大视场高像质简单光学系统的光学-算法协同设计

郑云达; 黄玮; 徐明飞; 潘云; 贾树强; 张晓菲; 卢勇男

doi:10.3788/CO.20191205.1090

大视场高像质简单光学系统的光学-算法协同设计

doi: 10.3788/CO.20191205.1090

郑云达^{1, 2,},
黄玮^1, ,,
徐明飞¹,
潘云^{1, 2},
贾树强¹,
张晓菲^{1, 2},
卢勇男^{1, 2}

1.
中国科学院长春光学精密机械与物理研究所, 吉林长春 130033
2.
中国科学院大学, 北京 100049

基金项目: 应用光学国家重点实验室自主基金资助

详细信息

作者简介:
郑云达(1992-), 男, 吉林延边人, 博士, 2014年于中国科学技术大学获得学士学位, 主要从事图像复原及光学设计方面的研究。E-mail:yundazheng@foxmail.com

黄玮(1965-), 男, 吉林长春人, 研究员, 博士生导师, 主要从事光学系统设计方面的研究。E-mail:huangw@ciomp.ac.cn

中图分类号: TP394.1;TH691.9
计量
- 文章访问数: 464
- HTML全文浏览量: 109
- PDF下载量: 14
- 被引次数: 0
出版历程
- 收稿日期: 2018-12-28
- 修回日期: 2019-02-26
- 刊出日期: 2019-10-01

Optical/algorithmic co-design of large-field high-quality simple optical system

ZHENG Yun-da^{1, 2
,},
HUANG Wei^{1
, ,},
XU Ming-fei¹,
PAN Yun^{1, 2},
JIA Shu-qiang¹,
ZHANG Xiao-fei^{1, 2},
LU Yong-nan^{1, 2}

1.
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
2.
University of Chinese Academy of Sciences, , Beijing 100049, China

Funds: Supported by the State Key Laboratory of Applied Optics

More Information

Corresponding author: HUANG Wei, E-mail:huangw@ciomp.ac.cn

摘要

摘要: 为了实现高像质相机低成本、小型化的需求，本文提出了一种大视场简单光学系统的光学-算法协同设计方法，并通过图像复原算法校正简单光学系统的残余像差。首先，针对大视场光学系统，对空间变化的交叉通道去卷积算法进行改进，加入倍率色差校正，使图像复原算法可显著去除色差的影响。然后，在光学设计过程中，放开色差的约束，并专注优化绿色通道的像质，使其成像锐利，在后期交叉通道去卷积算法中有助于红、蓝两通道图像复原。利用该方法设计了一个由两片同种材料的镜片构成的大视场简单光学系统。系统焦距为50 mm，全视场为46°，F数为5.6，探测器分辨率为1 000万像素。实验结果表明：本文设计的两片镜、大视场简单光学系统的成像质量可媲美三片式库克镜头，明显优于纯图像复原的结果。本文方法实现了大视场简单光学系统的设计，并能够通过系统最终获得高分辨率、高像质图像。
- 计算成像 /
- 光学系统设计 /
- 图像复原 /
- 去卷积
Abstract: In order to meet requirements of the low cost and miniaturization of high-quality cameras, an optical/algorithmic co-design method for a large-field simple optical system is proposed. The residual aberrations of this simple optical system are corrected using an image restoration algorithm. Firstly, spatially varying cross-channel deconvolution is improved for large-field optical systems, wherein correction of lateral chromatic aberrations is introduced so that they can be significantly removed through the image restoration algorithm. Then, when designing the optical system, the constraints of chromatic aberrations are removed and we concentrate on optimizing the quality of the green channel to make the image sharp, which will help the restoration of images in the red and the blue channels in later cross-channel deconvolution. Using this method, a large-field simple optical system with two lenses of the same material is designed. The focal length of the system is 50 mm, the full field is 46 degrees, the F number is 5.6 and the resolution of the sensor is 10 mega pixels. Experimental results indicate that the image quality of the proposed simple large-field optical system is comparable to that when using a Cooke triplet lens and is better than that when using pure image restoration algorithms. Our proposed method succeeds as a simple large-field optical system and can obtain high-resolution and high-quality images.
- computational imaging /
- optical system design /
- image restoration /
- deconvolution

