MODELING MULTISOURCE REMOTE SENSING IMAGE CLASSIFIER BASED ON THE MDL PRINCIPLE: THEORETICAL ASPECTS

摘要：

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.

关键词： Minimum Description Length remote sensing image classification technique model optimization

作者: QIAN YIN PING GUO ZHI-YONG YUAN ZU-KUAN WEI WEN-YI ZENG

作者单位: Image Processing & Pattern Recognition Laboratory, Beijing Normal University, Beijing 100875, China School of Computer Science, Wuhan University, Wuhan 430079, China School of Comp.Sci.& Engr., University of Electronic Science and Technology of China, Chengdu 610054

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 3497-3502

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）