Results 11 to 20 of about 5,362 (169)
Deep guided transformer dehazing network
Scientific Reports, 2023 Single image dehazing has received a lot of concern and achieved great success with the help of deep-learning models. Yet, the performance is limited by the local limitation of convolution.
Shengdong Zhang +5 more
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ED-Dehaze Net: Encoder and Decoder Dehaze Network.
International Journal of Interactive Multimedia and Artificial Intelligence, 2022 The presence of haze will significantly reduce the quality of images, such as resulting in lower contrast and blurry details. This paper proposes a novel end-to-end dehazing method, called Encoder and Decoder Dehaze Network (ED-Dehaze Net), which contains a Generator and a Discriminator. In particular, the Generator uses an Encoder-Decoder structure to
Zhang, Hongqi +3 more
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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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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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Single Image Dehazing Using Global Illumination Compensation
Sensors, 2022 The existing dehazing algorithms hardly consider background interference in the process of estimating the atmospheric illumination value and transmittance, resulting in an unsatisfactory dehazing effect. In order to solve the problem, this paper proposes
Junbao Zheng +3 more
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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.
Bertalmío, Marcelo +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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Single Image Dehazing Using End-to-End Deep-Dehaze Network [PDF]
Electronics, 2020 Haze is a natural distortion to the real-life images due to the specific weather conditions. This distortion limits the perceptual fidelity, as well as information integrity, of a given image. Image dehazing for the observed images is a complicated task because of its ill-posed nature.
Masud An-Nur Islam Fahim, Ho Yub Jung
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Sparse Depth-Guided Image Enhancement Using Incremental GP with Informative Point Selection
Sensors, 2023 We propose an online dehazing method with sparse depth priors using an incremental Gaussian Process (iGP). Conventional approaches focus on achieving single image dehazing by using multiple channels.
Geonmo Yang +3 more
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Enhanced Variational Image Dehazing [PDF]
SIAM Journal on Imaging Sciences, 2015 Images obtained under adverse weather conditions, such as haze or fog, typically/nexhibit low contrast and faded colors, which may severely limit the visibility within the scene. Unveiling/nthe image structure under the haze layer and recovering vivid colors out of a single image/nremains a challenging task, since the degradation is depth-dependent and
Adrian Galdran +3 more
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