Abstract: Provided is an apparatus for sharpening a blurred enlarged image, including a digital image output unit for outputting a digital image input through a digital image input unit. The apparatus includes a digital image processing unit for calculating a primary edge direction of the digital image input through the digital image unit to perform enlarging and edge sharpening on the input digital image. Accordingly, blurring is removed from the enlarged image without ringing or an artifact using an adaptive edge sharpening method, so that the enlarged image can be sharpened.

Abstract: In an image processing device, a lowpass filter extracts a low-frequency component of 8-bit input image data VI1 to obtain 10-bit image data LP1 expanded in the course of an operation during the extraction of the low-frequency component. Two less significant bits of the image data LP1 are rounded in a rounding circuit, and the obtained image data is output as 8-bit image data RD1. A comparator compares the image data RD1 with image data VI2, and an image output control circuit outputs a control signal OC1 based on a result CP1 of the comparison. A bit addition circuit adds 2 bits to the LSB of the image data VI1 to output 10-bit image data BS1. An output image selection circuit selects the image data LP2 or the image data BS2 based on the control signal OC1 to output as 10 bit-image data VO1.

Abstract: There is disclosed a mobile robot including an image processor that generates recognition information regarding a target object included in a taken image, and a main controller integrally controlling the robot based on this recognition information.

Abstract: An image processing device includes: a peaking filter for performing peaking processing on an input image signal to generate a peaking image signal; a selection circuit, coupled to the peaking filter, for selecting a plurality of pixels within the peaking image signal; and a median filter, coupled to the selection circuit, for filtering the plurality of pixels within the peaking image signal to generate a filtered image signal.

Abstract: A system determines the noise level of image data by high pass filtering image data. Absolutes values of the high pass filtered image data are determined. Thereafter, multiple mean values for absolute values less than a predetermined number of threshold values are determined. Based upon the determined mean values, a plurality of estimated mean values is calculated, each estimated mean value being calculated from a combination of two determined mean values. The noise of the image is determined from a combination of the minimum estimated mean value and the maximum estimated mean value. This noise can be optionally used by a sigma filter, at Step S740, to sigma filter the image data.

Abstract: The present invention relates to a method and a device for enhancing a digital image comprising samples or pixels. The method comprises: defining a patch of samples surrounding any given sample; computing distance values representing similarity between patches of a first sample and other samples to obtain a distance map; computing, using the distance map, weights to obtain a weight map; applying a filter enhancing high spatial frequencies to the weight map to obtain an enhanced weight map; filtering the first sample by averaging the samples using the enhanced weight map, to obtain an enhanced first sample. The invention provides a very efficient enhancement of the digital image since coherent structures that would usually not influence the enhancement of the image, are detected and made more significant thanks to the filtering of the weight map.

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 present invention provides two-scale tone management of an input image. A method of providing two-scale tone management contains the steps of: separating the input image into a base layer and a detail layer; separating a model image into a base layer and a detail layer; analyzing the input image globally for global contrast; analyzing the input image locally for local contrast; and performing detail preservation of the input image. A system contains a memory and a processor, where the processor is configured by the memory to perform the steps of: separating the input image into a base layer and a detail layer; separating a model image into a base layer and a detail layer; analyzing the input image globally for global contrast; analyzing the input image locally for local contrast; and performing detail preservation of the input image.

Abstract: A method of generating a multiscale contrast enhanced image is described wherein the shape of edge transitions is preserved. Detail images are subjected to a conversion, the conversion function of at least one scale being adjusted for each detail pixel value according to the ratio between the combination of the enhanced center differences and the combination of the unenhanced center differences.

Abstract: A device has a single scaling filter to filter a video signal once to perform both sharpening and scaling. A memory stores original scaling filter coefficients for the scaling filter. An integrated circuit calculates new sharpening-scaling filter coefficients derived from the original scaling filter coefficients and one of sharpening filter coefficients for a sharpening filter and a sharpening strength and applies the new sharpening-scaling filter coefficients to the single scaling filter.

Abstract: An image conversion unit (100) for converting an input image (602) into an output image (606) is disclosed. The image conversion unit (100) comprises: a filter (104) for selecting a group of connected input pixels from the input image (602), the group of connected input pixels having a size which is relatively small relative to the size of the input image (602), the input pixels of the group of connected input pixels having high luminance values relative to the range of input luminance values; and a pixel processor (104) for assigning luminance values to output pixels of the output image (606) on basis of the respective luminance values of the input pixels of the input image (602), whereby the luminance values of the output pixels corresponding to the group of connected input pixels are higher than the respective luminance values of the connected input pixels.

