Modified decision based median filter for impulse noise removal

Abstract

Removing impulse noise in digital images is one of the major challenges in digital image processing. Pixels in digital images get corrupted during transmission due to impulse noise. In this paper, we propose a modified decision based median filter that removes impulse noise from gray images. For noise removal from digital images, different types of median filters are used: Standard Median Filter (MF), Weighted Median Filter (WMF), Adaptive Median Filter (AMF) and Decision Based Median Filter (DBMF). In most of these methods except DBMF, processing pixels, irrespective of the fact whether it is corrupted or not, are replaced by the median value of the pixels in their nearby region without considering the local features present for example edges. However, our proposed method follows DBMF that considers only the noisy pixels and replaces the pixel value with median value of the pixels present in the processing window. In our method, we increase the window size as per the requirement. Our experimental results show that our proposed method performs better than Standard Median Filter (MF), Weighted Median Filter (WMF), Adaptive Median Filter (AMF) and Decision Based Median Filter (DBMF), especially when the noise intensity level is high. We compare our method to others based on Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM) values.