Abstract: An image processing apparatus includes an extraction section that extracts a first high brightness region from a source image where brightness is a first threshold value or greater, a mask generation section that performs blur processing and binarization processing on the first high brightness region and generates a mask containing the first high brightness region, a mask application section that based on the mask performs elimination processing, thinning processing, or both on the first high brightness region, a bright line generation section that generates a bright line based on a second high brightness region contained in output of the mask application section, and a synthesizing section that synthesizes the bright line onto the source image.

Abstract: Described are techniques for image deconvolution to deblur an image given a blur kernel. Localized color statistics derived from the image to be deblurred serve as a prior constraint during deconvolution. A pixel's color is formulated as a linear combination of the two most prevalent colors within a neighborhood of the pixel. This may be repeated for many or all pixels in an image. The linear combinations of the pixels serve as a two-color prior for deconvolving the blurred image. The two-color prior is responsive to the content of the image and it may decouple edge sharpness from edge strength.

Abstract: Video sequence processing is described with various filtering rules applied to extract dominant features for content based video sequence identification. Active regions are determined in video frames of a video sequence. Video frames are selected in response to temporal statistical characteristics of the determined active regions. A two pass analysis is used to detect a set of initial interest points and interest regions in the selected video frames to reduce the effective area of images that are refined by complex filters that provide accurate region characterizations resistant to image distortion for identification of the video frames in the video sequence. Extracted features and descriptors are robust with respect to image scaling, aspect ratio change, rotation, camera viewpoint change, illumination and contrast change, video compression/decompression artifacts and noise.

Abstract: The appearance of image details can be preserved and/or enhanced by applying contrast adaptive gain to the high spatial frequency component of the luminance information. The image details in bright and/or dark regions can be further boosted by applying a local mean adaptive gain. The contrast transfer mapping curve for luminance contrast enhancement can be re-scaled to account for the applied gain. The re-scaling may be performed from frame to frame of displayed video. The re-scaling may be temporally controlled for subsequent frames to make the re-scaling change gradually to prevent flickering.

Abstract: Aspects of an edge smoothing block filter and combinations of the filter with a motion compensated temporal filter are described. In one embodiment, edge smoothing block filtering includes selecting a current pixel to be filtered and selecting a candidate pixel within a search area about the current pixel. The edge smoothing block filtering generally seeks to identify candidate pixels having surrounding pixels similar to pixels surrounding the current pixel. The edge smoothing block filtering further computes a cost difference between pixels within a candidate pixel neighborhood and pixels within a current pixel neighborhood, and filters the current pixel based on the cost difference. Aspects of the filters and filter element combinations may preserve edges and textures adaptively based on image content. For example, diagonal or curved image edges may be filtered along edges while texture is preserved along the edges.

Abstract: A contour correcting device which includes a plurality of delay elements which delay an input video signal, a pixel-selection-control-signal generation circuit, a pixel selection circuit which selects outputs of the plurality of delay elements in response to outputs of the pixel-selection-control-signal generation circuit, a high-pass filter operation circuit and an adder circuit which adds an operation result of the high-pass filter operation circuit to the input video signal. When the pixel selection circuit extracts a contour component in a boundary portion between a horizontal video effective period and a period other than the horizontal video effective period of the input video signal, the pixel selection circuit replaces pixel data in the period other than the horizontal video effective period among pixel data input to the high-pass filter operation circuit, with pixel data at an edge-point of the horizontal video effective period.

Abstract: A method for matching social network participants includes receiving activity data pertaining to a plurality of participants in a social network. The activity data is parsed to generate activity pattern summaries for each of the participants. The participants are clustered into a plurality of groups according to the activity pattern summaries. At least one participant of influence is determined within at least one group according to the activity data. A social connection is established within the social network between the determined participant of influence and at least one other participant clustered into the same group.

Abstract: The present invention relates to a method and apparatus for reducing noise. A method of reducing noise according to an aspect of the present invention includes calculating a noise level of a reference pixel forming an input image, determining a weighted value to be allocated to the reference pixel based on similarity of a reference window including the reference pixel with respect to at least one comparative window existing in a comparative region of the input image and having the same size as the reference window, and the calculated noise level of the reference pixel, and filtering the input image using the determined weighted value.

