In this paper, we present a novel filter algorithm that is more capable in removing impulse noise than some of the common noise removal filters. The philosophy of the new algorithm is based on a pixel identification concept. Rather than processing every pixel in a digital image, this new algorithm intelligently interrogates a subimage region to determine which are the 'corrupted' pixels within the subimage. With this knowledge, only the 'corrupted' pixels are eventually filtered, whereas the 'uncorrupted' pixels are untouched. Extensive testing of the algorithm over a hundred noisy images shows that the new algorithm exhibits three major characteristics. First, its ability in removing impulse noise is better visually and has the smallest mean-square error compared with the median filter, averaging filter and sigma filter. Second, the effect of smoothing is minimal. As a result, edge and line sharpness is retained. Third, the new algorithm is consistently faster than the median filter in all our test cases. In its current form, the new filter algorithm performs well with impulse noise.
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