Abstract: The present application provides an image processing method and an image processing system. The image processing method includes: obtaining a first image matrix; generating a first classified image matrix, wherein the first classified image matrix Includes a plurality of parts corresponding to a plurality of classification; obtaining a plurality of weightings, for a first image process, corresponding to the plurality of parts of the first classified image matrix, and generating a first weighting matrix accordingly; and performing the first image process upon the first image matrix according to the first weighting matrix to generate a first processed image matrix.

Abstract: The present application provides an image processing method and an image processing system. The image processing method includes: obtaining a first image matrix; generating a first classified image matrix, wherein the first classified image matrix Includes a plurality of parts corresponding to a plurality of classification; obtaining a plurality of weightings, for a first image process, corresponding to the plurality of parts of the first classified image matrix, and generating a first weighting matrix accordingly; and performing the first image process upon the first image matrix according to the first weighting matrix to generate a first processed image matrix.

Abstract: A scaling device for receiving and scaling a digital image signal includes a scaling module and a data quantity control logic. The scaling module scales the digital image signal and then outputs a scaled output signal according to a scaling ratio. The data quantity control logic controls output quantity of the scaled output signal according to a scaling ratio. Thus, when the data quantity outputted from the scaling module is controlled within the data quantity that may be processed by the post stage of the scaling module per unit time, the data quantities that may be processed per unit time in the post stage processing devices of the scaling module approximate a constant value such that the post stage processing speed of the scaling module may be increased.

Abstract: An image noise detection method is disclosed. The image noise detection method includes the following steps: obtaining a spatial information of an image; obtaining a temporal information of the image; and determining a spatial noise or a temporal noise of the image according to both the spatial information, and the temporal information.

Abstract: Disclosed is a method for reducing temporal noise, comprising: performing motion detection on frames of a video data stream; calculating a pixel difference between pixels of frames in the video data stream to generate at least a pixel difference value; determining a set of weighting value for temporal filtering according to a result of the motion detection and a result of the pixel difference value calculation; and performing temporal filtering on frames in the video data stream according to the weighting values.

Abstract: The present invention provides a noise reduction apparatus and method thereof. The noise reduction apparatus includes a first detecting logic, a second detecting logic, a first noise filtering logic, a second noise filtering logic, and an output logic. The first detecting logic detects if a video signal has a first noise characteristic. The second detecting logic detects if the video signal has a second noise characteristic. The first noise filtering logic performs a first noise filtering process upon the video signal to generate a first filtered signal. The second noise filtering logic performs a second noise filtering process upon the video signal to generate a second filtered signal. The output logic receives the first filtered signal and the second filtered signal, and references detection results provided by the first detecting logic and the second detecting logic when generating an output signal.

Abstract: The present invention provides an image processing method for processing an image. The method includes: detecting at least an edge in the image; determining at least a pixel window including the edge; detecting whether a mosquito noise exists in the pixel window; and filtering out the detected mosquito noise in the pixel window.

Abstract: The present invention provides an image processing method for processing an image. The method includes: detecting at least an edge in the image; selecting at least a first pixel and at least a second pixel according to the edge; deciding whether the edge is a block effect by determining whether a pixel difference between the first pixel and the second pixel locates in a predetermined range; and filtering out the detected block effect.

Abstract: The present invention provides a device and a method for reducing impulse noise. The device includes a signal intensity detector, an intensity difference calculator, and a filtering circuit. The signal intensity detector receives an image signal and determines a first pixel having an extreme intensity, and a second pixel having a second extreme intensity of a window of the image frame corresponding to the image signal. The intensity difference calculator determines the intensity difference between the first pixel and the second pixel. The filtering circuit receives the image signal and optionally filters the image signal for reducing the impulse noise according to the intensity difference between the first pixel and the second pixel.

Abstract: An image processing method is disclosed for processing a first and a second image area of a video frame or a video field. The image processing method includes performing a first operation on the first image area wherein the first operation corresponds to a first criterion, performing a first image processing procedure on the first image area according to the result of the first operation so as to update the first image area, performing a second operation on the second image area wherein the second operation corresponds to a second criterion, and performing a second image processing procedure on the second image area according to the result of the second operation so as to update the second image area.

