Simulation Evaluation of Noise Suppressing Technique Based on Decision Based Adaptive Median Filter for Salt&Pepper Noise

Due to statistical characteristic, ROAD (Rank Order Absolute Difference) is one of the highest similar measurement performance in digital image for recognizing whether the impulsive noise pixel or the non-impulsive noise pixel whence the DBAMF (decision based adaptive median filter) was invented for suppressive an impulsive noise in 2010. As a result, the dissertation article aim to scrutinize the performance of the noise suppressing technique based on DBAMF under S&P noise. For evaluating the performance and its limitation of the noise suppressing technique based on DBAMF, the two assessment digital images constituted of Lena and Pepper are exploited in these simulation evaluations under SPN by initially disparaged by adding the impulsive noise (or SPN) at plentiful quantity. Next, each disparaged digital image is refined by the noise suppressing technique based on DBAMF. Moreover, the refined image is confronted with the refined image from the classical SMF (Standard Median Filter) and AMF (Adaptive Median Filter) for proving the DBAMF performance from quantitative indicator perspective.