Abstract: A facial image enhancement system includes a deformable face tracker that provides a tracked face model from a facial video stream. Additionally, the facial image enhancement system includes a face enhancement image processing engine that uses the tracked face model to process the facial video stream, wherein an image enhancement of the facial video stream provides an enhanced facial video stream. A facial image enhancement method is also provided.

Abstract: An image processing apparatus includes a thinning processing unit which performs thinning processing on image data and a smoothing processing unit which performs smoothing processing on the image data. The image processing apparatus further includes an edge direction determination unit which determines an edge direction with respect to each pixel of the image data, a blending processing unit which decides a pixel value of a target pixel of when the smoothing processing and the thinning processing are realized at the same time, and a thinning adjustment unit which determines whether a thinned pixel becomes isolated, and the thinning adjustment unit resets the change amount in pixel value due to the thinning processing of the thinned pixel to a value of zero, if the thinned pixel is determined to be isolated.

Abstract: In at least one embodiment of the invention, an apparatus for adaptive edge enhancement of a video signal includes a transient improvement module. The transient improvement module is configured to generate a first adjusted pixel value based on a window of pixel values for pixels surrounding a pixel-of-interest initially having an input pixel value. The apparatus includes an adaptive peaking module configured to generate a second adjusted pixel value based on the first adjusted pixel value and the input pixel value. In at least one embodiment of the apparatus, the adaptive peaking module comprises a high-pass filter configured to generate a pixel adjustment based on the first adjusted pixel value. In at least one embodiment of the apparatus, the adaptive peaking module further comprises a gain path configured to apply at least one adaptive gain value to the pixel adjustment to generate an adaptive adjustment value.

Abstract: Methods and apparatus according to various aspects take as input image data in a lower-dynamic-range (LDR) format and produce as output enhanced image data having a dynamic range greater than that of the input image data (i.e. higher-dynamic range (HDR) image data). In some embodiments, the methods are applied to video data and are performed in real-time (i.e. processing of video frames to enhance the dynamic range of the video frames is completed at least on average at the frame rate of the video signal).

Abstract: A method of processing an image includes the steps of receiving selection of the first region of interest (ROI) of an image, processing the first image data related to the first ROI, displaying the first image ROI based on the first image data, receiving selection of the second ROI of the image, which at least partially overlapping the first ROI, processing the second image data related to a portion of the second ROI that does not overlap the first ROI, combining the processed second image data with the processed first image data that overlaps the second ROI, and displaying the second image ROI based on the combined processed second image data and the processed first data.

Abstract: This document discloses, among other things, a method for removing a bullseye artifact from a radial image generated using magnetic resonance and using a swept frequency pulse.

Abstract: In the field of medical imaging using fluoroscopy, a method for reducing noise in a sequence of fluoroscopic images acquired by an X-ray detector comprises for each image (xn) of the sequence: applying temporal filtering to the image (xn) at instant n, the temporal filtering comprising fluoroscopic noise reduction processing; applying spatial filtering to the image (yn) at instant n, the spatial filtering comprising: transforming the image (yn) acquired at the instant n from the spatial domain into the curvelet domain using a curvelet transform, each transformed image being represented by a set of coefficients, thresholding the coefficients of the image (yn) using a thresholding function, the thresholding function cancelling the coefficients below a third predetermined threshold, and preserving or adjusting the coefficients above the third predetermined threshold, transforming the image (zn) whose coefficients have been thresholded from the curvelet domain into the spatial domain using an inverse curvelet tra

Abstract: An image processing method includes the steps of obtaining an input image that is an image in which information of an object space is obtained from a plurality of points of view using an image pickup apparatus that includes an image pickup element having a plurality of pixels and an imaging optical system, calculating a first position of a virtual imaging plane that corresponds to a specified focus position, setting the virtual imaging plane to a second position that is in a range of a depth of focus of the imaging optical system with reference to the first position so that a maximum value of an apparent pixel pitch that is formed by reconstructing the input image is decreased, and generating an output image in a state where the virtual imaging plane is set to the second position.

