基于FISTA 算法的编码孔径光谱图像压缩与复原系统

在研究现有光谱图像压缩与复原的基础上，提出了一种新型的光谱压缩与复原方法，即基于编码孔径的光谱压缩复原系统；在光谱仪的光学系统中加入由数字微镜阵列（DMD）实现的编码模板，该编码模板为一个随机矩阵，可对目标的图谱数据立方体实现瞬时编码，目标的反射光经过该编码模板后三维图谱数据立方体被压缩成一个隐含有光谱信息的二维矩阵。在解码算法方面，首次提出了利用快速迭代收缩阈值算法（FISTA）实现从少量观测值中重构三维图谱数据立方体。该算法在每次迭代中估计一次梯度的同时还计算了一个额外的点。实验结果表明，该算法无论是在收敛速度，还是在复原重构效果上均有明显提高。

Reconstruction of compressive spectral imaging system of a FISTA algorithm-based coded aperture

A compression and reconstruction solution based on coded aperture was proposed. In this system, the 3D spatial-spectral information about a scene of interest was coded by a random binary element pattern which was achieved by Digital Micro-Mirror Device (DMD), and the processing was snapshot. As a result the 3D information was encoded into a 2D representation. In decoding, a Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) was proposed on the basis of the Two-Step Iterative Shrinkage-Thresholding (TwIST) algorithm. The method developed in this paper did not require more than one gradient evaluation at each iteration, but just an additional point was smartly chosen and easy to compute. The experiments show that the reconstruction performance is much better than TwIST and GPSR both in spatial dimension and spectral dimension.