Title :
Sensitive fusion and segmentation of geophysical images in a complex space of information features on base SVM methodology
Author :
Akhmetshin, A.M.
Author_Institution :
Dniepropetrovsk Nat. Univ., Ukraine
Abstract :
The present paper outlines a new effective method of multiparameter images sensitive fusion. The support vector machines (SVM) methodology is used.
Keywords :
geophysical signal processing; geophysical techniques; image segmentation; learning automata; multidimensional signal processing; remote sensing; sensor fusion; SVM method; complex space information features; geophysical measurement technique; image fusion; image processing; image segmentation; land surface; multidimensional image processing; multiparameter images; remote sensing; sensitive fusion; support vector machine; support vector machines; terrain mapping; Brightness; Coordinate measuring machines; Geophysical measurements; Image analysis; Image fusion; Image segmentation; Magnetic analysis; Multidimensional systems; Support vector machines; Visualization;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International
Print_ISBN :
0-7803-7536-X
DOI :
10.1109/IGARSS.2002.1026561
