Single Image Dehazing
52 papers with code • 2 benchmarks • 8 datasets
Benchmarks
These leaderboards are used to track progress in Single Image Dehazing
| Trend | Dataset | Best Model | Paper | Code | Compare |
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O-HAZE
UIEB
RESIDE
I-HAZE
NH-HAZE
D-HAZY
SMOKE
Latest papers with no code
Robust Single Image Dehazing Based on Consistent and Contrast-Assisted Reconstruction
To properly address this problem, we propose a novel density-variational learning framework to improve the robustness of the image dehzing model assisted by a variety of negative hazy images, to better deal with various complex hazy scenarios.
Towards Multi-Domain Single Image Dehazing via Test-Time Training
Motivated by this observation, we propose a test-time training method which leverages a helper network to assist the dehazing model in better adapting to a domain of interest.
Learning to dehaze with polarization
Haze, a common kind of bad weather caused by atmospheric scattering, decreases the visibility of scenes and degenerates the performance of computer vision algorithms.
Model-Based Single Image Deep Dehazing
Model-based single image dehazing algorithms restore images with sharp edges and rich details at the expense of low PSNR values.
Multi-Scale Single Image Dehazing Using Laplacian and Gaussian Pyramids
Ambiguity between object radiance and haze and noise amplification in sky regions are two inherent problems of model driven single image dehazing.
Single image dehazing via combining the prior knowledge and CNNs
If the transmission map of a pixel is small, the base layer of the haze image is used to recover a haze-free image via atmospheric scattering model, finally.
DAMix: A Density-Aware Mixup Augmentation for Single Image Dehazing under Domain Shift
However, these methods are often subject to performance degradation when domain shifts are confronted.
Fully Non-Homogeneous Atmospheric Scattering Modeling with Convolutional Neural Networks for Single Image Dehazing
However, it is noted that ASM-based SIDM degrades its performance in dehazing real world hazy images due to the limited modelling ability of ASM where the atmospheric light factor (ALF) and the angular scattering coefficient (ASC) are assumed as constants for one image.
Pyramid Fusion Dark Channel Prior for Single Image Dehazing
In this paper, we propose the pyramid fusion dark channel prior (PF-DCP) for single image dehazing.
GridDehazeNet+: An Enhanced Multi-Scale Network with Intra-Task Knowledge Transfer for Single Image Dehazing
We also propose a novel intra-task knowledge transfer mechanism that can memorize and take advantage of synthetic domain knowledge to assist the learning process on the translated data.