Abstract: A signal is used to form intermediate feature vectors which are subjected to high-pass filtering. The high-pass-filtered intermediate feature vectors have a respective prescribed addition feature vector added to them.

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: 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 present disclosure relates to a method of improving an IR image comprising capturing a visual image and an IR image of an object, altering a resolution of at least one of said visual image and IR image, high pass filtering said visual image to generate a processed visual image, low pass filtering said IR image to generate a processed IR image, and combining information from said processed visual image and said processed IR image to generate a combined image.

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 camera or other optical system is focused by generating a plurality of digital images each obtained with a different focus setting of the optical system. These images are analysed to generate for each image a score (S) by comparing first groups of pixels chosen from the image with second groups chosen from the image such that the pixels of each second group have same respective positional relationships with respect to one another as the pixels of the first group with which it is compared have to one another, the score (S) being a function of the number of matches obtained with said comparisons. The focus setting that gives the score corresponding to the largest number of matches is chosen.

Abstract: In an image processing apparatus, a min-max pixel difference value computing unit computes the difference between the maximum and minimum pixel values in a first image portion including a target pixel and neighbor pixels. A maximum adjacent pixel difference value computing unit computes the maximum value among the difference values between adjacent pixels in the first image portion. An image change feature value computing unit computes a feature value corresponding to the suddenness of image change in the first image portion. A filter coefficient computing unit computes filter coefficients. A sharpen filter accepts, as input, pixels forming a second image portion including the same target pixel as the first image portion and neighbor pixels, and computes an output pixel value for the target pixel.

Abstract: Techniques for managing video stream data and portions of video stream data are disclosed. In particular, the present invention enables the user to match portions of video streams against stored, previously characterized video streams using Canny edge detection filtering coupled with Hu invariant third moments of those edges. According to one aspect of the present invention, the video stream data is encoded with the following technique, which selects specific frames from the video stream, finds the edges of objects within these selected frames using Canny edge detection, separates each edge into a distinct object, calculates Hu invariant third moments for each edge, and stores each edge together with the video stream and frame identification and it's Hu invariant third moments in a database for later comparison. Similar encoding can then be performed for a query video stream to compare against the previously identified video streams stored in the database to identify a unique video stream.

Abstract: Provided is a system and method for processing data and images including, but not limited to separating data into a plurality of data planes; performing noise analysis to determine an average noise amplitude and noise distribution for each data plane via a gradient calculation; applying an edge mask to weaken isolated transients in one or more of the data planes; applying a noise filter using one or more levels of filtering to one or more of the data planes; and performing detail recovery combining a composite data plane and filtered and unfiltered data planes according to the noise analysis.

Abstract: An image processing method is provided including the steps of generating a first band image through high-pass filter processing to a source image having an image of a subject falling thereon; generating a reduction image through reduction of the source image; performing low-pass filter processing to the reduction image to generate a low-pass image; magnifying the low-pass image to generate a magnified low-pass image; generating a second band image based on the source image, the first band image, and the magnified low-pass image; generating a third band image through performing of band-pass filter processing to the reduction image; and performing image processing to the source image with each of the band images.

Abstract: A method for segmentation of locally-defined regions is provided. The input data obtained for the image region under investigation is separated into a foreground mask and a background mask, two different filter operations are applied to the input data to determine segmentation starting points, the resulting data sets are subtracted and the image regions viewed as segmentation starting points, a filter operation is applied to generate a less restrictive mask for the input data, the resulting data subjected to a threshold value reduction, the less restrictive mask subjected to a labeling with regard to determination of the local values for generation of a restrictive mask, the mean values determined, segmentation starting points not obtained in the less restrictive mask are removed, a growth into all regions of the restrictive mask is carried out and the regions obtained in the restrictive mask are viewed as the segmented brightness regions.

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: A super-resolution processor according to the present invention includes: an N enlargement unit that generates an N-enlarged image by enlarging the input image by a factor N; an M enlargement unit that generates an M-enlarged image by enlarging the input image by a factor M; a high-pass filter unit that extracts a high-frequency component of the M-enlarged image, as an M-enlarged high-frequency image; a patch extraction unit that extracts an estimated patch of a predetermined size from the M-enlarged high-frequency image, the estimated patch being a part of the M-enlarged high-frequency image; and an addition unit that adds the estimated patch to a processing target block of the predetermined size in the N-enlarged image, to generate the output image, where M is smaller than N.

Abstract: An edge enhancing apparatus includes: an edge detector, for determining an edge direction of an image region corresponding to a target pixel; and a pixel value determining module, coupled to the edge detector, for obtaining a plurality of pixel values of a plurality of pixels and an initial pixel value of the target pixel according to the edge direction, and performing a calculation on the plurality of pixel values and the initial pixel value to generate a calibrated pixel value.

