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Sparse Technique for Images Corrupted by Mixed Gaussian-Impulsive Noise

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Abstract

In this paper, a novel framework is presented for denoising images that have been corrupted by a mixture of additive and impulsive noise. The proposed method consists of three main stages: impulsive noise suppression, additive noise suppression and post-processing. In the first stage, a pixel that has been contaminated by impulsive noise is detected and filtered. In the next stage, filtering is based on sparse representation and 3D-processing using discrete cosine transform. Finally, the post-processing stage increases the filtering quality by using a bilateral filter and an edge restoration technique. Evaluation is performed using objective criteria (PSNR and SSIM) and subjective human visual perception to confirm the methods performance compared with state-of-the-art techniques.

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Acknowledgements

Authors would like to thank to Instituto Politécnico Nacional (México) and Consejo Nacional de Ciencia y Tecnología (México) (Grant 220347) for their support in realizing this work.

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Authors and Affiliations

  1. Instituto Politecnico Nacional, ESIME Culhuacan, Mexico City, Mexico

    A. Palacios-Enriquez, V. Ponomaryov & R. Reyes-Reyes

  2. Instituto Mexicano del Petroleo, Lazaro Cardenas 152, Mexico City, Mexico

    S. Sadovnychiy

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  1. A. Palacios-Enriquez
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  2. V. Ponomaryov
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  3. R. Reyes-Reyes
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Correspondence to A. Palacios-Enriquez.

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Palacios-Enriquez, A., Ponomaryov, V., Reyes-Reyes, R. et al. Sparse Technique for Images Corrupted by Mixed Gaussian-Impulsive Noise. Circuits Syst Signal Process 37, 5389–5416 (2018). https://doi.org/10.1007/s00034-018-0820-x

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