wenbihan/reproducible-image-denoising-state-of-the-art
Collection of popular and reproducible image denoising works.
Covers filtering, sparse coding, low-rank, and deep learning approaches for AWGN denoising, spanning from classical methods (NLM, BM3D) through transform-domain techniques (K-SVD, WNNM) to modern CNNs (DnCNN, UDNet). Each algorithm includes verified open-source implementations and reproducible results on standard benchmarks, enabling direct performance comparison across methodologies. Also provides parallel collections for video and hyperspectral denoising to support multi-domain research.
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