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Recent advances in image dehazing
IEEE/CAA Journal of Automatica Sinica, 2017Images captured in hazy or foggy weather conditions can be seriously degraded by scattering of atmospheric particles, which reduces the contrast, changes the color, and makes the object features difficult to identify by human vision and by some outdoor computer vision systems.
Wencheng Wang 0002, Xiaohui Yuan 0001
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Semi-Supervised image dehazing network
The Visual Computer, 2021A semi-supervised image dehazing network was proposed which consists of the supervised branch and the unsupervised branch. In the supervision branch, the encoding–decoding neural network is used as the network structure, and the network is constrained by the supervision loss. In the unsupervised branch, two similar sub-networks are used to estimate the
Shunmin An +4 more
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Frequency component vectorisation for image dehazing
Journal of Experimental & Theoretical Artificial Intelligence, 2020Image captured in bad weather conditions confines scene prominence, appears grey and diminishes image contrast.
Muhammad Nazeer +6 more
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Weakly supervised single image dehazing
Journal of Visual Communication and Image Representation, 2020Abstract Single image dehazing is a critical image pre-processing step for many practical vision systems. Most existing dehazing methods solve this problem utilizing various of hand-crafted priors or by supervised training on the synthetic hazy image information (such as haze-free image, transmission map and atmospheric light).
Cong Wang 0018 +3 more
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Fast single image dehazing algorithm
2014 International Conference on Audio, Language and Image Processing, 2014Image captured in foggy weather conditions often suffer from poor visibility. In this paper, we proposed an improved method of dark channel prior. Using the semi-inverse algorithm, the proposed algorithm can accurately identify the foggy area and effectively obtain the global atmospheric light. Then the transmission is obtained according to the minimum
Xipan Lu, Guoyun Lv, Tao Lei
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Single Image Dehazing with Lab Analysis
Proceedings of the 3rd International Conference on Multimedia and Image Processing, 2018Images acquired by visual framework are genuinely corrupted under cloudy and foggy climate, therefore affecting detection, tracking and recognition of images. Thus, restoring the true scene from a hazy image is of great significance. To solve this problem, this paper presents a real-time effective dehazing algorithm for hazy surveillance images.
Jehoiada Kofi Jackson +2 more
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Single Image Dehazing via Image Generating
2018Outdoor images taken in bad weather conditions often suffer from poor visibility. However, single image haze removal is an ill-posed problem, because the number of the equations is smaller than the number of unknowns. In this paper, a deep learning-based method, called Dehaze CNN, is proposed to estimate a clear image patch from a hazy image patch ...
Shengdong Zhang +2 more
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Transformer based Image Dehazing
2022 16th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), 2022Patricia L. Suárez +3 more
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Image Dehazing Using Regularized Optimization
2014The presence of haze shifts the color and degrades the visibility of outdoor scenes in digital images. In this paper, we propose a novel and effective optimization algorithm for single image dehazing. We first formulate the dehazing model into a linear convex optimization problem, and we develop its cost function based on two basic observations: first,
Jiaxi He, Cishen Zhang, Ifat-Al Baqee
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Image Dehazing Based on Luminance Stretching
2019 International Conference on Information Technology (ICIT), 2019In this work, a method is proposed to restore the visual effects of hazy images with sky using dark channel prior (DCP) and luminance stretching (LS). The transmissions for the non-sky and sky regions of a hazy image is calculated by DCP and LS respectively.
Geet Sahu, Ayan Seal
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