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Semi-Supervised Image Dehazing
IEEE Transactions on Image Processing, 2020We present an effective semi-supervised learning algorithm for single image dehazing. The proposed algorithm applies a deep Convolutional Neural Network (CNN) containing a supervised learning branch and an unsupervised learning branch. In the supervised branch, the deep neural network is constrained by the supervised loss functions, which are mean ...
Lerenhan Li +6 more
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On parallelisation of image dehazing with OpenMP
International Journal of Embedded Systems, 2019In this paper, we present our learning experience on the design and implementation of image dehazing parallel code with OpenMP developed from existing fast sequential version. The aim of this work is to present an analysis of a case study showing the development of parallel haze removal with practical and efficient use of shared memory multi-core ...
Tien-Hsiung Weng +4 more
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An Efficient Image Dehazing Method
2012 Sixth International Conference on Genetic and Evolutionary Computing, 2012A novel efficient dehazing technique for image reconstruction from single haze image is proposed in this paper. We employ an effective haze detector to detect the hazy image, and an efficient contrast enhancement technique for color images to reconstruct the hazy image.
Chih-Yuan Lien +2 more
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Dehazing for images with sun in the sky
Journal of Electronic Imaging, 2019<p>Image dehazing is one of the most important image processing methods and it is widely used in daily application. A large number of dehazing algorithms have been proposed in recent years. In order to solve the problem that the dehazing performances of the classic dark channel prior methods for hazy images with the sun are bad, we propose a ...
Fangyu Hu +4 more
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No-reference image quality assessment for dehazed images
Journal of Electronic Imaging, 2022Traditional image quality prediction methods require the pristine image as a reference, such as structural similarity. However, it is difficult to provide a haze-free image as a reference when predicting the quality of the dehazed image. Therefore, it is necessary to use a no-reference image quality assessment (NR-IQA) method.
Bin Ji +4 more
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An efficient method for image dehazing
2016 IEEE International Conference on Image Processing (ICIP), 2016Hazy images hinder image understanding in many applications such as autonomous vehicle. In this paper, we propose an efficient method to improve image quality of hazy images. Our method estimates the transmission function based on a linear model that allows efficient computation and employs quadtree to search for a region that best represents the ...
Wencheng Wang 0002 +4 more
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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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2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
Haze limits visibility and reduces image contrast in outdoor images. The degradation is different for every pixel and depends on the distance of the scene point from the camera. This dependency is expressed in the transmission coefficients, that control the scene attenuation and amount of haze in every pixel.
Dana Berman, Tali Treibitz, Shai Avidan
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Haze limits visibility and reduces image contrast in outdoor images. The degradation is different for every pixel and depends on the distance of the scene point from the camera. This dependency is expressed in the transmission coefficients, that control the scene attenuation and amount of haze in every pixel.
Dana Berman, Tali Treibitz, Shai Avidan
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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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ACM Transactions on Graphics, 2008
In this paper we present a new method for estimating the optical transmission in hazy scenes given a single input image. Based on this estimation, the scattered light is eliminated to increase scene visibility and recover haze-free scene contrasts. In this new approach we formulate a refined image formation model that accounts for surface shading in ...
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In this paper we present a new method for estimating the optical transmission in hazy scenes given a single input image. Based on this estimation, the scattered light is eliminated to increase scene visibility and recover haze-free scene contrasts. In this new approach we formulate a refined image formation model that accounts for surface shading in ...
exaly +2 more sources