A Gray-Natural Logarithm Ratio Neighborhood Filters Method for Biomedical Image Denoising

Abstract

Denoising biomedical images can be completed by a spatial averaging of nearby pixels. Neighborhood filters are usually preferred. In this paper, we perform an analysis of neighborhood filters where the size of the gray Euclidean distance is small. We prove that the weak edges and details are smoothed and the gray level transition tends to become mild filtering with these neighborhood filters. As a solution, we propose a gray-natural logarithm ratio bilateral neighborhood filter. The new gray-natural logarithm ratio bilateral neighborhood filter method can not only well restrain noise but also keep much more weak edges and details of a biomedical image, and preserve the original gray level transition of gray level images. Experimental results show that the effectiveness for biomedical image denoising with our method is better.