Abstract: The current invention describes a method for filtering an input image with a bilateral filter to produce an output image. The bilateral filter includes a spatial filter and a range filter.

Abstract: An image processing apparatus enables image data to be handled easily after photography. A server apparatus patterns images and controls information in correspondence with user identifiers. A digital camera photographs a subject, obtains a pattern image and a piece of control information from the server apparatus, and judges whether a portion of the image data obtained by photography matches the obtained pattern image. If a matching portion exists, then the digital camera operates in accordance with an operation instruction included in the piece of control information. If the operation instruction is mosaic processing, then the digital camera performs mosaic processing to the matching portion. If the operation instruction is image replacement, then the digital camera replaces the matching portion with a predetermined image or performs CG processing on the matching portion. If the operation instruction is frame deletion, then the digital camera deletes the image data.

Abstract: A noise elimination apparatus has a subtracting section 11 for obtaining a difference value between input image data and reference image data; a calculation processing section 12a for performing calculation processing of multiplying the difference value by a prescribed coefficient; an adaptive integerization processing section 13a for obtaining an integerized difference value by adaptively performing rounding up processing or rounding down processing on the difference value having undergone the calculation processing; an adding section 14 for obtaining output image data from the integerized difference value and the reference image data; and a frame memory 15 for storing the output image data as the reference image data.

Abstract: The system described herein is a unified approach to three-dimensional filtering for the reduction of video noise. The technique is based on weight averaging pixels of the filter's output value in a three-dimensional neighborhood, in space and time, of the filter's output value. The weights can be computed for individual factors, such as distance, regional differences, etc., or can be combined into a weight that is indicative of all individual weights.

Abstract: Deblurring of digital camera images by estimating the blur function from an image extracted from a video sequence taken about the time of an image capture. The extracted image is selected to be the sharpest of the images of the video sequence, and comparison of this sharpest image with the (down-sampled) captured image provides blur function iterative estimation.

Abstract: An adaptive filter is applied to samples in an initial pattern of samples. The samples in the initial pattern correspond to a subset of the image pixels which are to be predicted using the samples. A level value of each sample in the pattern is varied. The level value corresponds to the intensity/signal value of the sample, and may have a strong effect on the prediction power of the samples. A first prediction pattern (i.e., the prediction signal corresponding to the sampling pattern) is generated from the samples. A sample movement process is performed on a current sample in the first prediction pattern to change a current position of the current sample in the first prediction pattern. A local prediction of pixels influenced by the sample is updated if the sample's position is changed. A sample removal process is performed on the current sample to remove the sample from the first pattern if a criteria is satisfied. A local prediction of pixels is updated if the current sample is removed.

Abstract: An image processing method for removing noise contained in an image includes: inputting an original image constituted with a plurality of pixels; generating a plurality of band-limited images, resolution levels of which are lowered in sequence, by executing a specific type of band pass filter processing on the original image; extracting a high-frequency component from each of the band-limited images by executing high-pass filter processing on the band-limited images; extracting a noise component contained in each of the band-limited images by separating the noise component through nonlinear conversion processing executed on the extracted high-frequency component; and removing the noise in the original image based upon the extracted noise component in each band-limited image.

Abstract: An adaptive temporal noise reduction method that adaptively combines motion adaptive filtering results and motion compensated results to reduce Gaussian additive noise in video sequences is described herein. The system determines the motion detection and motion compensation results from the current frame and the filtered previous frame. Measurements on the video are used to determine a probabilistic measure of noise that is employed to adaptively combine the motion detection and motion compensation results.

Abstract: A method for detecting and enhancing edges in an ultrasound image includes the steps of applying an edge detection filter to at least one of a plurality of pixels of an ultrasound image to compute an edge detection value having a magnitude and a direction; and applying either a directional edge enhancement filter or a non-directional smoothing filter to at least one of the plurality of pixels of the ultrasound image.

