DocumentCode :
1616168
Title :
A Hybrid PSO-ISODATA Algorithm for Remote Sensing Image Segmentation
Author :
Cai-hong, Ma ; Qin, Dai ; Shi-Bin, Liu
Author_Institution :
Center for Earth Obs. & Digital Earth, Grad. Univ. of Chinese Acad. of Sci., Beijing, China
fYear :
2012
Firstpage :
1371
Lastpage :
1375
Abstract :
Remote sensing image segmentation is a very important process in the remote sensing information extraction area. In order to avoid disadvantages of the current algorithms, this paper proposed a new algorithm combined PSO and ISODATA. The hybrid PSO-ISODATA algorithm first changes the color space of the images. Then, the initial cluster number is determined by the combined algorithm, and finally, the automatic segmentation of remote sensing images is achieved through multiple iterations. Many segmentation experiments on different spatial resolution remote sensing images using the proposed methods in this paper, we also compared the method to the current existing methods such as K-means, PSO, ISODATA, and PSO-K-means methods. The results show that the hybrid PSO-ISODATA algorithm can determine the initial cluster number adaptively, avoid the local optima of K-means and ISODATA algorithms, increase the searching capability of PSO, and the segmentation results are much more close to the actual situation.
Keywords :
geophysical image processing; image colour analysis; image resolution; image segmentation; particle swarm optimisation; remote sensing; PSO-K-means methods; hybrid PSO-ISODATA algorithm; image color space; initial cluster number; particle swarm optimization; remote sensing image segmentation; remote sensing information extraction area; spatial resolution remote sensing images; Classification algorithms; Clustering algorithms; Equations; Image color analysis; Image segmentation; Remote sensing; Vectors; ISODATA algorithm; PSO algorithm; feature distance; remote sensing image segmentation formatting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4673-1450-3
Type :
conf
DOI :
10.1109/ICICEE.2012.363
Filename :
6322652
Link To Document :
بازگشت