Switching Median Filter with Boundary Discriminative Noise Detection (BDND) is one of the useful methods that are capable to restore digital images which have been extremely corrupted by universal impulse noise. Following the fundamental framework of the switching median filter, the construction of BDND can be divided into two stages. The first stage classifies the pixels into either “noise” or “noise-free” pixels, while the second stage restores the image by changing only the intensity values of the “noise” pixels. Unfortunately, the originally proposed BDND employs sorting operations in both of its stages. This condition makes the originally proposed BDND computationally expensive. Therefore, in this paper, an implementation of BDND with reduced computational time is suggested. This reduction is achieved mainly by manipulating the local histograms’ properties. Experimental results show that the proposed implementation successfully produces the same results as the originally proposed BDND, but with much shorter processing time.
Key words: Digital image processing, impulse noise, median filter.
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