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High Resolution and Fast Processing of Spectral Reconstruction in Fourier Transform Imaging Spectroscopy

机译:傅里叶变换成像光谱中光谱重建的高分辨率和快速处理

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摘要

High-resolution spectrum estimation has continually attracted great attention in spectrum reconstruction based on Fourier transform imaging spectroscopy (FTIS). In this paper, a parallel solution for interference data processing using high-resolution spectrum estimation is proposed to reconstruct the spectrum in a fast high-resolution way. In batch processing, we use high-performance parallel-computing on the graphics processing unit (GPU) for higher efficiency and lower operation time. In addition, a parallel processing mechanism is designed for our parallel algorithm to obtain higher performance. At the same time, other solving algorithms for the modern spectrum estimation model are introduced for discussion and comparison. We compare traditional high-resolution solving algorithms running on the central processing unit (CPU) and the parallel algorithm on the GPU for processing the interferogram. The experimental results illustrate that runtime is reduced by about 70% using our parallel solution, and the GPU has a great advantage in processing large data and accelerating applications.
机译:在基于傅立叶变换成像光谱(FTIS)的光谱重建中,高分辨率光谱估计一直引起人们的极大关注。本文提出了一种使用高分辨率频谱估计的并行处理干扰数据的解决方案,以快速高分辨率地重建频谱。在批处理中,我们在图形处理单元(GPU)上使用高性能并行计算,以提高效率并缩短操作时间。另外,为我们的并行算法设计了并行处理机制以获得更高的性能。同时,介绍了现代频谱估计模型的其他求解算法,以进行讨论和比较。我们比较了在中央处理器(CPU)上运行的传统高分辨率求解算法和在GPU上用于处理干涉图的并行算法。实验结果表明,使用我们的并行解决方案可以将运行时间减少约70%,并且GPU在处理大数据和加速应用程序方面具有巨大优势。

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