DocumentCode :
3062626
Title :
A Quantum-Modeled Artificial Bee Colony clustering algorithm for remotely sensed multi-band image segmentation
Author :
Chih-Cheng Hung ; Casper, Ellis ; Bor-Chen Kuo ; Wenping Liu ; Jung, Edward ; Ming Yang
Author_Institution :
Anyang Normal Univ., Anyang, China
fYear :
2013
fDate :
21-26 July 2013
Firstpage :
2585
Lastpage :
2588
Abstract :
A Quantum-Modeled Artificial Bee Colony clustering algorithm for remotely sensed multi-band image segmentation is explored and evaluated. Data sets of interest include remotely sensed multi-band RGB imagery, which subsequent to classification is analyzed and assessed for accuracy. Results demonstrate that the algorithm exhibits improved accuracy, when compared to its classical counterpart. Moreover, solutions are enhanced via introduction of the quantum state machine, which provides random initial food sources and variables as input to the Artificial Bee Colony algorithm, and quantum operators, which bring about convergence and maximize local search space exploration. Typically, the algorithm has shown to produce better solutions.
Keywords :
geophysical image processing; geophysics computing; image segmentation; quantum computing; remote sensing; quantum state machine; quantum-modeled artificial bee colony clustering algorithm; random initial food sources; remotely sensed multiband RGB imagery; remotely sensed multiband image segmentation; Clustering algorithms; Extraterrestrial measurements; Image segmentation; Indexes; Kinetic theory; Logic gates; Vectors; clustering algorithms; image segmentation; quantum computing; quantum mechanics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International
Conference_Location :
Melbourne, VIC
ISSN :
2153-6996
Print_ISBN :
978-1-4799-1114-1
Type :
conf
DOI :
10.1109/IGARSS.2013.6723351
Filename :
6723351
Link To Document :
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