ED-Dehaze Net: Encoder and Decoder Dehaze Network. [PDF]
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 ...
Hongqi Zhang +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
doaj +2 more sources
Region Adaptive Single Image Dehazing [PDF]
Entropy, 2021 Image haze removal is essential in preprocessing for computer vision applications because outdoor images taken in adverse weather conditions such as fog or snow have poor visibility.
Changwon Kim
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DeSmoke-LAP: improved unpaired image-to-image translation for desmoking in laparoscopic surgery. [PDF]
Int J Comput Assist Radiol Surg, 2022 Purpose Robotic-assisted laparoscopic surgery has become the trend in medicine thanks to its convenience and lower risk of infection against traditional open surgery.
Pan Y +5 more
europepmc +3 more sources
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
doaj +2 more sources
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
doaj +3 more sources
Efficient Haze Removal from a Single Image Using a DCP-Based Lightweight U-Net Neural Network Model [PDF]
SensorsIn this paper, we propose a lightweight U-net architecture neural network model based on Dark Channel Prior (DCP) for efficient haze (fog) removal with a single input. The existing DCP requires high computational complexity in its operation.
Yunho Han +5 more
doaj +2 more sources
Deep guided transformer dehazing network. [PDF]
Sci Rep, 2023 AbstractSingle 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. To address such a limitation, we design a novel deep learning dehazing model by combining the transformer and guided filter, which is called as Deep Guided ...
Zhang S +5 more
europepmc +4 more sources