiment, the system collects a plurality of low resolution images as input, processes the collected images, and generates a high resolution image as output. During this process, the system pre-processes the collected low resolution images, and during this process, at least one characteristic of each of the low resolution image is changed with respect to a reference image. After the pre-processing stage, the images are then enhanced based on a plurality of final enhancement factors that are dynamically determined. Further, the enhanced images are fused to generate the high resolution image.

Abstract: A fusion decision processing section 36-3 performs, based on a feature amount calculated by using a moving image of a monochrome imaged image acquired by imaging a subject with an imaging section 21-1 and a color imaged image acquired by imaging the subject from a different point-of-view position with an imaging section 21-2, fusion decision as to whether or not deterioration of image quality is caused in fusion processing in the fusion processing section 35 for producing a fusion image by fusion of the monochrome imaged image and the color imaged image with the monochrome imaged image as a reference, for each image of the moving image.

Abstract: The present disclosure discloses an image display method and apparatus in a virtual reality (VR) device. The method includes: obtaining a first image to be displayed by the VR device, an edge of a target object in the first image having an aliasing shape, the VR device being provided with an electromagnetic vibrator, and the electromagnetic vibrator being configured to control the first image to move by a first distance along a first direction; obtaining a second image after the electromagnetic vibrator vibrates, the second image being an image obtained after the first image is moved by the first distance along the first direction; performing a superimposition operation on the first image and the second image to obtain a target image, an edge of the target object in the target image changing from the aliasing shape to a smooth shape; and displaying the target image in the VR device.

Abstract: Systems and methods for defection classification in a semiconductor process are provided. The system includes a communication line configured to receive a defect image of a wafer from the semiconductor process and a deep-architecture neural network in electronic communication with the communication line. The neural network has a first convolution layer of neurons configured to convolve pixels from the defect image with a filter to generate a first feature map. The neural network also includes a first subsampling layer configured to reduce the size and variation of the first feature map. A classifier is provided for determining a defect classification based on the feature map. The system may include more than one convolution layers and/or subsampling layers. A method includes extracting one or more features from a defect image using a deep-architecture neural network, for example a convolutional neural network.

Abstract: A method includes automatically aligning a laser-based timing analysis image of a semiconductor device with an image of a layout of the device. The method further includes controlling a speed at which a multitude of images subsequently obtained by the laser-based timing analysis are compared to the layout of the device to create a video overlay. The method further includes analyzing a multitude of potential failures of the semiconductor device by detecting movements of a multitude of hotspots on the layout as shown by the video overlay.

Abstract: Disclosed are a substrate inspection apparatus and a method for displaying a component in a three-dimensional inspection of a substrate. The substrate inspection apparatus measures a substrate or an inspection target region of interest of the substrate and displays an image of components positioned within the measured region on a display unit. The image of the components displayed on the display unit may be displayed in a predetermined reference direction. The difference between the reference direction and a direction in which the actual component is disposed on the substrate is displayed in the form of a numerical value or a figure. Alternatively, the image of the component in the reference direction and the image of the actually disposed component are simultaneously displayed on a screen, and a user may convert a display method of the image by using a toggle button.

Abstract: A fuel filter inspection method includes capturing an image of a fuel filter sample using an imaging device and sending the captured image to an image processor. The method further includes the image processor receiving the captured image, thresholding the captured image to generate a binary image, determining sizes for a plurality of particles present in the binary image, comparing the size of each of particle of the plurality of particles to a particle size threshold, and quantifying the number of particles of the plurality of plurality of particles with a size greater than the particle size threshold. The method further includes the image processor comparing the number of particles of the plurality of particles with a size greater than the particle size threshold to a particle count threshold, and modifying a graphical user interface to indicate a state of the fuel filter sample based on the comparison.

Abstract: Computer-implemented methods are used to analyze a medical image to assess the state of the sample region. In at least one embodiment, the method comprises receiving at least one medical image collected previously from an image source, the at least one medical image comprising a plurality of voxels, each characterized by a signal value; classifying the signal value of each voxel as representing one of healthy tissue or diseased tissue based on a threshold value; and analyzing at least one topographical feature of the at least one medical image.

