Analysis techniques for two-dimensional infrared data
In order to evaluate infrared detection and remote sensing systems, it is necessary to know the characteristics of the observational environment. For both scanning and staring sensors, the spatial characteristics of the background may be more of a limitation to the performance of a remote sensor than system noise. This limitation is the so-called spatial clutter limit and may be important for systems design of many earth application and surveillance sensors. The data used in this study is two dimensional radiometric data obtained as part of the continuing NASA remote sensing programs. Typical data sources are the Landsat multi-spectral scanner (1.1 micrometers), the airborne heat capacity mapping radiometer (10.5 - 12.5 micrometers) and various infrared data sets acquired by low altitude aircraft. Techniques used for the statistical analysis of one dimensional infrared data, such as power spectral density (PSD), exceedance statistics, etc. are investigated for two dimensional applicability. Also treated are two dimensional extensions of these techniques (2D PSD, etc.), and special techniques developed for the analysis of 2D data.