Abstract: Images are prepared for blending with a reflection. Angles of incidence and angles or reflection lead to reflections of a viewer appearing to be different than actual size. Accordingly, image preparation can include scaling images of objects to be blended with a reflection to an appropriate size. For a flat specular surface the size is one half the size the object would be if the object were sized to be associated with the feature that is reflected. A viewer will focus on the reflection of the viewer at an object plane. An image associated with the specular surface will be blurred. Accordingly, the preparation can include compensating for the blurring. Preparation can also include reducing an area coverage of the image of the object to no more than about fifty percent of the region of the refection to provide space for the reflection.

Abstract: An embodiment is configured to calculate a perceptual masking factor at a pixel location at a block boundary of the image, calculate a parameter for a filter at the pixel location at the block boundary, and filter the image around the pixel location at the block boundary employing the filter with the calculated parameter. The perceptual masking factor is formed as a product of a background activity masking map and a luminance masking map. The filter includes a parameter that is selected in view of a quality of experience performance measure for the image at the pixel location at the block boundary of the image.

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: A method for detecting a block raster in an image comprising a number of pixels, each of which having assigned at least one pixel value, said pixels being arranged one after the other along horizontal and vertical pixel boundaries. The method includes establishing a first raster with raster limits (xj+dxj) that run either parallel to the vertical pixel boundaries or to the horizontal pixel boundaries and, the position of said limits being predetermined by way of an offset (OF) and an opposite distance (SP). A raster scale is determined of the raster as a function of the edge scales of at least some of the raster limits (xj,+dxj). The method is repeated for a second raster, and the first or second raster is selected in consideration of the raster scales.

Abstract: An image processing apparatus, an image processing method, and a computer program, visually remove low-frequency noise contained in image data. Image data containing low-frequency noise is input from an input terminal. A window unit designates a window made up of a pixel of interest, and its surrounding pixels. A pixel selector selects a selected pixel to be compared with the pixel of interest from the window, and a pixel value determination unit determines a new pixel value of the pixel of interest on the basis of the pixel values of the selected pixel and pixel of interest. New image data is generated by substituting the pixel value of the pixel of interest by the new pixel value.

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 dense guide image or signal is used to inform the reconstruction of a target image from a sparse set of target points. The guide image and the set of target points are assumed to be derived from a same real world subject or scene. Potential discontinuities (e.g., tears, edges, gaps, etc.) are first detected in the guide image. The potential discontinuities may be borders of Voronoi regions, perhaps computed using a distance in data space (e.g., color space). The discontinuities and sparse set of points are used to reconstruct the target image. Specifically, pixels of the target image may be interpolated smoothly between neighboring target points, but where neighboring target points are separated by a discontinuity, the interpolation may jump abruptly (e.g., by adjusting or influencing relaxation) at the discontinuity. The target points may be used to select only a subset of the discontinuities to be used during reconstruction.

Abstract: This disclosure describes techniques for initially calibrating an image capture device. According to one aspect, the calibration includes calibrating parameters of an image filter for resolving the captured image. The method includes receiving a captured image of a test target and resolving the captured image using a set of initial parameters. A sharpness index of the resolved image is determined without matching the captured image to the test target. The sharpness index is used to minimize a cost function for determining parameters for use by the image capture device.

Abstract: A method of processing a digital image. The method comprises: populating (100) a bilateral grid (10) comprising a plurality of cells (20), based on information obtained from the image, each cell comprising at least one value; then cumulatively integrating (110) the at least one value over the bilateral grid to form an integrated grid comprising integrated values; generating (120) a modified bilateral grid, comprising computing the sum of the at least one value over a predetermined rectangular box of cells of the bilateral grid, by using the integrated values corresponding to the corners of the box; and slicing (130) the modified bilateral grid to generate an output image.

Abstract: An image file representing at least a portion of a printed document is processed to highlight the differences between foreground material (e.g., text or other characters) from background. The method includes selecting a neighborhood of pixels, determining a weighted average of an attribute values (e.g., luminance) for each pixel, and modifying each pixel's value based on the weighted average. Graylevel scaling, error diffusion, and a bit level conversion are also performed each pixel ends up with either a first attribute value level (e.g., luminance of 0) or a second attribute value level (e.g., luminance of 255).

