Abstract: A radiological image detection apparatus includes an imaging unit, a storage unit, a correction data generating unit, a correction unit, a disturbance detection unit, and a determination unit. The imaging unit acquires radiological image data. The storage unit stores correction data for correcting the radiological image data. The correction data generating unit generates new correction data based on dark image data and updates the correction data stored in the storage unit. The correction unit performs a correction process for the radiological image data using the correction data. The disturbance detection unit detects a disturbance acting when the imaging unit acquires the dark image data. The determination unit determines whether the updating of the correction data stored in the storage unit is permitted, or whether the acquisition of the dark image data is permitted, based on the detection result of the disturbance detection unit.

Abstract: A calculation method of optical proximity correction includes providing at least a feature pattern to a computer system. At least a first template and a second template are defined so that portions of the feature pattern are located in the first template and the rest of the feature pattern is located in the second template. The first template and the second template have a common boundary. Afterwards, a first calculation zone is defined to overlap an entire first template and portions of the feature pattern out of the first template. Edges of the feature pattern within the first calculation zone are then fragmented from the common boundary towards two ends of the feature pattern so as to generate at least two first beginning segments respectively at two sides of the common boundary. Finally, positions of the first beginning segments are adjusted so as to generate first adjusted segments.

Abstract: An image processing device includes a first production part configured to apply a first smoothing process to an original image data by using a first edge-preserving smoothing filter to produce first image data that include a low-frequency image and an edge image, a second production part configured to apply a second smoothing process to a differential image between the original image data and the first image data to produce second image data that include a high-frequency image, and a synthesis part configured to synthesize the first image data and the second image data.

Abstract: There is provided an image processing apparatus including a vector detection unit which detects flow vectors of pixels in an inputted image, a vector-coherency calculation unit which calculates vector coherency based on the flow vectors detected by the vector detection unit, a deformation-characteristic computation unit which computes a deformation characteristic by using the vector coherency calculated by the vector-coherency calculation unit, the deformation characteristic being used for deforming a tap shape of a filter used for each of the pixels, and a painterly conversion unit which converts the inputted image based on the deformation characteristic computed by the deformation-characteristic computation unit.

Abstract: A system for contextualizing noisy samples by substantially minimizing noise induced variance may include a memory, an interface, and a processor. The memory is operative to store exemplars. The processor is operative to receive, via the interface, a sample which includes exemplar content corresponding to one of the exemplars, and noise. Variance induced by the noise may differentiate the sample from one or more of the exemplars. The processor may generalize the sample and the exemplars in order to substantially minimize the variance. The processor may compare the generalized sample to the generalized exemplars to identify the exemplar corresponding to the exemplar content of the sample. The processor may contextualize the sample based on a document type of the identified exemplar. The processor may present the contextualized sample to a user to facilitate interpretation thereof, and in response thereto, receive data representative of a user determination associated with the noise.

Abstract: This invention is to provide an image processing apparatus, an image processing method, a program, and a display in which both of a secret image and a public image can be efficiently displayed with high picture quality without reducing contrast of the public image. One of output images is a secret image which displays an input secret image as one of input images in a partial area of a screen, all the output images including the secret image have a relationship to become, when a luminance value of each pixel thereof is totaled, an input public image as one of the input images; and during a period in which at least the secret image is being outputted, shutter glasses disposed between a display to which the image signals are inputted and user's eyes are set to a light transmission state.

Abstract: Disclosed are embodiments for a system, method, and computer program product for performing an process on an original image, the process being implemented by a computer system performs a comprising the at least one computer: performing an process on an image that renders the processed image legible than then the original image, wherein the analysis segregates dark pixels of the image from light pixels of the image. The method can comprise: first converting the image into a grayscale image. The method comprises processing a pixel area for each pixel of the image is a dark pixel or a light pixel and determining if a pixel is proximate to an edge.

Abstract: The present invention relates to a method and device for obtaining an image of a crumpled document from an image of this document when it is crumpled. The method comprises a step of determining a three-dimensional geometric model of the surface of the crumpled document by triangulation of three-dimensional points defined from the pattern of a target extracted from the image of this document when it is crumpled; the method is characterized in that it comprises a step of determining a projection of the three-dimensional geometric model onto a so-called acquisition plane, by means of error minimization of this projection under constraints of preserving defined geometric characteristics in the vicinity of the three-dimensional points, and in that it comprises a step of superimposing the textures associated with the three-dimensional model onto the projection of this model thus determined.

