SMACC


Image Exploitation Algorithms: SSI is active in the development of algorithms for spectral image exploitation, including use for target detection and classification.

For example, SSI scientists developed SMACC (Sequential Maximum Angle Convex Cone), a fast, fully automated endmember-finding and unmixing algorithm that can be applied to both multispectral and hyperspectral data. SMACC is included as a spectral analysis tool in ENVI, and is also available from SSI as a stand-alone code.

Material abundance maps generated with SMACC.


technical Contact

Steve Adler-Golden

adlergolden@spectral.com

Related Links

ABSTRACt

J.H. Gruninger, A.J. Ratkowski, and M.L. Hoke, The Sequential Maximum Angle Convex Cone (SMACC) Endmember Model. Proceedings SPIE, Algorithms for Multispectral and Hyper-spectral, and Ultraspectral Imagery, Vol.5425-1, Orlando FL, April, (2004).

Spectral Science, Inc