23 November 2011 Parallel implementation of N-FINDR algorithm for hyperspectral imagery on hybrid multiple-core CPU and GPU parallel platform
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Proceedings Volume 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 80060A (2011) https://doi.org/10.1117/12.901593
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
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.
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Wenfei Luo, "Parallel implementation of N-FINDR algorithm for hyperspectral imagery on hybrid multiple-core CPU and GPU parallel platform", Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 80060A (23 November 2011); doi: 10.1117/12.901593; https://doi.org/10.1117/12.901593
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