A new decision based unsymmetric trimmed median filter using Euclidean distance measure for removal of high density Salt and Pepper noise from images

Abstract

Image denoising is an important pre-processing step in image analysis. Developing the denoising algorithm is a difficult task because information must be preserved while removing the noise from the images. In this paper, a new Decision Based Unsymmetric trimmed median filter using Euclidean distance measure is proposed for the removal of Salt and Pepper noise from a gray scale images. The proposed algorithm replaces the noisy pixel by trimmed median value of uncorrupted pixels which are having minimum Euclidian distance between processing pixel and surrounding pixels. When all the pixels are 0's and 255's then the noisy pixel is replaced by mean value. The performance of the proposed algorithm is compared with the MDBUTMF using PSNR (Peak Signal to Noise Ratio). The proposed filter is experimented with different noise density in Lena image, Left iris image, Right iris image and Plant image in JPG/JPEG (Joint Photographic Experts Group) format. The results of the proposed algorithm shows a significant improvement in comparison with MDBUTMF filter even if the noise density in very high with better PSNR values.