Journal of the Institute of Electronics Engineers of Korea SP (대한전자공학회논문지SP)

The Institute of Electronics and Information Engineers (대한전자공학회)
권호 표지

Isotropic Out-of-focus Blur Estimation and Fully Digital Auto-Focusing Based on A Priori Estimated Set of PSF

등방성 초점열화 추정기법 및 사전 추정 점확산함수 집합을 이용한 완전 디지털 자동 초점 시스템

  • Published : 2004.09.01
Download PDF
⟨ Previous Next ⟩

Abstract

This paper proposes a method for estimating isotropic out-of-focus blur and a fully digital auto-focusing based on a priori estimate set of PSFs. The proposed algorithm for identifying the isotropic PSF is performed by approximating an isotropic blur to a novel discrete PSF model and estimating the PSF model coefficients from degraded edges. After acquiring the set of PSFs by proposed PSF estimation algorithm the proposed fully digital auto-focusing system can restore out-of-focused images by two steps: i) selecting an optimal PSF and ii) restoring the out-of-focused image by digital image restoration.

본 논문은 등방성 초점열화함수의 추정 기법 및 사전 추정 점확산함수 집합을 이용한 완전 디지털 자동초점 시스템의 구조를 제안한다. 제안하는 등방성 점확산함수 추정 기법은 초점 열화과정에서 점확산함수를 새로운 이산 등방성 점확산함수 모델을 이용하여 모델링하고 이를 열화된 영상의 에지로부터 추정해 내는 방법이다. 점확산함수 추정기법을 이용하여 여러 단계의 점확산함수를 사전에 추정한 후, 제안하는 완전 디지털 자동초점 시스템은 두 단계에 걸쳐 초점이 맞지 않은 입력 영상을 복원해 낸다. 첫째, 저장된 점확산함수 집합으로부터 최적의 점확산함수를 선택한다. 둘째, 선택된 점확산함수와 디지털 영상복원 기법을 이용하여 초점이 잘 맞은 영상으로 복원해 낸다.

Keywords

References

  1. H. C. Andrews and B. R. Hunt, Digital image restoration, Prentice-Hall, New Jersey, 1977
  2. S. K. Kim, S. R. Park, and J. K. Paik, 'Simultaneous Out-of-Focus Blur Estimation and Restoration for Digital AF System,' IEEE Trans. Consumer Electronics, vol. 44, no. 3, pp. 1071-1075, August 1998 https://doi.org/10.1109/30.713236
  3. A. M. Tekalp, H. Kaufman, and J. W. Woods, 'Identification of Image and Blur Parameters for the Restoration of Noncausal Blurs,' IEEE Trans. Acoustics, Speech, Signal Proc., vol. ASSP-34, no. 4, pp. 963-972, August 1986
  4. A. M. Tekalp and H. Kaufman, 'On Statistical Identification of a Class of Linear Space-Invariant Image Blurs Using Nonminimum-Phase ARMA Models,' IEEE Trans. Acoustics, Speech, Signal Proc., vol. 36, no. 8, pp. 1360-1363, August 1988 https://doi.org/10.1109/29.1666
  5. A. K. Katsaggelos, 'Maximum Likelihood Image Identification and Restoration Based on the EM Algorithm,' Proc. 1989 Multidimensional Signal Processing Workshop, September 1989 https://doi.org/10.1109/MDSP.1989.97107
  6. J. Biemond, F. G. van der Putten, and J. Woods, 'Identification and Restoration of Images with Symmetric Noncausal Blurs,' IEEE Trans. Circuits, Systems, vol. 35, no. 4, pp. 385-393, April 1988 https://doi.org/10.1109/31.1753
  7. R. L. Lagendijk, J. Biemond, and D. E. Boekee, 'Identification and Restoration of Noisy Blurred Image Using the Expectation-Maximization Algorithm,' IEEE Trans. Acoustics, Speech, Signal Proc., vol. 38 no. 7, pp. 1180-1191, July 1990 https://doi.org/10.1109/29.57545
  8. S. J. Reeves and M. R. Mersereau, 'Blur Identification by the Method of Generalized Cross-Validation,' IEEE Trans. Image Processing, vol. 1, no. 3, pp. 301-311, July 1992 https://doi.org/10.1109/83.148604
  9. D. P. K. Lun, T. C. L. Chan, T. C. Hsung, D. D. Feng, and Y. H. Chan, 'Efficient Blind Restoration Using Discrete Periodic Radon Transform,' IEEE Trans. Image Processing, vol. 13, no. 2, pp. 188-200, February 2004 https://doi.org/10.1109/TIP.2004.823820
  10. B. C. McCallum, 'Blind Deconvolution by Simulated Annealing,' Optics Communications, vol. 75(2), pp. 101-105, February 1990 https://doi.org/10.1016/0030-4018(90)90236-M
  11. D. Kundur and D. Hatzinakos, 'Blind Image Deconvolution,' IEEE Signal Processing Mag., vol. 4, pp. 43-64, May 1996 https://doi.org/10.1109/79.489268
  12. S. K. Kim and J. K. Paik, 'Out-of-Focus Blur Estimation and Restoration for Digital Auto-Focusing System,' Electronics letters, vol. 34, no. 12, pp. 1217-1219, June 1998 https://doi.org/10.1049/el:19980762
  13. W. K. Pratt, Digital Image Processing, 2nd Ed., John Wiley, London, 1991
  14. A. K. Jain, 'Advanced in Mathematical Models for Image Processing,' Proc. IEEE, vol. 69, no. 5, pp. 502-528, 1981 https://doi.org/10.1109/PROC.1981.12021
  15. B. R. Hunt, 'The Application of Constrained Least Squares Estimation to Image Restoration by Digital Computer,' IEEE Trans. Computers, vol. C-22(9), pp. 805-812, September 1973 https://doi.org/10.1109/TC.1973.5009169
  16. A. K. Katsaggelos, J. Biemond, R. W. Scharfer, and R. L. Mersereau, 'A Regularized Iterative Image Restoration Algorithm,' IEEE Trans. Signal Proc., vol. 39, no. 10, pp. 914-929, April 1991 https://doi.org/10.1109/78.80914
  17. N. P. Galatsanos and A. K. Katsaggelos, 'Methods for Choosing the Regularization Parameter and Estimating the Noise Variance in Image Restoration and Their Relation,' IEEE Trans. Image Proc., vol. 1, no. 3, pp. 322-336, July 1992 https://doi.org/10.1109/83.148606
  18. J. Biemond, R. L. Lagendijk, and R. M. Merserau, 'Iterative Methods for Image Deblurring,' Proc. IEEE, vol. 78, no. 5, pp. 856-883, May 1990 https://doi.org/10.1109/5.53403
  19. T. Berger, J. O. Stromberg, and T. Eltoft, 'Adaptive Regularized Constrained Least Squares Image Restoration,' IEEE Trans. Image Proc., vol. 8, no. 9, pp. 1191-1203, September 1999 https://doi.org/10.1109/83.784432
  20. B. Noble and J. Daniel, Applied Linear Algebra, Prentice Hall, 3rd edition, 1988
  21. J. H. Shin, J. H. Jung, and J. K. Paik, 'Regularized iterative image interpolation and its application to spatially scalable coding,' IEEE Trans. Consumer Electronics, vol. 44, no. 3, pp. 1042-1045, August 1998 https://doi.org/10.1109/30.713232
  22. J. Canny, 'A Computational Approach to Edge Detection,' IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-8, pp. 679-698, June 1986 https://doi.org/10.1109/TPAMI.1986.4767851