DocumentCode :
2605828
Title :
Image restoration using prior information physics model
Author :
Xing, Le ; Yang, Lianhe
Author_Institution :
Sch. of Comput. Sci. & Software Eng., Tianjin Polytech. Univ., Tianjin, China
Volume :
2
fYear :
2011
fDate :
15-17 Oct. 2011
Firstpage :
786
Lastpage :
789
Abstract :
Images captured in haze weather suffer from serious degradation of color and contrast due to incident light scattering and absorption. However, most of the existing methods which are based on depth information could not get satisfactory haze removal effect. In this paper, a simple but effective method is presented - image restoration using improved dark channel prior. The dark channel prior is based on a large number of statistical information. Most local patches in haze-free outdoor image contain some pixels which have very low intensities in at least one color channel. Using this prior with the haze image model, we can recover a high quality haze-free image. Image or video taken in haze day is restored using guided filtering finally. The simulation experiments based on Matlab demonstrate that the method is easy to use and able to improve quality of the images in haze efficiently. Meantime, the method can meet certain practical requirements.
Keywords :
image colour analysis; image restoration; statistical analysis; Matlab; captured images; color channel; dark channel; guided filtering; haze image model; haze weather; image restoration; incident light absorption; incident light scattering; prior information physics model; statistical information; Atmospheric modeling; Computational modeling; Image color analysis; Image restoration; Laplace equations; Mathematical model; dark channel prior; image restoration; physics model; video defog;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2011 4th International Congress on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9304-3
Type :
conf
DOI :
10.1109/CISP.2011.6100370
Filename :
6100370
Link To Document :
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