Abstract: A filtering method and apparatus for anti-aliasing takes advantage of improved existing hardware by using as input the data stored in the multisampling anti-aliasing (MSAA) buffers after rendering. The standard hardware box-filter is then replaced with a more intelligent resolve implemented using shader programs. Embodiments find scene edges using existing samples generated by Graphics Processing Unit (GPU) hardware. Using samples from a footprint larger than a single pixel, a gradient is calculated matching the direction of an edge. A non-linear filter over contributing samples in the direction of the gradient gives the final result.

Abstract: A method and system for providing a dynamic grain effect tool for a media-editing application that generates a grain effect and applies the grain effect to a digital image. The application first generates a random pixel field for the image based on a seed value. The application then generates a film grain pattern for the image by consecutively applying a blurring function and an unsharp masking function, based on an ISO value, to the randomly generated pixel field. The application then blends the grain field with the original image by adjusting each pixel based on the value of the corresponding pixel location in the grain field. The application then adjusts the grain amount in the previously generated full-grain image by receiving a grain amount value from a user and applying this value to the full-grain image.

Abstract: An image processing method is configured to denoise three-dimensional image data. The image processing method includes an image transform step of performing a frequency transform for the three-dimensional image data in the optical axis direction and of calculating three-dimensional transformed image data, an image modulation step of reducing an absolute value of the three-dimensional transformed image data in a specific frequency region and of calculating three-dimensional modulated image data, and an inverse image transform step of performing an inverse frequency transform corresponding to the frequency transform for the three-dimensional modulated image data in the optical axis direction and of calculating three-dimensional inversely transformed image data. The specific frequency region is a part of a predetermined.

Abstract: A method of large-radius edge-preserving low-pass filtering a digital signal having data points, including computing a weighted average of a signal layer at vertices spaced a distance apart such that an amount of the vertices is less than an amount of the data points; and producing, for each of the data points, a large-radius edge-preserving low-pass filtered signal based on the weighted average of the signal layer at vertices neighboring the data point.

Abstract: Devices, systems, apparatuses, methods, and other embodiments associated with bit resolution enhancement are described. In one embodiment, an apparatus includes logic configured to produce a high-resolution pixel from a low-resolution pixel. The apparatus includes logic configured to classify the high-resolution pixel as being in a smooth region of an image based on at least one of a gradient value and a variance value associated with the low-resolution pixel. The apparatus includes logic configured to selectively re-classify the high-resolution pixel as not being in the smooth region of the image based on a set of neighboring high-resolution pixels associated with high-resolution pixel. The apparatus includes logic configured to selectively filter the high-resolution pixel based on whether the high-resolution pixel remains classified as being in the smooth region of the image.

Abstract: The disclosed technology provides a system and a method for adaptive MPEG noise reduction. In particular, the disclosed technology provides a system and a method for reducing blocking artifacts and mosquito noise in an MPEG video signal. An overall MPEG noise detector may be used to determine the presence of noise in one or more frames of a video signal. When a sufficient amount of noise is detected in the one or more frames of the video signal, portions of the video signal that contain noise may be located and filtered to reduce the amount of noise present in the video signal.

Abstract: Image processing includes: receiving an image; applying shader code, using one or more processors, to the image to generate a blurred image version (BIV); receiving configuration information pertaining to a mask; generating the mask that includes an unblurred region and a blurred region, based at least in part on the configuration information; and applying the mask to combine the image and the BIV to render a composite image that includes an unblurred portion comprising a portion of the image corresponding to the unblurred region of the mask, and a blurred portion comprising a portion of the BIV corresponding to the blurred region of the mask.

