Anisotropic diffusion noise processing method based on edge enhancement operator

Abstract

The invention discloses an anisotropic diffusion noise processing method based on an edge enhancement operator. The anisotropic diffusion noise processing method comprises the steps: firstly inputtinga to-be-processed image containing Gaussian noise, carrying out the preprocessing of a noise image through a Gaussian filter, and removing bigger noise; establishing an eight-direction 5 * 5 edge enhancement operator template, and performing convolution operation on an enhancement operator and the preprocessed image to obtain corresponding gradient information; then, constructing a diffusion coefficient model based on a hyperbolic tangent function for controlling the diffusion degree; substituting the diffusion function into an improved anisotropic diffusion equation to obtain a denoised image; and finally, repeating the steps for N times to complete iteration, and outputting the filtered image. According to the anisotropic diffusion noise processing method, image edges, textures, fine lines, weak edges and details can be effectively reserved while image noise is filtered, and the step effect is prevented, and the processing speed is higher.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, and in particular relates to an anisotropic diffusion noise processing method based on an edge enhancement operator. Background technique [0002] Image noise processing is a basic and important step in image processing, which directly determines the feasibility and accuracy of subsequent work in image processing, including image segmentation, image classification, feature extraction, and pattern recognition. Image denoising aims to reconstruct images from noise erosion, which can improve degraded image quality for better interpretation and extraction of data. The anisotropic diffusion equation makes the image diffuse less at the edge with a larger gradient, and more diffuse at the flat area with a smaller gradient, so as to achieve the purpose of filtering image noise and retaining image edge information. In image filtering Remarkable results have been achieved. [0003] Each ...

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Problems solved by technology

[0005] Purpose of the invention: the purpose of the invention is to address the step effect existing in the existing anisotropic diffusion filtering process and the shortcomings of being unable to filter out large noise points, and propose an anisotropic diffusion noise processing method based on an edge enhancement operator, which can While filtering out image noise, it can effectively preserve image edges and details, preventing the staircase effect

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