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Image denoising method based on fractional order partial differential equation

A technique of partial differential equation and fractional differential, applied in the field of image processing, which can solve problems such as general denoising effect

Active Publication Date: 2017-08-22
江苏新视云科技股份有限公司
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Problems solved by technology

Patrick et al. proposed two improved fourth-order partial differential equation models, redesigned the diffusion function and discussed the influence of parameters, which improved the ability to preserve edges and suppressed the step effect to a certain extent, but the denoising effect of this method Relatively general; the prior art has not yet solved the image denoising method that retains the texture information of the original image as much as possible while removing the noise, and the present invention solves such problems

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  • Image denoising method based on fractional order partial differential equation
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  • Image denoising method based on fractional order partial differential equation

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Embodiment Construction

[0091] The present invention will be specifically introduced below in conjunction with the accompanying drawings and specific embodiments.

[0092] An image denoising method based on fractional partial differential equations, comprising the following steps:

[0093] Step 1, input a noise-contaminated image u 0 (x, y), the image size is M×N, and the set time interval Δt≤0.25; it should be noted that if the time interval is greater than 0.25, the denoising will be unstable, so Δt≤0.25 is preferred; as an embodiment, Such as figure 2 As shown, the image size is 512*512 pixels;

[0094] In step 2, the image is processed symmetrically, and the size of the processed image is four times that of the original image; the points in the boundary area of ​​the image will have a large deviation due to the boundedness of the boundary area when deriving, and the noise to be processed The image flipping symmetry is 1024*1024 pixels; the calculation formula is as follows:

[0095] forx=1:M...

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Abstract

The invention discloses an image denoising method based on a fractional order partial differential equation. According to the method, based on the non-local property of a fractional order derivative, the interference of noises can be alleviated during detection of edges, the image denoising method based on the fractional order partial differential equation is obtained with the combination of the partial differential equation, denoising is realized, and texture details of an original image can be reserved as many as possible; in the solving process, a method of fast Fourier transform is employed, expanded operation of complicated fractional order derivatives is avoided, and the solving speed is accelerated; and the fractional derivative is individually set for a variable of a spread function, good denoising effect can be achieved for different image variation differential orders, the convergence speed is fast, and the required iteration frequency is low.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to an image denoising method based on fractional partial differential equations. Background technique [0002] With the continuous deepening of research fields such as pattern recognition, artificial intelligence, remote sensing science, and computer vision, image processing has become a hot spot that has attracted much attention. It is the premise and foundation of image analysis and image understanding. Image processing mainly includes image denoising, image enhancement, image restoration, image segmentation, image compression, image fusion, image super-resolution, image feature extraction and other issues. During the acquisition and transmission process, due to the defects of sensor components, the transmission channel is disturbed, the environment changes such as the influence of light and weather, and the human factors in the subsequent transmission will cause the sign...

Claims

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T5/70
Inventor 李远禄丁亚庆孟霄
Owner 江苏新视云科技股份有限公司
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