HTML全文

图 1 空间变化方案示意图

Figure 1. Diagram of the space-variant strategy

下载: 全尺寸图片幻灯片

图 2 图片分块重叠部分的拼接示意图

Figure 2. Diagram of stitching method of image overlapping parts

下载: 全尺寸图片幻灯片

图 3 交叉通道先验示意图

Figure 3. Scanline diagrams of cross-channel prior

下载: 全尺寸图片幻灯片

图 4 简单光学系统结构图

Figure 4. Layout of simple optical system

下载: 全尺寸图片幻灯片

图 5 简单光学系统设计结果

Figure 5. Designed results of simple optical system

下载: 全尺寸图片幻灯片

图 6 简单光学系统的空间变化PSF

Figure 6. Space-variant PSFs of the simple optical system

下载: 全尺寸图片幻灯片

图 7 图像复原结果

Figure 7. Image restoration results

下载: 全尺寸图片幻灯片

图 8 常规设计的两片镜系统

Figure 8. Conventional designed two-lens optical system

下载: 全尺寸图片幻灯片

图 9 鲜花图像复原结果对比s

Figure 9. Comparison of restoration results of a flower image

下载: 全尺寸图片幻灯片

图 10 校园图像复原结果对比

Figure 10. Comparison of restoration results of a campus image

下载: 全尺寸图片幻灯片

图 11 库克三片式镜头

Figure 11. Cooke triplet lens

下载: 全尺寸图片幻灯片

表 1 简单光学系统的镜头参数

Table 1. Lens data of the simple optical system

Surface	Radius	Thickness	Glass	Semi-Aperture
Object	Infinity	Infinity
1	7.872 8	1.71	HK9L_CDGM	6.30
2	6.582 4	5.57		5.38
stop	Infinity	4.28		4.28
4	-33.333 4	10.00	HK9L_CDGM	6.28
5	-13.943 6	56.45		9.10
Image	Infinity	0		20.21

下载: 导出CSV

表 2 BRISQUE评价结果对比

Table 2. Comparison of BRISQUE scores

	Flowers	Campus
Ground truth	17.079 6	21.843 0
Krishnan et al.	51.551 5	49.697 0
Heide et al.	44.991 0	44.785 0
Ours	30.548 2	39.275 0
Cooke lens	29.490 0	36.888 0

下载: 导出CSV

表 3 NIQE评价结果对比

Table 3. Comparison of NIQE scores

	Flowers	Campus
Ground truth	3.238 0	3.333 8
Krishnan et al.	6.612 2	6.527 4
Heide et al.	6.059 0	5.825 9
Ours	4.838 0	4.577 5
Cooke lens	4.200 0	4.413 1

下载: 导出CSV

参考文献(22)

