DocumentCode :
85935
Title :
A No-Reference Perceptual Based Contrast Enhancement Metric for Ocean Scenes in Fog
Author :
Gibson, Kristofor B. ; Nguyen, Truong Q.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of California San Diego, La Jolla, CA, USA
Volume :
22
Issue :
10
fYear :
2013
fDate :
Oct. 2013
Firstpage :
3982
Lastpage :
3993
Abstract :
In this paper, we develop a perceptually based contrast enhancement metric as a means to solve the problem of autonomously enhancing images degraded by fog that are perceptually pleasing to humans. A learning based approach is considered to develop the contrast enhancement using human observations and low-level contrast enhancement metrics based on the human vision system. In addition, we provide new low-level metrics based on the physics of the scene to improve the performance of existing contrast enhancement metrics. This paper shows that a contrast enhancement metric can be designed to mimic human preference.
Keywords :
fog; image enhancement; learning (artificial intelligence); visual perception; autonomous image enhancement; fog; human vision system; learning based approach; mimic human preference; no-reference perceptual based contrast enhancement metric; ocean scene; AdaBoost; Contrast enhancement metric;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2013.2265884
Filename :
6522869
Link To Document :
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