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Advanced Signature-Matched Hyperspectral Change Detection

Award Information

Agency:
Department of Defense
Branch:
Air Force
Award ID:
82208
Program Year/Program:
2007 / SBIR
Agency Tracking Number:
F071-235-0495
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
Gitam Technologies Inc
9782 Country Creek Way Dayton, OH -
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2007
Title: Advanced Signature-Matched Hyperspectral Change Detection
Agency / Branch: DOD / USAF
Contract: FA8650-07-M-1168
Award Amount: $100,000.00
 

Abstract:

Gitam Technologies Inc. (GTI) in collaboration with Professor John Kerekes of Rochester Institute of Technology, propose to kernelize the Covariance Equalized Change Detection algorithm for Hyperspectral imagery. The primary focus will be to develop signature-based change detection with the capability to locate particular signatures in an observation scene, where prior knowledge about the target or the background is available from previous pass. Over the past decade, Kernel-based learning concepts have established as a powerful optimization tool when gaussian and linearity assumptions are invalid. In kernel-based methods, learning is implicitly performed in a high-dimensional feature space where high order correlation or nonlinearity within the data is exploited. The kernel concept has seen vast applications in wide variety of detection and recognition problems, including traditional detection and classification, change detection and anomaly change detection. However, although Covariance Equalized Change Detection (CECD) has seen several useful applications, the CECD concept has not been formalized within the Kernel framework. Hence, the main goal of this project is to study the effectiveness of the entire class of Kernels for CECD for HSI data. The Kernelization approach will be initially applied to the chronochrome algorithm and the covariance equalization algorithm both with and without matched filtering.

Principal Investigator:

William S. McCormick
Senior Scientist
9374227504
william.mccormick@wright.edu

Business Contact:

Arnab K. Shaw
President and Tech Lead
9378859767
gitam13@yahoo.com
Small Business Information at Submission:

GITAM TECHNOLOGIES, INC.
9782 Country Creek Way Dayton, OH 45458

EIN/Tax ID: 200059324
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No