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Erschienen in:
2014 | OriginalPaper | Buchkapitel
A Smart Filter Design for Removal of High-Density Noises of Image
verfasst von : Jieh-Ren Chang, Hong-Wun Lin, Hsien-Hsin Chou
Erschienen in: Future Information Technology
Verlag: Springer Berlin Heidelberg
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In this study, a novel smart edge-preservation filter (SEPF) is proposed for removal of high-density impulse noise in images. Using the sparse matrix transformation, the first stage of SEPF is not only to identify the noisy candidates but also to decide the processing order of them via a rank of noisepixel sparsity in working window. Then the second stage of SEPF utilizes a modified double Laplacian convolution to confirm the truly noisy pixels and yield a directional mean to recover them. This new approach has achieved remarkable success rate of the edge detection than other edge-preservation methods especially in high noise ratio over 0.5. As a result, SEPF has significant improvements in terms of edge preservation and noise suppression exhibited by the peak signal-to-noise ratio (PSNR). Simulation results show that this method is capable of producing better results compared to several median-based filters.