Abstract: Provided is an image processing apparatus including an infinite impulse response (IIR) mean value calculation section for calculating a mean value of signal values of reference pixels around a correction target pixel according to an IIR filter application process, an IIR variance value calculation section for calculating a variance value of the signal values of the reference pixels around the correction target pixel according to the IIR filter application process, an edge-preserving smoothing processing section for receiving the mean and variance values of the reference pixels and executing an edge-preserving smoothing process to which the mean and variance values are applied, and an IIR filter coefficient calculation section for updating an IIR filter coefficient to be applied to the IIR mean value calculation section and the IIR variance value calculation section according to a signal value of a pixel constituting an image.

Abstract: An image processing method and to an arrangement for implementing the method. The method includes filtering the original image with a low-pass filter for forming a low-pass filtered image, creating a high-pass filtered image by subtracting the low-pass filtered image from the original image, forming intermediate values from the created high-pass filtered image based on column-wise selection of pixel values in the suppression of column noise and row-wise selection of pixel values in the suppression of row noise, and subtracting formed intermediate values column-by-column and row-by-row from the original image. The arrangement includes a non-linear, one-dimensional digital finite impulse response filter, a computing unit for column-wise or row-wise formation of intermediate values, an image storage unit and a subtraction unit.

Abstract: An apparatus of reducing noise includes: an edge determining module determining whether each pixel of an image corresponds to an edge; a low pass filter module performing low pass filtering of the image in two directions and performing low pass filtering only for the pixel determined not to be the edge; a filter selecting module selecting a filter having a flexible size to be applied to a mask region for each of the images low pass filtered based on the average brightness of the entire region and the average brightness of the mask region having a predetermined size; a sigma filter module sigma filtering the mask region using the selected filter for each of the images low pass filtered; and an averaging module averaging the image sigma filtered in the two directions.

Abstract: A method for restoring and enhancing a space based image of point or spot objects. The method includes: 1) dividing a space-variable degraded image into multiple space-invariant image sub-blocks, and constructing a point spread function for each of the image sub-blocks; 2) correcting each of the image sub-blocks via a space-invariant image correction method whereby obtaining a corrected image {circumflex over (f)}i for each of the image sub-blocks; and 3) stitching the corrected image sub-blocks {circumflex over (f)}i altogether via a stitching algorithm whereby obtaining a complete corrected image {circumflex over (f)}.

Abstract: Systems and methods of blurring images may involve partitioning at least a portion of a non-separable finite impulse response (FIR) filter into a plurality of constant response sub-filters, wherein each constant response sub-filter has a rectangular aperture. In addition, the plurality of constant response sub-filters may be used to blur an image. In one example, the non-separable FIR filter may optionally be partitioned into one or more satellite sub-filters, wherein the one or more satellite sub-filters are also used to blur the image.

Abstract: A radiation imaging apparatus includes a radiation imaging unit configured to capture a radiation image of a subject, a wireless communication unit configured to perform wireless communication with an external apparatus, a wireless reception characteristics obtaining unit configured to obtain a wireless reception characteristic of the wireless communication unit, an estimation unit configured to estimate an amount of noise included in the radiation image on the basis of a characteristic value of the wireless reception characteristic, and a correction unit configured to correct the noise included in the radiation image on the basis of the amount of noise estimated by the estimation unit.

Abstract: Systems and methods are provided for a method of adjusting a digital image. A low pass filtering is performed on a digital image to remove high frequency data to generate filtered image data. The digital image is divided into a plurality of regions, and a brightness level of a particular region of the digital image is identified using the filtered image data. A transformation curve is selected for the particular region based on the brightness level, and the transformation curve is applied to the particular region to generate adjusted image data for the particular region having adjusted brightness. The adjusted image data is stored in a computer-readable medium.

Abstract: Systems and methods are provided for providing improved de-noising image content by using directional noise filters to accurately estimate a blur kernel from a noisy blurry image. In one embodiment, an image manipulation application applies multiple directional noise filters to an input image to generate multiple filtered images. Each of the directional noise filters has a different orientation with respect to the input image. The image manipulation application determines multiple two-dimensional blur kernels from the respective filtered images. The image manipulation application generates a two-two-dimensional blur kernel for the input image from the two-dimensional blur kernels for the filtered images. The image manipulation application generates a de-blurred version of the input image by executing a de-blurring algorithm based on the two-dimensional blur kernel for the input image.