Abstract: An image noise detection method is disclosed. The image noise detection method includes the following steps: obtaining a spatial information of an image; obtaining a temporal information of the image; and determining a spatial noise or a temporal noise of the image according to both the spatial information, and the temporal information.

Abstract: The present invention provides an image processing method for processing an image. The method includes: detecting at least an edge in the image; selecting at least a first pixel and at least a second pixel according to the edge; deciding whether the edge is a block effect by determining whether a pixel difference between the first pixel and the second pixel locates in a predetermined range; and filtering out the detected block effect.

Abstract: Methods and apparatuses for motion detection are disclosed. One proposed method includes: detecting at least a field to generate a plurality of statistical values; determining at least one threshold value according to the plurality of statistical values; and performing motion detection on pixel positions of a subsequent field according to the determined threshold value.

Abstract: A chip design-in aid system, wherein the chip has a plurality of chip controlling registers for storing at least one parameter. The system includes a user interfance for inputting user setting data, the user setting data corresponding to at least one function of the chip; a data processing unit for processing the user setting data; and a parameter adjusting unit for receiving the processed user setting data from the data processing unit, and transmitting the processed user setting data to the chip, so as to adjust the parameter stored in the chip controlling registers, whereby the chip is set to perform the function corresponding to the user setting data.

Abstract: The present invention provides an image processing method for processing an image. The method includes: detecting at least an edge in the image; determining at least a pixel window including the edge; detecting whether a mosquito noise exists in the pixel window; and filtering out the detected mosquito noise in the pixel window.

Abstract: An error diffusion method applied to halftone processing for image data. The image data comprise a plurality of pixels. The method comprising the steps of dividing the image data into a plurality of image blocks; selecting one of the pixels belonging to each of the image blocks as a target pixel, wherein the target pixel is located on the boundary of the corresponding image block; assigning a predicted error to the target pixel; and executing the error diffusion method on the rest of the pixels of the image blocks according to the predicted error of the target pixels of the image blocks. When the error diffusion is performed, target pixels are found in the image block and then predicted errors are assigned to the target pixels in order to calculate their output values. The target pixels are located at boundaries of the image blocks, and the predicted errors may be 0 or the transversal or longitudinal errors outputted from the pixels above the target pixels.

Abstract: The present invention provides a noise reduction apparatus and method thereof. The noise reduction apparatus includes a first detecting logic, a second detecting logic, a first noise filtering logic, a second noise filtering logic, and an output logic. The first detecting logic detects if a video signal has a first noise characteristic. The second detecting logic detects if the video signal has a second noise characteristic. The first noise filtering logic performs a first noise filtering process upon the video signal to generate a first filtered signal. The second noise filtering logic performs a second noise filtering process upon the video signal to generate a second filtered signal. The output logic receives the first filtered signal and the second filtered signal, and references detection results provided by the first detecting logic and the second detecting logic when generating an output signal.

Abstract: The invention discloses a pattern detecting apparatus. The pattern detecting apparatus includes a comparing module and a determining module. The comparing module compares a plurality of pixels of a pixel window in an image. The determining module determines whether the pixel window matches any predetermined pattern of a plurality of predetermined patterns according to results of comparing the pixels by the comparing module.

Abstract: Disclosed is a method for reducing temporal noise, comprising: performing motion detection on frames of a video data stream; calculating a pixel difference between pixels of frames in the video data stream to generate at least a pixel difference value; determining a set of weighting value for temporal filtering according to a result of the motion detection and a result of the pixel difference value calculation; and performing temporal filtering on frames in the video data stream according to the weighting values.

Abstract: The present invention provides a device and a method for reducing impulse noise. The device includes a signal intensity detector, an intensity difference calculator, and a filtering circuit. The signal intensity detector receives an image signal and determines a first pixel having an extreme intensity, and a second pixel having a second extreme intensity of a window of the image frame corresponding to the image signal. The intensity difference calculator determines the intensity difference between the first pixel and the second pixel. The filtering circuit receives the image signal and optionally filters the image signal for reducing the impulse noise according to the intensity difference between the first pixel and the second pixel.