Denoising method of strong noise pollution image on basis of partial differential equation
A partial differential equation and strong noise technology, applied in the field of image processing, can solve the problems of unsatisfactory denoising effect, unsatisfactory denoising results, poor denoising results, etc., to achieve reduced interference, improved accuracy, and improved The effect of running speed
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[0038] refer to figure 1 , the specific implementation steps of the present invention are as follows:
[0039] Step 1. The input size is M×N single noise image u 0 , use the wavelet soft thresholding method to image u 0 Perform pre-filtering to minimize the interference of strong noise on image texture details, so as to calculate edges and diffusion directions more accurately. The filtered result is recorded as u. In this example, both M and N are 512 or 256.
[0040] Step 2. Calculate the partial derivative of the image u in the x direction and the partial derivative in the y direction
[0041] Step 3. Based on the calculated partial derivatives and , use the gradient formula to calculate the gradient of the noise image u and gradient modulus
[0042] gradient gradient modulus
[0043] Among them, u x express , u y express
[0044] In the process of image denoising, it is required to retain as much detail information of the image itself as possible ...
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