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Blind Image Restoration with Defocus Blur by Estimating Point Spread Function in Frequency Domain

Published: 27 January 2022 Publication History

Abstract

A blind image restoration method is proposed to enhance the quality of defocus blurred image. Firstly, The defocused blurred image is converted to the frequency domain in order to analyze its spectral characteristics. Secondly, the defocus radius of the defocus point spread function is automatically estimated by calculating the distance between the center point and the nearest black circle. Thirdly, utilizing the estimated defocus point spread function, the image is blindly restored by the constrained least squares algorithm. Forthly, the impact of defocus point spread fuction on the restored image is tested. Experimental results show that the proposed defocus point spread function estimation algorithm has high accuracy, and the restored image achieves better visual effect and higher PSNR around the real defocus point spread function.

References

[1]
M.Y. Zou. 2004. Deconvolution and Signal Recovery.Defense Industry Publishing.
[2]
X.Y. Wang. 2017. Research on Image Denoising and Restoration Method.China Industry and Information Technology Publishing Group.
[3]
L.Zhang, and W.M. Zuo.2017. Fast Roughness Minimizing Image Restoration Under Mixed Posson-Gaussian Noise. IEEE Signal Processing Magazine. 172-179.
[4]
K. Alpaslan, and G.Albert. 2019. Design and evaluation of an accurate CNR-guided small region iterative restoration-based tumor segmentation scheme for PET using both simulated and real heterogeneous tumors. Medical & Biological Engineering & Computing.
[5]
N. Kwak, J. Yoo, and S. ho Lee. 2018. Image restoration by estimating frequency distribution of local patches. IEEE Conference on Computer Vision and Pattern Recognition.
[6]
F.-Q. Qin, X.-H. He, W.-L. Chen, X.-M. Yang and W. Wu. 2009. Video super-resolution reconstruction based on sub-pixel registration and iterative back projection. Journal of Electronic Imaging. vol.18,A1,0-11.
[7]
C.H.Lu, X.H. He, and Q.C.Tao. 2017. Min.Zhang.Research on Parameter Estimation Algorithm of Gaussian Point Spread Function in Image Restoration. Sichuan University. Vol.43, A10, 31-34.
[8]
T.Taxt.1997. Comparison of cepstrum-based methods for radial blind deconvolution of ultrasound images. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. Vol. 44, A3, 666-674.
[9]
Yitzhaky Y, and Kopeika N S. 1997. Identification of blur parameters from defocus blurred images. Graphical Models and Image Processing. Vol.59, A5, 310-320.
[10]
Lokhande R, Arya K V, and Gupta P. 2016. Identification of parameters and restoration of defocus blurred images.Dijon, France2. Vol.12, 2-10.
[11]
Ahlad Kumar. 2018. Deblurring of defocus blurred images using histogram of oriented gradients and geometric moments. Signal Processing: Image Communication. 55-65.
[12]
Alper Yilmaz, Omar Javed, and Mubarak Shah. 2006. Object tracking: A survey. ACM Comput. Surv. 38, 4 (December 2006), 13–es. https://doi.org/10.1145/1177352.1177355
[13]
Fengqing Qin.2012. Blind image restoration based on Wiener filtering and defocus point spread function estimation. 5th International Congress on Image and Signal Processing (CISP).
[14]
L Bar, N Sochen, N Kiryati.2017.Blind Space-Variant Single-Image Restoration of Defocus Blur.6th International Conference on SSVM.
[15]
Yin Shi-Bai, Wang Wei-Xing, Wang Yi-Bin, Li Da-Peng, Deng Zhen. 2016. Fast Bayesian blind restoration for single defocus image with iterative joint bilateral filters.Acta Physica Sinica. 65(23): 234202.

Cited By

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  • (2024)Ultra-high-definition underwater image enhancement via dual-domain interactive transformer networkInternational Journal of Machine Learning and Cybernetics10.1007/s13042-024-02379-x16:3(2093-2109)Online publication date: 15-Sep-2024
  • (2023)FSI: Frequency and Spatial Interactive Learning for Image Restoration in Under-Display Cameras2023 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV51070.2023.01152(12503-12512)Online publication date: 1-Oct-2023
  • (2022)UHD Underwater Image Enhancement via Frequency-Spatial Domain Aware NetworkComputer Vision – ACCV 202210.1007/978-3-031-26313-2_2(21-36)Online publication date: 4-Dec-2022

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cover image ACM Other conferences
ICAIP '21: Proceedings of the 5th International Conference on Advances in Image Processing
November 2021
112 pages
ISBN:9781450385183
DOI:10.1145/3502827
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 January 2022

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Author Tags

  1. Blind image restoration
  2. constrained least squares
  3. defocus blur
  4. frequency domain
  5. point spread function(PSF)

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Cited By

View all
  • (2024)Ultra-high-definition underwater image enhancement via dual-domain interactive transformer networkInternational Journal of Machine Learning and Cybernetics10.1007/s13042-024-02379-x16:3(2093-2109)Online publication date: 15-Sep-2024
  • (2023)FSI: Frequency and Spatial Interactive Learning for Image Restoration in Under-Display Cameras2023 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV51070.2023.01152(12503-12512)Online publication date: 1-Oct-2023
  • (2022)UHD Underwater Image Enhancement via Frequency-Spatial Domain Aware NetworkComputer Vision – ACCV 202210.1007/978-3-031-26313-2_2(21-36)Online publication date: 4-Dec-2022

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