Abstract: An image processor includes: an image group generating unit that generates, from an original image, a group of images including at least one smoothed image; an illumination image generating unit that generates an illumination image by use of at least one of the images included in the group of images; a smoothed image acquiring unit that acquires a particular smoothed image based on the at least one smoothed image; a reflection rate image generating unit that generates a reflection rate image based on the original image, the particular smoothed image, a synthesizing degree information which represents a synthesizing degree of the original image and the particular smoothed image, and the illumination image, and a reproduction image generating unit that generates a reproduction image which is reproduced so that visibility of the original image is enhanced, based on at least the reflection rate image and an enhancing degree information.

Abstract: A system for enhancing an input image including receiving an input image and filtering the input image with a plurality of non-linear smoothing filters providing a respective plurality of filtered outputs. The system processes a plurality of the filtered outputs with respect to at least one of another of the filtered outputs and the input image to determine a plurality of detail layers. The system filters the plurality of detail layers with a plurality of non-linear smoothing filters providing a respective plurality of smoothed layers. The system adjusts the plurality of smoothed layers in such a manner that regions closer to an edge are enhanced to a lesser extent than regions farther from an edge and combining the adjusted the smoothed layers to provide an enhanced output image.

Abstract: Disclosed are a depth image noise removal apparatus based on a camera pose, which includes: a depth image obtaining unit for obtaining a plurality of depth images; a camera pose converting unit for converting camera poses of the plurality of depth images into a camera pose of a reference depth image; and a depth image filtering unit for filtering the reference depth image by using a weighted average of each pixel of the reference depth image, and a method using this apparatus.

Abstract: An image forming apparatus and a printing control terminal apparatus include an input unit to receive printing data, a rendering unit to transform the printing data into bitmap data, an image processor to determine whether the bitmap data includes a transparency pattern and if it is determined that the bitmap data includes the transparency pattern, perform smoothing processing with respect to the bitmap data; and an output unit to output the bitmap data processed by the image processor. Accordingly, an image quality of printing data including a transparency pattern can be improved. In addition, an image forming method includes receiving image data including a plurality of pixels, determining whether an area of pixels is a patterned area including a pattern, determining the patterned area is transparent when the pattern of the patterned area matches a pre-stored pattern, performing a smoothing process on the patterned area, and printing the image data after performing the smoothing.

Abstract: Disclosed are embodiments for a system, method, and computer program product for performing an process on an original image, the process being implemented by a computer system performs a comprising the at least one computer: performing an process on an image that renders the processed image legible than then the original image, wherein the analysis segregates dark pixels of the image from light pixels of the image. The method can comprise: first converting the image into a grayscale image. The method comprises processing a pixel area for each pixel of the image is a dark pixel or a light pixel and determining if a pixel is proximate to an edge.

Abstract: A method and an apparatus for filtering an image using a guided image filter are described. A filter computes a filtering output using a guidance image. For calculating the filtering output confidence values associated to a filter input are taken into account. A confidence-weighted averaging is performed using the confidence values.

Abstract: A method and an image capturing device configured to generate a defocused image from a reference image and one or more of focal bracketed images to provide an artificially defocused blurred image. The artificially defocused blurred image is a fusion image composed by processing the reference image and one or more of focal bracketed images to provide a clear foreground with gradual blurred background based on a created depth map. The method is time efficient as it provides faster processing on a captured and down sampled reference image and one or more captured down sampled aligned focal bracketed images. The depth map created using region based segmentation reduces a misclassification at a time of classifying foreground-background and misclassification of pixels to provide fast, robust artificial blurring of background in the captured reference image.

Abstract: A method is provided that includes identifying a plurality of data sets, each data set is associated with a distribution model and each data set is associated with an image having a first noise level. The method includes partitioning the data sets into a plurality of groups and generating a best representative estimate for each group, the estimate is associated with a second noise level that is less than the first noise level. The method further includes annotating each group and receiving an input data set. The method includes assigning the input data set to a group and annotating the input data set according to that group's annotation.

Abstract: A method includes implementing, through a processor communicatively coupled to a memory and/or a hardware block, a Bilateral Filter (BF) including a spatial filter component and a range filter component, and implementing the spatial filter component with a low-complexity function to allow for focus on the range filter component. The method also includes determining, through the processor, filter tap value(s) related to the range filter component as a function of radiometric distance between a pixel of a video frame and/or an image and other pixels thereof based on a pre-computed corpus of data related to execution of an application in accordance with a filtering requirement of the pixel by the application. Further, the method includes constraining, through the processor, the filter tap value(s) to a form i×base based on the BF implementation. i is an integer and base is a floating point base.

