Single-pixel imaging: An overview of different methods to be used for 3D space reconstruction in harsh environments

计算机科学 光电探测器 图像传感器 像素 探测器 砷化铟镓 光学 噪音(视频) 多光谱图像 夜视 人工智能 光电子学 材料科学 计算机视觉 砷化镓 物理 电信 图像(数学)
作者
Carlos Osorio Quero,Daniel Durini,José Rangel-Magdaleno,José Martínez-Carranza
出处
期刊:Review of Scientific Instruments [American Institute of Physics]
卷期号:92 (11) 被引量:22
标识
DOI:10.1063/5.0050358
摘要

Different imaging solutions have been proposed over the last few decades, aimed at three-dimensional (3D) space reconstruction and obstacle detection, either based on stereo-vision principles using active pixel sensors operating in the visible part of the spectra or based on active Near Infra-Red (NIR) illumination applying the time-of-flight principle, to mention just a few. If extremely low quantum efficiencies for NIR active illumination yielded by silicon-based detector solutions are considered together with the huge photon noise levels produced by the background illumination accompanied by Rayleigh scattering effects taking place in outdoor applications, the operating limitations of these systems under harsh weather conditions, especially if relatively low-power active illumination is used, are evident. If longer wavelengths for active illumination are applied to overcome these issues, indium gallium arsenide (InGaAs)-based photodetectors become the technology of choice, and for low-cost solutions, using a single InGaAs photodetector or an InGaAs line-sensor becomes a promising choice. In this case, the principles of Single-Pixel Imaging (SPI) and compressive sensing acquire a paramount importance. Thus, in this paper, we review and compare the different SPI developments reported. We cover a variety of SPI system architectures, modulation methods, pattern generation and reconstruction algorithms, embedded system approaches, and 2D/3D image reconstruction methods. In addition, we introduce a Near Infra-Red Single-Pixel Imaging (NIR-SPI) sensor aimed at detecting static and dynamic objects under outdoor conditions for unmanned aerial vehicle applications.
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