Noise Reduction in Image Using Directional Modified Sigma Filter

Abstract

In this paper, we propose a new method using a modified sigma filter. The sigma filter among many algorithms is one of the simplest de-noising methods. The threshold of the sigma filter uses the estimated standard deviation of the noise by block-based noise estimation using the adaptive Gaussian filtering. In the proposed method, an input image is first decomposed into two components according to direction features. Then, two components are applied; HPF and LPF. By applying a conventional sigma filter separately on each of them, the output image is reconstructed from the filtered components. Comparative results from experiments show that the proposed algorithm achieves higher gains than the sigma filter and modified sigma filter, which are 2.6 dB PSNR on average and 0.5 dB PSNR, respectively. When relatively high levels of noise are added, the proposed algorithm shows better performance than the two conventional filters.KeywordsAdaptive Gaussian filteringimage de-noisingnoise estimationnoise removalsigma filter