Innovative Measurement Techniques for Space-Based Remote Sensing/Standoff Detection

The resolution of hyperspectral sensors is typically much less than that achieved by panchromatic and multi-spectral sensors due to fundamental noise limitations. The proposed work will demonstrate a new and innovative technique for improving the spatial resolution of hyperspectral image data and develop software implementations of the algorithm and the required multi-sensor registration. This technique, called Color Sharpening, combines a multi-spectral image with a lower spatial resolution hyperspectral image to produce a product that has the spectral properties of the hyperspectral image at a spatial resolution approaching that of the multi-spectral image. This approach is contrasted to panchromatic sharpening that is to combine a single panchromatic band with several lower resolution color bands. Color Sharpening is a departure from procedures that have been implemented before, and offers the benefits of high spatial and spectral resolution for subsequent hyperspectral processing such as terrain classification and target detection. Under Phase I, the resolution enhancement algorithm and required high quality registration procedures were developed. Tests were conducted on image data collected from airborne and satellite platforms with both high-resolution multi-spectral sensors and hyperspectral sensors. Under Phase II software tools for both registration and resolution enhancement will be developed and delivered to the government.