快照成像光谱仪快速光谱重构算法

为实现对光谱数据的快速实时处理,针对快照式傅里叶成像光谱仪,提出一种基于GPU的并行化光谱重构算法.通过分析快照式成像光谱仪的工作原理和数据特性,结合CUDA并行计算架构,对光谱重构算法可并行部分最大程度并行化,并针对并行计算中的内存分配等方面进行优化处理,实现并行化的光谱重构算法.实验结果表明:基于GPU的并行化光谱重构算法,相对CPU串行化算法,精度相同的情况下,计算效率提升了约25倍.利用GPU加速程序的并行部分,可以极大地提高光谱重构的效率,使得快照式成像光谱仪更加适用于实时测量当中.

Fast spectrum reconstruction method for snapshot imaging spectrometer

A GPU-based spectrum reconstruction algorithm is proposed and realized aiming to meet the need for real-time spectral data processing. By analyzing the working principle and data property of snapshot Fourier transform imaging spectrometer and combining with CUDA data Parallel Processing Architecture, the article optimizes the reconstruction algorithm, including paralleling the reconstruction algorithm and optimizing the memory accessing,and implements parallel spectrum reconstruction algorithm. As a consequence, the spectrum reconstruction rate is extremely increased. The experimental results indicate that, compared with CPU serial algorithm, the GPU-based parallel spectrum reconstruction algorithm proposed in this article achieves the same reconstruction accuracy but around 25 times in computational efficiency. By taking advantage of GPU parallel computing, spectrum reconstruction efficiency is extremely improved which lays the foundation for the implementation of snapshot imaging spectrometer in real-time measurement.