Abstract: Methods, systems, and devices for up-scaling a source input video from a lower, first resolution to a desired output video having a higher, second resolution, using fractal zooming techniques to replace each individual source pixel of each respective frame of the source input video with a multiple of proposed replacement pixels in the vertical and horizontal dimensions having similar characteristics as the individual source pixel, reducing noise associated with each respective frame of the desired output video, re-sizing, as necessary, each respective replacement frame to the second resolution, and outputting each zoomed replacement frame to generate the desired output video having a higher, second resolution, which is the up-scaled version of the source video. The fractal zooming techniques include identifying a plurality of candidate pixels from the source video and selecting a group of pixels from the candidate pixels that best matches the individual source pixel.

Abstract: A threshold matrix generating method includes: generating q(x, y, g) in which the number of dots in an initial dot pattern is varied; calculating an error matrix (ERR(x, y, g)) of q(x, y, g); calculating AVE(a, b) representing the uniformity of the number of dots in discrete blocks into which the dot pattern has been divided; determining two pixels, of which the dot positions are to be swapped, on the basis of ERR (x, y, g) and AVE(a, b); swapping the dot positions; calculating the evaluation value (MSE(n)) of q(x, y, g) after the positional swapping; and repeating the positional switch of the dots repeating the generation of q(x, y, g) and the positional swapping of the dots with q(x, y, g) functioning as the initial dot pattern until a q(x, y, g) satisfying MSN(n)<MSN(n?1) is obtained.

Abstract: An image processing apparatus includes: a first smoothing unit that outputs a first smoothed image by using a first edge-preserving smoothing filter to an input image; a second smoothing unit that outputs a second smoothed image by further using a second edge-preserving smoothing filter to the first smoothed image output by the first smoothing unit; a correction data derivation unit that derives a difference between the first and second smoothed images as correction data; and a correcting unit that corrects the input image based on the correction data.

Abstract: Systems and methods herein provide for reduced computations in image processing and a more efficient way of computing distances between patches in patch-based image denoising. One method is operable within a processing system to remove noise from a digital image by generating a plurality of lookup tables of pixel values based on a plurality of comparisons of the digital image to offsets of the digital image, generating integral images from the lookup tables, and computing distances between patches of pixels in the digital image from the integral images. The method also includes computing weights for the patches of pixels in the digital image based on the computed distances and applying the weights to pixels in the digital image on a patch-by-patch basis to restore values of the pixels.

Abstract: A method, computer program product, and computer system for identifying a first portion of a facial image in a first image, wherein the first portion includes noise. A corresponding portion of the facial image is identified in a second image, wherein the corresponding portion includes less noise than the first portion. One or more filter parameters of the first portion are determined based upon, at least in part, the first portion and the corresponding portion. At least a portion of the noise from the first portion is smoothed based upon, at least in part, the one or more filter parameters. At least a portion of face specific details from the corresponding portion is added to the first portion.

Abstract: A mask correcting unit corrects an externally set mask pattern. A depth map processing unit processes a depth map of an input image for each of a plurality of regions designated by a plurality of mask patterns corrected by the mask correcting unit. An image generation unit generates an image of a different viewpoint on the basis of the input image and depth maps processed by the depth map processing unit. The mask correcting unit performs a blurring process on an object boundary part of the mask pattern.

Abstract: Some embodiments provide several on-image tools of image editing application for applying effects to an image. Some on-image tools are visible to the user and are overlaid on the image. Some on-image tools are not visible. The tools are for receiving a selection of a location of the image and for applying effects to at least an area of the image that does not include the location of the image.

Abstract: A method of processing a plurality of time separated images comprises selecting a plurality of imaging units in each image; measuring a temporal difference in each imaging unit; and selecting temporal differences above a threshold limit.

Abstract: An image processing apparatus that converts a frame rate by creating a sub-frame from an input frame and outputting the sub-frame, the image processing apparatus includes a generation unit configured to generate the sub-frame from the input frame, a calculation unit configured to calculate a feature amount of brightness of the input frame, and a control unit configured to perform control so as to reduce luminance of the sub-frames generated by the generation unit based on the feature amount calculated by the calculation unit.

