Image de-noising method and image de-noising device

Abstract

The invention provides an image de-noising method which comprises the steps of initializing a preset dictionary for obtaining an initial dictionary, and initializing a to-be-processed image to an image matrix which corresponds with the initial dictionary; wherein useful information in the to-be-processed image has a specific structure and sparse representation of the useful information in the to-be-processed image can be performed in the initial dictionary, and a noise in the to-be-processed image has no structure characteristic and sparse representation of the noise cannot be performed in the initial dictionary, updating the initial dictionary and a sparse coefficient matrix so that a reconstruction mean square error of the image matrix is minimized, reconstructing a de-noised image block by means of an updated dictionary and an updated sparse coefficient matrix, and generating a new to-be-processed image through combining the de-noised image block and the to-be-processed image for updating the dictionary and solving the sparse coefficient matrix, so that the updated dictionary ion better matches the structure characteristic information of the original to-be-processed image, thereby facilitating filtering of the noise component in the original to-be-processed image and improving image de-noising precision.

Description

technical field [0001] The present application relates to the field of computer image processing, in particular to an image denoising method and device. Background technique [0002] During the digitization and transmission of images, due to the interference of imaging equipment and external environmental noise, etc., the image quality will be greatly reduced. In order to facilitate viewing and analysis of images, it is necessary to denoise the images. [0003] The existing technology divides the image to be processed into a series of image blocks, and uses the sparse decomposition algorithm to obtain the sparse decomposition vector of each image block in a given dictionary. Since the noise in the image block does not have structural characteristics, it is impossible to use the dictionary Therefore, the denoising image block is reconstructed by using the dictionary and the sparse decomposition vector, and finally the denoising image block is stitched into the original image...

AI Technical Summary

Problems solved by technology

[0005] In view of this, the present application provides an image denoising method and device to solve the problem of unsatisfactory image denoising effect in the prior art and improve the accuracy of image denoising

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