Abstract
In this paper, we present a two-phase random-valued impulse noise removal algorithm based on local deviation index (LDI) and edge-preserving regularization. In the first phase, we define an image statistic LDI. Then with image pixels’ LDI values, the outlier candidates are identified. In the second phase, the image is denoised by an edge-preserving regularization method. Extensive experimental results indicate that our method performances better than many existing filters do for its robust image restoration and accurate noise detection.
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