Methods for determining best multi-spectral bands using hyperspectral data

Edwin M. Winter

doi:10.1117/12.721271

26 April 2007 Methods for determining best multi-spectral bands using hyperspectral data

Edwin M. Winter

Proceedings Volume 6553, Detection and Remediation Technologies for Mines and Minelike Targets XII; 655318 (2007) https://doi.org/10.1117/12.721271
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

Over the years several methods have been used to determining the best bands for a visible near IR multi-spectral sensor. The most popular method, the committee method, places scientists with differing opinions on the phenomena and the sensor mission in one room, and a compromise set is developed. To avoid this, there have been several methods to automate this selection process. We have developed a method to examine hyperspectral data to find the best multi-spectral band set (whether 3, 4, 5 or 6 bands) based on the background, on the premise that, with the target unknown, the band set that best separates the background materials is the best. We start with a hyperspectral data set of a background area without any targets. We then run a program for determining the spectral endmembers. Any endmembers that look like they are due to sensor artifacts or an anomalous point on the ground (junk) are discarded from the list. The resulting hyperspectral endmembers are then input to an exhaustive search program. The goal of the exhaustive search is to find a set of N (say 4) multi-spectral bands that maximizes the spectral angles between all of the endmembers. Thus, at each trial the multi-spectral bands are made by binning the hyperspectral (to four bands in this case) and the spectral angles calculated between endmembers 1 and 2, 1 and 3, 1 and 4, 2 and 3, 2 and 4 etc. The endmembers in each case have been binned to four multi-spectral bands. We save the average of these spectral angle calculations. After examining often millions of combinations, the multi-spectral band set that maximizes the spectral separation is judged to be the best. We have applied this method to the selection of multi-spectral bands sets for several sensors.

Citation Download Citation

Edwin M. Winter "Methods for determining best multi-spectral bands using hyperspectral data", Proc. SPIE 6553, Detection and Remediation Technologies for Mines and Minelike Targets XII, 655318 (26 April 2007); https://doi.org/10.1117/12.721271

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