A Modified Weighted Based Filter for Removal of Random Impulse Noise (MWB) J.K. Mandal Department of Computer Science & Engineering University of Kalyani Kalyani, Nadia, West Bengal e-mail: jkm.cse@gmail.com Aparna Sarkar Department of Computer Science & Engineering University of Kalyani Kalyani, Nadia, West Bengal e-mail:sarkaraparna09@gmail.com. Abstract— In this paper an effort has been made to device an algorithm for highly corrupted images. In this paper a novel Modified Weighted Based(MWB) filter has been proposed, which is based on the weighted differences between the current pixel and its neighbors aligned with four main directions. Simulations showed that the MWB filter provides optimal performances of suppressing impulse with high noise level which may enhance the performance in terms of removal of random-valued impulse noise compared to the directional weighted median (DWM) filter [1] along with other filters like signal-dependent rank order mean (SD- ROM) filter[6], multistate median (MSM) filter[2], adaptive center weighted median (ACWM) filter[8], pixel-wise MAD (PWMAD) filter[7] etc. Keywords- Modified Weighted Based Filter (MWBF); PSNR; SNR; Median; DWM I. INTRODUCTION Images are often corrupted by impulse noises during acquisition and transmission [5, 6]. Based on the noise values, the noise can be classified as the easier-to-restore salt-and-pepper noise and the more difficult random- valued impulse noise [2]. Among all the methods for removal of impulse noise, the median filter [3, 4] is used widely because of its effective noise suppression capability and high computational efficiency [7]. However, it uniformly replaces the gray-level value of every pixel by the median of its neighbors. Consequently, some desirable details are also removed, especially when the window size is large. In order to improve the median filter, many filters with an impulse detector are proposed, DWM filter [1] is one of them. DWM filter performs much better than the other median-based filters in removing random-valued impulse noise, especially when the noise level is as high as 60%. In this paper a filter is used for removal of random- valued impulse noise for which the performance may be comparable/better with DWM filter. This filter has been proposed to obtain optimal performance for highly corrupted images. The organization of this paper is as follows. The new impulse detector is formulated in section I. Section II described the filtering framework. Section III provides the used algorithm. Section IV provides a number of experimental results to demonstrate the performance of the proposed MWB filter. Conclusions are drawn in section V and that of references in section VI. II. IMPULSE DETECTOR Fig. 1 shows the edges aligned with four main directions. The edges separate the smoothly varying areas of a noise free image. Let S k (k=1 to 4) denote a set of coordinates aligned with the k th direction centered at (0,0), i.e., S 1 ={(-2,-2), (-1,-1), (0,0), (1,1), (2,2)} S 2 ={(0,-2), (0,-1), (0,0), (0,1), (0,2)} S 3 ={(2,-2), (1,-1), (0,0), (-1,1), (-2,2)} S 4 ={(-2,0), (-1,0), (0,0), (1,0), (2,0)} (1) Now in a 5×5 window centered at (i, j), for each direction, we define d i, j (k) as the sum of all absolute differences of gray-level values between y i+s, j+t and y i, j with (s,t) є S k 0 , where S k 0 = S k \ (0,0) for all k from 1 to 4. The gray-level values of any two pixels should be close, if the spatial distance between them is small. We will weight the absolute differences between the two closest pixels with a larger value w s,t is very large, it will cause that d i,j (k) is mainly decided by the differences corresponding to w s,t . Thus we have eq.2. Fig. 1: Alignment of edges in four directions 2011 Second International Conference on Emerging Applications of Information Technology 978-0-7695-4329-1/11 $26.00 © 2011 IEEE DOI 10.1109/EAIT.2011.77 173