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Underwater image dehazing using a hybrid GAN with bottleneck attention and improved Retinex-based optimization. [PDF]

Sci Rep
Kaur A, Rani S, Shabaz M.
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DSNet enables feature fusion and detail restoration for accurate object detection in foggy conditions. [PDF]

Sci Rep
Jing Z, Chen Z, Shi Y, Shi L, Wei L, Gao Y.   +5 more
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IDDNet: Infrared Object Detection Network Based on Multi-Scale Fusion Dehazing. [PDF]

Sensors (Basel)
Sun S, Han S, Xu J, Zhao J, Xu Z, Li L, Han Z, Mo B.   +7 more
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An improved and advanced method for dehazing coal mine dust images. [PDF]

Sci Rep
Cao P, Wang X, Li L, Liu M, Wang M.
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Joint Dual-Branch Denoising for Underwater Stereo Depth Estimation. [PDF]

Sensors (Basel)
Zhou J, Hu Y, Rao Y, Fan H.
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Automated image inpainting for historical artifact restoration using hybridisation of transfer learning with deep generative models. [PDF]

Sci Rep
Swathi B, Rao DBJ.
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Remote sensing image dehazing using a wavelet-based generative adversarial networks. [PDF]

Sci Rep
Chen G, Jia Y, Yin Y, Fu S, Liu D, Wang T.   +5 more
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Single Image Dehazing by Multi-Scale Fusion

IEEE Transactions on Image Processing, 2013
Haze is an atmospheric phenomenon that significantly degrades the visibility of outdoor scenes. This is mainly due to the atmosphere particles that absorb and scatter the light. This paper introduces a novel single image approach that enhances the visibility of such degraded images.
Codruta Orniana, Ancuti, Cosmin, Ancuti
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