Title :
Fusion of multisensor and multitemporal data in remote-sensing image analysis
Author :
Bruzzone, Lorenzo ; Serpico, Sebastiano B.
Author_Institution :
Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy
Abstract :
The authors address both the classification and the detection of changes in multitemporal and multisensor remote-sensing images. They propose a technique that is based on the compound classification rule for minimum error. The basic idea of such a technique was presented by L. Bruzzone et al. (1997), where it was applied to the detection of changes in images acquired by a single optical sensor. The purpose of the present paper is to present an improved version of the authors´ technique and to highlight its potentialities for the analysis of multisensor images by reporting on experiments with a real data set
Keywords :
geophysical signal processing; geophysical techniques; image classification; image sequences; remote sensing; sensor fusion; change detection; compound classification rule; geophysical measurement technique; image analysis; image classification; image fusion; image processing; image sequence; land surface; minimum error; multisensor data; multisensor image; multitemporal data; remote sensing; sensor fusion; terrain mapping; Electronic mail; Image analysis; Image sensors; Neural networks; Optical sensors; Pixel; Remote sensing; Training data;
Conference_Titel :
Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS '98. 1998 IEEE International
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4403-0
DOI :
10.1109/IGARSS.1998.702836
