Under the condition of extremely under-sampling, the iterative algorithm based on the total variation(TV) constrain is common for the reconstruction of optical deflection tomography. In the algorithm, the minimization of TV is implemented by the gradient descent approach, and the constraints are performed by projection on convex sets (POCS). In this paper, we discuss the modulation factor of the gradient descent method, and propose a new adaptive modulation factor for gradient descent. Experiments were done on a series of modulation factor functions under different projection angles and noise environment, and the experimental results were compared and analysed. And the algorithm proposed in this paper is compared with the soft threshold filter TV minimization algorithm. The results demonstrate that the adaptive modulation factor proposed in this paper can automatically and continuously update the value of the modulation factor, reduce the reconstruction error and improve the reconstruction quality.

中文翻译：

---

用于光学偏转断层扫描重建的约束电视调制因子研究

在极度欠采样的情况下，基于总变异（TV）约束的迭代算法是光学偏转断层扫描重建的常用算法。在算法中，TV的最小化是通过梯度下降法实现的，约束是通过凸集投影（POCS）来实现的。在本文中，我们讨论了梯度下降法的调制因子，并提出了一种新的梯度下降自适应调制因子。对不同投影角度和噪声环境下的一系列调制因子函数进行了实验，并对实验结果进行了比较和分析。并将本文提出的算法与软阈值滤波器TV最小化算法进行了比较。