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