ADR network performs joint dehazing via extended IFM, Retinex enhancement, and attention U-Net++ refinement, reporting competitive results on UIEB and UFO-120 underwater image datasets.
Underwater image enhancement based on deep learning and image formation model
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UDehaze-iT is a lightweight deep network that enhances underwater images by implicitly estimating depth and deriving transmission via learnable Beer-Lambert attenuation coefficients, achieving competitive results on UIEB and UFO-120 with 0.9M parameters.
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An Attention-Enhanced Network with Joint Dehazing and Retinex-Based Enhancement for Underwater Images
ADR network performs joint dehazing via extended IFM, Retinex enhancement, and attention U-Net++ refinement, reporting competitive results on UIEB and UFO-120 underwater image datasets.
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An Underwater Dehazing Network with Implicit Transmission Estimation
UDehaze-iT is a lightweight deep network that enhances underwater images by implicitly estimating depth and deriving transmission via learnable Beer-Lambert attenuation coefficients, achieving competitive results on UIEB and UFO-120 with 0.9M parameters.