Level 0-2 fusion model for ATR using fuzzy logic

Charles F. Hester; Kelly K. Dobson

doi:10.1117/12.852915

28 April 2010 Level 0-2 fusion model for ATR using fuzzy logic

Charles F. Hester, Kelly K. Dobson

Proceedings Volume 7710, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2010; 771007 (2010) https://doi.org/10.1117/12.852915
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

The JDL model for fusion provides a structure for fusion of multispectral data at all levels. Fused data provides improved performance in Automatic Target Recognition (ATR). Critical to the overall fusion performance, however, is the low level(0-2) fusion of sensory and context information. Loss of information must be avoided at this level, but complexity must be reduced. A model is presented that uses fuzzy sets to form entities and capture the information needed for target recognition. Examples using multi-spectral imagery will be presented.

Citation Download Citation

Charles F. Hester and Kelly K. Dobson "Level 0-2 fusion model for ATR using fuzzy logic", Proc. SPIE 7710, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2010, 771007 (28 April 2010); https://doi.org/10.1117/12.852915

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