Smith Daniel, Gopinath Shivasubramanian, Arockiaraj Francis Gracy, Reddy Andra Naresh Kumar, Balasubramani Vinoth, Kumar Ravi, Dubey Nitin, Ng Soon Hock, Katkus Tomas, Selva Shakina Jothi, Renganathan Dhanalakshmi, Kamalam Manueldoss Beaula Ruby, John Francis Rajeswary Aravind Simon, Navaneethakrishnan Srinivasan, Inbanathan Stephen Rajkumar, Valdma Sandhra-Mirella, Praveen Periyasamy Angamuthu, Amudhavel Jayavel, Kumar Manoj, Ganeev Rashid A, Magistretti Pierre J, Depeursinge Christian, Juodkazis Saulius, Rosen Joseph, Anand Vijayakumar
Optical Sciences Center and ARC Training Centre in Surface Engineering for Advanced Materials (SEAM), School of Science, Computing and Engineering Technologies, Optical Sciences Center, Swinburne University of Technology, Hawthorn, Melbourne, VIC 3122, Australia.
PG & Research Department of Physics, Thiagarajar College, Madurai 625009, India.
J Imaging. 2022 Jun 20;8(6):174. doi: 10.3390/jimaging8060174.
Indirect-imaging methods involve at least two steps, namely optical recording and computational reconstruction. The optical-recording process uses an optical modulator that transforms the light from the object into a typical intensity distribution. This distribution is numerically processed to reconstruct the object's image corresponding to different spatial and spectral dimensions. There have been numerous optical-modulation functions and reconstruction methods developed in the past few years for different applications. In most cases, a compatible pair of the optical-modulation function and reconstruction method gives optimal performance. A new reconstruction method, termed nonlinear reconstruction (NLR), was developed in 2017 to reconstruct the object image in the case of optical-scattering modulators. Over the years, it has been revealed that the NLR can reconstruct an object's image modulated by an axicons, bifocal lenses and even exotic spiral diffractive elements, which generate deterministic optical fields. Apparently, NLR seems to be a universal reconstruction method for indirect imaging. In this review, the performance of NLR isinvestigated for many deterministic and stochastic optical fields. Simulation and experimental results for different cases are presented and discussed.
间接成像方法至少涉及两个步骤,即光学记录和计算重建。光学记录过程使用光学调制器,该调制器将来自物体的光转换为典型的强度分布。对该分布进行数值处理,以重建对应于不同空间和光谱维度的物体图像。在过去几年中,针对不同应用开发了众多光学调制函数和重建方法。在大多数情况下,光学调制函数和重建方法的兼容对可提供最佳性能。2017年开发了一种新的重建方法,称为非线性重建(NLR),用于在光学散射调制器的情况下重建物体图像。多年来,已经发现NLR可以重建由轴锥镜、双焦透镜甚至奇异螺旋衍射元件调制的物体图像,这些元件会产生确定性光场。显然,NLR似乎是一种用于间接成像的通用重建方法。在本综述中,研究了NLR在许多确定性和随机光场中的性能。给出并讨论了不同情况下的模拟和实验结果。