Video image denoising processing method and apparatus

Abstract

The invention provides a video image denoising processing method and an apparatus. The method comprises the following steps of using a preset denoising algorithm to carry out pre-denoising processing on a first video image to be processed so as to acquire a reference video image; determining a reference image block group possessing a similarity with an image block corresponding to an image block to be processed in the reference video image, mapping a coordinate position relation of the reference image block group into the first video image from the reference video image so as to acquire an image block group which is similar with the image block to be processed; and carrying out low rank approximation processing on the image block group in the first video image so as to acquire a second denoising video image. The reference video image after pre-denoising processing is taken as a basis of similarity measurement so that a similarity measurement result is accurate and quality of the final second denoising video image can be guaranteed. Based on a low rank approximation mode, the final second denoising video image is acquired so that a denoising effect of the video image is increased.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a video image denoising processing method and device. Background technique [0002] In real life, because video can convey information about objects intuitively, vividly and vividly, it occupies an extremely important position in multimedia systems. However, video images are often disturbed by various noises during acquisition, transmission, reception, and processing, such as photon and dark shot noise, amplifier noise, readout noise, and quantization noise. All kinds of noises degrade the quality of video images and negatively affect the subsequent processing quality of video images to a large extent. In order to improve the effectiveness and reliability of subsequent processing of video images, it is necessary to use video image denoising methods to eliminate various noises in video images. [0003] Various existing video image denoising methods can be di...

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Problems solved by technology

[0004] The above non-local mean method is based on the structural self-similarity of the video image in the time-space domain, and uses the weighted average of the gray value of the current pixel and all pixels in the video image that are similar to the current pixel structure to construct a noise-reduced video image. , but in this way, various noises in the video image will cause errors in the similarity measure of the video image blocks, thus reducing the effect of noise elimination; It is decomposed into coefficients of different frequencies, and the high-frequency noise coefficient is truncated by selecting an appropriate threshold, and then the denoised video image is reconstructed by wavelet inverse transform, but at the same time, part of the high-frequency signal in the image is lost, making the denoising effect unsatisfactory.

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