| Image processing and analysis is a major field of information science and engineering. The image restoration is an item basic moreover the important technology in the image processing domain. At the same time, it is the research topic which may not avoid. The image denoising is the earliest and most research in the image restoration domain, it is the essential step and the key link in the process of image processing. Now, Wavelet and Partial Differential Equation (PDE) are main denoising methods in image processing aspect.At first, this paper researches the difference scheme that is based on nonlinear anisotropic partial Differential Equation. It adopts a type of CN-ADI scheme to discrete nonlinear anisotropic diffusion equation. It is an effective scheme by comparing with additive operator splitting scheme. Second, this paper researches the relations between Wavelet and Partial Differential Equation in the image denoising. The expression form of PDE that based on wavelet threshold is then obtained. It adapts the method of fractional steps wavelet shrinkage for the solution of PDE based on above approach. It can receive higher SNR than other methods, It can receive better effect of image denoising than wavelet method. At last, according to de noising characteristic of wavelet and PDE, a mixed method of combining wavelet with PDE for image denoising is proposed. We normalize the higher frequency subbands so as to gain a continuous state quantity. It is important to protect edge that a continuous state quantity is de noised by means of forward and backward diffusion. We obtain the weight coefficient that is determined by new state quantity after diffusion. The new higher frequency subbands are gained when weight coefficient act on wavelet coefficient. We achieve the process of denoising through wavelet reconstruction in the end. It is indicated from the experimental results that new method can attain the purpose of preserving edge and smoothing noise at the same time. |
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