Modeling multisource remote sensing image classifier based on the MDL principle: Theoretical aspects

Qian Yin Qian Yin,Zhi-Yong Yuan Zhi-Yong Yuan,Ping Guo Ping Guo,Zu-Kuan Wei Zu-Kuan Wei,Wen-Yi Zeng Wen-Yi Zeng

doi:10.1109/icmlc.2008.4621009

Modeling multisource remote sensing image classifier based on the MDL principle: Theoretical aspects

Qian Yin Qian Yin, Zhi-Yong Yuan Zhi-Yong Yuan + Show 3 more

https://doi.org/10.1109/icmlc.2008.4621009

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Publication Date: Jul 1, 2008

Citations: 17

Affiliation: Beijing Normal University, Wuhan University, University of Electronic Science and Technology of China

#Minimum Description Length Principle #Minimum Description Length + Show 8 more

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Abstract

A theoretical study for modeling technique of the remote sensing image classification based on the minimum description length (MDL) principle is presented in the paper. According to the MDL principle, modeling problem is an optimization procedure to find the shortest expected code length. Kullback-Leibler (KL) divergence is adopted as the system cost function to measure expected codelength, and the codelength will be the model we desired. The advantage of using the MDL principle to build appropriate model is analyzed theoretically, model optimization technique also is described.

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