Image de-noising method based on partial differential equation filter

Abstract

The invention discloses an image de-nosing method based on a partial differential equation filter, mainly solving the problems that the traditional de-nosing method has weaker de-nosing effect and performance. The method comprises the following steps of: (1) inputting a noising image u and calculating a partial derivative of the image u; (2) calculating a gradient modulus absolute Delta of the noising image u; (3) establishing a partial differential equation according to the gradient Delta and the gradient modulus absolute Delta ; (4) calculating a diffusion coefficient and Phi in the partial differential equation; (5) solving the partial differential equation to obtain a filter image by utilizing the coefficient and Phi; (6) calculating the PSNR (Peak Signal to Noise Ratio) of the filter image; and (7) repeating from the step 1 to the step 6. When the PSNR value of the filter image output at some iteration is less than that of the filter image iteratively output at the last time, the iteration is stopped, and the filter image at the last iteration is output. The invention can carry out filtering by utilizing the detailed structures of the image, has simple calculation and fast operation speed, can keep image texture details better at the same time of smoothening noise and can be used for the de-noising treatment of natural images.

Description

technical field The invention belongs to the technical field of image processing, relates to an image denoising method, and is suitable for noise removal of SAR images and natural images. Background technique Image denoising aims to process some kind of noise-contaminated image through an algorithm to reduce the impact of noise on the original useful information and restore an idealized image as much as possible. The preprocessing technology often used in image processing in the fields of research, environmental disaster assessment, urban planning, national defense military monitoring, medical imaging and astronomical imaging has an urgent need and broad application prospects. Synthetic aperture radar SAR images and natural images both need denoising processing, and research on SAR image and natural image denoising processing technology has a very broad application prospect. In order to meet the urgent needs of image denoising applications, a lot of denoising methods have ...

AI Technical Summary

Problems solved by technology

Although these denoising methods can better achieve the purpose of denoising, but for images with rich image details, the denoising results of these methods are not ideal, and cannot meet the special requirements of denoising effect

In order to solve the problems of the above methods, the denoising method based on the partial differential equation filter has become a hot issue in the field of image denoising research, and many scholars have classified, analyzed and improved the existing denoising methods from different angles, but For different feature areas of the image, the effect of denoising is not very ideal

Especially for some images with high real-time requirements, the denoising speed is very slow, which affects the normal work of subsequent systems

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