Abstract: An image processing apparatus includes: an image information input unit which receives input of first image information; and a sharpness adjustment unit which divides a screen image corresponding to the first image information into a plurality of areas and performs a sharpness adjustment for each of the divided areas to output second image information.

Abstract: A digital image filtering method and system are provided. A first matrix of a plurality of pixels is selected from a digital image to be displayed. The luminosity values of each of the pixels in the pixel matrix are analysed and the luminosity difference between the maximum and minimum luminosity values thereof is calculated. The central pixel of the matrix is then classified according to the luminosity difference in comparison to a predetermined threshold luminosity value, and the above selection, analysis and classification is repeated for each of the pixels of the image in turn. A target pixel is then selected from the classified pixels for further analysis, wherein a second pixel matrix of which the target pixel is the central pixel is selected, the classification of the pixels surrounding the target pixel in the second matrix is analysed, and the target pixel is filtered to an extent dependent upon the classification analysis.

Abstract: In visual display devices such as LCD devices with backlight illumination, the backlight typically consumes most of device battery power. In the interest of displaying a given pixel pattern at a minimized backlight level, the pattern can be transformed while maintaining image quality, with a transform determined from pixel luminance statistics. Aside from, or in addition to being used for such minimizing, a transform also can be used for image enhancement, for a displayed image better to meet a visual perception quality. In either case, the transform preferably is constrained for enforcing one or several display attributes. In a network setting, the technique can be implemented in distributed fashion, so that subtasks of the technique are performed by different, interconnected processors such as server, client and proxy processors.

Abstract: Circuits, methods, and apparatus for measuring a video signal's noise level. The determination can be made based on pixel values for a single video image frame, for example, by comparing pixel color values, luminance, or other parameter for a first and second group of pixels in the frame. Each group of pixels may be part of a line in the frame, and several such measurements may be made along each line of the frame. These measurements can then be further refined depending on the measure noise level. Once a video noise level is determined, a decision on how to further process the video signal can be made. For example, the picture can be filtered or sharpened. The amount of noise filtering can be made dependent on the amount of noise measured.

Abstract: A circuit and a method for image processing are provided. The image processing circuit has an adaptor and a sharpening circuit. The adaptor has a processing unit and a weight generator. The processing unit receives an input video signal, and the input video signal has information of a plurality of pixels. The processing unit processes the input video signal to calculate a color difference value of a target pixel of the pixels. The weight generator generates a weighting signal according to the color difference value. The sharpening circuit performs a sharpening operation on the input video signal according to the weighting signal to generate a sharpened video signal.

Abstract: A video signal processing apparatus and video processing method are provided, which can reduce an influence of noise and enhance fineness of the image. A signal division unit divides a video signal into a low frequency component and a high frequency component of the video signal. A signal eliminating unit eliminates a component within a magnitude range of noise from the high frequency component of the video signal output from the signal division unit. A signal combining unit combines the low frequency component of the video signal output from the signal division unit and the high frequency component of the video signal from which the component within the magnitude range of noise is eliminated.

Abstract: A superior Color Transient Improvement technique is adaptive to the local image features, so that more natural color edge transition improvement can be accomplished. A gain control function is provided that depends on the local image feature so that different regions of the image can be treated differently. Further, a correction signal is controlled in such a way (by the local image feature) that neither undershoot nor overshoot occurs, eliminating the need for post-processing for undershoot/overshoot removal.

Abstract: A method for processing an image using a bilateral filter. The bilateral filter is reformulated at each pixel location in the image into a sum of the original signal value of a central pixel at said pixel location and a bilateral correction term which is a function of local signal differences between the central pixel and its neighbors. The bilateral correction term is calculated using a computationally efficient approximation.

Abstract: An apparatus for removing a noise of a video signal is disclosed, by which a noise level can be effectively estimated to enhance an image quality of the video signal, by which the noise can be removed in a manner of effectively estimating a noise level though motion adaptive filtering, and by which blurring is prevented in the process of removing the noises. The present invention includes a temporal noise level estimation unit estimating a level of a temporal noise included in the video signal using a difference between two temporally consecutive videos, a noise correction unit correcting a noise estimated by the temporal noise level estimation unit, and a noise removal unit removing the noise included in the video signal using a level of the corrected noise.

