The equivalence conditions of Wavelet Shrinkage and Anisotropic Diffusion and it´s application in denosing

The Wavelet Shrinkage distinguish between signals and noises according to their wavelet coefficient´s amplitude, thus removing noises from noised signals by means of shrinkage. Anisotropic Diffusion diffuse signals according to gradient´s direction and amplitude by different degree at different direction, removing the noises from noised signals while protecting signals. In this paper, the equivalence condition of Wavelet Shrinkage and Anisotropic Diffusion was proposed. Then the signals denoising algorithm based on the equivalence of Wavelet Shrinkage and Anisotropic Diffusion was proposed. The results show that the new algorithm combines the advantage of Wavelet Shrinkage and Anisotropic Diffusion, therefore it possesses the better ability of denoising and keeping the high frequency property of signals.