Abstract: An image processing device includes a component separation section configured to separate an original image signal into a plurality of components including a first component that is a framework component and a second component obtained from a residue corresponding to the original image signal from which the first component has been excluded, an edge information acquisition section configured to obtain edge information from the first component included in the plurality of components, a fluctuation-component reduction section configured to reduce a fluctuation component at least of the second component included in the plurality of components, a parameter acquisition section configured to acquire a parameter for the fluctuation-component reduction section based on the obtained edge information, and a component synthesis section configured to synthesize the first component and the component other than the first component in which the fluctuation component has been reduced.

Abstract: Interest points are markers anchored to a specific position in a digital image of an object. They are mathematically extracted in such a way that, in another image of the object, they will appear in the same position on the object, even though the object may be presented at a different position in the image, a different orientation, a different distance or under different lighting conditions. Methods are disclosed that are susceptible to implementation in hardware and corresponding hardware circuits are described.

Abstract: Methods and apparatuses for adjusting a global dynamic range of an image are described. An image is decomposed into (i) a low spatial frequency component and (ii) a high spatial frequency component. The global dynamic range of the low spatial frequency component is adjusted to produce an adjusted low spatial frequency component. The image is reconstructed with (i) the adjusted low spatial frequency component and (ii) the high spatial frequency component to thereby produce a processed image.

Abstract: A first generation unit generates a RAW image reduced in the horizontal direction from a RAW image including pixels each having single-color signal information, by limiting the band of spatial frequencies in the horizontal direction and decreasing the number of pixels in the horizontal direction. The RAW image reduced in the horizontal direction is stored in a line memory. A second generation unit generates a reduced RAW image by decreasing, at least in the vertical direction, the number of pixels of the RAW image reduced in the horizontal direction. This makes it possible to generate a reduced RAW image using little memory capacity.

Abstract: A noise reduction device includes a line buffer that stores a blend value obtained by blending a pixel value stored in the line buffer with a processing target pixel value at a given ratio by an amount of one line of an image, and a selector that selects the blend value when a difference between the blend value in the line buffer and the target pixel value is less than a threshold, and that selects the target pixel value when the difference is greater than or equal to the threshold.

Abstract: System, method, and apparatus for smoothing of edges in images to remove irregularities are disclosed. In one aspect of the present disclosure, a method of image processing includes, identifying an edge in an image having an associated set of edge characteristics, determining the associated set of edge characteristics, and applying a low pass filter to a pixel of the edge based on the associated set of edge characteristics to generate a second image based on the image, wherein the edge in the image is smoothed in the second image. The method further includes generating a third image which is a blend of the original image and the second (edge-smoothed) image based on the associated set of edge characteristics.

Abstract: An image processing apparatus includes a receiving unit, a specifying unit, a controlling unit, and an outputting unit. The receiving unit receives image data. The specifying unit specifies a correction amount of the image data for keystone correction processing. The controlling unit controls, based on the correction amount specified by the specifying unit, the keystone correction processing, filter processing for reducing a predetermined high frequency component, and edge enhancement processing. The outputting unit outputs processed image data which is processed based on the controlling by the controlling unit.

Abstract: A method to enhance detail of an image based on noise elimination includes calculating a noise weight corresponding to a probability that a center pixel, located in a block of pixels of a region of the image, is noise by using a difference between the center pixel and a surrounding pixel located in the block of pixels, calculating a first substitution value for the center pixel based on the noise weight; and calculating a second substitution value for the center pixel by using the noise weight and a sharpen filter.

Abstract: A set of pixels of a background element is identified according to a mask that defines a shape of a foreground element. A color value for a pixel of the foreground element is determined. The determining includes ascertaining a value of a measure of brightness of one or more pixels of a set of pixels of the background element and calculating the color value for the pixel of the foreground element based on the value of the measure of brightness and a value of an adjustable contrast variable. The calculating the color value for the pixel of the foreground element preserves in the foreground element a color component of the one or more pixels of the set of pixels of the background element and increases contrast with the value of the measure of brightness according to the value of the adjustable contrast variable.