Abstract: The present invention provides an apparatus and corresponding method for reducing temporal noise of a target frame and enhancing the motion of the target frame. The apparatus includes a storage device, a temporal noise reducing circuit, and a motion enhancing circuit. The storage device stores a first filtered signal of a previous frame. The previous frame is previous to the target frame. The temporal noise reducing circuit reduces temporal noise of the target frame according to the first filtered signal and an image signal of the target frame. The temporal noise reducing circuit then generates a second filtered signal of the target frame, which is stored in the storage device. The motion enhancing circuit enhances the motion of the target frame according to the first and the second filtered signals, and generates a motion-enhanced signal of the target frame.

Abstract: A method for determining a noise component in a video signal is proposed, in which the difference between a delayed and an undelayed video signal is formed. In order to be able to measure the noise component as precisely as possible, the delayed and the undelayed video signal are assigned to at least two different processing channels depending on their respective amplitude. At least two peak values for the noise signal for two different amplitude ranges are determined from the absolute value of the difference between the two video signals. Furthermore, a circuit is proposed which is suitable for implementing the method proposed.

Abstract: According to one embodiment, an MPEG noise reduction processing unit which performs a process of reducing a mosquito noise to a received video signal can be controlled in a setting state corresponding to a desired item selected on the setting screen in which the plural items to be set are displayed as an option.

Abstract: According to one embodiment, a video signal sharpening apparatus includes a video signal sharpening module and a sharpening parameter controller. The video signal sharpening module performs a sharpening process on a decoded video signal based on a sharpening parameter. In the sharpening process, the video signal sharpening module estimates an original pixel value from the decoded video signal and increases the pixels to obtain a high-resolution video signal. The decoded video signal is obtained by a decoder decoding an encoded video signal. The sharpening parameter controller determines the amount of variation in noise and detail component that varies by an I-frame period in a group of pictures (GOP) period of the decoded video signal, and controls the sharpening parameter for the video signal sharpening module.

Abstract: The present invention sets out to make available a method for reducing noise in an image sequence. This method can be implemented in an acquisition device such as a digital video camera or the like. The aim of this invention is attained with a method for filtering a sequence of digital images in CFA format.

Abstract: A method includes calculating a mean of a plurality of pixels of a motion window, calculating a pixel amount of pixels similar to a center pixel, calculating a variance of the pixels, determining whether a difference between the center pixel and the mean is greater than a first predetermined value, determining whether the pixel amount similar to the center pixel is greater than a second predetermined value if the difference between the center pixel and the mean is not greater than the first predetermined value, determining whether the variance is smaller than a threshold value if the pixel amount similar to the center pixel is not greater than the second predetermined value, and filtering the center pixel according to a result of determining whether the variance is smaller than the threshold value. Finally, temporal weighted mean filters involving motion estimation are used for motion compensation in images after spatial filtering.

Abstract: A method for processing a source digital image wherein the source digital image is comprised of a plurality of pixels. A spatial filter is applied to the source digital image to produce an enhanced digital image. An inverse spatial filter is applied to the enhanced digital image to produce an estimated digital image. A difference digital image is then produced from the estimated digital image and the source digital image, wherein the difference digital image is representative of a difference between the source digital image and the estimated digital image. The difference digital image and the enhanced digital image can be transmitted from a first device to a second device remote. At the second device, a reconstructed digital image can be generated from the difference digital image and the enhanced digital image, wherein the reconstructed digital image is substantially equivalent to the source digital image.

Abstract: There is provided a method of reducing block noise, mosquito noise and other image noises in an image by a filtering process using a smoothing filter, which block noise, mosquito noise and other image noises being caused at the time of decoding encoded, compressed image data on a block-by-block basis. The method includes changing the extent or intensity of the image noise reduction in the filtering process in a continuous or stepwise manner according to an output size or expansion rate of an image to be outputted to printer paper, photographic paper or other output media, thereby allowing the extent or intensity of the image noise reduction to be increased as the output size or expansion rate of the image increases. This method is capable of allowing the extent of the image noise reduction applied to image data to be perceived in a similar fashion, irrespective of the output size.

