Imaging through multimode fiber (MMF) provides high-resolution imaging through a fiber with cross section down to tens of micrometers. It requires interferometry to measure the full transmission matrix (TM), leading to the drawbacks of complicated experimental setup and phase instability. Reference-less TM retrieval is a promising robust solution that avoids interferometry, since it recovers the TM from intensity-only measurements. However, the long computational time and failure of 3D focusing still limit its application in MMF imaging. We propose an efficient reference-less TM retrieval method by developing a nonlinear optimization algorithm based on fast Fourier transform (FFT). Furthermore, we develop an algorithm to correct the phase offset error of retrieved TM using defocused intensity images and hence achieve 3D focusing. The proposed method is validated by both simulations and experiments. The FFT-based TM retrieval algorithm achieves orders of magnitude of speedup in computational time and recovers 2286 × 8192 TM of a 0.22 NA and 50 μm diameter MMF with 112.9 s by a computer of 32 CPU cores. With the advantages of efficiency and correction of phase offset, our method paves the way for the application of reference-less TM retrieval in not only MMF imaging but also broader applications requiring TM calibration.

Interferometric detection enables the acquisition of the amplitude and phase of the optical field. By making use of the synthetic wavelength as a computational construct arising from digital processing of two off-axis digital holograms, it is possible to identify the shape of an object obscured by fog and further increase the imaging range due to the increased sensitivity in coherent detection. Experiments have been conducted inside a 27 m long fog tube filled with ultrasonically generated fog. We show the improved capabilities of synthetic phase imaging through fog and compare this technique with conventional active laser illumination imaging.

Time-of-Flight （ToF）成像是利用光在目标和相机之间的飞行时间来获取场景的深度信息，具有体积小、成本低、实时成像等优势。在散射环境中，由于散射介质对光的散射作用，ToF成像受到多径干扰的影响，深度测量误差较大，限制了ToF相机在散射场景中的应用。ToF透散射介质成像技术是校正因散射光引起的多径干扰效应，从传感器接收到的混叠信号中分离出目标分量，实现散射场景中的深度信息恢复，其在雾天自动驾驶、水下勘测、生物医学等领域具有广阔的应用前景。依据ToF成像系统的不同，详细介绍了PL-ToF和CW-ToF成像的基本原理，阐述和分析了散射场景中ToF稳态成像和瞬态成像的机理和特点，分别回顾和总结了ToF稳态成像和瞬态成像的透散射介质成像研究现状，并介绍了ToF透散射介质成像的应用前景，最后依据现有ToF透散射介质成像技术的优缺点，对未来发展趋势进行了展望。

The problem of imaging through thick scattering media is encountered in many disciplines of science, ranging from mesoscopic physics to astronomy. Photons become diffusive after propagating through a scattering medium with an optical thickness of over 10 times the scattering mean free path. As a result, no image but only noise-like patterns can be directly formed. We propose a hybrid neural network for computational imaging through such thick scattering media, demonstrating the reconstruction of image information from various targets hidden behind a white polystyrene slab of 3 mm in thickness or 13.4 times the scattering mean free path. We also demonstrate that the target image can be retrieved with acceptable quality from a very small fraction of its scattered pattern, suggesting that the speckle pattern produced in this way is highly redundant. This leads to a profound question of how the information of the target being encoded into the speckle is to be addressed in future studies.