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SINGLE IMAGE DEHAZING USING PHYSICS-INFORMED CONVOLUTIONAL AUTOENCODER
Модели, системы, сети в экономике, технике, природе и обществеBackground. Generally, haze can be considered to be one of the most fundamental phenomena causing image visibility degradation. Numerous haze removal approaches have been proposed and most of them have achieved significant progress.
A.V. Kozhevnikova, M.A. Mitrokhin
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A variational framework for single image dehazing
Comunicació presentada a: European Conference on Computer Vision Workshops (ECCV 2014), celebrada del 6 al 7 de setembre de 2014 a Zurich, Suïssa.Images captured under adverse weather conditions, such as haze or fog, typically exhibit low contrast and ...
Pardo, David +3 more
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Single Image Dehazing Using Invariance Principle
IEICE Transactions on Information and Systems, 2017 Mingye Ju +3 more
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Benchmarking Single-Image Dehazing and Beyond [PDF]
IEEE Transactions on Image Processing, 2019 IEEE Transactions on Image Processing(TIP 2019)
Wenqi Ren, Dacheng Tao, Zhangyang Wang
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Vision Transformers for Single Image Dehazing
IEEE Transactions on Image Processing, 2023 Image dehazing is a representative low-level vision task that estimates latent haze-free images from hazy images. In recent years, convolutional neural network-based methods have dominated image dehazing. However, vision Transformers, which has recently made a breakthrough in high-level vision tasks, has not brought new dimensions to image dehazing. We
Yuda Song, Hui Qian, Zhuqing He
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Benchmarking Single Image Dehazing Methods
SN Computer Science, 2021Images acquired under hazy environment need processing for improving their contrast and color fidelity. Haze removal or dehazing is an important pre-processing stage in the field of computer vision and video applications. Several techniques have been proposed in the literature for dehazing outdoor images.
Deepa Nair, Praveen Sankaran
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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 ...
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Contrastive Learning for Compact Single Image Dehazing [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Single image dehazing is a challenging ill-posed problem due to the severe information degeneration. However, existing deep learning based dehazing methods only adopt clear images as positive samples to guide the training of dehazing network while negative information is unexploited.
Zhizhong Zhang, Yuan Xie, Yanyun Qu
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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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Pre-processing for single image dehazing
Signal Processing: Image Communication, 2020Abstract Existing single image haze removal algorithms could suffer from noise amplification in sky regions and possible color distortion in restored images due to noise in haze images. In this paper, a simple pre-processing tool is introduced for single image haze removal so as to reduce the effect of noise in the restored image.
Minmin Yang +3 more
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