Title :
Particle swarm mixel decomposition for remote sensing images
Author :
Wang, Dong ; Wu, Xiangbin ; Lin, Dongmei
Author_Institution :
Dept. of Comput. Sci. & Technol., Foshan Univ., Foshan, China
Abstract :
Mixel decomposition of remote sensing images is one of valid assistance means for improving quality of feature extraction from the images. Some problems exist in normal linear mixels decomposition, for example, registration error is too large, and neighbourhood information can be took full advantage of and so on. These result in that distortion of new images generated after linear mixels decomposition is more serious. Aiming at an above-mentioned circumstance, particle swarm intelligence searching method is put forward in this paper. New algorithm implements mixel decomposition of remote sensing images, combined with linear mixels decomposition model. The algorithm takes full advantage of neighbourhood information, makes the decomposition result more human, and presents better robustness to environment.
Keywords :
feature extraction; particle swarm optimisation; remote sensing; feature extraction; neighbourhood information; particle swarm mixel decomposition; remote sensing images; Clustering algorithms; Educational technology; Equations; Geoscience and remote sensing; Humans; Least squares methods; Particle swarm optimization; Reflection; Remote sensing; Robustness; linear mixels decomposition; mixel decomposition; particle swarm intelligence; remote sensing images; swarm intelligence search;
Conference_Titel :
Automation and Logistics, 2009. ICAL '09. IEEE International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-4794-7
Electronic_ISBN :
978-1-4244-4795-4
DOI :
10.1109/ICAL.2009.5262925