Abstract
ABSTRACT Median filters excel at removing impulse noise from digital signals, with high accuracy and quick running-times. However, they have limitations if the resulting signals are to be used for feature recognition purposes, as they often remove crucial details and add unwanted noise. In this paper, an algorithm for digital filtering using the logical transform is proposed. This method is able to achieve mean-squared-error results similar to median type filters while maintaining image details. Variations of the algorithm allow for grea ter noise reduction, but at the cost of increased computation. Keywords: impulse noise, digital filtering, Histogram of Primar y Implicants, Boolean Minimization, logical transform 1. INTRODUCTIONDigital signals can be corrupted by impulse noise (i.e. salt and pepper noise) in a variety of ways, from errors in collection sensors to noisy transmission channels to faulty storage devices. The industry standard for eliminating impulse noise is median type filters
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