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Proceedings Paper

Parallel implementation of N-FINDR algorithm for hyperspectral imagery on hybrid multiple-core CPU and GPU parallel platform
Author(s): Wenfei Luo
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Paper Abstract

Spectral unmixing in hyperspectral remote sensing image has been widely researched in the last two decades. N-FINDR algorithm is one of the most classical and commonly-used endmember extraction algorithms. Nevertheless, it is a timeconsuming task that cannot meet the time requirement of many applications. In order to make N-FINDR computationally feasible, we consider parallel implementation of N-FINDR algorithm on hybrid multiple-core CPU and GPU parallel platform. First, a multi-core CPU-based parallel N-FINDR algorithm is considered based on a modified N-FINDR with two improvements. And by using the increasing programmability and parallelism of commodity GPU, a GPU-based parallel N-FINDR is presented. Finally, by taking advantages of the capability of the aforementioned algorithms, a hybrid multiple-core CPU and GPU parallel N-FINDR is proposed by using a virtual thread technique and an adaptive algorithm in which the computational load can be adaptively adjusted according to the capability of CPU and GPU. In experiment, our proposed parallel N-FINDR algorithms improved the accuracy of the original N-FINDR algorithm, and most importantly, they greatly improved the performance of N-FINDR algorithm.

Paper Details

Date Published: 23 November 2011
PDF: 7 pages
Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 80060A (23 November 2011); doi: 10.1117/12.901593
Show Author Affiliations
Wenfei Luo, South China Normal Univ. (China)


Published in SPIE Proceedings Vol. 8006:
MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)

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