Design and Implementation of Content-based Remote Sensing Image Retrieval System
Remote sensing images are important geo-spatial data resource and contain a wealth of information. This paper studies the content-based remote sensing images retrieval technology based on spectral, texture and shape features. The system adopts the inertia ratio and mean based on the spectral histogram to extract the spectral feature, takes the Gray-Level CoOccurrence Matrix (GLCM) algorithm to extract the texture feature, and uses the torque characteristics based on contour shape to extract the shape feature. The Euclidean distance method is taken for similarity measuring. The related experiments proved the effectiveness of each method.
remote sensing image feature extraction similarity measure
Zhao-Hong Liu Ying Xia Hai-Jing Huang Guo-Wei Li Xiao-Bo Luo
College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, China
国际会议
重庆
英文
54-56
2010-04-22（万方平台首次上网日期，不代表论文的发表时间）