The Adaptive Spectral and Abundance Processing (ASAP) Algorithm

"This proposal addresses the urgent need for near real-time algorithms for detection, identification and tracking of objects in highly structured environments. Spectral Sciences, Inc. (SSI) proposes to develop an innovative new algorithm for improvedclutter mitigation and target detection for Hyperspectral Imaging (HSI) sensors called the Adaptive Spectral and Abundance Processing (ASAP) algorithm. ASAP will include fused spatial-spectral processing of endmember abundance images and spectra obtainedfrom a new real-time adaptive unmixing algorithm. The approach is based on the proven technology found in the Sequential Maximum Angle Convex Cone (SMACC) algorithm that simultaneously determines spectral endmembers, representing the most `pure' materialspectra in the scene, and abundance images for each endmember. In Phase I, SSI will define and demonstrate an adaptive version of the SMACC algorithm that is capable of processing a continuous stream of HSI data and is suitable for Phase II real-timeimplementation. Phase I also includes the definition, development and demonstration of fused spatial-spectral detection algorithms that will exploit the spatial information contained in the endmember abundance images and the spectral information containedin the endmember spectra. The processing chain will be demonstrated and evaluated with synthetic and measured HSI data. The development of ASAP will provide a needed real-time target detect