A new image denoising method based on BEMD and self-similar feature

Abstract

This paper presents a new method for image denoising through Bi-dimensional Empirical Mode Decomposition (BEMD). Although there have been many filter based methods for image processing, problems of non-adaptively and redundancy are still hard to solve. The BEMD is a locally adaptive method and suitable for the analysis of nonlinear or non-stationary signals. The image can be decomposed to several IMFs (intrinsic mode functions) by BEMD, which present new characters of the images. But for the BEMD, the boundary interference is a main limit for its application. In this paper, we firstly proposed a new BEMD method based on the self-similar extend method and the neighbor local extremes to reduce the boundary interference. And then based on the new BEMD method, a denoising algorithm based on the new BEMD is proposed.