Abstract: A system for edge enhancement includes an input unit to receive an input signal Yin, a vertical enhancement unit to perform a vertical enhancement of an edge of the input signal Yin to generate an output YEV, and a horizontal enhancement unit to perform a horizontal enhancement of the edge of the input signal Yin to generate an output YEH. The system also includes a local gradient analysis unit to generate a local gradient direction GradDir and a local gradient magnitude GradMag based at least partly upon the input signal Yin, and a mixer to generate an output Yout by mixing the output YEV with the output YEH using the local gradient direction GradDir. The system further includes an output unit to output the output Yout.

Abstract: A multiband signal generator generates multiband signals from 21 lines of input data by using a subset of N lines with each line delayed from 1 line to N lines respectively. M line buffers delay the multiband signals such that each line is delayed from 1 line to M lines respectively. An analyzer detects correlations between video data by selecting regions with a maximum size M×M in the multiband signals, and analyzes characteristics of the video data. A multiband signal generator generates multiband signals with cutoff frequencies based on an analysis result from the analyzer, by using the data from 1-line through N-line delayed multiband signal. An amplitude adjuster and synthesizer unit adjusts and synthesizes amplitudes of the multiband signals.

Abstract: In one system embodiment, an overlapped block processing module configured to provide three-dimensional (3D) denoising of plural frames corresponding to a raw video sequence; and a frame alignment module configured to represent the raw video sequence with motion compensated frames corresponding to the raw video sequence, the motion compensated frames consisting of the plural frames and fewer in quantity than the quantity of frames of the raw video sequence, the plural frames based on prior temporally matched frames corresponding to the raw video sequence.

Abstract: An auto-focus image system includes a focus signal generator and a pixel array coupled thereto that captures an image that includes a plurality of edges. The generator computes a focus signal from a plurality of edge-sharpness measures, each measured from and contributed by a different edge as a quantity with a unit that is a power of a unit of length. The generator reduces a relative weight of the contribution of an edge depending on a shape of a normalized gradient profile of the edge as identified by an n-tuple of values of n different shape measures (n?2). Each shape measure varies across normalized gradient profiles of different shapes. One shape measure may be the edge-sharpness measure itself. The weight may be zero if the n-tuple falls outside a predetermined region. At least one symmetrical shape that has perfect reflection symmetry receives reduced weight.

Abstract: Systems and methods may provide for conducting a real-time perceptual quality analysis of a video, wherein the perceptual quality analysis includes at least one of a noise measurement, a contrast measurement and a sharpness measurement. One or more strength parameters of one or more post-processing modules in a video processing pipe may be set based on the perceptual quality analysis resulting in overall video processing that adapts to the changing perceptual quality of the input. In one example, the strength parameters include at least one of a contrast parameter and a de-noising parameter. The invention results in visually enhanced video at the output of the post-processing module.

Abstract: An image sharpness device and a method for the same are disclosed. The image sharpness device includes a DC removal unit, at least one filter, at least one noise estimation unit, at least one soft threshold processing unit, and a summing unit. The DC removal unit receives a luminance signal of a field of a frame and removes a DC component of the luminance signal. The filter passes a component of an output of the DC removal unit within a predetermined frequency band. The noise estimation unit estimates a noise value of the field. The soft threshold processing unit forms a sharpness signal according to the noise value. The summing unit sums the luminance signal and the sharpness signal to output a resultant luminance signal. The present invention is capable of avoiding the problem that a noise in the luminance signal is enhanced.

Abstract: A multiband signal generator generates multiband signals from 21 lines of input data by using a subset of N lines with each line delayed from 1 line to N lines respectively. M line buffers delay the multiband signals such that each line is delayed from 1 line to M lines respectively. An analyzer detects correlations between video data by selecting regions with a maximum size M×M in the multiband signals, and analyzes characteristics of the video data. A multiband signal generator generates multiband signals with cutoff frequencies based on an analysis result from the analyzer, by using the data from 1-line through N-line delayed multiband signal. An amplitude adjuster and synthesizer unit adjusts and synthesizes amplitudes of the multiband signals.