Abstract: A method and apparatus, particularly suited to SIMD instruction sets, to filter streaming video information encoded under a predictive encoding algorithm specified under video encoding standards, such as MPEG 4 or H.264/AVC. The filtering operation de-blocks or removes unwanted borders in the perceived video. During the filtering process, a series of filtering mask is generated based on temporal and spatial statistics of predictive encoded video information, which is then recursively applied to the video in order to gate filtered or unfiltered video to an output channel according to coefficients of the masks. The filtering mask effectively yields a decision or rule-based map that transforms the video on a pixel-by-pixel basis thereby avoiding complex and processor-intensive decision tree logic customarily required to process individual pixels of successive macroblocks that may have different filtering requirements.

Abstract: A method and apparatus are provided for eliminating image noise to remove spatial-temporal noise and improve visibility. The method includes extracting a spatial-temporal noise level of neighbor pixels around a current pixel, filtering noise of the current pixel by applying a weight to spatial-temporal pixels around the current pixel based on the extracted spatial-temporal noise level, and applying a weight to the noise-filtered pixel and a boosted-up pixel based on an edge intensity and summing the weight-applied pixels. The spatial-temporal noise level is extracted based on spatial-temporal information of neighbor pixels around a current pixel in a current frame and spatial-temporal information of neighbor pixels around a current pixel in a previous frame.

Abstract: The system for edge direction detection for spatial deinterlace comprises an ignored region detector and an edge direction detection unit. The ignored region detector is configured to receive a first type field of a video frame and to define a search region based on the first type field. The edge direction detection unit is configured to select an edge direction within the search region. The edge direction is associated with an interpolated pixel located on one of a plurality of second type lines of a second type field, where the search region is smaller than the first type field.

Abstract: A method for improving image quality, and an image signal processing apparatus and an AV device using the same are provided. In the method for improving image quality, processing image signals relating to improving the image quality can be adaptively performed based on the amount of movement of an input movie-image so that the image quality of the movie-image can be improved without breaking the image.

Abstract: An image-processing device including a pulverization-core unit configured to divide input-image data into blocks, generate basic blocks by reducing each of the blocks in size, and arrange the basic blocks into the blocks so that processed-image data including at least one noise particle of the input-image data is generated, where the noise particle included in the processed-image data is reduced in size, an edge-detection unit configured to detect an edge degree from the input-image data, and an edge-blend unit configured to subject a pixel value of the input-image data and a pixel value of the processed-image data to load addition and output output-image data based on the detection result so that a weight to the pixel value of the input-image data increases as the edge degree increases is provided.

Abstract: A video noise reduction technique is presented. Generally, the technique involves first decomposing each frame of the video into low-pass and high-pass frequency components. Then, for each frame of the video after the first frame, an estimate of a noise variance in the high pass component is obtained. The noise in the high pass component of each pixel of each frame is reduced using the noise variance estimate obtained for the frame under consideration, whenever there has been no substantial motion exhibited by the pixel since the last previous frame. Evidence of motion is determined by analyzing the high and low pass components.

Abstract: Filter processing is performed on an image, in which a filter kernel having coefficients corresponding to positions of pixels is applied at a target pixel position and to sample pixels positioned in the neighborhood of the target pixel position. A bin is assigned to each unique coefficient of the filter kernel. A mask having respective positions corresponding to the positions of the filter kernel is created. Each respective position of the mask indexes to the bin for the coefficient corresponding to that position. The mask is positioned at the target pixel position, and the respective pixel value of each sample pixel is accumulated in the bin corresponding to the position of the sample pixel in the mask. The accumulated pixel values in each respective bin are multiplied by the coefficient corresponding to the bin. The resultant products are summed to determine a filtered pixel value at the target pixel position.

