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Coalescing ICA and Wavelets Coefficients for Image Information Mining in Earth Observation Data Archives

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4 Author(s)
Shah, V.P. ; Dept. of Electr. & Comput. Eng., Mississippi State Univ., Starkville, MS ; Durbha, S.S. ; Younan, N.H. ; King, R.L.

Reflectance pattern and spatial pattern characterize the geospatial data. Current semantic-enabled framework retrieval system extract primitive features based on color, texture (Spatial Gray Level Dependency - SGLD matrices), and shape from the segmented homogenous region. This system can use only three bands (true color or false color) at a time to capture color information as it converts RGB space into HSV space. Thus it fails to capture the complete reflectance pattern, an important characteristic of geospatial data. This paper describes a new method to perform image segmentation using the features obtained by coalescing of Independent Component Analysis and Wavelet transform, which are later on used for the region-based retrieval in the earth observation data archives. Experimental results show effectiveness of the proposed method for image information mining in Earth observation data archives.

Published in:

Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006. IEEE International Conference on

Date of Conference:

July 31 2006-Aug. 4 2006