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 interpolation method and a filtering method which utilize a correlation between pixel signals, and it is an object of the present invention to provide a sharp and high-quality image even if an error occurs in correlation degree judgment. To accomplish the above-mentioned object, an imaging device 10 is of a single-chip type, and includes a RGB Bayer pattern color filter 11, and an image is processed in a manner to be described below. Pixel signals outputted from the imaging device 10 are inputted through a signal processing part 20 to an image processing part 30. A correlation judgment part 31 judges a correlation between the pixel signals, and an interpolation processing part 32 performs a pixel interpolation process based on a correlation result. Thus, each pixel signal becomes a perfect signal having all R, G and B color components.

Abstract: A digital image processing apparatus for easily obtaining information regarding a face, a method of controlling the same, and a recording medium for storing a program for executing the method. The digital image processing apparatus includes a face recognition unit recognizing a face from an image, a face index assignment unit assigning a face index to the recognized face if the face recognized from the image is not a previously recognized face, and a relation index update unit that, if the image includes a second face, updates a relation index corresponding to the number of times the first face and second face appear together in a plurality of images.

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: An image processing method for boundary resolution enhancement is disclosed. Firstly, an image is transferred into an image layer. Noise of the image layer is removed by a bilateral filter and crisp edges are retained at the same time. Moreover, the image layer is interpolated by an interpolation filter for resolution enhancement. The image processing method of the present invention can lower the image blur degree substantially, enhance the image resolution and be widely implemented in all sorts of image/video processing hardware devices.

Abstract: Disclosed are an apparatus and method to improve clarity of images, which can prevent the degradation of the clarity of a display unit caused by deterioration of a contrast characteristic. The apparatus includes: an artifact reducing unit determining a representative color of one of the images and moving a color of an edge as the determined representative color; a filter extracting a high frequency component of the image; and a sharpness enhancement unit improving the clarity of the image having the color of the edge moved and the filtered high frequency component.

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: A post-processing circuit for processing an image signal according to frequency components of an image signal includes: a low-frequency extracting unit outputting a low-frequency image component of the image signal as a low-frequency signal; a high-frequency extracting unit multiplying a high-frequency image component of the image signal by a first gain and outputting the multiplication product as a high-frequency signal; an intermediate-frequency extracting unit multiplying an intermediate-frequency image component of the image signal by a second gain and outputting the multiplication product as an intermediate-frequency signal; and an adder adding the low-frequency signal, the high-frequency signal, and the intermediate-frequency signal and outputting the addition sum as a post-processed signal, wherein the first gain and the second gain are differently set according to a pixel location in a spatial domain.

Abstract: A method for downsampling fluoroscopic images and enhancing guidewire visibility during coronary angioplasty includes providing a first digitized image, filtering the image with one or more steerable filters of different angular orientations, assigning a weight W and orientation O for each pixel based on the filter response for each pixel, wherein each pixel weight is assigned to a function of a maximum filter response magnitude and the pixel orientation is calculated from the angle producing the maximum filter response if the magnitude is greater than zero, wherein guidewire pixels have a higher weight than non-guidewire pixels, and downsampling the orientation and weights to calculate a second image of half the resolution of the first image, wherein the downsampling accounts for the orientation and higher weight assigned to the guidewire pixels.

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: Blurred image data is sharpened by converting three channels of RGB data into a single channel of intensity data, processing the intensity data to generate integral image data, applying a variable size filter to the integral image data to generate box-filtered data, calculating a gain factor for each pixel position in dependence upon the box-filtered data, the intensity data and the size of the filter used for that pixel position, and multiplying the original RGB data of each pixel by the gain factor for that pixel to generate sharpened RGB data. The size of the filter is selected at each pixel position in dependence upon an estimate of the local amount of blur. In this way, as the amount of blur changes, the filter size changes appropriately. By processing the integral image data to generate box-filtered data, a constant number of processing operations are required for image sharpening irrespective of the size of filter that is used.

Abstract: A method is presented for processing an image of a two-dimensional (2D) matrix symbol having a plurality of data modules and a discontinuous finder pattern, each distorted by “donut effects”. A resulting processed image contains an image of the 2D matrix symbol having a continuous finder pattern suitable for conventional 2D matrix symbol locating techniques, and having a plurality of data modules, each data module having a center more truly representative of intended data, and suitable for conventional 2D matrix symbol sampling and decoding. The method includes sharpening the distorted image of the 2D matrix symbol to increase a difference between low frequency and high frequency image feature magnitudes, thereby providing a sharpened image, and smoothing the sharpened image using a moving window over the sharpened image so as to provide a smoothed image, the moving window and a module of the 2D matrix code being of substantially similar size.

