Natural image denoising method based on regional division

An area division and image technology, applied in the field of image processing, can solve the problems of high signal-to-noise ratio, unclear image in the block, etc., achieve the effect of clear edges and textures, and improve the degree of edge retention

Active Publication Date: 2012-09-12
XIDIAN UNIV
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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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  • Natural image denoising method based on regional division
  • Natural image denoising method based on regional division
  • Natural image denoising method based on regional division

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Embodiment Construction

[0029] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0030] Step 1: Input the test image and add Gaussian white noise with a standard deviation of 30 to obtain a noise image.

[0031] Step 2, the noisy image is divided into structural and non-structural regions.

[0032] (2a) Perform two-dimensional stationary wavelet transform on the noise image to obtain one low-frequency subband and three high-frequency subbands, set all the high-frequency sub-band coefficients to zero, and keep the low-frequency coefficients unchanged, and then set the high-frequency coefficients to zero The low-frequency coefficients are subjected to inverse two-dimensional stationary wavelet transform to obtain the reconstructed image;

[0033] (2b) Use primal sketch to extract the primal sketch image for the reconstructed image, such as figure 2 as shown, figure 2 The structural information of the edge of the noise image is reflected in the noise ...

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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...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 刘芳焦李成郝红侠王伟伟戚玉涛赵静马晶晶王爽马文萍尚荣华
Owner XIDIAN UNIV
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