论文标题
连贯光学和全息图中的三维体积反向卷积
Three-dimensional volumetric deconvolution in coherent optics and holography
论文作者
论文摘要
提出了三维反卷积（3DD）的方法或具有3D点扩散功能的3D样品衍射的光学复合物值波前的体积解卷积。特别是，解决了回收的3D样品分布的定量正确性。可以从其3D衍射的波前与非著作（Wiener Filter）3DD从其3D衍射波前检索样品。连续扩展样品，包括复合物值（相）样品，可以通过迭代（金和Richardson-Lucy）3DD算法来检索。结果表明，定量正确的3D样本分布只能使用迭代3DD恢复，并提供最佳协议。证明3DD可以将横向分辨率提高到分辨率限制，并且轴向分辨率至少要比分辨率限制高四倍。提出的复杂值光场的3DD方法可用于3D光学成像和全息图。
Methods of three-dimensional deconvolution (3DD) or volumetric deconvolution of optical complex-valued wavefronts diffracted by 3D samples with the 3D point spread function are presented. Particularly, the quantitative correctness of the recovered 3D sample distributions is addressed. Samples consisting of point-like objects can be retrieved from their 3D diffracted wavefronts with non-iterative (Wiener filter) 3DD. Continuous extended samples, including complex-valued (phase) samples, can be retrieved with iterative (Gold and Richardson-Lucy) 3DD algorithms. It is shown that quantitatively correct 3D sample distribution can be only recovered with iterative 3DD, and with the optimal protocols provided. It is demonstrated that 3DD can improve the lateral resolution to the resolution limit and the axial resolution can be at least four times better than the resolution limit. The presented 3DD methods of complex-valued optical fields can be applied for 3D optical imaging and holography.
