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Unsupervised water scene dehazing network using multiple scattering model.
PLoS ONE, 2021 In water scenes, where hazy images are subject to multiple scattering and where ideal data sets are difficult to collect, many dehazing methods are not as effective as they could be.
Shunmin An +4 more
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Dehazing in hyperspectral images: the GRANHHADA database
Scientific Reports, 2023 In this study, we present an analysis of dehazing techniques for hyperspectral images in outdoor scenes. The aim of our research is to compare different dehazing approaches for hyperspectral images and introduce a new hyperspectral image database called ...
Sol Fernández Carvelo +3 more
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Image Dehazing Using LiDAR Generated Grayscale Depth Prior
Sensors, 2022 In this paper, the dehazing algorithm is proposed using a one-channel grayscale depth image generated from a LiDAR point cloud 2D projection image. In depth image-based dehazing, the estimation of the scattering coefficient is the most important.
Won Young Chung +2 more
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SIDE—A Unified Framework for Simultaneously Dehazing and Enhancement of Nighttime Hazy Images
Sensors, 2020 Single image dehazing is a difficult problem because of its ill-posed nature. Increasing attention has been paid recently as its high potential applications in many visual tasks. Although single image dehazing has made remarkable progress in recent years,
Renjie He, Xintao Guo, Zhongke Shi
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International Journal of Interactive Multimedia and Artificial Intelligence, 2021 Our study aims to review and analyze the most relevant studies in the image dehazing field. Many aspects have been deemed necessary to provide a broad understanding of various studies that have been examined through surveying the existing literature ...
Karrar Hameed Abdulkareem +6 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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Zero-Shot Remote Sensing Image Dehazing Based on a Re-Degradation Haze Imaging Model
Remote Sensing, 2022 Image dehazing is crucial for improving the advanced applications on remote sensing (RS) images. However, collecting paired RS images to train the deep neural networks (DNNs) is scarcely available, and the synthetic datasets may suffer from domain-shift ...
Jianchong Wei +4 more
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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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Remote Sensing Image Dehazing Based on an Attention Convolutional Neural Network
IEEE Access, 2022 Haze may affect the quality of optical remote sensing images, thus limiting the scope of their application. Remote sensing image dehazing has become important in remote sensing image preprocessing, promoting the use of remote sensing data and the ...
Zhijie He, Cailan Gong, Yong Hu, Lan Li
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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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