TY - CONF T1 - Automatic target recognition based on simultaneous sparse representation T2 - Image Processing (ICIP), 2010 17th IEEE International Conference on Y1 - 2010 A1 - Patel, Vishal M. A1 - Nasrabadi,N.M. A1 - Chellapa, Rama KW - (artificial KW - algorithm;feature KW - based KW - classification;iterative KW - classification;learning KW - Comanche KW - data KW - dictionary;matching KW - extraction;image KW - forward-looking KW - infrared KW - intelligence);military KW - learning KW - MATCHING KW - matrix;dictionary KW - measure;military KW - methods;learning KW - orthogonal KW - pursuit KW - pursuit;confusion KW - recognition;class KW - recognition;target KW - representation;feature KW - representation;sparse KW - set;automatic KW - signal KW - similarity KW - simultaneous KW - sparse KW - supervised KW - systems;object KW - target KW - target;simultaneous KW - tracking; AB - In this paper, an automatic target recognition algorithm is presented based on a framework for learning dictionaries for simultaneous sparse signal representation and feature extraction. The dictionary learning algorithm is based on class supervised simultaneous orthogonal matching pursuit while a matching pursuit-based similarity measure is used for classification. We show how the proposed framework can be helpful for efficient utilization of data, with the possibility of developing real-time, robust target classification. We verify the efficacy of the proposed algorithm using confusion matrices on the well known Comanche forward-looking infrared data set consisting of ten different military targets at different orientations. JA - Image Processing (ICIP), 2010 17th IEEE International Conference on M3 - 10.1109/ICIP.2010.5652306 ER -