Abstract: Aspects of the present invention are related to systems and methods for image enhancement, wherein an input image may be separated into two images: a first image comprising image content, from the input image, which may be sharpened; and a second image comprising image content, from the input image, which may be attenuated. One aspect of the present invention relates to determining a noise estimate associated with the input image and using the noise estimate to control the separation of the input image into the two images. Another aspect of the present invention relates to controlling the image separation based on the level of sharpening being applied to the first image.

Abstract: An image processing apparatus for processing pixels is disclosed. The image processing apparatus comprises one or more functional blocks adapted to perform a corresponding functional task on the pixels. Further, the image processing apparatus includes one or more line-delay elements for delaying a horizontal scan line of the pixels. A desired processing task, which includes at least one functional task, is performed by configuring each functional block based on an actual number of the line-delay elements used for performing the desired processing task. Each functional block used for performing the desired processing task receives a group of pixels for processing from one or more horizontal scan lines such that the group overlaps another group of pixels for processing from one or more horizontal scan lines by another functional block.

Abstract: An image processing circuit and a method thereof are provided herein. The image processing circuit has a first scaling circuit, a plurality of line buffers, a first sharpness circuit, a second scaling circuit, and a second sharpness circuit. The first scaling circuit enlarges an input image along a first direction to generate a first enlarged image. The line buffers temporarily store the pixel values of a plurality of pixel rows of the first enlarged image. The first sharpness circuit vertically sharpens the first enlarged image to generate a first sharpened image. The second scaling circuit enlarges the first sharpened image along a second direction to generate a second enlarged image. The second sharpness circuit horizontally sharpens the second enlarged image to generate a second sharpened image. Accordingly, it is possible to use the line buffers having shorter data lengths to perform the vertical sharpening.

Abstract: According to one embodiment, an image processing apparatus includes a decoder, a first sharpening module, and a second sharpening module. The decoder decodes an encoded image to obtain a decoded image. The first sharpening module performs first sharpening on the decoded image. The second sharpening module performs second sharpening on the decoded image subjected to the first sharpening. The second sharpening requires a different processing time from a processing time required for the first sharpening. The first sharpening module includes a first noise remover that removes noise generated by encoding from the decoded image.

Abstract: Apparatus and methods of motion detection for mosquito noise reduction in video sequences are provided. In one aspect, a method of motion detection in a sequence of digital images classifies a pixel of a plurality of pixels of a current image frame represented by a digital video input signal as a motion or non-motion pixel. A motion value for the pixel is calculated based on the classification of the pixel. The motion value is mapped to a coefficient of a temporal filter based on a control curve. A digital video output signal is generated based on the coefficient.

Abstract: An apparatus for improving image sharpness includes a pixel detector that labels each of pixels in an image as one of an edge/texture type and a non-edge/texture type, a pixel type determiner that classifies each of the pixels that are labeled as the edge/texture type as one of a border point type pixel, a transition point type pixel, and a peak point type pixel, and a filter. The filter includes a shrinking/expanding filter and a high boost filter, the shrinking/expanding filter filtering the border point type pixels, and the high boost filter subsequently filtering the peak point type pixels and then filtering the transition point type pixels.

Abstract: An image processing method includes: receiving a plurality of image frames; receiving a definition signal; and performing an noise reduction operation upon the image frames according to the definition signal, where the definition signal is utilized for representing a sharpness level of the image frames, and a degree of the noise reduction operation the image frames being processed is varied with the sharpness level of the image frames.

Abstract: A method for sharpness enhancing digital image data (ID), including: generating an intermediate processed image (IPI), in which uniform sections of the digital image data (ID) are cleaned from noise and in which at least one of a group consisting of contours, edges, wedges, structures and textures are detected, wherein the uniform section each fulfil a predefined uniformity criterion, which is descriptive for at least one of a group consisting of uniformity, flatness, structure, and noise content; deriving a blend value b for each pixel (Pbjkab) from the intermediate processed image (IPI) with b ranging between 0 corresponding to flatness and 1 corresponding to texture; two-dimensional sharpness enhancing the digital image data (ID) to generate processed digital image data (PID); and generating output data (outD) by pixelwise blending the digital image data with the processed digital image data.

Abstract: A video processor includes a spatio-temporal noise reduction controller to determine current and previous image edge slopes and adaptively control a spatio-temporal noise reduction processor to blend current and previous images dependent on the current and previous image edge slope values.