[1]	杨利红, 赵变红, 张星祥, 等.点扩散函数高斯拟合估计与遥感图像恢复[J].中国光学, 2012, 5(2):181-188. http://www.chineseoptics.net.cn/CN/abstract/abstract8812.shtml YANG L H, ZHAO B H, ZHANG X X, et al.. Gaussian fitted estimation of point spread function and remote sensing image restoration[J]. Chinese Optics, 2012, 5(2):181-188.(in Chinese) http://www.chineseoptics.net.cn/CN/abstract/abstract8812.shtml
[2]	闫敬文, 彭鸿, 刘蕾, 等.基于L₀正则化模糊核估计的遥感图像复原[J].光学精密工程, 2014, 22(9):2572-2579. http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201409037 YAN J W, PENG H, LIU L, et al.. Remote sensing image restoration based on zero-norm regularized kernel estimation[J]. Opt. Precision Eng., 2014, 22(9):2572-2579.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201409037
[3]	曹海霞, 巴音贺希格, 崔继承, 等.基于图像复原的高光谱图像前向像移补偿[J].中国光学, 2013, 6(6):856-862. http://www.chineseoptics.net.cn/CN/abstract/abstract8994.shtml CAO H X, BAYAIHESHIG, CUI J CH, et al.. Forward image motion compensation of hyper spectral image based on image restoration[J]. Chinese Optics, 2013, 6(6):856-862.(in Chinese) http://www.chineseoptics.net.cn/CN/abstract/abstract8994.shtml
[4]	杨航, 吴笑天, 王宇庆.基于结构字典学习的图像复原方法[J].中国光学, 2017, 10(2):207-218. http://d.old.wanfangdata.com.cn/Periodical/zggxyyygxwz201702005 YANG H, WU X T, WANG Y Q. Image restoration approach based on structure dictionary learning[J]. Chinese Optics, 2017, 10(2):207-218.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/zggxyyygxwz201702005
[5]	WIENER N. Extrapolation, Interpolation, and Smoothing of Stationary Time Series[M]. Cambridge, Massachusetts, USA:MIT Press, 1964.
[6]	RICHARDSON W H. Bayesian-based iterative method of image restoration[J]. Journal of the Optical Society of America, 1972, 62(1):55-59. doi: 10.1364/JOSA.62.000055
[7]	LUCY L B. An iterative technique for the rectification of observed distributions[J]. The Astronomical Journal, 1974, 79(6):745-754. doi: 10.1086/111605
[8]	LEVIN A, FERGUS R, DURAND F, et al.. Image and depth from a conventional camera with a coded aperture[J]. ACM Transactions on Graphics, 2007, 26(3):70. doi: 10.1145/1276377.1276464
[9]	KRISHNAN D, FERGUS R. Fast image deconvolution using hyper-Laplacian priors[C]. Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009, NIPS, 2009, 22: 1-9.
[10]	郭从洲, 秦志远.非凸高阶全变差正则化自然光学图像盲复原[J].光学精密工程, 2015, 23(12):3490-3499. http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201512027 GUO C ZH, QIN ZH Y. Blind restoration of nature optical images based on non-convex high order total variation regularization[J]. Opt. Precision Eng., 2015, 23(12):3490-3499.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201512027
[11]	YUE T, SUO J L, WANG J, et al.. Blind optical aberration correction by exploring geometric and visual priors[C]. 2015 IEEE Conference on Computer Vision and Pattern Recognition, IEEE, 2015: 1684-1692.
[12]	张金刚, 相里斌, 汶德胜, 等.采用色差先验约束的像差校正技术[J].中国光学, 2018, 11(4):560-567. http://www.chineseoptics.net.cn/CN/abstract/abstract9579.shtml ZHANG J G, XIANG L B, WEN D SH, et al.. Aberration correction technology based on chromatic aberration prior constraints[J]. Chinese Optics, 2018, 11(4):560-567.(in Chinese) http://www.chineseoptics.net.cn/CN/abstract/abstract9579.shtml
[13]	SCHULER C J, HIRSCH M, HARMELING S, et al.. Non-stationary correction of optical aberrations[C]. 2011 International Conference on Computer Vision, IEEE, 2011: 659-666.
[14]	HEIDE F, ROUF M, HULLIN M B, et al.. High-quality computational imaging through simple lenses[J]. ACM Transactions on Graphics, 2013, 32(5):149. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=fbb2ee3c18e52a4fff4d6d4f6cea3b40
[15]	LI W L, LIU Y, YIN X Q, et al.. A computational photography algorithm for quality enhancement of single lens imaging deblurring[J]. Optik, 2015, 126(21):2788-2792. doi: 10.1016/j.ijleo.2015.07.030
[16]	WANG J Y, WANG L, YANG Y, et al.. An integral design strategy combining optical system and image processing to obtain high resolution images[J]. Proceedings of SPIE, 2016, 9874:98740F. doi: 10.1117/12.2224394
[17]	谭政, 相里斌, 吕群波, 等.基于像差选择性校正的光学-数字联合设计[J].光子学报, 2018, 47(5):0511001. http://d.old.wanfangdata.com.cn/Periodical/gzxb201805022 TAN ZH, XIANG L B, LV Q B, et al.. Optics/digital processing co-design method based on aberration optional-correcting[J]. Acta Photonica Sinica, 2018, 47(5):0511001. in Chinese http://d.old.wanfangdata.com.cn/Periodical/gzxb201805022
[18]	崔金林.基于计算光学的非完善光学系统图像质量提高及其应用研究[D].长春: 中国科学院长春光学精密机械与物理研究所, 2018. CUI J L. Research on enhancing imaging quality of imperfect optical systems and its application via computational optics[D]. Changchun: Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, 2018.(in Chinese)
[19]	CHAMBOLLE A, POCK T. A first-order primal-dual algorithm for convex problems with applications to imaging[J]. Journal of Mathematical Imaging and Vision, 2011, 40(1):120-145. doi: 10.1007/s10851-010-0251-1
[20]	张以谟.应用光学[M].北京:电子工业出版社, 2012. ZHANG Y M. Applied Optics[M]. Beijing:Publishing House of Electronics Industry, 2012.(in Chinese)
[21]	MITTAL A, MOORTHY A K, BOVIK A C. No-reference image quality assessment in the spatial domain[J]. IEEE Transactions on Image Processing, 2012, 21(12):4695-4708. doi: 10.1109/TIP.2012.2214050
[22]	MITTAL A, SOUNDARARAJAN R, BOVIK A C. Making a "completely blind" image quality analyzer[J]. IEEE Signal Processing Letters, 2013, 20(3):209-212. doi: 10.1109/LSP.2012.2227726