Abstract: A method is disclosed for finding a deformed pattern in an image using a plurality of sub-patterns. By advantageously restricting sub-pattern search ranges, search speed is improved, and the incidence of spurious matches is reduced. The method also quickly decides which sub-pattern result, of several potential candidates, is most likely to be the correct match for a deformed sub-pattern. Also, a method is provided for characterizing a deformed pattern in an image by using results from feature-based search tools to create a mapping that models the deformation of the pattern. A transform, selectable by a user, is fit to the results from the search tools to create a global deformation mapping. This transformation is fit only to feature points derived from matches resulting from successful sub-pattern search, without including data from areas of the pattern that were blank, not matched, or otherwise didn't contain information about the pattern's distorted location.

Abstract: Implementations consistent with the principles described herein relate to ranking a set of images based on features of the images determine the most representative and/or highest quality images in the set. In one implementation, an initial set of images is obtained and ranked based on a comparison of each image in the set of images to other images in the set of images. The comparison is performed using at least one predetermined feature of the images.

Abstract: An image processing apparatus includes: an area setting section that sets a searching area of a predetermined size in inputted image data; a searching section that searches for pixels having a predetermined pixel value in the searching area set by the area setting section; an attribute determining section that determines attribute of pixels contained in the searching area on the basis of at least one of a number and an arrangement of the pixels searched for by the searching section; and an attribute assigning section that assigns the attribute determined by the attribute determining section to the searched pixels.

Abstract: This invention provides a decoding apparatus including an intensity setting unit that sets a modification intensity based on modified image information and a modification unit that modifies decoded image information with an intensity set by the intensity setting unit.

Abstract: A video processing system may implement a video scaling algorithm using interpolation based on polyphase filtering. A video or graphics scaler may be utilized to scale luma, chroma, and/or alpha information in a video image. The scaler may comprise a first polyphase sub-filtering with zero phase shift that generates an in-phase filtered output from an input video image and a second polyphase sub-filtering that generates an out-of-phase filtered output from the input video image. The video scaler may also comprise an interpolator that may generate a scaled video image based on the generated in-phase and out-of-phase filtered outputs and a scaling factor. The scaling factor may be determined based on an input video size (M) and a desired output video size (N). The interpolation of the generated in-phase and out-of-phase filtered outputs in the video scaler may be implemented by utilizing a Farrow structure.

Abstract: An image is generated by receiving a first image that is acquired during a first exposure period and defining the first image as a reference image; defining multiple reference regions of interest within the reference image, wherein an aggregate number of pixels within the multiple reference regions of interest is substantially smaller than a number of pixels of the first image; receiving a second image that is acquired during a second exposure period; and updating the reference image in response to a content of the reference image, content of the second image and a first type of spatial relationship (e.g., a shift) defined between the reference image and the second image, wherein the shift is defined in response to multiple spatial relationships between the multiple reference regions of interest and between multiple regions of interest of the second image.

Abstract: Images can be laid out easily without a template. Reference areas are set in a background area, and the images are laid out by being inscribed therein. In the case where the image laid out in one of the reference areas has high priority, a similar area is generated from the reference areas, and the image is enlarged to be inscribed in the similar area.

Abstract: A diagnostic imaging system (10) corrects metal artifact streaks (38) emanating from a metal object (36) in a tomographic image (T). A first processor (40) reduces streaks (38) caused by mild artifacts by applying an adaptive filter (82). The filter (82) is perpendicularly oriented toward the center of the metal object (36). The weight of the filter (82) is a function of the local structure tensor and the vector pointing to the metal object (36). If it is determined that the strong artifacts are present in the image, a second processor (48) applies a sinogram completed image algorithm to correct for severe artifacts in the image. The sinogram completed image and adaptively filtered image are fused to a final corrected image. In the fusion process, highly corrupted tomographic regions are replaced by the result of the sinogram completed image and the remainder is replaced by the adaptively filtered image.

Abstract: Provided are an apparatus and method for generating an image using a multi-channel filter. More particularly, provided are an apparatus and method for generating an image using a multi-channel filter, wherein images input into a plurality of image sensors are allowed to pass through different filters, each of which includes a plurality of channels, and segmented images passed through the filters are combined to produce a desired image. The apparatus includes a filter unit including a plurality of filters having different patterns with respect to a plurality of image channels and filtering images input into the filters, an image sensing unit including a plurality of image sensors sensing images filtered through the plurality of the filters, an interpolation unit calculating image channel values of pixels of the sensed images, and an image combination unit assigning the calculated image channel values to corresponding pixel positions to generate a single desired image.

Abstract: A block noise detector has a spatial difference calculator that calculates differences between values of adjacent pixels. A spatial difference comparator detects edges by comparing the calculated differences. Eight counters count edges detected at different groups of positions spaced eight pixels apart in each horizontal line. The maximum count and the group of positions at which it occurs are detected at the end of each horizontal line to detect block noise and the positions of the block boundaries. The block noise detector is small in size because it only has to count edges in one line at a time, and detects edges accurately by comparing the difference at a given position separately with differences to the left and differences to the right.