Abstract: An image processing device includes: an estimated plane calculation portion calculating, for inputted image data, estimated planes defined by luminance values in blocks each containing a predetermined number of pixels including a reference pixel; an optimal estimated plane selection portion selecting an optimal estimated plane having a least summation of errors between luminance values of respective pixels in a block and an estimated plane among the estimated planes; a weighting factor calculation portion calculating a weighting factor for the reference pixel base on luminance values of the reference pixel and in the optimal estimated plane; and a weighted smoothing portion computing a sum of products of relative luminance differences between the luminance values of the respective pixels in the block and in the optimal estimated plane and the weighting factor for the reference pixel and adding a luminance value in the optimal estimated plane at a reference pixel position to a result of computation.

Abstract: A Gaussian filter 2 having a first cutoff frequency extracts a low frequency component signal of a video signal. A subtracter 3 extracts a high frequency component signal by subtracting the low frequency component signal from the video signal. A low pass filter 5 having a second cutoff frequency higher than the first cutoff frequency extracts a lower high frequency component signal, which is a low-frequency-side signal of the high frequency component signal. A multiplier 6 generates a corrected component signal by multiplying the lower high frequency component signal by a predetermined gain G1. An adder 7 adds the corrected component signal to the video signal.

Abstract: Even when an enlarged image is deteriorated due to a block noise or color mixture, the contour in the enlarged image is sharpened and a quality of the image is improved. A contour extracting unit 103 determines a pixel indicating the contour in an interpolation image, using brightness gradient strength and a brightness gradient direction.

Abstract: A system and method for enhancing the detail edges and transitions in an input video signal. This enhancement may be accomplished by enhancing small detail edges before up-scaling and enhancing large amplitude transitions after up-scaling. For example, detail edge enhancement (detail EE) may be used to enhance the fine details of an input video signal. An edge map may be used to prevent enhancing the large edges and accompanying mosquito noise with the detail enhancement. Noise may additionally be removed from the signal. After the fine details are enhanced, the signal may be up-scaled. Luminance transition improvement (LTI) or chrominance transition improvement (CTI) may be used to enhance the large transitions of the input video signal post scaler.

Abstract: An image processing device, method, an image display device and method which can obtain a high-definition display image by properly controlling processing of reducing the blur of a displayed image caused by the time integration effect of an image sensor. The image display device comprises a motion detection part (1) which detects the moving amount of an input image signal, and an edge emphasis part (2) which subjects the input image signal to edge emphasis processing, and the image display device increases an edge emphasis degree of edge emphasis processing to an area where the moving amount of the input image signal is large.

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: An imaging device of the present invention includes an image capturing unit, a noise obtaining unit, a fixed noise calculating unit, and a noise eliminating unit. The image capturing unit generates image data by photoelectrically converting, pixel by pixel, a subject image formed on an available pixel area of a light-receiving surface. The noise obtaining unit reads a noise output from a partial area of the available pixel area. The fixed noise calculating unit calculates an estimation of fixed pattern noise of the available pixel area based on the noise output read from the partial area. The noise eliminating unit subtracts the fixed pattern noise from the image data.

Abstract: A video processing device includes an input to receive pixel values for a set of pixels comprising a pixel window substantially centered around a select pixel that initially has a first pixel value. The video processing device further includes a first filter unit to determine a horizontal transient improvement value based on non-linear filtering of the pixel values in a horizontal direction, a second filter unit to determine a vertical transient improvement value based on non-linear filtering of the pixel values in a vertical direction, a third filter unit to determine a first diagonal transient improvement value based on non-linear filtering of the pixel values in a first diagonal direction, and a fourth filter unit to determine a second diagonal transient improvement value based on non-linear filtering of the pixel values in a second diagonal direction that is perpendicular to the first diagonal direction.

Abstract: An image processing device and an image processing method of the invention generate multiple images having different edge preservation performances based on an original image, and synthesize the multiple images based on edge information. In the synthesis, the generated images are synthesized in such a manner that an image of an edge portion in the generated image having a low edge preservation performance is replaced by the generated image having a high edge preservation performance.

