Browse > Article

Morphology-Based Step Response Extraction and Regularized Iterative Point Spread Function Estimation & Image Restoration  

Park, Young-Uk (Dept. of Image Engineering, Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University)
Jeon, Jae-Hwan (Dept. of Image Engineering, Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University)
Lee, Jin-Hee (Dept. of Image Engineering, Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University)
Kang, Nam-Oh (Dept. of Image Engineering, Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University)
Paik, Joon-Ki (Dept. of Image Engineering, Graduate School of Advanced Image Science, Multimedia, and Film, Chung-Ang University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.46, no.6, 2009 , pp. 26-35 More about this Journal
Abstract
In this paper, we present morphology-based step region extraction and regularized iterative point-spread-function (PSF) estimation methods. The proposed PSF estimation method uses canny edge detector to extract the edge of the input image. We extract feasible vertical and horizontal edges using morphology analysis, such as the hit-or-miss transform. Given extracted edges we estimate the optimal step-response using flattening and normalization processes. The PSF is finally characterized by solving the equation which relates the optimal step response and the 2D isotropic PSF. We shows the restored image by the estimated PSF. The proposed algorithm can be applied a fully digital auto-focusing system without using mechanical focusing parts.
Keywords
점확산함수 추정;디지털 자동초점;반복적 정칙화 알고리듬;Hit-or-Miss 변환;
Citations & Related Records
연도 인용수 순위
  • Reference
1 H. Andrews and B. Hunt, Digital image restoration, Prentice-Hall, New Jersey, 1977
2 S. Kim and J. Paik, "Out-of-focus blur estimation and restoration for digital auto-focusing system," Electronic Letters, vol. 34, no. 12, pp. 1217-1219, June 1998   DOI   ScienceOn
3 D. Kundur and D. Hatzinakos, "Blind image deconvolution," IEEE Signal Processing Magazine, vol. 4, pp. 43-64, May 1996
4 A. 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 Processing, vol. 36, no. 8, pp. 1360-1363, August 1988   DOI   ScienceOn
5 R. Lagendijk, J. Biemond, and D. Boekee, "Identification and restoration of noisy blurred image using the expectation-maximization algorithm," IEEE Trans. Acoustics, Speech, Signal Processing, vol. 38 no. 7, pp. 1180-1191 July 1990   DOI   ScienceOn
6 R. Gonzalez and R. Woods, Digital image processing, 2nd ed., Prentice Hall, 2001
7 J. Canny, "A computational approach to edge detection," IEEE Trans. Pattern Analysis, Machine Intelligence, vol. 8, no. 6, pp. 679-697, November 1986   DOI   ScienceOn
8 B. McCallum, "Blind deconvolution by simulated annealing," Optics Communications, vol. 75, pp. 101-105, February 1990   DOI   ScienceOn
9 Kodak Lossless True Color Image Suite, http://r0k.us/graphics/kodak/
10 S. Kim, T. Kim, and J. Paik, "A fully digital auto-focusing system based on image restoration," Proc. 1997 IEEE Region 10 Conference, vol. 1, pp. 13-16, December 1997
11 J. Yoon, J. Shin, C. Cho, and J. Paik, “Enhancement of out of focused image using fusion-based PSF estimation and restoration,” Proc. SPIE Visual Communication & Image Processing, vol. 4310, pp. 819-829, January 2001