Results 101 to 110 of about 16,734,778 (159)
Densely integrated multi-branch attentive net for image dehazing
Ain Shams Engineering JournalSingle image dehazing is a fundamental but challenging task in image processing. Various deep learning-based methods have achieved great dehazing performance.
Ping Zong, Zhen Hua, Jinjiang Li
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Winscaleformer: Diffusion-Attention-Based Single Remote Sensing Image Dehazing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingThe Transformer architecture has demonstrated outstanding performance in image dehazing with its global modeling capability. However, it suffers from a quadratic computational complexity bottleneck when processing high-resolution images, leading to the ...
Nan Liu +6 more
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SAM2-Dehaze: Fusing High-Quality Semantic Priors with Convolutions for Single-Image Dehazing
SensorsSingle-image dehazing suffers from severe information loss and the under-constraint problem. The lack of high-quality robust priors leads to limited generalization ability of existing dehazing methods in real-world scenarios. To tackle this challenge, we
Sen Li, Jianchao Wang, Zhanqiang Huo
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Multiscale implicit frequency selective network for single-image dehazing
Image dehazing is aimed to reconstruct a clear latent image from a degraded image affected by haze. Although vision transformers have achieved impressive success in various computer vision tasks, the limitations in scale and quality of available datasets
Jia Jia, Jeongik Min, Zhibo Wang
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An improved image dehazing and enhancing method using dark channel prior
, 2015 In fog and haze weather conditions, the outdoor visibility is greatly reduced by the atmospheric scattering. Images taken in this weather suffer from serious degradation.
Luo HB(罗海波) +3 more
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Single Image Dehazing Using Scene Depth Ordering [PDF]
Images captured in hazy weather generally suffer from quality degradation, and many dehazing methods have been developed to solve this problem. However, single image dehazing problem is still challenging due to its ill-posed nature.
Ling, Pengyang +4 more
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Single image dehazing using deep neural networks [PDF]
, 2019 The rapid growth in computer vision applications that are affected by environmental conditions challenge the limitations of existing techniques. This is driving the development of new deep learning based vision techniques that are robust to environmental
Rahmani, Hossein +2 more
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U-shaped Vision Mamba for Single Image Dehazing [PDF]
Currently, Transformer is the most popular architecture for image dehazing, but due to its large computational complexity, its ability to handle long-range dependency is limited on resource-constrained devices.
Zheng, Zhuoran, Wu, Chen
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Joint Underwater Depth Estimation and Dehazing from a Single Image using Attention U-Net
International audienceUnderwater imaging presents unique challenges compared to open-air photography, primarily due to diminished visibility and geometric distortions, impeding the development of underwater Computer Vision (CV) and robotic vision ...
Asiyabi, Reza Mohammadi +2 more
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Depth Information Assisted Collaborative Mutual Promotion Network for Single Image Dehazing [PDF]
Recovering a clear image from a single hazy image is an open inverse problem. Although significant research progress has been made, most existing methods ignore the effect that downstream tasks play in promoting upstream dehazing. From the perspective of
Zhang, Yafei, Li, Huafeng, Zhou, Shen
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