Data reconstructing for windowing broom Fourier transform imaging spectrometers based on multi-core techniques

The windowing broom Fourier transform imaging spectrometer, based on space-time modulation, has the characteristics of high luminous flux, static interference part etc. However, the large amount of raw data and the data reconstruction increase the difficulty of the whole data processing and extend the computing time. In this paper, a parallel calculation algorithm for reconstruction of raw data is proposed. The proposed algorithm is achieved by using Task Parallel Library (TPL), which is provided by .NET framework, and a visualized processing system is further established. A set of data collected from a windowing broom Fourier transform imaging spectrometer is processed using both the proposed method and the ordinary serial algorithm. The scalability of this presented algorithm is verified by employing it on computers with different number of cores. The experimental results show that, compared to the serial algorithm, the proposed method can greatly speed up the processing with the same hardware condition, and it also has ideal scalability with different hardware.