Results 161 to 170 of about 11,243,828 (208)
Some of the next articles are maybe not open access.
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 ...
Raanan Fattal
exaly +2 more sources
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 ...
Raanan Fattal
exaly +2 more sources
The Visual Computer, 2021
Image dehazing aims to remove the haze noise and restore the image content from hazy images. It is a challenging task because of the unbalanced distribution of the haze noise and the variety of the image contents. Most existing methods apply convolutional neural networks to learn the dehazing process by blind end-to-end training, which relies on the ...
Fei Yang, Qian Zhang
openaire +1 more source
Image dehazing aims to remove the haze noise and restore the image content from hazy images. It is a challenging task because of the unbalanced distribution of the haze noise and the variety of the image contents. Most existing methods apply convolutional neural networks to learn the dehazing process by blind end-to-end training, which relies on the ...
Fei Yang, Qian Zhang
openaire +1 more source
IEEE Transactions on Image Processing, 2020
In this paper, we study two less-touched challenging problems in single image dehazing neural networks, namely, how to remove haze from a given image in an unsupervised and zeroshot manner. To the ends, we propose a novel method based on the idea of layer disentanglement by viewing a hazy image as the entanglement of several "simpler" layers, i.e., a ...
Boyun Li +5 more
openaire +2 more sources
In this paper, we study two less-touched challenging problems in single image dehazing neural networks, namely, how to remove haze from a given image in an unsupervised and zeroshot manner. To the ends, we propose a novel method based on the idea of layer disentanglement by viewing a hazy image as the entanglement of several "simpler" layers, i.e., a ...
Boyun Li +5 more
openaire +2 more sources
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
openaire +3 more sources
A confidence prior for image dehazing
Pattern Recognition, 2021Abstract By sorting channel-minimized values in an ascending order, we individually put the values of several existing image dehazing priors on the curve of sorted values to propose a framework for unifying and understanding these priors. Then we propose a confidence ratio to specify the probability of each channel-minimized value within a range, and
Feiniu Yuan +4 more
openaire +2 more sources
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
openaire +1 more source
Dehazing for images with sun in the sky
Journal of Electronic Imaging, 2019Image 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 dehazing ...
Fangyu Hu +4 more
openaire +2 more sources
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
openaire +2 more sources
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
openaire +1 more source
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
openaire +1 more source
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
openaire +1 more source