Correcting bad detectors in hyperspectral data: the effect on the processing stream

Edwin M. Winter

doi:10.1117/12.509638

7 January 2004 Correcting bad detectors in hyperspectral data: the effect on the processing stream

Edwin M. Winter

Proceedings Volume 5159, Imaging Spectrometry IX; (2004) https://doi.org/10.1117/12.509638
Event: Optical Science and Technology, SPIE's 48th Annual Meeting, 2003, San Diego, California, United States

Abstract

More and more hyperspectral sensors are now employing two-dimensional focal plane arrays to simultaneously record the spectra for a line of points on the ground. Since a large number of spectra are obtained simultaneously, the instantaneous data rate can be much higher than that achieved with a flying spot scanner. Unfortunately, the use of more than one detector per band means that there are many new sources of sensor pattern that must be removed during preprocessing. These sources of pattern usually are the limitation to the performance of imaging array spectrometers. One of the more troublesome problems with focal plane arrays is the existence of dead or bad detectors. For an imaging system, the effect of these detectors is removed by interpolation with neighbors. The problem is much more difficult to solve when the array is used as the focal plane in a hyperspectral instrument. If the bad detectors are ignored, the result is a stripe down the image in a particular band. Simple interpolation in the spectral direction can be atempted, but often the interpolation itself is the source of stripes in the image. The effect of inaccurate interpolation is particularly noticeable in the vicinity of atmospheric absorption features, where the spectral variation with wavelength is far from linear. The bad detector is replaced by the average of its two neighboring point in the spectra, which fails to match the proper value for that point. While this value is a better match than the uncorrected detector, the result is still a stripe in the image. This stripe will show up in many hyperspectral analysis operations. One solution is to move the atmospheric compensation step into the preprocessing to remove the rapidly changing spectral features before the bad detectors are removed by interpolation. This would be a rearrangement of the normal division between level 1 and level 2 processing. In this paper an alternative procedure to minimize the effect of bad detectors is discussed. This procedure avoids the atmospheric correction in preprocessing.

Citation Download Citation

Edwin M. Winter "Correcting bad detectors in hyperspectral data: the effect on the processing stream", Proc. SPIE 5159, Imaging Spectrometry IX, (7 January 2004); https://doi.org/10.1117/12.509638

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