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| The Equivalence Framework and the Application to Image Denoising of Two Dimensional Wavelet Shrinkage and Anisotropic Diffusivity |
| Zhu Jing-fu①②; Huang Feng-gang① |
| ①College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China; ②College of Information Technology, Heilongjiang August First Land Reclamation University, Daqing 163319, China |
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Abstract Image denoising is one of important technology in image processing. The denoising image can be gotten by shrink the amplitude of wavelet coefficient of noise according to the fact that it is smaller than others in Wavelet Shrinkage (WS). The Anisotropic Diffusivity (AD) completes denoising according to the direction and amplitude of gradient while as far as possible to keep the characteristic of image. In this paper, the equivalence framework of two dimensional wavelet shrinkage and anisotropic diffusivity is proved with experiment. After that, the Anisotropic Wavelet Shrinkage (AWS) is proposed that synthesizes the merits of the wavelet shrinkage and anisotropic diffusivity according to the equivalence. The contrastive experiments show that the AWS is better for image denoising.
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Received: 05 June 2007
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2008, Vol. 30 
