1. Single image dehazing using kernel regression model and dark channel prior
- Author
-
Wen-Hao Ying, Wei-Wei Qiao, Zhe Liu, and Cong-hua Xie
- Subjects
Channel (digital image) ,business.industry ,Computer science ,020207 software engineering ,Pattern recognition ,Improved method ,02 engineering and technology ,Real image ,Transmission (telecommunications) ,Signal Processing ,0202 electrical engineering, electronic engineering, information engineering ,Kernel regression ,020201 artificial intelligence & image processing ,Multimedia information systems ,Computer vision ,Artificial intelligence ,Electrical and Electronic Engineering ,Single image ,business - Abstract
Haze is one of the major factors that degrade outdoor images, and dehazing becomes an important issue in many applications. In order to address the problems of being unsmooth and the absence of neighbor information for the transmission estimation under Dark Channel Prior (DCP) framework, we proposed a new improved method using Kernel Regression Model (KRM) on local neighbor data. Firstly, the initial transmission in atmospheric light model is estimated by DCP. Secondly, the transmission is refined according to KRM. Experimental results on synthetic and real images show that our method can address this problem and has better dehazing results than several state-of-the-art methods.
- Published
- 2016