Holographic reconstruction is affected by the phase-conjugate wave arising from the symmetry of the complex field. Compressive sensing (CS) has been used in in-line digital holography (DH) to eliminate noise, especially the interference from twin images. Herein, CS with total variation regularization combining autofocusing is presented. It provides an autofocusing function from a single-exposure hologram and obtains reconstructed objects without twin image noise. A series of images at a fixed interval within a reconstruction distance are processed using a two-step iterative shrinkage/thresholding algorithm in CS. It can calculate the focus distance in a larger range around the focal plane using twin-image-free reconstruction, so it can achieve a higher focusing accuracy than traditional focusing methods, including the Laplace operator, absolute gradient operator, and Tamura coefficient. The proposed method is a simple combination of algorithms and a powerful extension that can effectively improve simulated and experimental image quality and handle difficult datasets, which existing algorithms cannot.

全息重建受复场对称性产生的相位共轭波的影响。压缩传感 (CS) 已被用于在线数字全息 (DH) 以消除噪声，尤其是来自孪生图像的干扰。在此，提出了结合自动对焦的全变分正则化CS。它提供来自单次曝光全息图的自动对焦功能，并获得没有双图像噪声的重建对象。使用 CS 中的两步迭代收缩/阈值算法处理重建距离内固定间隔的一系列图像。它可以使用无双像重建技术在焦平面周围的较大范围内计算焦距，因此与传统的聚焦方法（包括Laplace运算符，绝对梯度算子和田村系数。所提出的方法是算法的简单组合和强大的扩展，可以有效提高模拟和实验图像质量并处理现有算法无法处理的困难数据集。