Impulse Noise Reduction using Distance Weighted Average Filter

Abstract

Switching median filter is known as one of effective algorithms for impulse noise reduction. In this paper, we present an improved switching median filter by considering weighted neighboring pixel locations. Specifically, the proposed method generates a flag map using boundary discriminative noise detection(BDND) detector. Next, we conduct a noise reduction by estimating the local noise density. When the local noise density is low, a corrupted pixel is replaced with the median value of uncorrupted neighboring pixels. In contrast, when the density is high, a noise searching window size increases until the predefined conditions are met. Then, a noise pixel is corrected by the weighted average of the uncorrupted values. Experiment results show that the proposed method outperforms the existing methods by about 0.5-3.7 dB on average.