Mitigating the effects of bad and noisy detectors on hyperspectral data

In order to increase both spatial resolution and coverage, most imaging spectrometers developed over the past several years use a two-dimensional detector array 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. 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 instruments. 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 attempted, 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. Methods to alleviate these interpolation errors are discussed from the point of view of their impact on classification and anomaly detection.