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Proceedings Paper

Cross-sensor registration optimization study
Author(s): Nga Nguyen; Jay K. Hackett
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Paper Abstract

Multi-sensor and multi-spectral data fusion is becoming a very useful technology to solve a host of defense and commercial imaging and computer vision problems. Many of the techniques that can be used to fuse multi-sensor image data require coregistration or alignment of pixels between image bands. We have performed a non-parametric study to determine which multi-spectral bands should be chosen for optimum pixel level alignment. The data used during this study is composed of two aerial multi-spectral sensors (one with 3 visible bands and one with 5 bands in the visible and short wave infrared and one synthetic aperture radar sensor in the X-band. The study is presented in a scientific manner to allow for objective analysis of the results. A similarity measure and normalization approach was developed to allow for direct comparison between all combinations of visible, short wave infrared, and SAR phenomenology. All combinations of data alignment are performed and analytical results are extracted, analyzed, and statistically plotted. Variations in time of day of collection, atmospheric transmission, and collection path length are investigated. This approach has applicability for band selection in both manual and automatic registration techniques that are used to co-register multi-sensor data.

Paper Details

Date Published: 23 August 2000
PDF: 12 pages
Proc. SPIE 4049, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI, (23 August 2000); doi: 10.1117/12.410370
Show Author Affiliations
Nga Nguyen, Harris Corp. (United States)
Jay K. Hackett, Harris Corp. (United States)


Published in SPIE Proceedings Vol. 4049:
Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI
Sylvia S. Shen; Michael R. Descour, Editor(s)

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