A computational experimental investigation of noise suppressing technique stand on hard decision threshold dissimilarity under fixed-intensity impulse noise

Due to the extreme insistence for digital image processing, the noise suppressing techniques have been immensely researched during the last twenty-five years for the reason that the capability of the modern advance digital image processing dramatically degrades when the processed photograph is corrupted by outlier. As a result, plentiful modern noise suppressing techniques, which are usually embodied of dissimilarity process and suppressing process. One of the extreme capability dissimilarity is Hard Decision Threshold (HDT) dissimilarity, which has been recently declared in 2012, for suppressing the impulsive noisy photographs thus the computer experimental statement attempts to investigate the capability of the noise suppressing technique that is stand on HDT dissimilarity for the processed photographs, which are corrupted by fixed-intensity impulse noise (FIIN). This paper proposes the noise suppressing technique stand on HDT dissimilarity for fix intensity impulsive noise. There are 3 primary contributions of this experimental statement. The first contribution is the statistical average of the HDT dissimilarity of noise-free elements, which are computed from plentiful ground-truth photographs by varying window size from 3x3 to 7x7 for determining the best window size of the HDT dissimilarity. The second contribution is the statistical average of the HDT dissimilarity of corrupted elements, which are computed from plentiful corrupted photographs by varying outlier density from 0% to 90% for determining the best window size of the HDT dissimilarity. The final contribution is the statistical interrelation of the capability of the noise suppressing technique and hard consistent of HDT dissimilarity are investigated by varying the outlier denseness from 0% to 90% for determining the best hard consistent of HDT dissimilarity.