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: This disclosure describes an apparatus and method of multi-spectral imaging to obtain and analyze information contained in the spectral distribution (reflection, absorption, or emission) of components within the image. The spectral information is captured in a series of images from differing spectral regions. This series of images are then combined into a composite image using re-colorization and image stabilization algorithms for display in real time. The process can be repeated continuously allowing spectral changes over time to be captured and analyzed. In the alternative one sequence of images can be captured for use as a still image.

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

Abstract: A parallel scaler unit for simultaneously scaling multiple pixels from a source image. The scaler unit includes multiple vertical scalers and multiple horizontal scalers. A column of pixels from the source image is presented to the vertical scalers, and each vertical scaler selects appropriate pixels from the column of pixels for scaling. Each vertical scaler scales the selected pixels in a vertical direction and then conveys the vertically scaled pixels to a corresponding horizontal scaler. Each horizontal scaler scales the received pixels in a horizontal direction.

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: A method for providing an output image based on an input image, the method comprising determining a location of an output pixel with respect to an input image, determining values of elements of a filter array such that the effective width of the filter array depends on the density of exposed input pixels within the input image, and determining the value of the output pixel by performing a sum-of-products operation between non-zero values of the elements of the filter array and the values of input pixels of the input image located at respective positions, when the filter array is superimposed on the input image such that the center of the filter array corresponds to the location of the output pixel.

Abstract: An image processing method for removing a noise component contained in an original image, includes: separating an original image into a temporary noise-free image and a temporary noise component; extracting an edge component in the temporary noise-free image by executing edge detection on the temporary noise-free image; determining a fine edge component in the original image contained in the temporary noise component based upon a level of the extracted edge component; extracting an actual noise component by excluding the fine edge component from the temporary noise component; and removing noise from the original image based upon the extracted actual noise component.

Abstract: The present invention controls blur and sharpness according to a depth without performing processes repeatedly for each object determination or for each distance. A filter for a target pixel is determined by comparing multiple thresholds representing an optical characteristic of an image capturing unit and multiple values representing distance to a subject in the target pixel and pixels around the target pixel. Then, the filter is applied to the target pixel.

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: Embodiments of an apparatus and method for decoding an encoded bitstream to generate a video signal are taught. A decoder receives the bitstream and decodes a portion thereof to obtain at least a portion of a predictive reference frame. The reference frame is generated by, for example, selecting a filter set including a target frame with a block having a plurality of pixels and at least one adjacent frame, determining a coding mode associated with the block, determining a block-specific factor derived from the coding mode, determining weighted averages of pixels in the filter set and using the weighted averages to generate the predictive reference frame. The decoder also generates a residual from another portion of the encoded bitstream that represents a portion of a frame of the plurality of frames and reconstructs the portion of the frame by adding the residual to the predictive reference frame.

Abstract: Devices, systems, methods, and other embodiments associated with reducing digital image noise are described. In one embodiment, a method includes filtering a digital image with a plurality of adaptive filters, wherein the plurality of adaptive filters include a first filter configured to filter noise surrounding one or more edges in the digital image, and a second filter configured to filter noise caused by a block based encoding of the digital image. The method further includes reducing a compression artifact from selected pixels in the digital image, wherein the compression artifact is reduced by (i) combining an output from the first filter and an output from the second filter in response to the digital image being determined to be blocky, and (ii) not combining the output from the first filter with the output of the second filter in response to the digital image not being determined to be blocky.

Abstract: A method and an apparatus for image filtering are described. Structural information is employed during the calculation of filtering coefficients. The structural information is described by the regions defined through an edge map of the image. In one embodiment, the region correlation between the target pixel and a contributing pixel is selected as a structural filtering coefficient. The region correlation, which indicates the possibility of two pixels being in the same regions, is calculated by evaluating the strongest edge cut by a path between the target pixel and a contributing pixel. The structural filtering coefficient is further combined with spatial information and intensity information to form a spatial-intensity-region (SIR) filter. The structural information based filter is applicable to applications such as denoising, tone mapping, and exposure fusion.

Abstract: A system and method for a blur brush performing adaptive bilateral filtering is disclosed. The method may include receiving user input selecting an area of an image to be filtered, such as by pointing to the image area using the blur brush. The selected image may comprise an edge and a plurality of pixels. The method may operate to the blur brush identifying the edge in the selected image area. The method may operate to apply a filter tool (e.g., a bilateral filter) to the selected image area, while preserving the edge. The methods may be implemented by program instructions executing in parallel on CPU(s) or GPUs.