Abstract: A ringing area detector classifies the input image into two regions: a mosquito noise region (i.e. filtering region) and a non-mosquito noise region (i.e. non-filtering region), and uses this classification information to adaptively remove the mosquito noise in a mosquito noise reduction system. The mosquito noise reduction system includes a ringing area detector, a local noise power estimator, a smoothing filter, and a mixer. The ringing area detector includes an edge detector, a near edge detector, a texture detector, and a filtering region decision block. The ringing detection block detects the ringing area where the smoothing filter is to be applied. The local noise power estimator controls the filter strength of the smoothing filter. The smoothing filter smoothes the input image. The mixer mixes the smoothed image and the original image properly based on the region information from the ringing area detection block.

Abstract: A method performed by a processing system is provided. The method comprises detecting a first pixel value associated with an artifact in a current frame of a digital video using a previous frame and a next frame and replacing the first pixel value in the first frame with a replacement value.

Abstract: A batch processing method for enhancing an appearance of a face located in a digital image, where the image is one of a large number of images that are being processed through a batch process, comprises the steps of: (a) providing a script file that identifies one or more original digital images that have been selected for enhancement, wherein the script file includes an instruction for the location of each original digital image; (b) using the instructions in the script file, acquiring an original digital image containing one or more faces; (c) detecting a location of facial feature points in the one or more faces, said facial feature points including points identifying salient features including one or more of skin, eyes, eyebrows, nose, mouth, and hair; (d) using the location of the facial feature points to segment the face into different regions, said different regions including one or more of skin, eyes, eyebrows, nose, mouth, neck and hair regions; (e) determining one or more facially relevant character

Abstract: This invention provides an image processing apparatus which can effectively remove conspicuous noise contained in image data, while suppressing deterioration of image information. Image data containing noise is input from an input terminal (100). Based on the output condition upon outputting image data after noise is removed, a parameter determination module (103) determines predetermined parameters used in a noise removal process. An example of the output condition is information associated with a resolution upon outputting image data. An individual noise removal module (104) removes noise contained in the image data using the parameters, and image data after the noise has been removed is output from an output terminal (105).

Abstract: In a method of removing a noise signal from a video signal and enhancing edge sharpness to improve the video signal definition, a different weight is assigned depending on a characteristic of input pixels. To this end, at least two pixel blocks including the input and at least two adjacent pixels. A pixel difference between the pixels in the each of the pixel blocks is calculated and one of the calculated pixel differences is selected. The input pixel is assigned with a weight corresponding to the selected pixel difference. Accordingly, the definition of the video signal is improved.

Abstract: A method for selectively optimizing a plurality of image characteristics for captured images, that includes modifying two or more one-dimensional image characteristic controls using a single loop position controller having one-dimensional control. The single loop position controller traverses useful ranges of each of the two or more one-dimensional image characteristic controls. Additionally, a user cycles through several combinations of the two or more one-dimensional image characteristic controls within a video loop; and has a means of selecting a desired image rendered according to the two or more one-dimensional image characteristic controls.

Abstract: A batch processing method for enhancing an appearance of a face located in a digital image, where the image is one of a large number of images that are being processed through a batch process, comprises the steps of: (a) providing a script file that identifies one or more original digital images that have been selected for enhancement, wherein the script file includes an instruction for the location of each original digital image; (b) using the instructions in the script file, acquiring an original digital image containing one or more faces; (c) detecting a location of facial feature points in the one or more faces, said facial feature points including points identifying salient features including one or more of skin, eyes, eyebrows, nose, mouth, and hair; (d) using the location of the facial feature points to segment the face into different regions, said different regions including one or more of skin, eyes, eyebrows, nose, mouth, neck and hair regions; (e) determining one or more facially relevant character

Abstract: A method of designing filters for filtering digitized images includes constructing a set of difference-of-Gaussian (DoG) filters that partition a frequency space, forming a linear combination of said DoG filters to form a trial filter, convolving said trial filter with a training image to obtain a trial image, summing a square difference of said trial image and a target image, wherein if said sum is a minimum, outputting said trial filter as a final filter, and using a singular value decomposition on said final filter wherein an eigenvector corresponding to the largest eigenvalue of the final filter is obtained.

