Department of Information and Physical Sciences, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan.
Opt Lett. 2011 Jun 1;36(11):2071-3. doi: 10.1364/OL.36.002071.
In this Letter, we propose a preconditioning method to improve the convergence speed of iterative reconstruction algorithms in a compact, multidimensional, compound-eye imaging system called the thin observation module by bound optics. The condition number of the system matrix is improved by using a preconditioner matrix. To calculate the preconditioner matrix, the system model is expressed in the frequency domain. The proposed method is simulated by using a compressive sensing algorithm called the two-step iterative shrinkage/thresholding algorithm. The results showed improved reconstruction fidelity with a certain number of iterations for high signal-to-noise ratio measurements.
在这封信中，我们提出了一种预处理方法，通过使用预条件矩阵来提高称为薄观测模块的紧凑、多维、复眼成像系统中迭代重建算法的收敛速度，该系统是通过束缚光学来实现的。通过使用预条件矩阵来改善系统矩阵的条件数。为了计算预条件矩阵，系统模型在频域中表示。所提出的方法通过使用称为两步迭代收缩/阈值算法的压缩感知算法进行模拟。结果表明，对于高信噪比测量，在一定的迭代次数下，重建保真度得到了提高。
