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- W2347954920 abstract "Low efficiency of traditional hyperspectral processing algorithm can not meet the demand of mass remote sensing data real-time processing. This paper exploits the paralleled optimization method based on graphic processing unit(GPU) for hyperspectral image processing, and develops a parallel optimized algorithm based on the matrix multiplication. The algorithm is designed for pixel purity index(PPI), which is widely applied in mixed pixel decomposition. In the end, it gives a detailed experimental comparison and performance testing. The experiments show that GPU-based parallel optimization methods significantly enhance the efficiency of the implementation while maintaining the accuracy of the results. This new parallel algorithm acceleration values reaches up to 634 times, which demonstrates the effectiveness of the GPU-based parallel optimization algorithm and promotes the real-time information processing of hyperspectral remote sensing." @default.
- W2347954920 created "2016-06-24" @default.
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- W2347954920 date "2014-01-01" @default.
- W2347954920 modified "2023-09-23" @default.
- W2347954920 title "Parallel Optimization of Pixel Purity Index Algorithm Based on GPU for Hyperspectral Remote Sensing Image" @default.
- W2347954920 hasPublicationYear "2014" @default.
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