Abstract: A method of filtering a digital image is described. A filter kernel is applied to a respective pixel in a set of pixels to smooth noise and preserve spatial frequencies associated with image edges in the digital image in accordance with a first filtering parameter. The filter kernel is a function of the respective pixel and has a closed form for the respective pixel. The filter kernel includes contributions from a first set of neighboring pixels and has a content-dependent normalization such that a sum of elements in the filter kernel equals a substantially fixed value.

Abstract: In each of stages of a nonlinear filter, a successively determined target signal and plural adjacent signals are weighted-averaged with plural sets of different coefficients to calculate plural smoothed signals. Differences in level between the target signal and each of adjacent signals and signals arranged within the predetermined interval from the each of the adjacent signals are compared with a threshold value. According to the comparison, flags are set to the adjacent signal, to an adjacent signal arranged at a symmetrical position, and to adjacent signals arranged beyond the adjacent signals. The intervals of adjacent signals are different among stages. The target signal in level is used instead of the adjacent signals with smoothed signals, which are selected according to the flags. Weighting coefficients may be calculated on the basis of the comparison result, and smoothed signals may be synthesized according to the weighting coefficients.

Abstract: An apparatus and method of filtering a digital image signal. The apparatus includes: a noise reduction filter which selectively outputs one of results obtained by temporally and spatially filtering pixel values of pixels of each of frames of an image as a temporal or spatial filtering value in response to magnitudes of the results of temporal and spatial filtering; and a sharpness enhancement filter which highlights and outputs a high pass component of the temporal or spatial filtering value.

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for distinguishing false motion from true motion, in a video signal that is received by a television set. The video signal is received at the television set. The video signal includes a luma component and a chroma component. A motion detection operation is performed for each of the chroma component and the luma component in several frequency regions of the received video signal. Each frequency region has a unique, adjustable threshold value for distinguishing false motion from true motion, that is dynamically adjustable based on the incoming video signal, and as a result the motion detection accuracy is improved and image artifacts are minimized in an image that is described by the video signal and is to be displayed on the television set.

Abstract: Methods of noise reduction and edge enhancement in image processing. An exemplary method comprises extracting a plurality of pixels from the video signal, evaluating measures of edge existence in a plurality of directions within the extracted pixels, determining a level of variation from the measures of edge existence, mapping the level of variation to a first and second control signal in accordance with a predetermined function, performing noise reduction on the extracted pixels according to the first control signal, and performing edge enhancement on the extracted pixels according to the second control signal.

Abstract: A method and system for smoothing a frame to remove jagged edges are presented. The method and system generates a smoothing filter with consolidated pixels. Edges within the smoothing filter are analyzed to select an edge direction used for smoothing. A smoothed pixel is generated based on a normalized linear combination of a first edge end pixel, a second edge end pixel and center entry of the smoothing filter. Subtle structure checking can be used to determine whether to use the smoothed pixel in place of the current pixel.

Abstract: A method and program product for real-time correction of non-functioning pixels in digital radiography, where the method comprises: receiving a list of non-functioning pixels; determining which neighboring functioning pixels are needed to correct the non-functioning pixels; organizing those neighboring functioning pixels and corresponding non-functioning pixels into a plurality of groups by a number of pixels used to perform correction; and performing correction of data from non-functioning pixels within one of the plurality of groups and subsequently performing correction of data from non-functioning pixels within another one of the plurality of groups.

Abstract: An image processing apparatus (100) comprises: receiving means for receiving a video signal representing input images; a film-detector unit (108) for detecting whether the input images have been captured by a film camera or by a video camera; and a sharpness enhancement unit (106) for calculating sharpness enhanced images on basis of the input images. The sharpness enhancement unit (106) is controlled by the film-detector unit (108), whereby the sharpness enhancement is larger if the film-detector unit (108) has detected that the input images have been captured by the film camera than if the film-detector unit (108) has detected that the input images have been captured by the video camera.

