Research Of Image Denoising Arithmetic Based On Matching Pursuit And Adaptive Dictionaries

Image denoising is one of the key steps in image processing and the basis of iamge subsequent processing.An adaptive image denoising method is proposed in this thesis.The anisotropic atom dictionary that is more suitable for image sparse representation is chosen according to the feature of the matching pursuit image sparse decomposition.Based on study of the different characteristic of image and noise in sparse decomposition,the difference between image and noise is identified.According to the different coherent ratio between image,noise and over-complete dictionary,image information and noise are distinguished.One image adaptive filtering is realized by taking coherent ratio threshold as the condition to end the sparse decomposition process.The effectness of image denoising between sparse decomposition and wavelet soft thresholding denosing are compared.According to the vision effect,image denosing results based on sparse decomposition is better than that of wavelet soft thresholding.