Abstract: An image generation method is described, comprising obtaining a plurality of 2D images through an object to be imaged, obtaining a 3D image data set of the object to be imaged, and registering the 2D images with the 3D image data set. The method then further includes defining an image reconstruction plane internal to the object, being the plane of an image to be reconstructed from the plurality of 2D images. Then, for a pixel in the image reconstruction plane, corresponding pixel values from the plurality of 2D images are mapped thereto, and the mapped pixel values are combined into a single value to give a value for the pixel in the image reconstruction plane. Another aspect of the method provides for clutter removal from the image. In a medical imaging context this can provide for “de-boned” images, allowing soft tissue to be more clearly seen.

Abstract: A device and method integrates a lesion stager in a reporting tool. The method includes receiving a user input. The user input is image data including at least one variable value. The variable value is indicative of a variable parameter of the image data. The method includes associating each of the at least one variable value with a corresponding variable parameter to generate at least one variable-value pair. The method includes determining a computed output value as a function of select ones of the at least one variable-value pair.

Abstract: Embodiments access an image of a region of interest (ROI) demonstrating cancerous pathology; extract radiomic features from the ROI; define a radiomic feature expression scene based on the ROI and radiomic features; generate a cluster map by superpixel clustering the expression scene; generate an expression map by repartitioning the cluster map into expression levels; compute a textural and spatial phenotypes for the expression map based on the expression levels; construct a radiomic spatial textural (RADISTAT) descriptor by concatenating the textural and spatial phenotypes; provide the RADISTAT descriptor to a machine learning classifier; receive, from the machine learning classifier, a first probability that the ROI is a responder or non-responder, or a second probability that the ROI will experience long-term survival or short-term survival, based, at least in part, on the RADISTAT descriptor; and generate a classification of the ROI as a responder or non-responder, or long-term survivor or short-term surv

Abstract: A plurality of projection images are obtained, on a basis of plural pieces of three-dimensional image data obtained by imaging an object at a plurality of different time points, by projection from a plurality of different projection directions corresponding to projection images in accordance with a three-dimensional partial region where a pixel value is increased and a three-dimensional partial region where the pixel value is decreased at a second time point with respect to a first time point among the plurality of time points, and the plurality of projection images are displayed on a display unit.

Abstract: A method and system for inspecting a customized orthodontic aligner for manufacturing defects are described. The method includes obtaining images of the customized orthodontic aligner, determining a digital file associated with the aligner, the digital file including a digital model of a mold used during manufacture of the customized orthodontic aligner, determining an inspection recipe for the aligner, determining an intended property for the customized orthodontic aligner by digitally manipulating the digital model of the mold, determining an actual property of the customized orthodontic aligner from the images, determining whether there is a manufacturing defect in the customized orthodontic aligner by comparing the intended property with the actual property, and outputting an output associated with the determination of whether there is a manufacturing defect.

Abstract: Disclosed are Computer Aided Diagnosis (CAD) apparatus and method to combine information on sequential image frames and to provide a superior classification result for the ROI in the image frame. The CAD apparatus may include a Region of Interest (ROI) detector configured to detect an ROI from image frames, a categorizer configured to create groups of image frames having successive ROI sections from among the image frames based on a result of the detection, a classifier configured to classify an ROI detected from each of the image frames belonging to the groups, and a result combiner configured to combine classification results for the image frames belonging to each group from the groups and to calculate a group result for the each group.

Abstract: The subject matter disclosed herein relates to methods for diagnosing a neurological disorder in a subject. In certain aspects, the methods described herein involve determining one or more critical areas in the brain from PET data where two groups differ and measuring PET signal within determined critical areas in a new subject in order to assign risk or diagnosis.