Abstract: In a method, apparatus and integrated circuit for improving image sharpness, the method includes the following steps: (a) labeling each of pixels in an image as one of an edge/texture type and a non-edge/texture type; (b) classifying each of the pixels that are labeled as the edge/texture type into one of a border point type, a transition point type, and a peak point type; and (c) using a shrinking/expanding filter to filter the pixels of the border point type, and subsequently using a high boost filter to first filter the pixels of the peak point type and then filter the pixels of the transition point type to sharpen the image.

Abstract: A method for contrast enhancement for digital images, including filtering an original image having original color values, to generate a filtered image, receiving parameters for a response curve, the response curve being a function of color value that is user-adjustable, deriving local multipliers by applying the response curve to the filtered image, multiplying the original color values by the local multipliers, thereby generating a contrast-enhanced image from the original image. A system and a computer-readable storage medium are also described.

Abstract: Systems, methods, and apparatus, including computer program products, are provided for changing the look of an image. In some implementations a computer-implemented method is provided. The method includes decomposing a first image using a first plurality of wavelet transforms, each first wavelet transform creating a first transformation resolution, each first transformation resolution having respective first data, and decomposing a second image using a second plurality of wavelet transforms, each second wavelet transform creating a second transformation resolution, each second transformation resolution having respective second data. The method also includes determining a first measure of texture for each first transformation resolution's respective data, applying each first transformation resolution's first measure of texture to each corresponding second transformation resolution's data, and recomposing the second image based on the modified second transformation resolutions.

Abstract: A method for estimating the white Gaussian noise level that corrupts a digital image by discriminating homogeneous blocks from blocks containing a textured area and skipping these last blocks when evaluating the noise standard deviation.

Abstract: Embodiments of the present invention comprise systems and methods for image noise characterization, parameterization, removal, reconstruction and/or re-combination with a denoised image.

Abstract: The present invention relates to a video picture display method that aims to reduce the effects of blurring and multiple contours when the picture display frequency is doubled. According to the invention, for each source video picture, a video level dissymmetry is created between the two pictures from the source video picture after doubling the frequency in the areas in motion of the source video picture.

Abstract: A transition enhancement method and system for use with television or computer displays submits single transitions occurring in an input signal to a first transition enhancement process; and submits double transitions of opposite signs occurring in the input signal to a second transition enhancement process that is different from the first transition enhancement process.

Abstract: A data processing apparatus that appropriately adjusts the image quality of an image. At a plurality of user terminals, image data transmitted from a broadcasting station is processed based on parameters input by users, and user information including the image data and the parameters is provided to a management server. The management server calculates noise amounts of the respective sets of image data included in the user information provided from the plurality of user terminals, calculates an average value of parameters input by users for each noise amount, and associates the average value with the noise amount. Furthermore, the management server provides a user terminal with server information including a parameter associated with a noise amount of image data from a user terminal. The user terminal processes the image data based on the parameter included in the server information from the management server.

Abstract: A device for removing noise by using an adjustable threshold. The device for removing noise in accordance with an embodiment of the present invention determines a difference value between a maximum value and a minimum value of elements of inputted image data, determines a method of removing noise of the image data in accordance with the difference value, and removes noise in accordance with the method. With the present invention, improved picture quality can be achieved because noise can be removed as desired by the user.

Abstract: An exemplary signal interference control system is disclosed that utilizes a computer system, such as programmable logic circuits or computer controlled logic gates, to generate blanking or control signals for various types of radio frequency receiver and transmitter combinations. Control signals are generated based on signal characteristic information stored in a memory including a delay following receipt of a pre-trigger signal from a radio frequency transmitter and a pulse width of control signal(s) generated for specified receivers, frequencies or systems. In one embodiment, information can be retrieved from a memory and used to generate an interference control signal. One or more control signals can be routed to a related or associated receiver to reduce or eliminate interference effects.

Abstract: Aspects of the present invention are related to systems and methods for image enhancement, wherein an input image may be separated into two images: a first image comprising image content, from the input image, which may be sharpened; and a second image comprising image content, from the input image, which may be attenuated. One aspect of the present invention relates to determining a noise estimate associated with the input image and using the noise estimate to control the separation of the input image into the two images. Another aspect of the present invention relates to controlling the image separation based on the level of sharpening being applied to the first image.

