Nonhomogeneous Image Dehazing

7 papers with code • 1 benchmarks • 1 datasets

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Most implemented papers

Fast Deep Multi-patch Hierarchical Network for Nonhomogeneous Image Dehazing

diptamath/Nonhomogeneous_Image_Dehazing IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2020

Recently, CNN based end-to-end deep learning methods achieve superiority in Image Dehazing but they tend to fail drastically in Non-homogeneous dehazing.

PMS-Net: Robust Haze Removal Based on Patch Map for Single Images

weitingchen83/PMS-Net CVPR 2019

Conventional patch-based haze removal algorithms (e. g. the Dark Channel prior) usually performs dehazing with a fixed patch size.

PMHLD: Patch Map Based Hybrid Learning DehazeNet for Single Image Haze Removal

weitingchen83/Dehazing-PMHLD-Patch-Map-Based-Hybrid-Learning-DehazeNet-for-Single-Image-Haze-Removal-TIP-2020 IEEE Transaction on Image Processing 2020

In addition, to further enhance the performance of the method for haze removal, a patch-map-based DCP has been embedded into the network, and this module has been trained with the atmospheric light generator, patch map selection module, and refined module simultaneously.

Single image dehazing for a variety of haze scenarios using back projected pyramid network

ayu-22/BPPNet-Back-Projected-Pyramid-Network 15 Aug 2020

Learning to dehaze single hazy images, especially using a small training dataset is quite challenging.

Efficient Re-parameterization Residual Attention Network For Nonhomogeneous Image Dehazing

Owen718/ERA-Net 12 Sep 2021

This paper proposes an end-to-end Efficient Re-parameterizationResidual Attention Network(ERRA-Net) to directly restore the nonhomogeneous hazy image.

A Novel Encoder-Decoder Network with Guided Transmission Map for Single Image Dehazing

tranleanh/edn-gtm 8 Feb 2022

A novel Encoder-Decoder Network with Guided Transmission Map (EDN-GTM) for single image dehazing scheme is proposed in this paper.