Abstract: In order to preserve edges of a picture and to suppress a residual distorted signal in a reproduced picture, a picture processing device (in-loop filter) includes a first filter unit for applying a first filter to an input picture to generate a first filter picture, an attribute information generator which generates an attribute value indicating whether or not to apply a second filter to each pixel of the generated first filter picture, and a second filter unit for applying the second filter to a target pixel of the first filter picture selected on the basis of the attribute value of each pixel of the generated first filter picture, to generate a second filter picture.

Abstract: This invention provides an image processing apparatus, image processing method, and computer program, which can visually remove low-frequency noise contained in image data. Image data containing low-frequency noise is input from an input terminal (201). A window unit (202) designates a window made up of a pixel of interest, and its surrounding pixels. A pixel selector (204) selects a selected pixel to be compared with the pixel of interest from the window, and a pixel value determination unit (206) 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: The invention relates to a method and an apparatus for increasing the resolution of a data sequence, such as for example a video data sequence. Between two data values of a given data sequence at least one intermediate value is interpolated by applying low-pass filtering and at least one first and one second high-pass filterings to data values of the data sequence, subjecting the filter values obtained by the high-pass filterings to rank-order filtering and combining the filter result so obtained with the filter result obtained by low-pass filtering.

Abstract: An image processing apparatus includes a contour pixel extraction unit configured to extract a contour pixel component from a bit plane. The bit plane is a set of bits, the number of which is equal to the number of pixels, and each of which is 1 bit of a plurality of bits representing an intensity of each of pixels. Also provided is a connectedness detection unit configured to detect equivalent bits adjacent to each other in a window including a bit corresponding to a target pixel on the bit plane. Also provided is a filter unit configured to reduce an intensity of the target pixel by a reduction amount determined in accordance with the contour pixel component extracted by the contour pixel extraction unit and the equivalent bits adjacent to each other detected by the connectedness detection unit.

Abstract: An image processing system includes an identification unit, a region division unit and a pixel value change unit. The identification unit identifies a second pixel among an image including a first pixel and the second pixel. A pixel value of the first pixel is not to be changed. A pixel value of the second pixel is to be changed. The region division unit divides the image into regions. The pixel value change unit changes the value of the second pixel to a predetermined value through a filtering process when the second pixel identified by the identification unit is included within the regions obtained by the region division unit.

Abstract: In an image-processing apparatus having a capability of performing region distinction processing and an image region discrimination processing method, a first region distinction unit uses a previously set threshold value for an image region distinction to perform a region distinction processing of a character and a non-character on image data read from an original document, an edge feature amount image and a character determination signal are obtained, a second region distinction unit makes a region distinction on the edge feature amount image based on the threshold value and generates and displays sub-region images obtained by dividing the edge feature amount image into plural parts, a character discrimination strength adjustment is performed on a display screen while each of the sub-region images is visually identified, the correction parameter is reflected in the edge feature amount image, and the region distinction processing is performed again.

Abstract: A method of difference sensing. A first step involves producing a reference image using temporal averaging and spatial averaging. A second step involves producing a test image. A third step involves computationally comparing the reference image with the test image to arrive at a resulting difference image. The temporal averaging and spatial averaging effectively isolates in the difference image coherent changes imbeded in a complex and rapidly changing environment from transient changes inherent to the complex and rapidly changing environment.

Abstract: A system and method includes acquisition of a set of image data comprising a plurality of image voxels and isolation of a set of pulmonary emboli candidates from the plurality of image voxels. The system and method also includes application of a non-linear contrast enhancement to the set of pulmonary emboli candidates, filtration of the enhanced set of pulmonary emboli candidates, output of a final set of pulmonary emboli candidates, and creation of an image comprising the final set of pulmonary emboli candidates.

Abstract: An apparatus for scaling an input image is disclosed. The apparatus includes a resolution determining circuit and a scaler. The determining circuit determines the resolution of the input image. The scaler includes a scaling filter with an adjustable number of filter taps and scales the input image to output scaled pixels, wherein an amount of taps of scaling filter corresponds to the resolution of the input image.

