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2015 Colour and Visual Computing Symposium (CVCS), 2015
Today, there are typically two main approaches for dehazing, that is, enhancing images taken in hazy or foggy conditions. The first method is based on general image enhancement techniques where algorithms such as histogram equalization or Retinex are often used.
Vincent Whannou De Dravo +1 more
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Today, there are typically two main approaches for dehazing, that is, enhancing images taken in hazy or foggy conditions. The first method is based on general image enhancement techniques where algorithms such as histogram equalization or Retinex are often used.
Vincent Whannou De Dravo +1 more
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Hierarchical Density-Aware Dehazing Network
IEEE Transactions on Cybernetics, 2022The commonly used atmospheric model in image dehazing cannot hold in real cases. Although deep end-to-end networks were presented to solve this problem by disregarding the physical model, the transmission map in the atmospheric model contains significant haze density information, which cannot simply be ignored.
Jingang Zhang +6 more
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ICycleGAN: Single image dehazing based on iterative dehazing model and CycleGAN
Computer Vision and Image Understanding, 2021Abstract The current competitive approaches to restoring haze-free images are mainly based on physical models and learning methods. Maintaining detail information of the image while thoroughly removing fog is a challenging task in single-image dehazing.
Ziyi Sun +5 more
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Physically Plausible Dehazing for Non-physical Dehazing Algorithms
2019Images affected by haze usually present faded colours and loss of contrast, hindering the precision of methods devised for clear images. For this reason, image dehazing is a crucial pre-processing step for applications such as self-driving vehicles or tracking.
Vasqez-Corral, Javier +2 more
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2018
Haze is a major problem in videos captured in outdoors. Unlike single-image dehazing, video-based approaches can take advantage of the abundant information that exists across neighboring frames. In this work, assuming that a scene point yields highly correlated transmission values between adjacent video frames, we develop a deep learning solution for ...
Wenqi Ren, Xiaochun Cao
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Haze is a major problem in videos captured in outdoors. Unlike single-image dehazing, video-based approaches can take advantage of the abundant information that exists across neighboring frames. In this work, assuming that a scene point yields highly correlated transmission values between adjacent video frames, we develop a deep learning solution for ...
Wenqi Ren, Xiaochun Cao
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ACM SIGGRAPH 2008 papers, 2008
In this paper we present a new method for estimating the optical transmission in hazy scenes given a single input image. Based on this estimation, the scattered light is eliminated to increase scene visibility and recover haze-free scene contrasts. In this new approach we formulate a refined image formation model that accounts for surface shading in ...
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In this paper we present a new method for estimating the optical transmission in hazy scenes given a single input image. Based on this estimation, the scattered light is eliminated to increase scene visibility and recover haze-free scene contrasts. In this new approach we formulate a refined image formation model that accounts for surface shading in ...
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UCL-Dehaze: Toward Real-World Image Dehazing via Unsupervised Contrastive Learning
IEEE Transactions on Image ProcessingWhile the wisdom of training an image dehazing model on synthetic hazy data can alleviate the difficulty of collecting real-world hazy/clean image pairs, it brings the well-known domain shift problem. From a different yet new perspective, this paper explores contrastive learning with an adversarial training effort to leverage unpaired real-world hazy ...
Yongzhen, Wang +7 more
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Depth-Aware Unpaired Video Dehazing
IEEE Transactions on Image ProcessingThis paper investigates a novel unpaired video dehazing framework, which can be a good candidate in practice by relieving pressure from collecting paired data. In such a paradigm, two key issues including 1) temporal consistency uninvolved in single image dehazing, and 2) better dehazing ability need to be considered for satisfied performance.
Yang Yang, Chun-Le Guo, Xiaojie Guo
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