Abstract: A pixel interpolation process is based on detection of a potential edge in proximity to a pixel being estimated, and the angle thereof. The potential edge and its angle is determined based on filtering of offset or overlapping sets of lines from a pixel window centered around the pixel being estimated and then cross-correlating the filter results. The highest value in the correlation result values represents a potential edge in proximity to the pixel being estimated and the index of the highest value represents the angle of the potential edge. This information is used in conjunction with other information from the cross-correlation and analysis of the differences between pixels in proximity to verify the validity of the potential edge. If determined to be valid, a diagonal interpolation based on the edge and its angle is used to estimate the pixel value of the pixel. Otherwise, an alternate interpolation process, such as vertical interpolation, is used to estimate the pixel value for the pixel.

Abstract: A method for removing color noise on a slowly varying component contained in color difference component image data of image data which is imported from an image sensor and converted to brightness and the color difference component image data, includes the steps of: sampling pixels of said color difference component image data by thinning out according to a first defined sampling format when not performing a color noise removal process on the slowly varying component; determining if the color noise removal process is necessary to be performed or not; producing the color difference component image data, corresponding to a compressed image data size smaller than an image data size without said color noise removal process, by thinning out according to a second defined sampling format when performing said color noise removal process; and recording the color difference and brightness component image data.

Abstract: Dynamic adjustment of noise filter strengths for use with dynamic range enhancement of images is performed to produce better quality images by adapting dynamically to the image noise profile. Global and local brightness and contrast enhancement (GLBCE) is performed on a digital image to form an enhanced image. The GLBCE applies local gain values to the digital image based on local intensity values. A GLBCE gain versus intensity curve is determined for the enhanced image. A set of noise filter thresholds is adjusted in response to the GLBCE gain versus intensity curve to form a set of dynamically adjusted noise filter thresholds. The enhanced image is noise filtered using the set of dynamically adjusted noise filter thresholds to form a noise filtered enhanced image.

Abstract: Image processing devices include a color extractor circuit configured to extract color information from input image data, a color shifter circuit configured to color shift the input image data according to the extracted color information and a definition enhancement circuit configured to detect a color difference from the color-shifted image data and to unsharp mask filter the color-shifted image data according to the detected color difference.

Abstract: Image data processing is facilitated. According to an example embodiment, image data is processed using photometric similarity and, where appropriate, a classification of sample pixels for the image data. In some applications, a trained bilateral filter function is used with a filter coefficient selected for a particular classification of image data to filter artifacts in the image data.

Abstract: Systems and methods of determining motion vectors, such as for video encoding, are disclosed. In one example, motion vectors are determined for a current frame, using sampled pixel information from a reference frame. Sampled pixel information is obtained using a sampling pattern. The sampling pattern, in one example, includes subsampling pixels at different rates for horizontal and vertical directions. The subsampling rate can differ, based on an amount of motion represented by a matching block (e.g., the farther a match is found away from an origin of the block, the more subsampling can be done). In another example, a full pixel resolution is maintained proximal an original location of the block; as distance increases in one or more directions, subsampling can begin and/or increase. Sampled pixels can be stored. Interpolation of the sampled pixels can be performed and the sampled and resulting interpolated pixels can be used for comparison.

Abstract: Disclosed herein is a movement-adaptive noise reduction apparatus, including a memory, a mixing control section, a movement component extraction section, a low-pass filter section, and a movement decision control section. In the apparatus, the movement decision control section and the low-pass filter section receive, from the outside, information regarding the gain value upon an amplification process to which the image signal is subjected before inputted to the mixing control section to control at least one of the threshold value and the filter characteristic in response to the information.

Abstract: A technique is provided for generating sharp, well-exposed, color images from low-light images. A series of under-exposed images is acquired. A mean image is computed and a sum image is generated each based on the series of under-exposed images. Chrominance variables of pixels of the mean image are mapped to chrominance variables of pixels of the sum image. Chrominance values of pixels within the series of under-exposed images are replaced with chrominance values of the sum image. A set of sharp, well-exposed, color images is generated based on the series of under-exposed images with replaced chrominance values.

Abstract: In a method and device for improving image rendition by contrast and/or sharpness enhancement the sharpness enhancement is made dependent on the local average luminance value. A mix is made of spatially enhanced image signals is used, wherein for various signal differing spatial frequencies are boosted. The mixing factors for mixing of the boosted signals are dependent on a local average luminance value such that the distribution over frequency bands shifts to higher frequencies and sharper enhancement as the luminance value increases.

