Title :
Modeling multisource remote sensing image classifier based on the MDL principle: Theoretical aspects
Author :
Yin, Qian ; Guo, Ping ; Yuan, Zhi-Yong ; Wei, Zu-kuan ; Zeng, Wen-yi
Author_Institution :
Image Process. & Pattern Recognition Lab., Beijing Normal Univ., Beijing
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.
Keywords :
geophysical signal processing; image classification; remote sensing; Kullback-Leibler divergence; MDL principle; minimum description length; multisource remote sensing image classifier; optimization technique; shortest expected code length; Atmospheric modeling; Context modeling; Cybernetics; Feature extraction; Image classification; Image recognition; Machine learning; Power system modeling; Remote monitoring; Remote sensing; Minimum Description Length; classification technique; model optimization; remote sensing image;
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
DOI :
10.1109/ICMLC.2008.4621009
