An information measure of sensor performance and its relation to the ROC curve

Jörgen Ahlberg; Ingmar G. Renhorn; Niclas Wadströmer

doi:10.1117/12.851322

12 May 2010 An information measure of sensor performance and its relation to the ROC curve

Jörgen Ahlberg, Ingmar G. Renhorn, Niclas Wadströmer

Proceedings Volume 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI; 769520 (2010) https://doi.org/10.1117/12.851322
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

The ROC curve is the most frequently used performance measure for detection methods and the underlying sensor configuration. Common problems are that the ROC curve does not present a single number that can be compared to other systems and that no discrimination between sensor performance and algorithm performance is done. To address the first problem, a number of measures are used in practice, like detection rate at a specific false alarm rate, or area-under-curve. For the second problem, we proposed in a previous paper¹ an information theoretic method for measuring sensor performance. We now relate the method to the ROC curve, show that it is equivalent to selecting a certain point on the ROC curve, and that this point is easily determined. Our scope is hyperspectral data, studying discrimination between single pixels.

Citation Download Citation

Jörgen Ahlberg, Ingmar G. Renhorn, and Niclas Wadströmer "An information measure of sensor performance and its relation to the ROC curve", Proc. SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI, 769520 (12 May 2010); https://doi.org/10.1117/12.851322

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KEYWORDS

Sensors

Sensor performance

Target detection

Detection and tracking algorithms

Berkelium

Quantization

Algorithm development

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