Abstract
An effective algorithm for automatic removal impulse noise from highly corrupted monochromatic images is proposed. The method consists of two steps. Outliers are first detected using local spatial relationships between image pixels. Then the detected noise pixels are replaced with the output of a rank-order filter over a local spatially connected area excluding the outliers, while noise-free pixels are left unaltered. Simulation results in test images show a superior performance of the proposed filtering algorithm comparing with conventional filters. The comparisons are made using mean square error, mean absolute error, and subjective human visual error criterion.
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Kober, V., Mozerov, M., Álvarez-Borrego, J. (2005). Automatic Removal of Impulse Noise from Highly Corrupted Images. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_4
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DOI: https://doi.org/10.1007/11578079_4
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