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Enhancing underwater image clarity: a multi-branch network with commonality-specificity fusion
Abstract Underwater images often suffer from degradation due to light attenuation and scattering, posing challenges for vision-based tasks. This paper introduces a novel Edge-Guided Multi-Branch Commonality-Specificity Network (EGMCS-Net) to enhance underwater image quality. The network integrates an RGB branch for initial enhancement and an edge branch for refined edge features, followed by a Commonality-Specificity Fusion Module (CSFM) to achieve complementary feature interaction.
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