Efficient hierarchical fusion using adaptive grouping techniques for visualization of hyperspectral images

Shah, P and Drumetz, M and Merchant, S N and Desai, U B (2011) Efficient hierarchical fusion using adaptive grouping techniques for visualization of hyperspectral images. In: 8th International Conference on Information, Communications and Signal Processing, ICICS 2011, 13-16, December 2011, Singapore.

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Abstract

Visualization of hyperspectral images that combines the data from multiple sensors is a major challenge due to huge data set. An efficient image fusion could be a primary key step for this task. To make the approach computationally efficient and to accommodate a large number of image bands, we propose an efficient hierarchical fusion based on adaptive grouping techniques. The consecutive image bands in the hyperspectral data cube exhibit a high degree of feature similarity among them due to the contiguous and narrow nature of the hyperspectral sensors. Exploiting this redundancy in the data, we generate clusters of similar images and fuse them at every level of hierarchy using bilateral filter. For grouping similar images, we propose six very generic yet proficient similarity criteria based on either information theoretic metrics or image quality metrics. We also investigate each similarity criterion based on statistical evaluation of quality of final fused image.

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IITH Creators:
IITH CreatorsORCiD
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Grouping techniques; Hierarchical image fusion; Hyperspectral imaging; Visualization
Subjects: Physics > Electricity and electronics
Divisions: Department of Electrical Engineering
Depositing User: Team Library
Date Deposited: 28 Nov 2014 05:10
Last Modified: 28 Nov 2014 05:10
URI: http://raiithold.iith.ac.in/id/eprint/983
Publisher URL: http://dx.doi.org/10.1109/ICICS.2011.6173575
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