Abstract: There is provided an image processing apparatus. The image processing apparatus includes a first image processing unit configured to perform image processing affecting a high frequency component used to generate a detail component of an image. The image processing apparatus includes a detail component generating unit configured to generate the detail component, which is emphasized, using an output of the first image processing unit. The image processing apparatus includes an emphasis unit configured to emphasize detail of the image by combining the emphasized detail component generated by the detail component generating unit with the image.

Abstract: A method of improving an image quality of a video signal, which is supplied on a frame-by-frame basis, includes extracting low frequency components from a video signal of an n-th frame, where n is a natural number excluding zero, subtracting the extracted low frequency components from a video signal of an (n+m)th frame to produce high frequency components, where no is a natural number excluding zero, and adding the produced high frequency components to the video signal of the (n+m)th frame. The extracted low frequency components include a horizontal component and a vertical component.

Abstract: Provided is an image processing device capable of performing appropriate noise reduction without causing blurring of edges and details of the image.

Abstract: An image processing device is provided. The image processing device includes a weighted low-pass filter which performs weighted low-pass filtering on illumination of sub-sampled pixel signals, and an illumination interpolation circuit which compares illumination of the weighted low-pass filtered pixel signals with illumination of current pixel signals and performs interpolation while applying a weight to illumination of the weighted low-pass filtered pixel signals according to the comparison result.

Abstract: An image processing apparatus creates a basic-structure component image representing an image that an input image except edge is smoothed while preserving the edge in the input image; and creates a detail component image representing an image that the basic-structure component image is subtracted from the input image. Subsequently, the image processing apparatus decomposes the detail component image into a plurality of frequency-band images through multiresolution transform processing, and performs noise removal on the obtained frequency-band images. After that, the image processing apparatus performs inverse multiresolution transform processing of combining the noise-removed frequency-band images, thereby creating a noise-removed detail-component image.

Abstract: Various embodiments of methods and apparatus for image deblurring and sharpening using local patch self-similarity are disclosed. In some embodiments, an input blurred image is down-sampled to generate a downsized image. The downsized image is convolved with a blur kernel to obtain a smoothed image. For each of a plurality of patches of the input blurred image, a corresponding patch in the smoothed image is found. High frequency components between each of the plurality of corresponding patches in the smoothed image and corresponding patches of the downsized image are computed. The high frequency components are applied to the plurality of patches of the input blurred images to generate a deblurred version of the input blurred image.

Abstract: A method for sharpening a captured image includes the steps of (i) identifying a plurality of edge pixels in the captured image, (ii) reviewing the plurality of edge pixels to identify one or more line pixels, and one or more non-line pixels in the captured image (354), and (iii) sharpening the captured image utilizing a first level of overshoot control for the non-line pixels (362), and utilizing a second level of overshoot control for the line pixels (360) The method also includes the steps of (i) identifying an intensity value for each of a plurality of neighboring pixels that are positioned near a selected pixel in a predetermined pixel window that have the highest intensity values and the lowest intensity values.

Abstract: Techniques to sample texels efficiently for an image effect may include determining a number of texels (kernel size) needed to compute a weighted average for an image effect on an image. The technique may further include selecting at least one mipmap generated by a graphics processing unit (GPU) according to a function of the determined kernel size. The function may also consider a threshold kernel size. The technique may further sampling texels, with the GPU, from the selected mipmap(s), and calculate the weighted average of the sampled texels to produce the image effect.

Abstract: An image editing device of the present invention replaces part of a first image that has been subjected to lossy compression with a second image, and comprises a image quality adjustment section for carrying out image quality conversion processing that is the same as image quality variation arising due to the lossy compression, and an editing section for carrying out editing processing using the second image that has been adjusted by the image quality adjustment section.

