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An adaptive algorithm for restoring image corrupted by mixed noise

Pham Cong Thang, Tran Thi Thu Thao, Phan Tran Dang Khoa, Dinh Viet Sang, Pham Minh Tuan, Nguyen Minh Hieu
Image denoising is one of the fundamental problems
in image processing. Digital images are often contaminated
by noise due to the image acquisition process under
poor conditions. In this paper, we propose an effective
approach to remove mixed Poisson-Gaussian noise
in digital images. Particularly, we propose to use a spatially
adaptive total variation regularization term in order
to enhance the ability of edge preservation. We also propose
an instance of the alternating direction algorithm to solve the proposed denoising model as an optimization problem. The experiments on popular natural images demonstrate that our approach achieves superior accuracy than other recent state-of-the-art techniques.
CYBERNETICS AND PHYSICS, Vol. 8, No. 2. 2019, 73–82. https://doi.org/10.35470/2226-4116-2019-8-2-73-82
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