Abstract: The present invention relates to an apparatus for and a method of providing a sharper image by preventing the deterioration of an image caused by the difference in dynamic ranges of a center part and a surrounding part of the image photographed by an image sensor or by the difference of lens resolution. In accordance with an embodiment of the present invention, an image edge detection apparatus and a method thereof, a sharpness emphasis apparatus and a method thereof, and a recoding medium recorded with a program performing the method can acquire the sharpness and quality of a desired image by detecting an edge of a surrounding part by use of an edge detection filter having a different filter area size and/or a weight of a computed edge value in a center part and the surrounding part, respectively, of the image, and then by giving a weight to the detected edge.

Abstract: Methods and corresponding apparatus are presented that perform dynamic range compensation (DRC) and noise reduction (NR) together, adjusting the noise reduction parameters in response to the dynamic range compensation decisions. By such a modification of image noise reduction parameters based on the dynamic range compensation gain or, more generally, other such factors, these techniques make it possible to perform DRC on noisy images, achieving an image with low and uniform noise levels.

Abstract: The image processing device according to an aspect of the invention comprises an image input device for inputting image data representing a color image, a distance calculation device for calculating a distance on a color space between a noticed pixel of the inputted color image and each of peripheral pixels including the noticed pixel, a factor calculation device for calculating a weighting factor for each peripheral pixel in accordance with the calculated distance, and a weighted average processing device for calculating image data of the noticed pixel by obtaining a weighted average of image data of the peripheral pixels using the weighting factor calculated for each peripheral pixel.

Abstract: The invention distinguishes not only character areas and halftone dot areas in an image, but also makes highly accurate decisions concerning characters present in halftone dot areas. A decision signal generating unit generates a decision signal having luminance as a main component from a signal indicating inputted image data, and supplies the decision signal to a character decision unit, a halftone dot decision unit, and a character-in-halftone dot decision unit. The character decision unit generates data indicating whether a pixel of interest is inside a character image area. The halftone dot decision unit generates data indicating whether a pixel of interest is inside a halftone dot area. The character-in-halftone dot decision unit generates data indicating whether there is a character image inside the halftone dot area. Based on these three signals, an attribute flag generating unit generates attribute data of the pixel of interest.

Abstract: Methods and systems for image noise filtering are provided. One method of image noise filtering includes generating a plurality of sub-images of a digital image, applying a noise filter with small support to each sub-image, and generating a filtered digital image by merging the filtered sub-images. Another method of image noise filtering includes receiving a digital image including a plurality of color channels in the Bayer domain, applying a strong noise filter to each color channel to generate filtered color channels, computing a luminance image from the digital image, applying a weak noise filter to the luminance image to generate a filtered luminance image, computing a luminance recovery factor map using the luminance image and the filtered luminance image, and computing output color channels of the digital image using the filtered color channels and the luminance recovery factor map.

Abstract: An operation input reception unit (201) receives an operation input for a virtual vehicle. A running condition managing unit (203) manages the running condition of the virtual vehicle based on the received operation input. An image producing unit (204) produces a view field image seen from the viewpoint of the moving object based on stored image information and the managed moving condition. A velocity calculation unit (205) calculates the velocity of the moving object based on the managed moving condition. A deformed image producing unit (206) extracts an image of a rectangular area based on the velocity from the produced view field image and produces a deformed image obtained by deforming the extracted image into a trapezoidal shape. A display control unit (207) synthesizes the produced view field image and the produced deformed image and displays the synthesized image.

Abstract: A method of improving picture quality in a composite video burst signal includes dividing the composite video burst signal into a plurality of frequency bands using a low pass filter and a high pass filter, performing wavelet packet filtering of frequency bands including a chrominance signal having energy higher than a specified threshold among the plurality of frequency bands, and performing Wiener filtering of frequency bands including a chrominance signal having energy lower than a specified threshold.

