DocumentCode :
684270
Title :
Hyperspectral image clustering method based on Artificial Bee Colony algorithm
Author :
Xu Sun ; Lina Yang ; Bing Zhang ; Lianru Gao ; Liang Zhang
Author_Institution :
Inst. of Remote Sensing & Digital Earth, Beijing, China
fYear :
2013
fDate :
19-21 Oct. 2013
Firstpage :
106
Lastpage :
109
Abstract :
Pixel clustering is a common hyperspectral image processing technique. Its process is to find the appropriate cluster centers and assign each pixel to a center according to a certain metric. Artificial Bee Colony (ABC) algorithm based pattern clustering is proved to have better performance than traditional clustering methods such as K-means. Therefore, studies on hyperspectral image clustering method based on ABC algorithm are done. The target function and feasible solution space are determined, and the complete process is given. The proposed algorithm and other algorithms are compared and analyzed with the use of two sets of real hyperspectral remote sensing data and ground survey results.
Keywords :
hyperspectral imaging; image recognition; pattern clustering; ABC algorithm; K-means; artificial bee colony algorithm; ground survey; hyperspectral image clustering method; hyperspectral remote sensing data; pattern clustering; target function; Artificial Bee Colony; Clustering; Hyperspectral image;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computational Intelligence (ICACI), 2013 Sixth International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-6341-9
Type :
conf
DOI :
10.1109/ICACI.2013.6748483
Filename :
6748483
Link To Document :
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