Image denoising method based on non-uniform partition and wavelet transform

A new images denoising method based on nonuniform partition approximation and wavelet transform is proposed. The key point of non-uniform partition approximation is that the gray values of the pixels are regarded as fitting data, which is fitted with the least squares method, and then the digital image is expressed as a piecewise polynomial. The nonuniform partition approximation can realize image denoising by expressing the contaminated image as a piecewise polynomial. Since non-uniform partition can retain the edges as well as detailed characteristics, and wavelet transform can well retain field texture in image denoising, this paper combines these two methods to process image denoising. The experimental results show that the proposed method is efficient to improve the quality of denoised images and PSNR.