Further optimizations of the GPU-based pixel purity index algorithm for hyperspectral unmixing

Xianyun Wu; Bormin Huang; Antonio Plaza; Yunsong Li; Chengke Wu

doi:10.1117/12.979310

8 November 2012 Further optimizations of the GPU-based pixel purity index algorithm for hyperspectral unmixing

Xianyun Wu, Bormin Huang, Antonio Plaza, Yunsong Li, Chengke Wu

Proceedings Volume 8539, High-Performance Computing in Remote Sensing II; 85390D (2012) https://doi.org/10.1117/12.979310
Event: SPIE Remote Sensing, 2012, Edinburgh, United Kingdom

Abstract

Many algorithms have been proposed to automatically find spectral endmembers in hyperspectral data sets. Perhaps one of the most popular ones is the pixel purity index (PPI), available in the ENVI software from Exelis Visual Information Solutions. Although the algorithm has been widely used in the spectral unmixing community, it is highly time consuming as its precision increases asymptotically. Due to its high computational complexity, the PPI algorithm has been recently implemented in several high performance computing architectures including commodity clusters, heterogeneous and distributed systems, field programmable gate arrays (FPGAs) and graphics processing units (GPUs). In this letter, we present an improved GPU implementation of the PPI algorithm which provides real-time performance for the first time in the literature.

Citation Download Citation

Xianyun Wu, Bormin Huang, Antonio Plaza, Yunsong Li, and Chengke Wu "Further optimizations of the GPU-based pixel purity index algorithm for hyperspectral unmixing", Proc. SPIE 8539, High-Performance Computing in Remote Sensing II, 85390D (8 November 2012); https://doi.org/10.1117/12.979310

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