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2 Phase I Selections from the 04.1 Solicitation

(In Topic Number Order)
7763 Old Telegraph Road, Suite 7
Severn, MD 21144
(410) 969-7044
Dr. Joseph C. Harsanyi
NIMA 04-001       Awarded: 01JUL04
Title:Advanced Signal Processing for Non-Literal Exploitation of Spectral Imagery
Abstract:To maximize the utility of spectral imagery sensors it is essential that processing techniques for data from these sensors are highly automated, provide high probability of target detection with low false alarm rates, and offer a reliable confidence assessment capability. The detection and false alarm probabilities required for a hyperspectral sensor to be a useful intelligence asset varies based on specific applications, therefore this activity responds in general to the prevailing opinion that current algorithms for spectral processing are not meeting the needed performance goals of the present and potential users of spectral data. Current processing short-falls are especially notable when the spectral backgrounds are complex or highly structured both in the VIS/NIR/SWIR and MWIR/LWIR regions of the spectrum. This Phase I program will be directed toward the development of: 1) Innovative spectral signal processing algorithms and flows that improve current detection, identification, and quantification techniques while simultaneously minimizing false alarm rates. 2) Novel clutter suppression/contrast enhancement algorithms that demonstrate reliable and acceptable performance in the structured environments that inherently exhibit high dimensionality and significant spectral variability. 3) Software prototypes compatible with existing NGA software tools that provide for objective evaluation using data with wavelengths ranging from .4 - 13 microns.

P.O. Box 6024
Sherman Oaks, CA 91413
(703) 413-0290
Dr. Douglas F. DeProspo
NIMA 04-001       Awarded: 14JUL04
Title:Passive multi-view, multi-channel detection of highly obscured targets
Abstract:The goal of this Phase I SBIR is to define a set of algorithms that will detect and characterize static man-made objects highly obscured by foliage within multi-view, multi-channel optical data collected passively from UAVs or other aerial platforms. The proposed algorithm stream will be constructed so as to comprehend and mitigate real-world interfering effects such as clouds, smoke and haze. During Phase I, critical components of the defined algorithm stream will be demonstrated and evaluated using data from simulated and actual, multi-channel, multi-view image data collections.