Abstract
Method noise is the residual image containing significant structural information lost during the process of denoising and can be effectively used for image restoration. In this paper, we propose an efficient two stage filtering approach using nonlocal means and method noise for the reduction of Gaussian noise from the images. In first stage, the block-based NLM is applied to obtain the denoised image and in second stage, the nonlocal similarities present in the method noise and the denoised image are used for the computation of effective weights for weighted NLM denoising. Experimental results demonstrate significant improvements in the denoising performance of the proposed approach as compared to the classical and block-based NLM approaches.
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Acknowledgments
One of the authors (Karamjeet Singh) is grateful to University Grant Commission (UGC) and the Ministry of Minority Affairs (MOMA), Govt. of India, for providing Maulana Azad National Fellowship (F1-17.1/2012-13/MANF-2012-13-SIK-PUN-13364) for carrying out the research work.
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Singh, K., Ranade, S.K., Singh, C. (2017). Method Noise Based Two Stage Nonlocal Means Filtering Approach for Gaussian Noise Reduction. In: Deep, K., et al. Proceedings of Sixth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 547. Springer, Singapore. https://doi.org/10.1007/978-981-10-3325-4_18
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DOI: https://doi.org/10.1007/978-981-10-3325-4_18
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