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Advances in Spectral-Spatial Classification of Hyperspectral ImagesRecent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation and contrast of the spatial structures present in the image. Then the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines using the available spectral information and the extracted spatial information. Spatial post-processing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple classifier system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.
Document ID
20120010343
Acquisition Source
Goddard Space Flight Center
Document Type
Preprint (Draft being sent to journal)
Authors
Fauvel, Mathieu
(Toulouse Univ. France)
Tarabalka, Yuliya
(Inria Sophia Antipolis, France)
Benediktsson, Jon Atli
(Iceland Univ. Reykjavik, Iceland)
Chanussot, Jocelyn
(Genoble Institute of Technology Grenoble, France)
Tilton, James C.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
August 26, 2013
Publication Date
April 26, 2012
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC.JA.0036.2012
Distribution Limits
Public
Copyright
Other

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