Abstract: In some aspects, the described systems and methods provide for a method for training a statistical model to predict tissue characteristics for a pathology image. The method includes accessing annotated pathology images. Each of the images includes an annotation describing a tissue characteristic category for a portion of the image. A set of training patches and a corresponding set of annotations are defined using an annotated pathology image. Each of the training patches in the set includes values obtained from a respective subset of pixels in the annotated pathology image and is associated with a corresponding patch annotation determined based on an annotation associated with the respective subset of pixels. The statistical model is trained based on the set of training patches and the corresponding set of patch annotations. The trained statistical model is stored on at least one storage device.

Abstract: A method is for classifying an examination object by way of recordings. In an embodiment, the method includes capturing at least one optical recording of the examination object; determining and quantifying a number of defined characteristics of the examination object based upon an analysis of the optical recordings with the aid of a machine learning method; and affecting the classification of the examination object in respect of a classification criterion, based upon the quantified characteristics with the aid of a machine learning method. Also described are a classification entity and a medical imaging modality.

Abstract: A medical image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry acquires image data including image data of a blood vessel of a subject. The processing circuitry performs analysis related to the blood vessel by using the image data, and specifies a region of interest in the blood vessel based on a result of the analysis. The processing circuitry performs fluid analysis on a region other than the region of interest at a first accuracy, and performs fluid analysis on the region of interest at a second accuracy that is higher than the first accuracy.

Abstract: An image segmentation method, an image segmentation system, a storage medium and an apparatus including the image segmentation system or the storage medium are provided. The image segmentation method includes: obtaining a connected region where a target object is located from a depth image; determining a principal direction or a secondary direction of the connected region by a principal component analysis method; and acquiring an image of the target object from the connected region according to relationship between morphology of the target object and the principal direction or the secondary direction.

Abstract: Embodiments can provide a strategy for controlling information flow both from known opacity regions to unknown regions, as well as within the unknown region itself. This strategy is formulated through the use and refinement of various affinity definitions. As a result of this strategy, a final linear system can be obtained, which can be solved in closed form. One embodiment pertains to identifying opacity information flows. The opacity information flow may include one or more of flows from pixels in the image that have similar colors to a target pixel, flows from pixels in the foreground and background to the target pixel, flows from pixels in the unknown opacity region in the image to the target pixel, flows from pixels immediately surrounding the target pixels in the image to the target pixel, and any other flow.

Abstract: An interactive image segmenting apparatus and method are provided. The image segmenting apparatus and corresponding method include a boundary detector, a condition generator, and a boundary modifier. The boundary detector is configured to detect a boundary from an image using an image segmentation process. The feedback receiver is configured to receive information about the detected boundary. The condition generator is configured to generate a constraint for the image segmentation process based on the information. The boundary modifier is configured to modify the detected boundary by applying the generated constraint to the image segmentation process.

Abstract: There is provided an image processing apparatus. A line segment detecting unit detects line segments from an image. An obtainment unit obtains distance information indicating a distance in a depth direction of the image. A selecting unit selects a line segment for vanishing point detection from the line segments detected by the line segment detecting unit. A vanishing point detecting unit detects a vanishing point of the image on a basis of the line segment for vanishing point detection. For each line segment detected by the line segment detecting unit, the selecting unit selects the line segment in a case where the distance indicated by the distance information is in a monotonically changing trend along the line segment.

Abstract: The inventive subject matter is directed to point-of-care analytical devices that accurately determine the volume of test samples using image analysis to improve the accuracy of test results performed on the sample. Most preferably, the image analysis is based on rate changes in optical saturation that parallels sample saturation in a porous structure containing the sample.

Abstract: Feature based visual simultaneous localization and mapping (SLAM) do not produce reliable camera and structure estimates due to insufficient features in a low-textured environment. Moreover, existing visual SLAMs produce partial reconstruction when the number of 3D-2D correspondences is insufficient for incremental camera estimation using bundle adjustment. Systems and methods of the present disclosure provide edge points based monocular visual SLAM that mitigates these problems. The SLAM is initialized through a validation process. A local optimization process is provided for stable pose estimation in situations where camera tracking becomes unreliable in a very low-textured challenging environment. An efficient and reliable loop closing process that uses structural properties of edges in the frames is also provided.