Abstract: An electronic correction system and method for correcting optical anomalies, namely distortions, color non-convergence (excluding axial chromatic aberration) and luminance (or chrominance) non-uniformity. Each effect is modeled as a transformation in either spatial (positional) space or color space. Representing the effects as transformations of digital pixel data, allows the different anomalies to be resolved within a common framework, namely that of image ‘warping’. The anomaly, having been expressed as a pixel transformation, is then eliminated by electronically applying the inverse transformation. This process is equivalent to digitally manipulating or warping the image in position and/or color space and accordingly this can be achieved using commercially known warping circuits. In addition, the transformation can also contain a component to additionally perform any application specific image warping (e.g. scaling and geometric transformations).

Abstract: An image sequence includes consecutive video images each exhibiting at least one image region having a number of pixels, where each pixel includes at least one intensity value. For each image a motion measure value is determined indicative of temporal change of a video content of the image region and varying the intensity values of the pixels of the image region relative to the associated intensity values from video image to video image, a measure for the variation of the intensity values being dependent on the motion measure value determined and the change in the intensity values relative to the associated intensity values being greater the larger the motion represented by the motion measure value.

Abstract: Anti-aliasing characters for improved display on an interlaced television monitor is described. In one implementation, an expanded character is generated by increasing a character's original dimensions. The expanded character includes multiple sub-blocks and each sub-block includes multiple pixels. The pixels of each sub-block are mapped to a single destination color that is based on specific numbers of foreground pixels in the sub-block and a particular number of gray levels used to represent the character. Subsequent to this mapping, the expanded character is scaled back to its original size.

Abstract: This invention provides an image processing apparatus which can effectively remove conspicuous noise contained in image data, while suppressing deterioration of image information. Image data containing noise is input from an input terminal (100). Based on the output condition upon outputting image data after noise is removed, a parameter determination module (103) determines predetermined parameters used in a noise removal process. An example of the output condition is information associated with a resolution upon outputting image data. An individual noise removal module (104) removes noise contained in the image data using the parameters, and image data after the noise has been removed is output from an output terminal (105).

Abstract: An apparatus to improve an image sharpness and a method thereof which can improve the image sharpness of an image through an adaptive operation of the apparatus according to resolutions of input/output video signals and an emphasis of edge portions of the image.

Abstract: A dodging process which brightens a dark portion sometimes makes noise components contained in an image obtained by an image sensor conspicuous. A gray image generator extracts a luminance component Y of an image, an unsharp image generator generates an unsharp image L on the basis of the luminance component Y, a correction coefficient calculator calculates a correction coefficient g for correcting a brightness difference of the image in accordance with the unsharp image L, a corrector performs a dodging process in accordance with the correction coefficient g, and a noise eliminator eliminates noise of the image in accordance with the correction coefficient g.

Abstract: Image processing methods and systems for noise reduction and edge enhancement. A variation detector is provided to evaluate measures of edge existence in a plurality of predetermined directions within pixels of a video signal, and determine a control signal according to a level of variation on the measures of edge existence. A noise reduction circuit and edge enhancement circuit filter and edge enhance the video signal, respectively, according to the control signal.

Abstract: Provided is a method of removing noise from digital moving picture data reducing the number of frames used in a temporal filtering operation and able to detect motion between frames easily. The method comprises a method of spatial filtering, a method of temporal filtering, and a method of performing the spatial filtering and the temporal filtering sequentially. The spatial filtering method applies a spatial filtering in a YCbCr color space, preserving a contour/edge in the image in the spatial domain, and generating a weight that is adaptive to the noise for discriminating the contour/edge in the temporal filtering operation.

Abstract: A video signal improving circuit comprises an input section which receives a video signal; a delay circuit which delays the video signal to generate a plurality of delayed video signals which have delayed times different from one another; an improving signal producing circuit which generates, as an improving signal, an improving amount for performing a transient improvement on the video signal based upon an original video signal before delay and the plurality of delayed video signals; a band-limiting filter which performs a frequency band limitation on the improving signal; a timing correcting circuit which causes timings of any one of the plurality of delayed video signals and the improving signal which has passed through the band-limiting filter to match with each other; and an adder which adds the improving signal which has passed through the band-limiting filter to the delayed video signal which has passed through the timing correcting circuit.