Abstract: Provided is a video signal processing method of measuring a noise level of an input video signal, the method including the steps of: setting a plurality of areas in the input video signal and extracting a characteristic amount which is an index of the noise level of the input video signal for each area; detecting characteristic amounts suitable to a measurement of the noise level from among the characteristic amounts of the plurality of areas; and creating a histogram by using the detected characteristic amounts suitable to the measurement of the noise level and detecting the noise level by analyzing the histogram.

Abstract: A system and method for reducing the noise induced in a particular section or level of a signal bandwidth. The section is isolated from the rest of the signal data, by rescaling this data to produce a buffer section adjacent the section with little or no data in it. The signal is then transmitted to the output device where all data is the buffer section is considered to be the result of noise, and is mapped back to the predetermined level. The signal data is inversely rescaled to move data back into the buffer section. In this way, more of the data that was input at the predetermined level, will also be at the predetermined level afterwards, thereby correcting noise induced in that level by noise inducing transmission techniques such as JPEG compression.

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: Flicker occurs in a flicker-noticeable area consisting of pixels with no pixel value variations. An image processing device (100) includes a variance calculation unit (101) that obtains a variance of an area consisting of a target pixel and neighboring pixels included in a first frame, and changes, according to the variance, the rate at which an error generated at the target pixel through tone level restriction is distributed within the frame and between frames. The image processing device (100) includes an error diffusion unit (113) that distributes the error generated at the target pixel to the neighboring pixels included in the first frame based on an intra-frame error diffusion rate and an intra-frame error distribution weight, and distributes the error generated at the target pixel to a target pixel and neighboring pixels included in the second frame based on an inter-frame error diffusion rate and an inter-frame error distribution weight.

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: An apparatus for removing a noise of a video signal is discussed, 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.

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: 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: A digital image processing method is disclosed, which comprises the steps of: (A) capturing a digital image; (B) selecting at least a target pixel within the digital image according to a predetermined rule; (C) performing a first filtering on a graphic region including the target pixel and its neighboring pixels within the digital image, to generate a set of first filtered values; and (D) performing a second filtering on the set of first filtered values to generate a set of second filtered values, and performing a digital image adjustment process on the digital image according to the set of second filtered values.

Abstract: A method for digitally filtering a video signal comprises: converting the video signal into a plurality of sampled values; determining whether distribution of at least one portion of the sampled values belongs to one of a plurality of specific types according to the sampled values; and generating a plurality of output values according to a correction operation corresponding to the one of the specific types.

Abstract: A video noise reducer divides a signal into spatial frequency bands and derives both recursively and non-recursively filtered signals for each band. Both signals are processed non-linearly. These signals are combined in ways that vary between the bands to provide a noise signal and a detail signal. A clean video signal with all noise removed is used in the recursive loop. The output signal includes detail enhancement and may have a subjectively pleasant amount of noise added back.

Abstract: An image processing method has an edge intensity value calculating section (4) for calculating an edge intensity value in a neighborhood of a pixel of interest from feature values of micro regions calculated by a feature value calculating section (3); an edge intensity value correcting section (5) for correcting the edge intensity value calculated by the edge intensity value calculating section (4) in accordance with an edge intensity correction curve; and a filter value calculating section (6) for calculating a low-pass filter value of the pixel of interest from image signal values of neighboring pixels having the same color component as the pixel of interest. It corrects the image signal value of the pixel of interest by carrying out weighted addition of the image signal value of the pixel of interest and the low-pass filter value using the edge intensity values before and after the correction.

Abstract: A video processing device includes an input to receive pixel values for a set of pixels comprising a pixel window substantially centered around a select pixel that initially has a first pixel value. The video processing device further includes a first filter unit to determine a horizontal transient improvement value based on non-linear filtering of the pixel values in a horizontal direction, a second filter unit to determine a vertical transient improvement value based on non-linear filtering of the pixel values in a vertical direction, a third filter unit to determine a first diagonal transient improvement value based on non-linear filtering of the pixel values in a first diagonal direction, and a fourth filter unit to determine a second diagonal transient improvement value based on non-linear filtering of the pixel values in a second diagonal direction that is perpendicular to the first diagonal direction.

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.