Abstract: An ink jet printing apparatus which inhibits possible bleeding by thinning color data adjacent to black data and enables printing free from image quality degradation such as gradation skip is provided. Specifically, when only one pixel has color data and pixels located vertically and horizontally adjacent to that pixel have no color data, an isolated point pixel containing a color dot is detected only in that pixel. Then, the dots other than the isolated point are thinned-out. This makes it possible to inhibit possible bleeding at the boundary between a color area and a black area and to achieve proper printing with the appropriate gradation of the entire image maintained.

Abstract: The present invention discloses a method for decomposing a target pattern containing features to be printed on a wafer, into multiple patterns, the features having a plurality of patterns within a minimum pitch for processes utilized to image the target pattern. The method includes superposing a predefined kernel over a pixel, and moving the kernel from one pixel to another, the pixels representing the sub-patterns of the target pattern. Polarity of the kernel may be reversed when the pixel has a stored intensity value that is negative.

Abstract: In order to prevent illegal copying more effectively in an image forming apparatus, when a specified ground pattern for preventing copying is detected in input image data, the detected ground pattern is emphasized in the image data. Alternatively, information for detecting the specified ground pattern is stored in a storage device, in order to detect the ground pattern with the stored information. When the ground pattern is not detected, a ground region in the image data is analyzed further to determine whether a different ground pattern exits or not. When a ground pattern is detected, information for detecting the ground pattern is stored in the storing device.

Abstract: Provided are methods and systems for registering image data from two imaging modalities, to produce an image having features from both imaging technologies. In particular, the methods and systems relate to intensity-based registration of the image data. The imaging modalities may be, for example, ultrasound and x-ray, magnetic resonance imaging, or a pre-operative plan.

Abstract: An exposure condition when obtaining a sensed image is input. Shake information when obtaining the sensed image is input. A filter to be used to correct a blur of the sensed image is generated based on the exposure condition and a weight value including a non-integer obtained from the shake information.

Abstract: A method of processing an image based upon edge energy is disclosed. The method comprises providing (100) an edge map (540) for a group of pixels, classifying (100, 110, 120) pixels in the group as either smooth region pixels or edge region pixels, identifying (120), in the group of pixels, a pixel in the proximity of an edge region pixel, and defining (160) the identified pixel as a ringing noise pixel if the identified pixel is a smooth region pixel.

Abstract: One embodiment of the present invention provides a system for applying a bilateral filter to an image. During operation, the system selects a first region within the image which is associated with a first pixel. Next, the system constructs a first histogram using pixel values within the first region. The system then computes a new value for the first pixel using the current value of the first pixel and the first histogram. The system then selects a second region within the image which is associated with a second pixel. Next, the system determines a non-overlapping region between the first region and the second region. The system then constructs a second histogram using the first histogram and pixel values in the non-overlapping region. Next, the system computes a new value for the second pixel using the current value of the second pixel and the second histogram.

Abstract: A system and method for enhancing digital images is described. A digital image is transformed into a series of decomposed images in frequency bands, or different resolution grids. A decomposed image is noise suppressed and contrast enhanced. Representative value of signal at each pixel is computed based on contributions to signals from pixels in a neighborhood of the pixel. Lookup tables are applied to pixel values to selectively enhance signal in a predetermined range of signal strength. Another set of lookup tables are applied to pixel values to suppress noise components contained therein. Optionally, operations are applied to decomposed images to suppress quantum noise, enhance object edges or enhance global contrast, among others. These decomposed images, after signal enhancement and noise suppression, are then recombined to result in an enhanced image.

Abstract: Method for detecting edge of fixed pattern includes receiving and analyzing a first image to obtain a first edge information. Second image and a corresponding second edge information are received, in which the second image includes an accumulation of image history information. According to the first edge information and the second edge information, a consistent number and an inconsistent number for pairs of pixels at the corresponding location of the first image and the second image are calculated, in which the consistent number represents how many pairs of pixels of which two compared pixels of each pair are both edge pixels, and the inconsistent number represents one of the two compared pixels is not the edge pixel. When the consistent number is greater than first predetermined value and meanwhile the inconsistent number is less than second predetermined value, first image and second image have a fixed pattern with fixed edge.

