Nighttime Image Dehazing by Render
Journal of Imaging, 2023 Nighttime image dehazing presents unique challenges due to the unevenly distributed haze caused by the color change of artificial light sources. This results in multiple interferences, including atmospheric light, glow, and direct light, which make the ...
Zheyan Jin +3 more
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Enhancement of Marine Lantern’s Visibility under High Haze Using AI Camera and Sensor-Based Control System [PDF]
Micromachines, 2023 This thesis describes research to prevent maritime safety accidents by notifying navigational signs when sea fog and haze occur in the marine environment. Artificial intelligence, a camera sensor, an embedded board, and an LED marine lantern were used to
Jehong An +6 more
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SAM2-Dehaze: Fusing High-Quality Semantic Priors with Convolutions for Single-Image Dehazing [PDF]
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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Dehaze-attention: enhancing image dehazing with a multi-scale, attention-based deep learning framework [PDF]
Scientific ReportsOver the last decade, significant progress has been made in image dehazing, particularly with the advent of deep learning-based methods. However, many of the existing dehazing approaches face critical limitations such as relying on assumptions that fail ...
Hao Huang +4 more
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Efficient Dehazing with Recursive Gated Convolution in U-Net: A Novel Approach for Image Dehazing [PDF]
Journal of Imaging, 2023 Image dehazing, a fundamental problem in computer vision, involves the recovery of clear visual cues from images marred by haze. Over recent years, deploying deep learning paradigms has spurred significant strides in image dehazing tasks.
Zhibo Wang +3 more
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DSNet enables feature fusion and detail restoration for accurate object detection in foggy conditions [PDF]
Scientific ReportsIn real-world scenarios, adverse weather conditions can significantly degrade the performance of deep learning-based object detection models. Specifically, fog reduces visibility, complicating feature extraction and leading to detail loss, which impairs ...
Zhiyong Jing +5 more
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Online knowledge distillation network for single image dehazing [PDF]
Scientific Reports, 2022 Single image dehazing, as a key prerequisite of high-level computer vision tasks, catches more and more attentions. Traditional model-based methods recover haze-free images via atmospheric scattering model, which achieve favorable dehazing effect but ...
Yunwei Lan +7 more
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Physical-model guided self-distillation network for single image dehazing [PDF]
Frontiers in Neurorobotics, 2022 MotivationImage dehazing, as a key prerequisite of high-level computer vision tasks, has gained extensive attention in recent years. Traditional model-based methods acquire dehazed images via the atmospheric scattering model, which dehazed favorably but ...
Yunwei Lan +5 more
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ICAFormer: An Image Dehazing Transformer Based on Interactive Channel Attention [PDF]
SensorsSingle image dehazing is a fundamental task in computer vision, aiming to recover a clear scene from a hazy input image. To address the limitations of traditional dehazing algorithms—particularly in global feature association and local detail ...
Yanfei Chen +6 more
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