LAUSR

Abstract. This paper proposes an adaptive rank-ordered impulse detector based on local statistics for identifying random-valued impulse noise (RVIN) pixels. A piecewise power function is applied to the rank-ordered statistic so as to enlarge the difference between noisy pixels and noise-free pixels. The proposed detector performs well over most well-known detectors. By combining the noise detector with an improved edge-preserving regularization filter, a two-stage iterative denoising procedure is performed to remove RVIN. An effective and robust adaptive stop criterion is also proposed based on the number of restored pixels for the iterative running of the filtering process. Experimental results indicate that the proposed denoising algorithm achieves a satisfying performance in terms of quantitative evaluation and visual effect.