Dissimilar pixel counting based impulse detector for two-phase mixed noise removal

Mixed noise is a challenging noise model due to its statistical complexity. A new two-phase denoising method based on an impulse detector using dissimilar pixel counting is proposed in this paper. This method consists of two stages: detection and filtering. For the detection phase, average difference scheme is proposed to distinguish whether two neighboring pixels are similar or not, and then the number of dissimilar pixels is compared with a threshold to locate the outlier point in noisy image. An iterative framework is used for detection accuracy with the least numbers of iteration. For the filtering phase, an extended trilateral filter is used to remove the mixture of Gaussian and impulse noise, which are treated differently depending on the guidance matrix from the detection phase. Extensive experimental results demonstrate that the proposed method exhibits better noise detection capability and outperforms many existing two-phase mixed noise removal methods in both quantitative evaluation and visual quality.