Abstract
In signal processing, filters generally play a pivotal role to remove unwanted parts of the signal, such as random noise, or to extract useful parts of the signal, such as the components lying within a certain frequency range to enhance the performance and denoising scenario. This paper presents the implementation of linear and non-linear filtering schemes for noise reduction and images enhancement. This is achieved by performing convolution of a grayscale image with a mask filter of multiple sizes using MATLAB software. The average and median filters are implemented on the same image of an injected salt and pepper noise. In accordance with the findings, the nonlinear filters show more promising performance with a better peak-signal-noise ratio (PSNR) compared to the linear filters.
Published Version
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