基于FP微阵列的压缩感知光谱重建研究

Research on compressed sensing spectral reconstruction based on Fabry-Perot micro-array

  • 摘要: 针对现有星载扫描光谱成像中无法同时实现高通量、高光谱分辨率的问题,提出采用法布里珀罗(FP)微阵列与压缩感知光谱成像方法。该方法通过在成像探测器前加FP微阵列,FP微阵列调制器每一单元对应不同高度,进而对输入光信号进行调制得到不同的光谱响应。结合扫描和压缩感知复原算法,最终获得高光谱图像数据立方体。该系统光谱范围为400 nm~700 nm,光谱通道数高达700个。通过仿真激光入射光谱与压缩感知重构光谱进行对比,仿真均方误差(MSE)为0.002。此外,通过实验对两个不同颜色的单色光光谱进行重构,实验结果与标准光谱仪测得的光谱基本一致,验证了该方法光谱重构的可行性。该方法可广泛应用于高通量、高光谱星载或扫描光谱成像测量中。

     

    Abstract: Aiming at the problem that high throughput and high spectral resolution cannot be realized simultaneously in the existing space-borne scanning spectral imaging, a Fabry-Perot (FP) micro-array and compressed sensing spectral imaging method was proposed. By adding FP micro-arrays in front of the imaging detector, each unit of the FP micro-array modulator was corresponding to the different heights, and then the input optical signal was modulated to obtain the different spectral responses. Combined with the scanning and compressed sensing restoration algorithm, the hyper-spectral image data cube was finally obtained. The spectral range of the system was 400 nm~700 nm, and the number of spectral channels was as high as 700. By comparing the simulated laser incident spectrum with the compressed sensing reconstructed spectrum, the simulated mean square error (MSE) was 0.002. In addition, the two monochromatic light spectra with different colors were reconstructed by experiments. The experimental results were basically consistent with the spectrum measured by the standard spectrometer, which verified the feasibility of the spectrum reconstruction by this method. This method can be widely used in the measurements of high throughput, hyper-spectral space-borne or scanning spectral imaging.

     

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