Abstract: According to one embodiment, an image processing apparatus includes a detection module configured to detect a specific color area included in image data, an image processing control module configured to generate an image processing control signal for controlling an image process for the specific color area among image processes including a sharpening process for the image data, and an image processing module configured to subject the image data to the image process on the basis of the image processing control signal.

Abstract: A noise reduction apparatus is presented that includes groups of one or more serially connected non-linear filter units. Each of the filter unit groups are driven by decimated input image data at a different level of decimation and the output of at least one of these groups serves as one of a plurality of inputs to another group driven at a different decimation level.

Abstract: A method and apparatus for adaptively filtering an input image are provided. The method includes dividing an input image into a plurality of color domains according to a distribution of colors in the input image, respectively calculating a plurality of filter coefficients for the color domains, and adaptively filtering the color domains using the respective filter coefficients. The apparatus includes a domain classification unit which divides an input image into a plurality of color domains according to a distribution of colors in the input image, a filter coefficient calculation unit which respectively calculates a plurality of filter coefficients for the color domains, and a filtering unit which respectively filters the color domains using the filter coefficients. Accordingly, it is possible to enhance picture quality by addressing the problem of limited texture representation capabilities of existing filtering methods and apparatuses especially for memory color domains.

Abstract: A system for processing video data to improve image quality at low data rates comprising an encoder generating an entropy signal representing the relative entropy of the video data and a plurality of filters each receiving the entropy signal and a threshold setting and filtering the video data if the entropy signal is greater than the threshold setting.

Abstract: A method and system for retouching digital images for a motion picture removes semi-transparent artifacts or ‘blotches’ caused by contaminates in the optical path of the camera. This approach provides the benefit of only having to retouch a single average image that is than automatically applied via a correction power map to the entire sequence of images for the affected scene. The formation of an average image tends to reinforce the artifacts making them easier to identify and reduce background detail making it easier to retouch the artifact.

Abstract: A method for decomposing a target pattern containing features to be printed on a wafer.

Abstract: Apparatus and method of optically detecting click events are described. Images of a contact surface are captured at respective capture times. The captured images are convolved with a two-dimensional circularly symmetric spatial bandpass filter to produce corresponding filtered images each including a set of pixels with respective pixel value magnitudes. Based on the pixel value magnitudes of the corresponding filtered images, each of the capture times is assigned to one of an in-contact time class during which the contact surface is determined to be in-contact with a user's finger and an out-of-contact time class during which the contact surface is determined to be out-of-contact with the user's finger. A select signal indicating that the contact surface has been touched to make a selection is generated based on a click event predicate defining at least one condition on the time classes respectively assigned to successive ones of the capture times.

Abstract: A system and method of processing infrared imagery to determine projectile trajectories and the locations of shooters with a high degree of accuracy. The method includes image processing infrared image data to reduce noise and identify streak-shaped image features, using a Kalman filter to estimate optimal projectile trajectories, updating the Kalman filter with new image data, determining projectile source locations by solving a combinatorial least-squares solution for all optimal projectile trajectories, and displaying all of the projectile source locations. Such a shooter-localization system is of great interest for military and law enforcement applications to determine sniper locations, especially in urban combat scenarios.

Abstract: In a method for processing an input image to reduce compression-related artifacts, a plurality of block transforms of the input image having respective plurality of block-grid locations are generated, where each of the block-grid locations is shifted with respect to the block-grid locations in each of the other block transformed images. In addition, a plurality of respective intermediate transform domain filtered images having modified transform coefficients are generated. Per-pixel relative weights are assigned to each of the intermediate transform domain filtered images, where each of the intermediate transform domain filtered images has different contexts, and where the per-pixel relative weights are adaptive to the local context in each of the intermediate transform domain filtered images.

