Paper
25 May 2005 An information-theoretic approach to band selection
Author Affiliations +
Abstract
When we digitize data from a hyperspectral imager, we do so in three dimensions; the radiometric dimension, the spectral dimension, and the spatial dimension(s). The output can be regarded as a random variable taking values from a discrete alphabet, thus allowing simple estimation of the variable's entropy, i.e., its information content. By modeling the target/background state as a binary random variable and the corresponding measured spectra as a function thereof, we can compute the information capacity of a certain sensor or sensor configuration. This can be used as a measure of the separability of the two classes, and also gives a bound on the sensor's performance. Changing the parameters of the digitizing process, bascially how many bits and bands to spend, will affect the information capacity, and we can thus try to find parameters where as few bits/bands as possible gives us as good class separability as possible. The parameters to be optimized in this way (and with respect to the chosen target and background) are spatial, radiometric and spectral resolution, i.e., which spectral bands to use and how to quantize them. In this paper, we focus on the band selection problem, describe an initial approach, and show early results of target/background separation.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Joergen Ahlberg and Ingmar Renhorn "An information-theoretic approach to band selection", Proc. SPIE 5811, Targets and Backgrounds XI: Characterization and Representation, (25 May 2005); https://doi.org/10.1117/12.607136
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CITATIONS
Cited by 3 scholarly publications and 2 patents.
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KEYWORDS
Sensors

Information theory

Binary data

Detection and tracking algorithms

Sensor performance

Electro optical modeling

Quantization

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