Abstract: An image correction method comprises the steps of: median-processing the original image in a direction normal to a direction in which the streak unevenness extends to produce a median-processed image, subtracting the median-processed image from the original image to produce a subtraction image, threshold-processing a part of the subtraction image having a density exceeding a given threshold to reduce the density and produce a threshold-processed image, frequency-processing the threshold-processed image using a one-dimensional low-pass filter in the direction in which the streak unevenness extends to produce a processing image, and subtracting the processing image from the original image to remove the streak unevenness from the original image.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes receiving a set of dynamic computed tomography image data from a computed tomography imaging system, registering the image data, applying a smoothing filter to at least a selection of the registered image data, and outputting the results. The smoothing filter may be, for example, a uniform filter, a triangular filter, a Gaussian filter, a median filter, a percentile filter, a Kuwahara filter, an anisotropic filter, or any combination thereof. Additional methods, systems, and devices are also disclosed.

Abstract: A method for iterative reconstruction of an object containing noise using the pixon method determines the pixon map from a variable that is used to update the object in the iteration. The updating variable is based on an optimized merit function, and smoothes the updating variable during each iteration. The updating variable depends on the reconstruction method, but is typically a gradient of a merit function or a multiplicative update factor. The updated object can optionally also be further smoothed at the end of the iteration, using the pixon map determined during the iteration.

Abstract: A video enhancement processing system improves perceptual quality of video data with limited processing complexity. The system may perform spatial denoising using filter weights that may vary based on estimated noise of an input image. Specifically, estimated noise of the input image may alter a search neighborhood over which the denoising filter operates, may alter a profile of weights to be applied based on pixel distances and may alter a profile of weights to be applied based on similarity of pixels for denoising processes. As such, the system finds application in consumer devices that perform such enhancement techniques in real time using general purpose processors such as CPUs or GPUs.

Abstract: An image filter and method of smoothing pixel values. A pixel value of a pixel to be smoothed is compared with block average pixel values of each of a plurality of pixel blocks. The pixel to be smoothed may be downstream from each of the pixel blocks. If the difference between the pixel value and each of the block average pixel values is less than a corresponding sigma threshold value for each of the pixel blocks, a first sigma filter utilizing the block average pixel values is applied to the pixel to be smoothed. If the difference between the pixel value and any one of the block average pixel values is not less than a corresponding sigma threshold value, a second sigma filter is applied to the pixel to be smoothed.

Abstract: An image forming apparatus includes an image interpolation unit to compute a correct pixel value of a target pixel subject to interpolation of a halftone image. The image interpolation unit includes a base pattern setting unit to set a base pattern including the target pixel, a reference pattern setting unit to set reference pattern in a region peripheral to the target pixel, an analogous pattern acquisition unit to acquire at least one analogous pattern analogous to the base pattern from the reference pattern, a high-resolution pattern creating unit to create a high-resolution pattern having a predetermined resolution or higher by synthesizing the acquired analogous pattern, a pixel value estimating unit to compute an estimated pixel value of the target pixel based on the created high-resolution pattern, and a pixel value determination unit to determine the correct pixel value of the target pixel based on the computed estimated pixel value.

Abstract: An image processing apparatus includes a first halftone processor, a first filtering processor, a second filtering processor, and an evaluator. The first halftone processor generates first halftone image data from input image data using thresholds. The first filtering processor smoothes the first halftone image data using a first filter having a size corresponding to a cycle of the thresholds. The second filtering processor smoothes the input image data using a second filter having a characteristic corresponding to the first filter. The evaluator evaluates a moiré caused in the first halftone image data based on a difference between the first halftone image data smoothed by the first filtering processor and the image data smoothed by the second filtering processor.

Abstract: A weighting coefficient sequence defining unit generates an array in which weighting coefficients are held at positions defined by the directional components of blur vectors, and adjusts the weighting coefficients to increase the sum of the frequency components of the array or reduce variations of the frequency components. A weighting unit multiplies respective captured images by corresponding weighting coefficients, generating L weighted captured images. The weighting unit then generates the synthesized image of the L weighted captured images. A corrected image generation unit performs deconvolution processing using the frequency component of the array in which the weighting coefficients are held at positions defined by the directional components of blur vectors, and the frequency component of the synthesized image. The corrected image generation unit performs an inverse frequency transform for the deconvolution processing result, generating an output image.