Results 1 to 10 of about 139,205 (117)

Self-supervised zero-shot dehazing network based on dark channel prior [PDF]

Frontiers of Optoelectronics, 2023
Most learning-based methods previously used in image dehazing employ a supervised learning strategy, which is time-consuming and requires a large-scale dataset. However, large-scale datasets are difficult to obtain.
Xinjie Xiao, Yuanhong Ren, Zhiwei Li, Nannan Zhang, Wuneng Zhou   +4 more
doaj   +2 more sources

Image Defogging Framework Using Segmentation and the Dark Channel Prior [PDF]

Entropy, 2021
Foggy images suffer from low contrast and poor visibility problem along with little color information of the scene. It is imperative to remove fog from images as a pre-processing step in computer vision.
Sabiha Anan, Mohammad Ibrahim Khan, Mir Md Saki Kowsar, Kaushik Deb, Pranab Kumar Dhar, Takeshi Koshiba   +5 more
doaj   +2 more sources

Efficient Traffic Video Dehazing Using Adaptive Dark Channel Prior and Spatial–Temporal Correlations [PDF]

Sensors, 2019
In order to restore traffic videos with different degrees of haziness in a real-time and adaptive manner, this paper presents an efficient traffic video dehazing method using adaptive dark channel prior and spatial-temporal correlations. This method uses
Tianyang Dong, Guoqing Zhao, Jiamin Wu, Yang Ye, Ying Shen   +4 more
doaj   +2 more sources

IMAGE FAST DEHAZING ALGORITHM BASED ON DARK CHANNEL PRIOR IMPROVEMENT [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020
Aiming at the long-running time and the defogging image darkening problem in the dark channel prior algorithm, a fast deaeration algorithm based on the guided filter and improved two-dimensional gamma function for dark channel prior image is proposed ...
J. W. Li, J. W. Li, L. Liu, J. W. Jiang, J. W. Jiang, Y. Hu, X. Q. Han, F. X. Li   +7 more
doaj   +1 more source

Dynamic Dark Channel Prior Dehazing with Polarization

Applied Sciences, 2023
For traditional dark channel prior (DCP) imaging through haze environments, intensity information acts as the carrier to acquire the reflective character of the dehazed target image. We introduce polarization as auxiliary information into the traditional
Haotong Suo, Jinge Guan, Miao Ma, Yongsheng Huo, Yaoyu Cheng, Naying Wei, Liying Zhang   +6 more
doaj   +1 more source

Single-Image Dehazing Using Extreme Reflectance Channel Prior

IEEE Access, 2021
Image dehazing algorithms based on dark channel prior principle have achieved good results for most scenes. However, the popular dark channel prior tends to underestimate transmissions of bright areas or objects, such as the skies, white areas and self ...
Yutong Zhang, Kun Gao, Junwei Wang, Xiaodian Zhang, Hong Wang, Zizheng Hua, Qiong Wu   +6 more
doaj   +1 more source

A Single Image Enhancement Technique Using Dark Channel Prior

Applied Sciences, 2021
In this paper, we propose a novel single image enhancement technique for defogging by using dark channel prior. The traditional dark channel prior methods for defogging have problems of high time complexity, edge effect, and failure of dark channel prior.
Cong Wang, Mingli Ding, Yongqiang Zhang, Lina Wang   +3 more
doaj   +1 more source

Region Adaptive Single Image Dehazing

Entropy, 2021
Image haze removal is essential in preprocessing for computer vision applications because outdoor images taken in adverse weather conditions such as fog or snow have poor visibility.
Changwon Kim
doaj   +1 more source

Efficient Sandstorm Image Enhancement Using the Normalized Eigenvalue and Adaptive Dark Channel Prior

Technologies, 2021
A sandstorm image has features similar to those of a hazy image with regard to the obtaining process. However, the difference between a sand dust image and a hazy image is the color channel balance.
Ho Sang Lee
doaj   +1 more source

Efficient Color Correction Using Normalized Singular Value for Duststorm Image Enhancement

J, 2022
A duststorm image has a reddish or yellowish color cast. Though a duststorm image and a hazy image are obtained using the same process, a hazy image has no color distortion as it has not been disturbed by particles, but a duststorm image has color ...
Ho-Sang Lee
doaj   +1 more source