NDLI: Realtime dehazing using colour uniformity principle

Content Provider	IET Digital Library
Author	Kumar, Himanshu Gupta, Sumana Venkatesh, K. Subramanian
Abstract	Dehazing is an important process as it can significantly improve the performance of computer vision applications in outdoor environments. The two main requirements that an online dehazing system demands are low processing time and high visual range. The authors present a novel dehazing algorithm based on colour uniformity principle (CUP) which meets the desired requirements of a realtime implementation. Estimation of atmospheric scattering parameter and transmission map forms the key step in dehazing problem. At first, the authors use CUP to generate the transmission map and refine it further by Fast Guided Filter. They estimate the atmospheric scattering parameter with the help of the estimated transmission map. Experimental results show that the quality of dehazed output, produced in real-time using the proposed method, is comparable with the results achieved by the state of the art techniques. The proposed dehazing method produces reliable dehazed output in varying haze conditions, unlike current methods.
Starting Page	1931
Ending Page	1939
Page Count	9
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 11, Sep (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5240
Journal	IET Image Processing
Publisher Date	2019-07-09
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Atmospheric Scattering Parameter Estimation Colour Uniformity Principle Computer Vision And Image Processing Technique Computer Vision Application CUP Fast Guided Filter Image Colour Analysis Image Filtering Online Dehazing System Optical, Image And Video Signal Processing Outdoor Environments Parameter Estimation Transmission Map Estimation
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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