Abstract: An exemplary method for increasing brightness of an image captured in low light includes: transforming the captured image into an original image that has a brightness component; copying the brightness component of the original image as a brightness image; inverting the brightness image into a negative image; and incorporating the negative image into the original image such that a predetermined percentage of gray scale values of pixels of the negative image corresponding to pixels in a dark portion of the original image are respectively added to gray scale values of the pixels in the dark portion of the original image to produce a processed image.

Abstract: A method of filtering noise from a picture may include determining a set of pixel noise metrics for a set of selected pixels in the picture based solely on information from the set of selected pixels in the picture. The method may also designate as valid a subset of pixel noise metrics in the set of pixel noise metrics those associated pixels are not located at an edge or are not located in a complicated area of the picture. A set of block noise metrics may be calculated from the valid subset of pixel noise metrics, and a global noise metric for the picture may be ascertained from the set of block noise metrics. The picture may be filtered using the global noise metric to generate a filtered picture.

Abstract: A method, medium and system processing an image signal. The system includes an edge detection module to detect a pixel belonging to an edge in an input image, a period determination module to determine a period of change in pixel values based on a first value of the pixel belonging to the edge and a second value of a pixel that is adjacent to the pixel belonging to the edge, and a signal correction module to correct one or more sub-pixels of the pixel belonging to the edge using a weight allocated according to a result of the determination performed by the period determination module.

Abstract: In some embodiments, the present invention relates to methods or suppressing edge ringing in images. For example, in some embodiments a method of processing an image to suppress ringing and broadened edges induced by image correction processing, includes high-pass filtering a first image to obtain a second image, processing said second image including applying non-linear apodization to said second image to obtain a third image, low-pass filtering said first image to obtain a fourth image, and combining the third image and the fourth image to obtain an output image, wherein the output image is characterized by having reduced edge-response sidelobes as compared to the first images. In some embodiments, the present invention relates to devices comprising means and/or modules to suppress edge ringing in images.

Abstract: A system to perform modifications, or adjustments, to a digital image includes an interface component to receive selection input to enable selection of the digital data to be modified. A detector then detects a characteristic of the digital data. A configurator automatically configures a function, supported by a data modification component, to modify the digital data. The automatic configuration of the function is performed using the detected characteristic of the digital data to be modified.

Abstract: A wide-field image input device that joins a series of partial images obtained by continuously imaging an imaging object by an imaging device while the imaging device is manually scanned by a user, thereby generating a wide-field image, includes: a camera position/posture estimation unit for receiving a partial image series and calculating a change state of three-dimensional position and posture of the imaging device as time-series camera position/posture information; a deformation parameter estimation unit for calculating a geometrical deformation parameter between adjacent partial images from the camera position/posture information; an image joining unit for joining the partial images by using the geometrical deformation parameter so as to generate a wide-field image; and a camera scan error detection unit for detecting motion of the imaging device according to the camera position/posture information and outputting a camera scan error detection signal when an error is detected.

Abstract: A mosaicing method taking into account motion distortions, irregularly sampled frames and non-rigid deformations of the imaged tissue. The method for mosaicing frames from a video sequence acquired from a scanning device such as a scanning microscope, includes the steps of: a) compensating for motion and motion distortion due to the scanning microscope, b) applying a global optimization of inter-frame registration to align consistently the frames c) applying a construction algorithm on the registered frames to construct a mosaic, and d) applying a fine frame-to-mosaic non rigid registration. The method is based on a hierarchical framework that is able to recover a globally consistent alignment of the input frames, to compensate for the motion distortions and to capture the non-rigid deformations.

Abstract: A system and method is provided for using a first vascular image, or more particularly a plurality of control points located thereon, to identify a border on a second vascular image. Embodiments of the present invention operate in accordance with an intra-vascular ultrasound (IVUS) device and a computing device electrically connected thereto. Specifically, in one embodiment of the present invention, an IVUS console is electrically connected to a computing device and adapted to acquire IVUS data. The IVUS data (or multiple sets thereof) is then provided to (or acquired by) the computing device. In one embodiment of the present invention, the computing device includes a plurality of applications operating thereon—i.e., a border-detection application, an extrapolation application, and an active-contour application. These applications are used to (i) identify a border and control points on a first IVUS image (i.e., any IVUS image), (ii) extrapolate the control points to a second IVUS image (i.e.

Abstract: One camera having a horizontally wide view angle is installed at each of the left and right rear ends of a tractor. The visual field of the left camera includes the road surface located to the left side of the tractor and a trailer, and the like. The visual field of the right camera includes the road surface located to the right side of the tractor and the trailer, and the like. The left and right cameras have a common visual field at the rear side of the trailer. A panorama image obtained by synthesizing images respectively obtained by the left and right cameras is displayed on a display device located in the interior of the tractor.

Abstract: A method and system of merging a pair of images to form a seamless panoramic image including the following steps. A set of feature points are extracted along the edges of the images, each feature point defining an edge orientation. A set of registration parameters is obtained by determining an initial set of feature points from a first one of the images which matches a set of feature points of a second one of the images. A seamless panoramic image is rendered using the first and second images with the set of registration parameters.