Volume 12 Issue 6
Dec.  2019
Turn off MathJax
Article Contents
ZHENG Yun-da, HUANG Wei, PAN Yun, XU Ming-fei, JIA Shu-qiang, ZHANG Xiao-fei, LU Yong-nan. Wide-spectrum PSF estimation for simple optical system[J]. Chinese Optics, 2019, 12(6): 1418-1430. doi: 10.3788/CO.20191206.1418
Citation: ZHENG Yun-da, HUANG Wei, PAN Yun, XU Ming-fei, JIA Shu-qiang, ZHANG Xiao-fei, LU Yong-nan. Wide-spectrum PSF estimation for simple optical system[J]. Chinese Optics, 2019, 12(6): 1418-1430. doi: 10.3788/CO.20191206.1418

Wide-spectrum PSF estimation for simple optical system

doi: 10.3788/CO.20191206.1418
Funds:

the State Key Laboratory of Applied Optics 

More Information
  • Author Bio:

    ZHENG Yunda (1992—), Ph.D., male, from Yanbian, Jilin, obtained a bachelor's degree from the University of Science and Technology of China in 2014, he is mainly engaged in research in image restoration and optical design.E-mail:yundazheng@foxmail.com

    HUANG Wei (1965—), researcher and doctoral tutor, male, from Jilin Changchun, he is mainly engaged in the research of optical systems design.E-mail:huangw@ciomp.ac.cn

  • Corresponding author: HUANG Wei, E-mail:huangw@ciomp.ac.cn
  • Received Date: 10 Jan 2019
  • Rev Recd Date: 09 Mar 2019
  • Publish Date: 01 Dec 2019
  • In order to obtain point spread functions(PSFs) of a simple optical system accurately and improve the restored image quality, we present a wide-spectrum PSF estimation method based on PSF measurements. First, narrow-band PSFs are measured, and combining image matching algorithm, the sensor position and the deviation of the optical axis in the real optical system are calibrated. Then, the PSF of each wavelength and field of view is simulated and used for calculating the wide-spectrum PSFs of the real optical system according to the object reflectance spectrum and the spectral sensitivity information of the sensor. Experimental results indicate that the proposed PSF estimation method is better than the narrow-band PSF estimation and blind PSF estimation. The restored image is more stable and its quality is improved significantly. The proposed method can estimate the PSFs of the real optical imaging system accurately.

     

  • loading
  • [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. doi: 10.3969/j.issn.2095-1531.2012.02.014

    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) doi: 10.3969/j.issn.2095-1531.2012.02.014
    [2]
    常松涛, 孙志远, 张尧禹, 等.基于点扩散函数的小目标辐射测量[J].光学 精密工程, 2014, 22(11):2879-2887. http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201411001

    CHANG S T, SUN ZH Y, ZHANG Y Y, et al.. Radiation measurement of small targets based on PSF[J]. Opt. Precision Eng., 2014, 22(11):2879-2887.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201411001
    [3]
    KRISHNAN D, TAY T, FERGUS R. Blind deconvolution using a normalized sparsity measure[C]. Proceedings of the 2011 Computer Vision and Pattern Recognition, IEEE, 2011, 42: 233-240.
    [4]
    SCHULER C J, HIRSCH M, HARMELING S, et al.. Blind correction of optical aberrations[C]. Proceedings of the European Conference on Computer Vision, Springer, 2012: 187-200.
    [5]
    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
    [6]
    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
    [7]
    KEE E, PARIS S, HEN S, et al.. Modeling and removing spatially-varying optical blur[C]. Proceedings of the 2011 IEEE International Conference on Computational Photography, IEEE, 2011: 1-8.
    [8]
    BRAUERS J, SEILER C, AACH T. Direct PSF estimation using a random noise target[J]. Proceedings of SPIE, 2010, 7537:75370B. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=CC0210191959
    [9]
    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://d.old.wanfangdata.com.cn/NSTLQK/NSTL_QKJJ0231441120/
    [10]
    郝玲.基于空变系统图像恢复的点扩散函数获取研究[D].哈尔滨: 哈尔滨工业大学, 2012.

    HAO L. Point spread function obtaining research based on the linear space variant image restoration[D]. Harbin: Harbin Institute of Technology, 2012.(in Chinese)
    [11]
    ZHENG Y D, HUANG W, PAN Y, et al.. Optimal PSF estimation for simple optical system using a wide-band sensor based on PSF measurement[J]. Sensors, 2018, 18(10):3552. doi: 10.3390/s18103552
    [12]
    陈新华, 季轶群, 沈为民, 等.基于星点图像的小像差复原[J].光学 精密工程, 2012, 20(4):706-711. http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201204004

    CHEN X H, JI Y Q, SHEN W M, et al.. Small-aberration retrieval based on spot images[J]. Opt. Precision Eng., 2012, 20(4):706-711.(in Chinese) http://d.old.wanfangdata.com.cn/Periodical/gxjmgc201204004
    [13]
    SIMPKINS J D, STEVENSON R L. A spatially varying PSF model for Seidel aberrations and defocus[J]. Proceedings of SPIE, 2013, 8666:86660F. doi: 10.1117/12.2008851
    [14]
    WANG CH, HEN J, JIA H G, et al.. Parameterized modeling of spatially varying PSF for lens aberration and defocus[J]. Journal of the Optical Society of Korea, 2015, 19(2):136-143. doi: 10.3807/JOSK.2015.19.2.136
    [15]
    SHIH Y, GUENTER B, JOSHI N. Image enhancement using calibrated lens simulations[C]. Proceedings of the European Conference on Computer Vision, Springer, 2012, 7575: 42-56.
    [16]
    GONZALEZ R C, WOODS R E. Digital Image Processing[M]. 3rd ed.India:Prentice Hall, 2008.
    [17]
    KRISHNAN D, FERGUS R. Fast image deconvolution using hyper-Laplacian priors[C]. Proceedings of the 22nd International Conference on Neural Information Processing Systems, Curran Associates Inc., 2009: 1033-1041.
    [18]
    ALMEIDA M S C, ALMEIDA L B. Blind and semi-blind deblurring of natural images[J]. IEEE Transactions on Image Processing, 2010, 19(1):36-52. doi: 10.1109-TIP.2009.2031231/
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(10)  / Tables(2)

    Article views(1899) PDF downloads(135) Cited by()
    Proportional views

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return