A novel image de-noising method based on spherical coordinates system

Abstract

Abstract In this article, a novel image de-noising method is proposed. This method is based on spherical coordinates system. First, spherical transform is re-defined in wavelet domain, and the properties of the spherical transform in wavelet domain are listed. Then, a new adaptive threshold in spherical coordinate system is presented. It has been proved based on Besov space norm theory. After that, a novel curve shrinkage function is proposed to overcome the limitation of the traditional shrinkage functions. The new function can reach and exceed the true value and enhance the edge of the image. Finally, the multi-scale product in wavelet domain is introduced to spherical coordinates system. This article names the multi-scale product in spherical coordinates system as Multi-Scale Norm Product. The experimental results compared the improved algorithm with other methods from the peak signal-to-noise ratio, mean square error, and running time. The results indicate that improved algorithm is simple and effective.