Anomaly detection using simulated MTI data cubes derived form HYDICE data

Mary M. Moya; John G. Taylor; Brian R. Stallard; Sheila E. Motomatsu

doi:10.1117/12.328116

16 October 1998 Anomaly detection using simulated MTI data cubes derived form HYDICE data

Mary M. Moya, John G. Taylor, Brian R. Stallard, Sheila E. Motomatsu

Proceedings Volume 3438, Imaging Spectrometry IV; (1998) https://doi.org/10.1117/12.328116
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

Abstract

In this work we quantify the separability between specific materials and the natural background by applying receiver operating curve (ROC) analysis to the residual errors from a linear unmixing. We apply the ROC analysis to quantify performance of the multi-spectral thermal imager (MTI). We describe the MTI imager and simulate its data by filtering HYDICE hyperspectral imagery both spatially and spectrally and by introducing atmospheric effects corresponding to the MIT satellite altitude. We compare and contrast the individual effects on performance of spectral resolution, spatial resolution, atmospheric corrections, and varying atmospheric conditions.

Citation Download Citation

Mary M. Moya, John G. Taylor, Brian R. Stallard, and Sheila E. Motomatsu "Anomaly detection using simulated MTI data cubes derived form HYDICE data", Proc. SPIE 3438, Imaging Spectrometry IV, (16 October 1998); https://doi.org/10.1117/12.328116

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