Natural image denoising method based on regional division

Abstract

The invention discloses a natural image denoising method based on the regional division, which mainly solves the problem that patches exist in an image after an image is donoised through the existing three-dimensional block matching denoising algorithm. The method comprises the following steps: firstly, performing two-dimensional stationary wavelet transform on an input image to be denoised, and performing inverse transform on a high frequency coefficient subjected to zero setting, so as to obtain a reconstructed image; secondly, exacting the structural information of the reconstructed image, so as to obtain an image structure sketch; thirdly, dividing the noisy original image into a structure region, a smooth region and a non-smooth region through statistic features of an image block and the image structure sketch; fourthly, performing denoising on the smooth region with an improved non-local mean method, performing denoising on the non-smooth region with a BM3D (Block matching 3D) method, and performing denoising on the structure region with a directional feature-based BM3D method; and fifthly, combining estimated results of the structure region, the smooth region and the non-smooth region, so as to obtain the final denoised image. The method can be used for preprocessing natural images.

Description

technical field [0001] The invention belongs to the technical field of image processing, relates to an image denoising method, and can be used for preprocessing natural images. Background technique [0002] Image denoising has always been an important issue in the field of image processing. Due to the imperfection of image acquisition equipment, problems in the process of acquisition and transmission, and the interference of some unavoidable natural phenomena, the image data will be polluted by noise. Therefore, image denoising has become a commonly used image preprocessing method in order to improve image quality and image recognizability. [0003] Image denoising refers to the use of various filtering models to remove noise parts from known noise-containing images through traditional filtering, wavelet and other methods. Image denoising belongs to the technical category of image restoration from the technical point of view of digital image processing, and it has very imp...

AI Technical Summary

Problems solved by technology

This method not only has a high signal-to-noise ratio, but also maintains the texture and edges of the original image well, especially for the edges that change slowly. However, the biggest defect of this method is that, There will be some plaque artifacts in smooth areas, resulting in unclear images within the blocks

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