Abstract: An image processing apparatus determines whether or not a target pixel TP which is the object of the smoothing process is an edge-forming pixel based on the edge level (gradient g). If the pixel is determined to be an edge-forming pixel, the smoothing process employs an elliptical median filter instead of a moving average filter. The median filter MF has an elliptical reference area RA that is tilted (angled) to match the orientation of the edge Eg (edge angle), allowing the smoothing process to be carried out without compromising the edge components. The angle of the edge Eg is thus determined in the smoothing process, a median filter MF with an angle matching the determined edge angle is selected, and the selected median filter MF is used to carry out the smoothing process on target pixels TP which are edge-forming pixels.

Abstract: A method is provided for selecting a filter for interpolating a target pixel for reducing noise in an image. The method comprises the following steps. A plurality of pixels along a predetermined contour is compared with a plurality of predefined patterns. The patterns represent visually significant patterns possible along said contour. A filter is selected from a predefined set of filters in accordance with the results of the comparison.

Abstract: In a video signal processing method of processing a luminance signal of a video signal generated by causing a CCD to receive light transmitted through color filters, a control signal yf1 is generated by calculating Cy/Y using a complementary color signal Cy and a luminance signal Y, and coring correction is performed to the luminance signal by using the control signal yf1. The characteristic difference between the color filters is suppressed, and, as a result, flickers are suppressed from being generated.

Abstract: A superior Color Transient Improvement technique is adaptive to the local image features, so that more natural color edge transition improvement can be accomplished. A gain control function is provided that depends on the local image feature so that different regions of the image can be treated differently. Further, a correction signal is controlled in such a way (by the local image feature) that neither undershoot nor overshoot occurs, eliminating the need for post-processing for undershoot/overshoot removal.

Abstract: In order to render information contained in images more detectable in the presence of noise, the present invention discloses a system and method to binarize the images in the presence of noise. The method of this invention comprises the steps of applying a dynamic range reducing filter to the digitized image values, obtaining a range reduced image; applying an edge detecting filter to the range reduced image, obtaining a filtered image; and then, adaptively binarizing the digitized image utilizing the corresponding filtered image to obtain an adaptive threshold.

Abstract: To enable a satisfactory suppression of overemphasized component after converting the number of scanning lines of video signal, when the video signal is converted in the number of scanning lines and a high-frequency component at least in a vertical direction of the converted video signal is emphasized, signals delayed by a plurality of stages of time equal to or more than a time required for converting the number of scanning lines are obtained by a delay circuit 18, and an appropriate delay signal is selected from among the plurality of delay signals by a selection circuit 19. The selected delay signal is compared with the emphasized video signal in emphasized-component detector circuits 16a, 16b and the overemphasized component is detected. Processing to suppress the emphasis is performed by suppressor circuits 13a, 13b with respect to a portion where the overemphasized signal component is detected.

Abstract: A batch processing method for enhancing an appearance of a face located in a digital image, where the image is one of a large number of images that are being processed through a batch process, comprises the steps of: (a) providing a script file that identifies one or more original digital images that have been selected for enhancement, wherein the script file includes an instruction for the location of each original digital image; (b) using the instructions in the script file, acquiring an original digital image containing one or more faces; (c) detecting a location of facial feature points in the one or more faces, said facial feature points including points identifying salient features including one or more of skin, eyes, eyebrows, nose, mouth, and hair; (d) using the location of the facial feature points to segment the face into different regions, said different regions including one or more of skin, eyes, eyebrows, nose, mouth, neck and hair regions; (e) determining one or more facially relevant character

Abstract: A batch processing method for enhancing an appearance of a face located in a digital image, where the image is one of a large number of images that are being processed through a batch process, comprises the steps of: (a) providing a script file that identifies one or more original digital images that have been selected for enhancement, wherein the script file includes an instruction for the location of each original digital image; (b) using the instructions in the script file, acquiring an original digital image containing one or more faces; (c) detecting a location of facial feature points in the one or more faces, said facial feature points including points identifying salient features including one or more of skin, eyes, eyebrows, nose, mouth, and hair; (d) using the location of the facial feature points to segment the face into different regions, said different regions including one or more of skin, eyes, eyebrows, nose, mouth, neck and hair regions; (e) determining one or more facially relevant character