Abstract: In one embodiment, the present invention includes a method for generating and storing in a lookup table a first array of next field values for use in generation of weighted pixel values and generating and storing a second array in the lookup table of previous field values for use in generation of the weighted pixel values, determining if motion is present in a pixel of a field under analysis, if the motion is present, performing spatial de-noising using a weighted pixel average of a window of a predetermined size, otherwise performing temporal de-noising using a weighted pixel value between the pixel and a previous pixel using information in the lookup table. Other embodiments are described and claimed.

Abstract: A sharpening technique for digital images for presentation on a display is provided. In the technique, an image is modified in order to sharpen the features while at the same time suppress the noise. The image is first filtered resulting in at least two different channels of information. The channels can contain such information as texture information or edge and flat region information. Each channel is then further filtered in order to enhance the information stored in that channel. Finally, the channels are combined to result in a modified image with a different sharpness.

Abstract: Systems and methods are provided for variable source rate sampling in connection with image rendering, which accumulate and resolve over all samples forward mapped to each pixel bin. In accordance with the invention, the textured surface to be rendered is sampled, or oversampled, at a variable rate that reflects variations in frequency among different regions, taking into account any transformation that will be applied to the surface prior to rendering and the view parameters of the display device, thus ensuring that each bin of the rendering process receives at least a predetermined minimum number of samples. A variety of image processing applications are contemplated wherein variable rate source sampling, and accumulation and resolution of forward mapped point samples can be applied, ranging from 3-D graphics applications to applications wherein images recorded in a recording/storage environment are mapped to the arbitrary requirements of a display environment.

Abstract: A high-definition magnified image is obtained by simple computation. A magnified image is obtained by obtaining a deteriorated image on the basis of an input original image, determining enhancement filters used for individual small areas of the original image using the deteriorated image at least, performing a filtering process by applying the filters thus determined to the individual small areas to achieve enhancement, and interpolating the image for magnification.

Abstract: According to one embodiment, an image processing apparatus includes an obtaining module, a coefficient filter, a large area filter, and a determination module. The obtaining module obtains a feature value indicating an image structure of a pixel block comprising a target pixel to be processed and a surrounding pixel neighboring the target pixel in an input image. The coefficient filter performs filtering on the pixel block using a filter coefficient corresponding to the feature value. The large area filter performs smoothing on a pixel block that are larger than blocks used with coefficient filter. The determination module determines to cause the large area filter to perform the smoothing when the image structure indicated by the feature value is smooth.

Abstract: A method for processing an image which has the steps of a) receiving acquired data necessary to obtain an image and estimating a preliminary image; b) selecting at least one image element within the image; c) performing an iterative algorithm for processing the image at least on the at least one image element; d) computing a difference between the processed at least one image element and the at least one image element; and e) repeating the steps c) and d) until the difference is below a predefined threshold.

Abstract: An image processing method, for receiving an input image and separating pixels having text characteristics and pixels having figure characteristics, includes: applying a first filtering processing for the input image to derive a first image processing result; applying a second filtering processing for the first image processing result to derive a second image processing result, wherein a distribution of filtering parameters of the first filtering processing is different from a distribution of filtering parameters of the second filtering processing; deriving a set of first reference values according to the first image processing result and the second image processing result; and determining whether each pixel within the input image is a text pixel or a figure pixel according to at least the set of the first reference values and a predetermined threshold.

Abstract: A method for enhancing image quality includes: performing a peaking operation on an image signal to generate a peaking signal; selecting a plurality of pixels from the peaking signal and the image signal; and deciding a luminance value for a target pixel of the image signal according to luminance values of the plurality of pixels.

Abstract: The present invention relates to an interpolation method for enlarging a digital image or predicting a moving vector of a compressed image system as a sub-pixel unit when the image digitized through a CCD (Charge Coupled Device) camera ect. has a low resolution in a video phone or video conference or general digital video system, particularly the present invention can be adapted to a post processor of a compressed digital image in order to improve the image quality, and can be used for finding a moving vector of a moving picture compressed type, accordingly the present invention is capable of improving the image quality.