Abstract: A lane detection method and apparatus is disclosed. The lane detection apparatus may set a regions of interest (ROIs) in a forward-view image of a vehicle obtained by a camera, estimate lane pixels corresponding to a lane from each of the ROIs using a neural network-based detector, and determine a lane region in the forward-view image based on the lane pixels.

Abstract: There are provided a system and method of vehicle image comparison, the method including: obtaining an input image capturing at least part of a vehicle; segmenting the input image into one or more input segments corresponding to one or more mechanical components; retrieving a set of reference images, thereby obtaining a respective set of corresponding reference segments for each input segment; and generating at least one difference map corresponding to at least one input segment, comprising, for each input segment: comparing the input segment with each corresponding reference segment thereof using a comparison model, giving rise to a set of difference map candidates each indicating probability of presence of DOI between the given input segment and the corresponding reference segment; and providing a difference map corresponding to the given input segment according to probability of each difference map candidate in the set of difference map candidates.

Abstract: A system, computer-readable medium, and method for improving semantic mapping and traffic participant detection for an autonomous vehicle are provided. The methods and systems may include obtain a two-dimensional image, obtain a three-dimensional point cloud comprising a plurality of points, perform semantic segmentation on the image to map objects with a discrete pixel color, and overlaying the semantic segmentation on the image to generate a updated image, generate superpixel clusters from the semantic segmentation to group like pixels together, project the point cloud onto the updated image comprising the superpixel clusters, and remove points determined to be noise/errors from the point cloud based on determining noisy points within each superpixel cluster.

Abstract: A phase correlation method (PCM) can be used for translational and/or rotational alignment of 3D medical images even in the presence of non-rigid deformations between first and second images of a registered volume of a patient.

Abstract: A method for tracking eye movement is provided. One embodiment of the method includes receiving a first measurement from a first sensor configured to detect a gaze location, determining an initial gaze location based at least on the first measurement, receiving at least one of eye motion amplitude and eye motion direction measurement from a second sensor, and determining an estimated gaze location based at least on the initial gaze location and the at least one of eye motion amplitude and eye motion direction. Systems perform similar steps, and non-transitory computer readable storage mediums each store one or more computer programs.

Abstract: The present technology relates to a display control apparatus and a method, an image processing apparatus and a method, and a program that enable easy and noninvasive observation of an object to be observed. A first display control unit configured to perform display control of a cell image with one or a plurality of images including cells, and a second display control unit configured to perform display control such that a part or all of a motion amount generated for each of subregions with the one or the plurality of images is associated with each of the subregions, and is superimposed on the cell image and is displayed, are provided. The present disclosure can be applied to a display control apparatus or an image processing apparatus.

Abstract: According to an embodiment, a measurement device includes a processing circuitry. A plurality of images are captured in time series by an image capturing unit installed in a moving object. The processing circuitry identifies a region in which other moving object moving in surroundings of the moving object is present for each of the images, based on position and direction information of the moving object, and moving object information of the other moving object. The processing circuitry estimates position and posture of the image capturing unit based on the images. The processing circuitry searches for sets of corresponding points among non-moving object regions in the respective images. The processing circuitry performs 3D measurement based on the position and posture of the image capturing unit and the sets of the corresponding points.

Abstract: The present application relates to systems and methods used to characterize or verify the accuracy of a tracker comprising optically detectable features. The tracker may be used in spatial localization using an optical sensor. Characterization results in the calculation of a Tracker Definition that includes geometrical characteristics of the tracker. Verification results in an assessment of accuracy of a tracker against an existing Tracker Definition.

Abstract: A method includes obtaining reference imaging data. The reference imaging data is acquired at a first time and includes tissue of interest. The method further includes obtaining update imaging data. The update imaging data is acquired at a second time. The second time is subsequent to the first time. The method further includes identifying a difference between the reference imaging data and the update imaging data. The method further includes changing the reference imaging data based on the identified difference. The method further includes displaying the changed reference imaging data.