Title :
Multi-sensor data classification in remote sensing using MRF regional growing algorithm
Author :
Lee, Sanghoon ; Suh, Asook ; Jung, Myunghee
Author_Institution :
Dept. of Ind. Eng., Kyungwon Univ., Kyunggi, South Korea
Abstract :
This paper studies a multi-stage method using hierarchical clustering for unsupervised image classification to classify the land-cover using remotely-sensed data from multiple sensors. The multi-stage method performs region-growing segmentation using a hierarchical clustering procedure which makes use of the spatial contextual information by characterizing geophysical connectedness of digital image structure with Markov random field
Keywords :
Markov processes; airborne radar; image classification; image segmentation; pattern clustering; remote sensing by radar; sensor fusion; synthetic aperture radar; terrain mapping; unsupervised learning; MRF regional growing algorithm; Markov random field; digital image structure; geophysical connectedness; hierarchical clustering; land-cover; multi-sensor data classification; multi-stage method; region-growing segmentation; remote sensing; remotely sensed data; spatial contextual information; unsupervised image classification; Bayesian methods; Geophysical measurements; Image classification; Image segmentation; Image sensors; Layout; Pixel; Remote sensing; Sensor fusion; Smoothing methods;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-7031-7
DOI :
10.1109/IGARSS.2001.978194