Abstract: The multi-image sharpening and denoising technique described herein creates a clean (low-noise, high contrast), detailed image of a scene from a temporal series of images of the scene. The technique employs a process of image alignment to remove global and local camera motion plus a novel weighted image averaging procedure that avoids sacrificing sharpness to create a resultant high-detail, low-noise image from the temporal series. In addition, the multi-image sharpening and denoising technique can employ a dehazing procedure that uses a spatially varying airlight model to dehaze an input image.

Abstract: A process includes acquiring radar images on the same area, calculating a vector of n amplitude or intensity values relating to a sample pixel in the n images available, identifying the vector as a sample vector, and defining an estimation window for the sample pixel for identifying a set of pixels around the sample pixel. Additionally, calculating vectors of N amplitude or intensity values for each pixel contained in the estimation window, comparing each vector with the sample vector, identifying pixels associated with the vectors that have passed a statistical test and identifying pixels associated with the vectors that have not passed the statistical test, eliminating the pixels contained in the estimation window that are not connected to the sample pixel, and identifying the set of pixels that are statistically homogeneous with the sample pixel.

Abstract: To filter a digital signal, in which, for each sample of the signal, a plurality of context functions take account of a predetermined number of other samples of the signal: the value of a context function from the plurality of context functions for each sample to be filtered is calculated; the signal is divided into a set of sub-signals corresponding respectively to the different values of the context functions; and, for each sub-signal: an optimal filter is determined according to a first criterion that depends on the values of the sub-signal; and the optimal filter is associated with the context function corresponding to the sub-signal. Application to the coding of a digital signal representing an image.

Abstract: Clusters of pixels are defined for use in image compression and decompression. The image information used to define the clusters may include pixel values at predetermined positions relative to a pixel or related motion vectors, gradients, texture etc. During compression of images the image information relative to pixels is examined to determine the cluster to which it belongs. Thus pixels can be classified according to the cluster for their image information. In an embodiment the definitions of the clusters are selected dynamically, dependent on image content. For each cluster a control parameter set is computed for a post-processing operation, such as filter coefficients for filtering or statistical data for locally generating texture. The control parameter set is selected dependent on the image content so that, when the post-processing operation is applied to the image after decompression it will improve image quality for the pixels that are classified as belonging to the cluster.

Abstract: In an embodiment, a device comprises a plurality of elements, including logical elements, wherein the elements are configured to perform the operations of: in a neighborhood of pixels surrounding and including a particular pixel, applying a filter to multiple groups of pixels in the neighborhood to generate a set of filtered values; generating, based at least in part upon the set of filtered values, one or more sets of gradient values; based at least in part upon the one or more sets of gradient values, computing a first metric for an image environment in which the particular pixel is situated; determining a second metric for the image environment in which the particular pixel is situated, wherein the second metric distinguishes between a detail environment; and based at least in part upon the first metric and the second metric, computing a gradient improvement (GI) metric for the particular pixel.

Abstract: An image and video enhancement technique is described that allows a core enhancement algorithm to be applied to images captured in various challenging lighting conditions. The technique detects a lighting impairment and inverts the image if it is a low-light impairment. The inverted low-light image is similar to haze impairment images, allowing both haze images and low-light images to be enhanced using the same enhancement algorithm.

Abstract: A frame prediction system and a prediction method thereof. An initializing module initializes a first image block having a plurality of pixels. A providing module provides a first centroid and a first motion vector of a second image block. The location lookup module finds a location according to the first centroid, and generates a first weight and a second weight respectively according to a relationship between each of the pixels, the first centroid and the location. A vector lookup module finds a second motion vector, which gives a minimum pixel intensity error for the plurality of pixels in the first image block according to the first centroid, the first motion vector, the location, the first weight and the second weight. A processing module sequentially calculates a plurality of predictive intensity values according to the motion vectors and the weights.

Abstract: The invention discloses an image processing system and method thereof. The image processing system includes an local variance estimator, a noise detector, a spatial de-noise filter. The local variance estimator estimates each pixel of an input image signal to separately output a local variance value of each pixel, and generates a noise threshold according to the local variance values. The noise detector determines which pixel indicates noise or image according to the noise threshold. The spatial de-noise filter filers the pixel indicating noise to generate an output image signal.

Abstract: An image processing device and a method thereof are provided. In the method, an original image and a corresponding depth image are received, wherein the depth image includes a plurality of depth values, and the depth values indicate depth of field of a plurality of blocks in the original image respectively. Further, each of the blocks is processed to obtain a corresponding smoothness and/or sharpness effect according to each of the depth values. Thereby, a stereoscopic sensation of the original image can be enhanced.