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摘要: 目前对于超分辨成像技术的研究主要集中在超分辨重建算法方面,光学系统本身的装调误差对超分辨成像结果的影响尚未见报道。针对这一问题,开展了装调误差对超分辨成像影响的研究,建立了基于数字微镜器件(DMD)的超分辨成像光学系统的基本成像模型,设计了一个工作波段为8~12 μm的DMD超分辨成像光学系统,提出了装调误差对超分辨成像质量影响的分析方法。在成像模型中分别引入适当的偏心、倾斜、镜片间隔误差、离焦等装调误差,对超分辨重建结果进行仿真分析,得出了该超分辨成像光学系统装调时的公差范围:该系统在加工装调时X方向总体偏心误差控制在±0.07 mm以内,Y方向总体偏心误差控制在±0.05 mm以内,X方向和Y方向的总体倾斜误差控制在±0.06°以内,总体镜片间隔误差控制在±0.02 mm以内,成像物镜的离焦量控制在±0.04 mm以内,投影物镜的离焦量控制在±0.05 mm以内,在此范围内超分辨成像光学系统可以保证超分辨成像的质量。Abstract: At present, most of the research on super-resolution imaging technology is focused on the super-resolution reconstruction algorithm, but the influence of the alignment error of an optical system on the super-resolution imaging results has not been reported. To solve this problem, We researche the influence of alignment error on super-resolution imaging. First, the basic imaging model of super-resolution imaging optical system based on Digital Micro-mirror Device (DMD) is established. A DMD super-resolution imaging optical system with operating band of 8~12 μm is designed, and a method used to analyze the influence of the alignment error on super-resolution imaging quality is proposed. In the imaging model, alignment errors such as eccentricity, tilt, lens spacing error and defocus are introduced, and the reconstruction results are analyzed. Finally, the range of tolerance of the super-resolution imaging optical system is obtained. The results show that the total eccentricity error in the X direction is controlled within ± 0.07 mm, and that in the Y direction is within ±0.05 mm; the total tilt error in the X and Y directions is controlled within ±0.06°; the overall lens spacing error is controlled within ±0.02 mm; the defocusing amount of the imaging object lens is controlled within ±0.04 mm; the defocusing amount of the projection objective lens is controlled within ±0.05 mm, and within this range, the super-resolution imaging optical system can ensure the quality of super-resolution imaging.
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表 1 光学系统参数
Table 1. Performance parameters of the optical system
Parameter Value Wavelength/μm 8~12 Field of view FOV(X/Y)/(°) 0~4.4/0~3.52 F number 1.76 DMD array size 1920 pixel×1080 pixel DMD pixel size/μm 10.8 Detector pixel size/μm 17 Detector array size 640 pixel×512 pixel Dynamic range of detector/dB 29 表 2 公差分配结果
Table 2. Tolerance allocation results
偏心/mm 倾斜/(°) 镜片间隔
误差/mm成像物镜
离焦/mm投影物镜
离焦/mmX Y X Y 0.07 0.05 0.06 0.06 0.02 0.04 0.05 -
[1] 张旭东. 基于压缩感知和深度学习的超分辨成像方法研究[D]. 上海: 中国科学院大学(中国科学院上海技术物理研究所), 2019.ZHANG X D. Research on super-resolution imaging based on compressive sensing and deep learning[D]. Shanghai: University of Chinese Academy of Sciences (Shanghai Institute of Technical Physics Chinese Academy of Sciences), 2019. (in Chinese). [2] TIMOFTE R, AGUSTSSON E, VAN GOOL L, et al.. NTIRE 2017 challenge on single image super-resolution: methods and results[C]. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, IEEE, 2017: 1110-1121. [3] YANG J CH, WRIGHT J, HUANG T S, et al. Image super-resolution via sparse representation[J]. IEEE Transactions on Image Processing, 2010, 19(11): 2861-2873. doi: 10.1109/TIP.2010.2050625 [4] YANG SH Y, SUN F H, WANG M, et al.. Novel super resolution restoration of remote sensing images based on compressive sensing and example patches-aided dictionary learning[C]. 2011 International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping, IEEE, 2011: 1-6. [5] 张赛文, 林丹樱, 于斌, 等. 基于压缩感知的三维单分子定位显微成像方法研究[J]. 中国光学,2020,13(5):1065-1074. doi: 10.37188/CO.2020-0003ZHANG S W, LIN D Y, YU B, et al. Three-dimensional single-molecule localization microscopy imaging based on compressed sensing[J]. Chinese Optics, 2020, 13(5): 1065-1074. (in Chinese) doi: 10.37188/CO.2020-0003 [6] 朱丹彤. 