Results 11 to 20 of about 3,318 (186)
Benchmarking Single-Image Dehazing and Beyond [PDF]
IEEE Transactions on Image Processing, 2019 IEEE Transactions on Image Processing(TIP 2019)
Boyi Li +6 more
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A Model-Driven Deep Dehazing Approach by Learning Deep Priors
IEEE Access, 2021 Photos taken in hazy weather are usually covered with white masks and lose important details. Haze removal is a fundamental task and a prerequisite to many other vision tasks.
Dong Yang, Jian Sun
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Cycle-Dehaze: Enhanced CycleGAN for Single Image Dehazing [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018 In this paper, we present an end-to-end network, called Cycle-Dehaze, for single image dehazing problem, which does not require pairs of hazy and corresponding ground truth images for training. That is, we train the network by feeding clean and hazy images in an unpaired manner.
Deniz Engin +2 more
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AED-Net: A Single Image Dehazing
IEEE Access, 2022 In the past decade, significant research effort has been directed toward developing single-image dehazing algorithms. Despite this effort, dehazing continues to present a challenge, particularly in complex real-world cases.
Sargis A. Hovhannisyan +3 more
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Robust Single-Image Dehazing [PDF]
Electronics, 2021 This paper proposes a new single-image dehazing method, which is an important preprocessing step in vision applications to overcome the limitations of the conventional dark channel prior. The dark channel prior has a tendency to underestimate transmissions of bright regions or objects that can generate color distortions during the process of dehazing ...
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IFE-Net: An Integrated Feature Extraction Network for Single-Image Dehazing
Applied Sciences, 2023 In recent years, numerous single-image dehazing algorithms have made significant progress; however, dehazing still presents a challenge, particularly in complex real-world scenarios.
Can Leng, Gang Liu
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New approach to dehaze single nighttime image
Xibei Gongye Daxue Xuebao, 2021 This paper focus on the dehazing of a single image captured at nighttime. The current state-of-the-art nighttime dehazing approaches usually suffer from the color shift problem due to the fact that the assumptions enforced underdaytime cannot get applied
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Vision Transformers for Single Image Dehazing
IEEE Transactions on Image Processing, 2023 Image dehazing is a representative low-level vision task that estimates latent haze-free images from hazy images. In recent years, convolutional neural network-based methods have dominated image dehazing. However, vision Transformers, which has recently made a breakthrough in high-level vision tasks, has not brought new dimensions to image dehazing. We
Yuda Song, Zhuqing He, Hui Qian, Xin Du
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Physical-based optimization for non-physical image dehazing methods [PDF]
, 2020 Images captured under hazy conditions (e.g. fog, air pollution) usually present faded colors and loss of contrast. To improve their visibility, a process called image dehazing can be applied.
BertalmÃo, Marcelo +2 more
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Single Image Dehazing Using Wavelet-Based Haze-Lines and Denoising
IEEE Access, 2021 Haze reduces the contrast of an image and causes the loss in colors, which has a negative effect on the subsequent object detection; therefore, single image dehazing is a challenging visual task.
Wei-Yen Hsu, Yi-Sin Chen
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