Abstract: A system and method of color interpolation includes a spatial convolution unit that receives an output of an image sensor and then performs spatial convolution on the received image-sensor output, thus generating a convolution signal. A color interpolation unit performs color interpolation on the convolution signal, thus generating a color-interpolated signal. Finally, a spatial deconvolution unit performs spatial deconvolution, which is the inverse of the spatial convolution, on the color-interpolated signal, thus generating a preprocessed image.

Abstract: Briefly, in accordance with at least one embodiment, a technique for combining images to create or produce one or more optical effects is disclosed.

Abstract: Presented herein are a system and method for sharpening edges in a region. In one embodiment, there is presented a method for sharpening edges. The method comprises measuring differences between at least a value associated with a first pixel and a value associated with a second pixel of a plurality of pixels; and applying a sharpening mask to the plurality of pixels, wherein the sharpening mask is a function of at least one of the measured differences, a first value associated with any one of the plurality of pixels, and a second value associated with any other of the pixels, thereby resulting in sharpened pixels.

Abstract: A method and system for scaling an original image into a scaled image is disclosed. Rather than using the corresponding position in the original image to generate the pixels values of a current pixel in the scaled image, image scalers in accordance with the present invention, calculate a high frequency adjusted position based on the high frequency components of pixels near the corresponding position. Pixel values based on the high frequency adjusted position provide better picture quality for the scaled image than pixel values based on the corresponding position. Furthermore, some embodiments of the present invention also use sharpness compensation to further improve the picture quality of the scaled image.

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: Blurred image data is sharpened by converting three channels of RGB data into a single channel of intensity data, processing the intensity data to generate integral image data, applying a variable size filter to the integral image data to generate box-filtered data, calculating a gain factor for each pixel position in dependence upon the box-filtered data, the intensity data and the size of the filter used for that pixel position, and multiplying the original RGB data of each pixel by the gain factor for that pixel to generate sharpened RGB data. The size of the filter is selected at each pixel position in dependence upon an estimate of the local amount of blur. In this way, as the amount of blur changes, the filter size changes appropriately. By processing the integral image data to generate box-filtered data, a constant number of processing operations are required for image sharpening irrespective of the size of filter that is used.

Abstract: An image processing method for an image processing system for enhancing image quality after a sharpening procedure includes receiving a plurality of original image data, performing the sharpening procedure for the plurality of original image data for generating a plurality of sharpened image data, adjusting the plurality of sharpened image data according to the plurality of original image data, and outputting the plurality of sharpened image data.

Abstract: A video image capture component includes a light source operable in a first spectrum, a first image detector operable in the first spectrum, a second light source operable in a second spectrum, and a second image detector operable in the second spectrum. A filtering component generates a combination image by filtering a first image obtained by the first image detector with a high-contrast filter, resulting in a high-contrast image, and masking a second image obtained by the second image detector using the high-contrast image. A compositing component creates a composite image from the combination image and a selected image. A display component displays the composite image. Alternative systems and methods for creating a combination image include techniques involving thermal imaging, laser detection, and narrow band frequency detection.

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: An image processing method for filtering image data, which is constituted with a plurality of pixels, at each pixel position by using pixel values indicated by pixels present within a predetermined range containing a target pixel, includes: determining two arguments that are a first argument defined by a spatial distance from the target pixel and a second argument defined by a difference in signal intensity relative to the target pixel, in correspondence to each of the pixels present within the predetermined range; obtaining a weighting coefficient to be used when filtering each of the pixels present within the predetermined range, based upon a single integrated argument represented by a product of the first argument and the second argument; and filtering the image data by using a filter coefficient corresponding to the weighting coefficient having been obtained.

Abstract: A method of creating a super-resolved color image from multiple lower-resolution color images is provided by combining a data fidelity penalty term, a spatial luminance penalty term, a spatial chrominance penalty term, and an inter-color dependencies penalty term to create an overall cost function. The data fidelity penalty term is an L1 norm penalty term to enforce similarities between raw data and a high-resolution image estimate, the spatial luminance penalty term is to encourage sharp edges in a luminance component to the high-resolution image, the spatial chrominance penalty term is to encourage smoothness in a chrominance component of the high-resolution image, and the inter-color dependencies penalty term is to encourage homogeneity of an edge location and orientation in different color bands. A steepest descent optimization is applied to the overall cost function for minimization by applying a derivative to each color band while the other color bands constant.

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.