基于瞬态图像的非视距成像技术综述

doi:10.16337/j.1004-9037.2022.01.002

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基于瞬态图像的非视距成像技术综述
DOI:
                        10.16337/j.1004-9037.2022.01.002
                    
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作者单位:华南农业大学数学与信息学院，广州 510642
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基金项目:广东省科技计划(2019A050510034)；国家自然科学基金(61772209)；教育部产学研协同育人项目(201901240030)；2019 年度广东省重点领域研发计划(2019B020219001)；广州市智慧农业重点实验室资助项目(201902010081）。

Overview of Non-Line-of-Sight Imaging Technology Based on Transient Images

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College of Mathematics and Informatics, South China Agricultural University, Guangzhou 510642, China

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瞬态图像是一种场景对光脉冲进行响应的快速图像序列。通过对时间维度信息的捕获，瞬态图像实现了对时域中蕴藏的场景信息的有效利用，而非视距成像是瞬态图像在场景解析领域中最典型的应用。非视距成像是一种对视线范围外物体或场景进行成像的技术，近几年在国内外广受关注。本文根据不同的成像机理，对瞬态图像的不同成像方式进行分类，并根据算法原理或实现效果的不同，对比了多种基于瞬态图像的非视距成像算法。最后总结了基于瞬态图像的非视距成像技术面临的挑战，并展望了未来的发展方向。

Abstract:

Transient image is a fast image sequence in which a scene responds to light pulses. By capturing the time dimension information， the transient image realizes the use of the scene information contained in the time domain， and the non-line-of-sight imaging is the most typical application of transient images in the field of scene analysis. It is a technology for imaging objects or scenes outside the line of sight， and has emerged at home and abroad in recent years. According to different imaging mechanisms， this paper classifies different imaging methods of transient images， and compares a variety of non-line-of-sight imaging algorithms based on transient images according to different algorithm principles or implementation effects. Finally， the challenges of non-line-of-sight imaging technology based on transient images are summarized， and the future development direction is prospected.

表 2 非视距成像重建算法比较Table 2 Comparison of NLOS imaging algorithms

表 1 不同瞬态成像方法的空间及时间分辨率对比Table 1 Comparison of spatial and temporal resolutions of different transient imaging methods

图1 光脉冲与场景的交互瞬间[1]Fig.1 Moment of interaction between light pulse and scene[1]

图2 NLOS场景瞬态图像数据采集Fig.2 Transient image acquisition in NLOS scenes

图3 Laurenzis等[16]使用的激光门控系统及捕获的图像序列Fig.3 Laser gated system used by Laurenzis et al.[16] and the captured image sequence

图4 Velten等[8-9]使用的条纹相机及拍摄的瞬态图像Fig.4 Streak sensor used by Velten et al.[8-9] and streak image taken by the streak sensor

图5 SPAD拍摄飞行光脉冲及光子计数直方图[11]Fig.5 SPAD camera captures light-in-flight pulses and the photon count histogram[11]

图6 基于幅度调制的ToF发射器及传感器的基本工作原理[32]Fig.6 Basic operation principle of a time-of-flight emitter-sensor setup[32]

图7 干涉测量方法及干涉图像[37]Fig.7 Interferometric method and interference image[37]

图8 基于反投影算法复原隐藏物体的三维形状[40-41]Fig.8 Recovering the 3D shape of hidden objects based on back-projection algorithm[40-41]

图9 LCT及反投影算法对隐藏物体三维形状复原效果的对比[45]Fig.9 Comparison of effects of LCT and back projection algorithms on 3D shape restoration of hidden objects[45]

图10 表面几何优化及结果[3]Fig.10 Surface geometry optimization and result[3]

图11 费马路径与瞬态不连续点路径长度[50]Fig.11 Fermat path and path length of transient discontinuities[50]

图12 反照率体积复原及表面形状重建效果对比[3]Fig.12 Comparison of effect of albedo volume restoration and surface shape reconstruction[3]

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梁云,宋柏延.基于瞬态图像的非视距成像技术综述[J].数据采集与处理,2022,37(1):21-34

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收稿日期:2021-04-30
最后修改日期:2021-09-29
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在线发布日期: 2022-01-29

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