Image and Signal Processing Methods

Spatial segmentation of multi/hyperspectral imagery by fusion of spectral-gradient-textural attributes

[+] Author Affiliations
Sreenath Rao Vantaram, Sankaranarayanan Piramanayagam, David Messinger

Rochester Institute of Technology, Chester F. Carlson Center for Imaging Science, 54 Lomb Memorial Drive, Rochester, New York 14623, United States

Eli Saber

Rochester Institute of Technology, Chester F. Carlson Center for Imaging Science, 54 Lomb Memorial Drive, Rochester, New York 14623, United States

Rochester Institute of Technology, Department of Electrical and Microelectronic Engineering, 54 Lomb Memorial Drive, Rochester, New York 14623, United States

J. Appl. Remote Sens. 9(1), 095086 (Mar 31, 2015). doi:10.1117/1.JRS.9.095086
History: Received May 9, 2014; Accepted March 4, 2015
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Abstract.  We propose an unsupervised algorithm that utilizes information derived from spectral, gradient, and textural attributes for spatially segmenting multi/hyperspectral remotely sensed imagery. Our methodology commences by determining the magnitude of spectral intensity variations across the input scene, using a multiband gradient detection scheme optimized for handling remotely sensed image data. The resultant gradient map is employed in a dynamic region growth process that is initiated in pixel locations with small gradient magnitudes and is concluded at sites with large gradient magnitudes, yielding a map comprised of an initial set of regions. This region map is combined with several co-occurrence matrix-derived textural descriptors along with intensity and gradient features in a multivariate analysis-based region merging procedure that fuses the regions with similar characteristics to yield the final segmentation output. Our approach was tested on several multi/hyperspectral datasets, and the results show a favorable performance in comparison with state-of-the-art techniques.

© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Sreenath Rao Vantaram ; Sankaranarayanan Piramanayagam ; Eli Saber and David Messinger
"Spatial segmentation of multi/hyperspectral imagery by fusion of spectral-gradient-textural attributes", J. Appl. Remote Sens. 9(1), 095086 (Mar 31, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.095086


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