Abstract
An adaptive decision based inverse distance weighted interpolation (DBIDWI) algorithm for the elimination of high-density salt and pepper noise in images is proposed. The pixel is initially checked for salt and pepper noise. If classified as noisy pixel, replace it with an inverse distance weighted interpolation value. This interpolation estimates the values of corrupted pixels using the distance and values nearby non-noisy pixels in vicinity. Inverse distance weighted interpolation uses the contribution of non-noisy pixel to the interpolated value. The window size is varied adaptively depending upon the non-noisy content of the current processing window. The algorithm is tested on various images and found to exhibit good results both in terms of quantitative (PSNR, MSE, SSIM, Pratt’s FOM) and qualitative (visually) at high noise densities. The algorithm performs very well in restoring an image corrupted by high-density salt and pepper noise by preserving fine details of an image.
Highlights
The term interpolation comes from the topic of resampling described by Hanumantharaju et al By definition, re-sampling [1] is a process of transforming a discrete image that is indicated at one particular set of coordinate locations to a new set of coordinate points
The performance of asymmetrical trimmed median [17] by Esakkiarajan et al was improved by finding mean of the window, which was entirely corrupted by salt and pepper noise
A decision based asymmetrical trimmed variants [19] proposed by Vasanth et al (2012) replaced the corrupted pixel with asymmetrical trimmed midpoint based on the content of the current processing window
Summary
The term interpolation comes from the topic of resampling described by Hanumantharaju et al By definition, re-sampling [1] is a process of transforming a discrete image that is indicated at one particular set of coordinate locations to a new set of coordinate points. Decision based algorithm [13] was proposed by Srinivasan et al to eliminate high density impulse noise This algorithm replaces the corrupted pixel with median value or the preprocessed neighbor. A cascaded filters [15] were proposed by Balasubramanian et al for high density salt and pepper noise This algorithm initially applies decision based median filter as first stage, and asymmetrical trimmed median and midpoint were applied on the later stage. This algorithm exhibits smoothing effect at high noise densities. A novel decision based asymmetric trimmed median filter [16] was proposed by Aiswarya et al which used reduced computation for calculation of median by asymmetrical trimming This algorithm exhibits fading at high noise densities.
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