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Advanced Intelligent SystemsImage dehazing, a fundamental computer vision task, is crucial for the stability of multiple downstream systems. Traditional methods have limited generalization, while deep learning methods face bottlenecks like error accumulation and poor adaptability ...
Ruipeng Wang +4 more
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Single image dehazing for a variety of haze scenarios using back projected pyramid network [PDF]
ECCV Workshops, 2020 Learning to dehaze single hazy images, especially using a small training dataset is quite challenging. We propose a novel generative adversarial network architecture for this problem, namely back projected pyramid network (BPPNet), that gives good ...
Ayush Singh, A. Bhave, D. K. Prasad
semanticscholar +3 more sources
Remote SensingRemote sensing image dehazing aims to enhance the visibility of hazy images and improve the quality of remote sensing imagery, which is essential for various applications such as object detection and classification.
Yitong Zheng +4 more
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Progressive Pruning of Light Dehaze Networks for Static Scenes
Applied SciencesThis paper introduces an progressive pruning method for Light DeHaze Networks, focusing on a static scene captured by a fixed camera environments. We develop a progressive pruning algorithm that aims to reduce computational complexity while maintaining ...
Byeongseon Park +3 more
doaj +2 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
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MathematicsSingle-image dehazing of high-voltage power transmission lines (HPTLs) using deep learning methods confronts two critical challenges: the non-homogeneous haze distribution in HPTL images and the unavailability of paired clear images for supervised ...
Xiaoyi Cuan +4 more
doaj +2 more sources
ED-Dehaze Net: Encoder and Decoder Dehaze Network [PDF]
, 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 ...
Zhang, Hongqiang +3 more
core +4 more sources
UCL-Dehaze: Toward Real-World Image Dehazing via Unsupervised Contrastive Learning [PDF]
IEEE Transactions on Image Processing, 2022 While the wisdom of training an image dehazing model on synthetic hazy data can alleviate the difficulty of collecting real-world hazy/clean image pairs, it brings the well-known domain shift problem.
Yongzhen Wang +7 more
semanticscholar +1 more source
Deep Generative Models for Automated Dehazing Remote Sensing Satellite Images [PDF]
E3S Web of Conferences, 2023 Remote Sensing (RS) is the process of observing and measuring the physical features of an area from a distance by monitoring its reflected and emitted radiation, usually from a satellite or aircraft.
Poornima E. +5 more
doaj +1 more source
Enhanced Variational Image Dehazing [PDF]
SIAM Journal on Imaging Sciences, 2015 Images obtained under adverse weather conditions, such as haze or fog, typically exhibit low contrast and faded colors, which may severely limit the visibility within the scene. Unveiling the image structure under the haze layer and recovering vivid colors out of a single image remains a challenging task, since the degradation is depth-dependent and ...
Adrian Galdran +3 more
openaire +2 more sources