Abstract: A method for recognition of a predetermined pattern in an image data set recorded by a device for recording of at least two electromagnetic frequency spectra is provided. A first difference value is formed for the image points of the selected area as a function of a difference between a data vector of a corresponding image point and a first reference data vector. A second difference value is formed for an image point of a selected area as a function of a difference between the data vector of this image point and a second reference data vector. A predetermined pattern is recognized when it is determined at least one pattern correlation quantity is below a predetermined threshold value and a local minimum is present.

Abstract: An apparatus includes an attention region determining unit and a blurring unit. The attention region determining unit is configured to determine an attention region of an image that includes an intended subject of the image. The blurring unit is configured to blur all of the image regions outside of the attention region.

Abstract: A computer-implemented method for applying a filter to an image comprising: receiving a filter setting, selecting a selected filter from a family of filters stored on a computer-readable storage medium, based at least on the filter setting, wherein the family of filters comprises a plurality of filters each being an approximation of a function on different orders, and applying the selected filter to a stored image with a processor.

Abstract: A method for imaging an object is provided. The method includes acquiring image data of the object, wherein the image data includes a plurality of original voxels each having an original CT number, identifying, using a processing device, a subset of the original voxels based on at least one of an original CT number and a location of each original voxel, applying, using the processing device, an anisotropic smoothing filter to the identified original voxels in the subset to generate a set of smoothed voxels each having a smoothed CT number, generating, using the processing device, smoothed image data by combining the original voxels and the smoothed voxels, and analyzing the smoothed image data to determine whether the object contains contraband.

Abstract: A method and apparatus for enhancing and improving image quality are provided. The method includes separating an input image into at least one low frequency component and at least one high frequency component; modulating the low frequency components in a block unit by dithering; modulating the high frequency components by sampling; and combining the modulated low frequency components and the modulated high frequency components.

Abstract: Techniques for sharpening an image using local spatial adaptation and/or patch-based image processing. An image can be sharpened by creating a high-frequency image and then combining that high frequency image with the image. This process can be applied iteratively by using the output of one iteration, i.e., the sharpened image, as the input to the next iteration. Using local spatial adaptation and/or patch-based techniques can provide various advantages. How to change the intensity at a given position in the image can be calculated from more than just information about that same position in the input image and the blurred image. By using information about neighboring positions an improved high frequency image can be determined that, when combined with the input image, reduces ringing and halo artifacts, suppresses noise boosting, and/or generates results with sharper and cleaner edges and details.

Abstract: Systems, methods, and computer-readable media acquire an image captured with a mobile device. Motion sensor data of the mobile device at or near a time when the image was captured is acquired. An angle of rotation is computed based on the motion sensor data, and the image is transformed based on the angle of rotation. In another aspect, a user interface enables user control over image transformation. The user interface enables user control over rotating an image on a display at two or more granularities. A point of rotation may be user-defined. Rotated images may be scaled to fit within a viewing frame for displaying the transformed image.

Abstract: A system for contextualizing noisy samples by substantially minimizing noise induced variance may include a memory, an interface, and a processor. The memory is operative to store exemplars. The processor is operative to receive, via the interface, a sample which includes exemplar content corresponding to one of the exemplars, and noise. Variance induced by the noise may differentiate the sample from one or more of the exemplars. The processor may generalize the sample and the exemplars in order to substantially minimize the variance. The processor may compare the generalized sample to the generalized exemplars to identify the exemplar corresponding to the exemplar content of the sample. The processor may contextualize the sample based on a document type of the identified exemplar. The processor may present the contextualized sample to a user to facilitate interpretation thereof, and in response thereto, receive data representative of a user determination associated with the noise.

Abstract: Embodiments of the present invention comprise systems, methods and devices for display-mode-dependent adjustment of image code values.

