Title :
Integration of Segmentation Techniques for Classification of Hyperspectral Images
Author :
Ghamisi, Pedram ; Couceiro, Micael S. ; Fauvel, M. ; Atli Benediktsson, Jon
Author_Institution :
Fac. of Electr. & Comput. Eng., Univ. of Iceland, Reykjavik, Iceland
Abstract :
A new spectral-spatial method for classification of hyperspectral images is introduced. The proposed approach is based on two segmentation methods, fractional-order Darwinian particle swarm optimization and mean shift segmentation. The output of these two methods is classified by support vector machines. Experimental results indicate that the integration of the two segmentation methods can overcome the drawbacks of each other and increase the overall accuracy in classification.
Keywords :
geophysical image processing; hyperspectral imaging; image classification; image segmentation; particle swarm optimisation; support vector machines; fractional-order Darwinian particle swarm optimization; hyperspectral image classification; hyperspectral image segmentation technique; mean shift segmentation; spectral-spatial method; support vector machine; Hyperspectral image analysis; mean shift segmentation; multilevel segmentation;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2013.2257675
