DocumentCode :
2127332
Title :
Segmentation of Multi-spectral Satellite Images Based on Watershed Algorithm
Author :
Chen, Sheng ; Luo, Jiancheng ; Shen, Zhanfeng ; Hu, Xiaodong ; Gao, Lijing
Author_Institution :
Inst. of Remote Sensing Applic., Chinese Acad. of Sci., Beijing
fYear :
2008
fDate :
21-22 Dec. 2008
Firstpage :
684
Lastpage :
688
Abstract :
In this paper, a two-step segmentation algorithm is proposed based on watershed transform to segment multi-spectral satellite images. The first step is to use watershed segmentation to gain the initial over-segmented regions and the next one is region merging using a strategy of minimizing the overall heterogeneity increased within segments at each merging step. Textural, color and shape information of segments is used in the merging process. The study was conducted to explore an efficient approach to segment remote sensing images especially for high resolution multi-spectral satellite imagery. Experimental results show that the proposed method can produce quite good segmentation results and is very promising in segmentation of remotely sensing imagery in the future.
Keywords :
image colour analysis; image segmentation; image texture; minimisation; color information; image segmentation; multispectral satellite image; region merging; shape information; textural information; watershed algorithm; Color; Gray-scale; Image resolution; Image segmentation; Knowledge acquisition; Merging; Pixel; Remote sensing; Satellites; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3488-6
Type :
conf
DOI :
10.1109/KAM.2008.84
Filename :
4732915
Link To Document :
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