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1.中国科学院 长春光学精密机械与物理研究所 光学系统先进制造技术重点 实验室,吉林 长春 130033
2.中国科学院大学,北京 100049
[ "王蔚松(1995-),山东威海人,硕士,2018年于中国海洋上大学获得学士学位,现为中科院长春光学精密机械与物理研究所硕士研究生,主要从事单像素成像方面的研究。E-mail: wangweisong258@126.com" ]
收稿日期:2021-03-03,
修回日期:2021-03-23,
纸质出版日期:2021-08-15
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王蔚松,吴洪波,王灵杰等.自适应Radon单像素成像[J].光学精密工程,2021,29(08):1976-1984.
WANG Wei-song,WU Hong-bo,WANG Ling-jie,et al.Adaptive radon single-pixel imaging method[J].Optics and Precision Engineering,2021,29(08):1976-1984.
王蔚松,吴洪波,王灵杰等.自适应Radon单像素成像[J].光学精密工程,2021,29(08):1976-1984. DOI: 10.37188/OPE.20212908.1976.
WANG Wei-song,WU Hong-bo,WANG Ling-jie,et al.Adaptive radon single-pixel imaging method[J].Optics and Precision Engineering,2021,29(08):1976-1984. DOI: 10.37188/OPE.20212908.1976.
使用单像素探测器实现成像需要大量采样。对于目标区域仅占场景一部分的情况时,我们提出了自适应Radon单像素成像方法,能够使用单像素探测器实现目标区域的定位和成像。本文对该方法的目标定位方式、编码采样算法、重建算法等进行研究,以减少单像素成像的采样数量。基于Radon变换的基本原理,使用图像在水平和垂直方向的投影信息,以获取场景中目标区域的大小和位置。建立自适应Radon-Hadamard单像素成像模型,仅对目标区域进行单像素采样,然后使用滤波反投影技术重建目标区域。研究结果表明:所提出的自适应Radon单像素成像方法能够实现对场景中目标区域的成像,采样数量远低于重建图像的分辨率,重建图像的结构相似性系数大于95%,有效的提高了单像素成像方法的成像效率。
Single-pixel imaging requires a large amount of sampling. In this study, an adaptive Radon single-pixel imaging method is proposed for the target region that only occupies a part of the scene. This method uses single-pixel detectors to position and image the target region. We used the target positioning method, coding sampling, and reconstruction algorithms to reduce the number of single-pixel imaging samples. Based on the fundamental principle of Radon transformation, the projection information of an image in horizontal and vertical directions was used to obtain the size and position of the target region in the scene. This method established the adaptive Radon-Hadamard single-pixel imaging model. Only single-pixel sampling was performed on the target region and filtered back-projection technology was used to reconstruct the target region. The results show that the proposed adaptive Radon single-pixel imaging method can achieve imaging of the target region in a scene. The number of samples was much lower than the resolution of the reconstructed image and the structural similarity index of the reconstructed image was greater than 95%, which effectively improved the imaging efficiency of single-pixel imaging method.
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