Abstract: The invention relates to the improvement of the resolution of regularly sampled multi-dimensional signals, where a single low-resolution signal is available. These methods are generically referred to as example-based super-resolution or single-image super-resolution. The method for super-resolving a single image comprises three stages. First, an interpolation-based up-scaling of the input image is performed, followed by an equivalent low-pass filtering operation on the low-resolution image. The second stage comprises a search for low-frequency matches between an inspected patch in the high-resolution image and patches in a local neighborhood in the low-resolution low-frequency image, including partly overlapping patches, and accumulating the high-frequency contribution obtained from the low-resolution image. The third stage comprises adding the contributions of the low-frequency band of the high-resolution image and the extrapolated high-frequency band.

Abstract: Stereoscopic image capture is provided. A blur value expected for multiple pixels in left and right images is predicted. The blur value is predicted based on designated capture settings. A disparity value expected for multiple pixels in the left and right images is predicted. The disparity value is predicted based on the designated capture settings. Stressed pixels are identified by comparing the predicted disparity value to a lower bound of disparity value determined from the predicted blur value using a predetermined model. A pixel with predicted disparity value less than the lower bound is identified as a stressed pixel. The predicted disparity is adjusted by modifying the designated capture settings to reduce the number of stressed pixels, or an alert to the presence of stressed pixels is given to the user.

Abstract: The present invention relates to a method for determining noise levels in a subband of an image. The method comprises receiving the subband of the image, defining block regions in the at least two space domains of the subband, for each defined block region, identifying first wavelet coefficients associated with coordinate values in the at least two space domains in the defined block region, computing a correlation matrix between identified wavelet coefficients to determine the correlation between first wavelet coefficients according to the at least one color domain, computing second wavelet coefficients, the computation of second wavelet coefficients being based on the correlation matrix and the first wavelet coefficients, computing at least one noise level, the noise level computation being based on at least one second wavelet coefficient and providing the at least one noise level.

Abstract: Provided is an image processing apparatus including: a prediction portion to perform an inter-magnification-ratio blur-compensation prediction with respect to a reduced-size reference focus face image, to thereby generate an inter-magnification-ratio blur-compensation predicted image at each of a plurality of focus positions, the reduced-size reference focus face image being obtained by reducing a size of a reference focus face image to be a reference of a plurality of focus face images obtained by imaging a subject at the plurality of focus positions; a differential data generation portion to generate, for each of the plurality of focus positions, differential data between the focus face image and the inter-magnification-ratio blur-compensation predicted image generated by the prediction portion; and an encoding portion to encode the reduced-size reference focus face image and the differential data generated by the differential data generation portion.

Abstract: An image forming apparatus, including: a reading portion configured to read an original to generate original image data; a code detecting portion configured to detect a code indicating image density reduction information from the original image data; a reconstruction processing portion configured to generate output image data from the original image data by using density input-output characteristics corresponding to the image density reduction information; a filter portion configured to perform unsharpness processing on the output image data by using a degree corresponding to the image density reduction information; and an image forming portion configured to form an image based on the output image data subjected to the unsharpness processing.

Abstract: A method for estimating blur degree of image and a method for evaluating image quality are revealed. First, an input image is transmitted to an image processing device for producing a synthesized blur image including a nonlinear image sensing function according to a pixel intensity distribution parameter of the input image. Next, the image processing device matches the pixel intensity distribution according to the input image and the synthesized blur image for producing a blur degree parameter; By the way, the image processing device further estimating an estimated blur result according to the blur degree parameter. The method for estimating blur degree of image can be further applied to estimate blur distribution for a plurality of regions of interest of a plurality of input images. Thereby, the blur distribution of the input images can be estimated, and thus further evaluating the image quality of the plurality of input images.

Abstract: Disclosed are a system and a method for recognizing a disguised face using a Gabor feature and a support vector machine (SVM) classifier according to the present invention. The system for recognizing a disguised face includes: a graph generation means to generate a single standard face graph from a plurality of facial image samples; a support vector machine (SVM) learning means to determine an optimal classification plane for discriminating a disguised face from the plurality of facial image samples and disguised facial image samples; and a facial recognition means to determine whether an input facial image is disguised using the standard face graph and the optimal classification plane when the facial image to be recognized is input.

Abstract: Embodiments of the present invention comprise systems, methods and devices for increasing the perceived brightness of an image. In some embodiments this increase compensates for a decrease in display light source illumination.