Abstract: Improving the quality of underwater images is essential for advancing marine research and technology. This work introduces a sparsity-driven interpretable neural network (SINET) for the ...
Abstract: Low-light images often suffer from significant noise and detail loss, making it challenging to effectively distinguish signals from noise when processed directly in the spatial domain. To ...
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