DocumentCode :
2370448
Title :
The method of image restoration in the environments of dust
Author :
Wang, Yuanyu ; Li, Yuanzong ; Zhang, Tianxu
Author_Institution :
Dept. of Comput. Fundamental Educ., TaiYuan Univ. of Technol., Taiyuan, China
fYear :
2010
fDate :
4-7 Aug. 2010
Firstpage :
294
Lastpage :
298
Abstract :
In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, a particle swarm optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with dual threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.
Keywords :
aerosols; air pollution; dust; environmental science computing; image restoration; particle swarm optimisation; atmospheric light; dark channel prior principle; dual threshold; dust environments; exposure parameters; first-order multiple scattering method; image degradation problem; image evaluation; image restoration method; kirsch operator; optimization algorithm; particle swarm optimization algorithm; target recognition; Atmospheric modeling; Degradation; Image edge detection; Image restoration; Optical imaging; Optical scattering; Dark channel prior; dust; image quality evaluation function; multiple scattering; particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation (ICMA), 2010 International Conference on
Conference_Location :
Xi´an
ISSN :
2152-7431
Print_ISBN :
978-1-4244-5140-1
Electronic_ISBN :
2152-7431
Type :
conf
DOI :
10.1109/ICMA.2010.5589057
Filename :
5589057
Link To Document :
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