Analysis of HYDICE noise characteristics and their impact on subpixel object detection

A number of organizations are using the data collected by the HYperspectral Digital Imagery Collection Experiment (HYDICE) air;borne sensor to demonstrate the utility of hyperspectral imagery (HSI) for a variety of applications. The interpretation and extrapolation of these results can be influenced by the nature and magnitude of any artifacts introduced by the HYDICE sensor. A shea study was undertaken which first reviewed the literature for discussions of the sensor's noise characteristics and then extended those results with additional analyses of HYDICE data. These investigations used unprocessed image data from the onboard Flight Calibration Unit (FCU) lamp and ground scenes taken at three different sensor altitudes and sample integration times. Empirical estimates of the sensor signal-to-noise ratio (SNR) were compared to predictions from a radiometric performance model, The spectral band-to-band correlation structure of the sensor noise was studied. Using an end-to-end system performance model, the impact of various noise sources on subpixel detection was analyzed. The results show that, although a number of sensor artifacts exist, they have little impact on the interpretations of HSI utility derived from analyses of HYDICE data.