Yang Bo
College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
Jia Zhen-Hong
College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
Qin Xi-zhong
College of Information Science and Engineering, Xinjiang University, Urumqi, 830046, China
Yang Jie
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, China
Hu Ying-jie
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, China
ABSTRACT
An improved maximum between-cluster variance (OTSU) algorithm was proposed to obtain the threshold adaptively in order to overcome the disadvantages of traditional Pal-King algorithm. The algorithm is able to globally enhance the remote sensing images but, for the relevance of neighboring pixel information is not taken into account in the improved algorithm, the visual effect of low contrast images is also not so good. The algorithm in this study can be used to realize the self-adaptive contrast enhancement when the relative entropy is regarded as a criterion. In order to test the enhancement effect of the proposed algorithm for remote sensing image, we choose 50 remote sensing images for test. Experimental results show that a good visual effect is obtained and the clarity, standard deviation has been improved greatly. Therefore, the algorithm is thought to be an effective ways to get better visual effects and more obvious detailed information.
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How to cite this article
Yang Bo, Jia Zhen-Hong, Qin Xi-zhong, Yang Jie and Hu Ying-jie, 2013. Remote Sensing Image Enhancement Based on Relative Entropy and Fuzzy Algorithm. Journal of Applied Sciences, 13: 2394-2398.
DOI: 10.3923/jas.2013.2394.2398
URL: https://scialert.net/abstract/?doi=jas.2013.2394.2398
DOI: 10.3923/jas.2013.2394.2398
URL: https://scialert.net/abstract/?doi=jas.2013.2394.2398
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