编码孔径成像光谱仪系统集成及光谱复原实验研究[D]. 长春: 中国科学院大学(中国科学院长春光学精密机械与物理研究所), 2018.ZHU D T. Research on system integration and spectral restoration experiment of coded aperture imaging spectrometer[D]. Changchun: University of Chinese Academy of Sciences (Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences), 2018. (in Chinese). [7] DUMAS J P, LODHI M A, BAJWA W U, et al. Computational imaging with a highly parallel image-plane-coded architecture: challenges and solutions[J]. Optics Express, 2016, 24(6): 6145-6155. doi: 10.1364/OE.24.006145 [8] 孙小桐. 基于常见模糊类型的图像复原技术方法研究[D]. 长春: 长春工业大学, 2019.SUN X T. Research on image restoration technology based on common fuzzy types[D]. Changchun: Changchun University of Technology, 2019. (in Chinese). [9] 刘铭鑫, 张新, 王灵杰, 等. 压缩感知光谱成像技术的编码孔径与探测器匹配优化[J]. 中国光学,2020,13(2):290-301. doi: 10.3788/co.20201302.0290LIU M X, ZHANG X, WANG L J, et al. Optimization of matching coded aperture with detector based on compressed sensing spectral imaging technology[J]. Chinese Optics, 2020, 13(2): 290-301. (in Chinese) doi: 10.3788/co.20201302.0290 [10] 周程灏, 王治乐, 刘尚阔. 基于空间变化点扩展函数的图像直接复原方法[J]. 光学学报,2017,37(1):0110001. doi: 10.3788/AOS201737.0110001ZHOU CH H, WANG ZH L, LIU SH K. Method of image restoration directly based on spatial varied point spread function[J]. Acta Optica Sinica, 2017, 37(1): 0110001. (in Chinese) doi: 10.3788/AOS201737.0110001 [11] TROPP J A, GILBERT A C. Signal recovery from random measurements via orthogonal matching pursuit[J]. IEEE Transactions on Information Theory, 2007, 53(12): 4655-4666. doi: 10.1109/TIT.2007.909108 [12] 张一, 余卿, 张昆, 等. 基于数字微镜器件的并行彩色共聚焦测量系统[J]. 光学 精密工程,2020,28(4):859-866.ZHANG Y, YU Q, ZHANG K, et al. Parallel chromatic confocal measurement system based on digital micromirror device[J]. Optics and Precision Engineering, 2020, 28(4): 859-866. (in Chinese) [13] 王丽, 王威, 陈博. 改进的粒子群优化正交匹配追踪重构算法[J]. 小型微型计算机系统,2019,40(8):1755-1759. doi: 10.3969/j.issn.1000-1220.2019.08.034WANG L, WANG W, CHEN B. Improved particle swarm optimization orthogonal matching pursuit reconstruction algorithm[J]. Journal of Chinese Computer Systems, 2019, 40(8): 1755-1759. (in Chinese) doi: 10.3969/j.issn.1000-1220.2019.08.034 [14] 吕博, 冯睿, 寇伟, 等. 折反射式空间相机光学系统设计与杂散光抑制[J]. 中国光学,2020,13(4):822-831. doi: 10.37188/CO.2019-0036LV B, FENG R, KOU W, et al. Optical system design and stray light suppression of catadioptric space camera[J]. Chinese Optics, 2020, 13(4): 822-831. (in Chinese) doi: 10.37188/CO.2019-0036 [15] 陈明惠, 王帆, 张晨曦, 等. 基于压缩感知的频域OCT图像稀疏重构[J]. 光学 精密工程,2020,28(1):189-199. doi: 10.3788/OPE.20202801.0189CHEN M H, WANG F, ZHANG CH X, et al. Sparse reconstruction of frequency domain OCT image based on compressed sensing[J]. Optics and Precision Engineering, 2020, 28(1): 189-199. (in Chinese) doi: 10.3788/OPE.20202801.0189 [16] 刘琳, 沈为民, 周建康. 中波红外大相对孔径消热差光学系统的设计[J]. 中国激光,2010,37(3):675-679. doi: 10.3788/CJL20103703.0675LIU L, SHEN W M, ZHOU J K. Design on athermalised middle wavelength infrared optical system with large relative aperture[J]. Chinese Journal of Lasers, 2010, 37(3): 675-679. (in Chinese) doi: 10.3788/CJL20103703.0675 [17] 李杰, 朱京平. 光波导短程透镜加工容限误差研究[J]. 物理学报,2012,61(24):244208. doi: 10.7498/aps.61.244208LI J, ZHU J P. Fabrication tolerances in four analytical designs of geodesic lenses[J]. Acta Physica Sinica, 2012, 61(24): 244208. (in Chinese) doi: 10.7498/aps.61.244208 [18] 马原, 吕群波, 刘扬阳, 等. 编码孔径成像光谱仪光学放大率误差影响分析[J]. 光谱学与光谱分析,2014,34(11):3157-3161. doi: 10.3964/j.issn.1000-0593(2014)11-3157-05MA Y, LV Q B, LIU Y Y, et al. Effect evaluation of optical magnification errors for coded aperture spectrometer[J]. Spectroscopy and Spectral Analysis, 2014, 34(11): 3157-3161. (in Chinese) doi: 10.3964/j.issn.1000-0593(2014)11-3157-05