Research Article Open Access

COMPARISON OF NONLINEAR MEDIAN FILTERS: SMF USING BDND AND MDBUTM

Abstract

Digital images are often corrupted by impulse noise which has two models namely, random valued impulse noise and salt & pepper noise. In this paper performance of two modified median filters viz., Switching Median Filter (SMF) using Boundary Discriminative Noise Detection (BDND) algorithm and Modified Decision Based Unsymmetric Trimmed Median (MDBUTM) filter for the removal of impulse noise was tested & compared using Peak Signal to Noise Ratio (PSNR), Image Enhancement Factor (IEF), number of Correctly Detected Corrupted (CDC) pixels, Miss Detected (MD) pixels, False Alarm (FA) pixels and execution time. These two filters basically identify corrupted pixels from noisy image and then filter only those corrupted pixels. In SMF, BDND algorithm is used to determine two boundaries to identify corrupted pixels, and then modified adaptive filter is used to replace corrupted pixels. MDBUTM filter deems pixels having values ‘0’ or ‘255’ as corrupted and replaces these pixels either by trimmed median or by mean of neighborhood pixels. The performance of filters is tested on gray scale images corrupted with variable percentage of salt & pepper noise and random valued impulse noise. Qualitative and quantitative result analysis show that for salt and pepper noise performance of MDBUTM filter and SMF using BDND was found to be nearly equal at all noise densities. For random valued impulse noise, performance of SMF using BDND was found to be better than that of MDBUTM filter. However SMF using BDND requires more time for execution due BDND algorithm.

Sakhare V. C., V. Jayashree

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