18 July 2014 Classification of hyperspectral urban data using adaptive simultaneous orthogonal matching pursuit
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Abstract
Simultaneous orthogonal matching pursuit (SOMP) has been recently developed for hyperspectral image classification. It utilizes a joint sparsity model with the assumption that each pixel can be represented by a linear combination of labeled samples. We present an approach to improve the performance of SOMP based on
© 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)
Jinyi Zou, Wei Li, Xin Huang, Qian Du, "Classification of hyperspectral urban data using adaptive simultaneous orthogonal matching pursuit," Journal of Applied Remote Sensing 8(1), 085099 (18 July 2014). https://doi.org/10.1117/1.JRS.8.085099 . Submission:
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