Title :
Classification of remotely sensed images using mathematical morphology
Author :
Wang, Demin ; He, Dong-Chen ; Morin, Denis
Author_Institution :
Centre d´´Appl. et de Recherches en Teledetection, Sherbrooke Univ., Que., Canada
Abstract :
Presents the supervised classification result of a remotely sensed image using only its spatial characteristics. A SPOT panchromatic image is decomposed into three scale bands, instead of spectral bands, by multiscale morphological decomposition. Each scale band contains the objects and texture primitives of certain sizes of the image. The classification is performed by applying the maximum-likelihood classifier to local gray level means of the scale bands
Keywords :
geophysical signal processing; geophysical techniques; image classification; image colour analysis; image texture; mathematical morphology; maximum likelihood estimation; optical information processing; remote sensing; SPOT panchromatic image; geophysical measurement technique; gray level; image classification; image texture; mathematical morphology; maximum-likelihood classifier; multiscale morphological decomposition; optical imaging visible multispectral method; remote sensing; scale band; spatial characteristics; supervised classification; terrain mapping land surface; Classification algorithms; Data mining; Electronic mail; Helium; Image decomposition; Morphology; Multispectral imaging; Satellites; Spatial resolution; Visual perception;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1994. IGARSS '94. Surface and Atmospheric Remote Sensing: Technologies, Data Analysis and Interpretation., International
Conference_Location :
Pasadena, CA
Print_ISBN :
0-7803-1497-2
DOI :
10.1109/IGARSS.1994.399516
