An Improved Method to Remove Salt and Pepper Noise in Noisy Images

Abstract

In the field of image processing, removal of noise from Gray scale as well as RGB images is an ambitious task. The important function of noise removal algorithm is to eliminate noise from a noisy image. The salt and pepper noise (SPN) is frequently arising into Gray scale and RGB images while capturing, acquiring and transmitting over the insecure several communication mechanisms. In past, the numerous noise removal methods have been introduced to extract the noise from images adulterated with SPN. The proposed work introduces the SPN removal algorithm for Gray scale at low along with high density noise (10\% to 90\%). According to the different conditions of proposed algorithm, the noisy pixel is reconstructed by Winsorized mean or mean value of all pixels except the centre pixel which are present in the processing window. The noise from an image can be removed by using the proposed algorithm without degrading the quality of image. The performance evaluation of proposed and modified decision based unsymmetric median filter (MDBUTMF) is done on the basis of different performance parameters such as Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Image Enhancement Factor (IEF) and Structure Similarity Index Measurement (SSIM).