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Hierarchical Blur Identification from Severely Out-of-Focus Images

  • Jungsoo Lee
  • Yoonjong Yoo
  • Jeongho Shin
  • Joonki Paik
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4319)

Abstract

This paper proposes a blur identification method from severely out-of-focus images. The proposed blur identification algorithm can be used in digital auto-focusing and image restoration. Since it is not easy to estimate a point spread function (PSF) from severely out-of-focus images, a hierarchical approach is applied in the proposed algorithm. For severe out of focus blur, the proposed algorithm uses an hierarchical approach for estimating and selecting feasible PSF from successive down sampled images. The down sampled images contain more useful edge information for PSF estimation. The feasible PSF selected, can then be reconstructed for original image resolution level by up sampling methods. In order to reconstruct the PSF accurately, a regularized PSF reconstruction algorithm is used. Finally, we can restore the severely blurred image with the reconstructed PSF. Experimental results show that reconstructed PSF by the proposed hierarchical algorithm can efficiently restore severely out-of-focus images.

Keywords

Point Spread Function Concentric Circle Image Restoration Edge Information Support Size 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jungsoo Lee
    • 1
  • Yoonjong Yoo
    • 1
  • Jeongho Shin
    • 2
  • Joonki Paik
    • 1
  1. 1.Image Processing and Intelligent Systems Laboratory, Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and FilmChung-Ang UniversitySeoulKorea
  2. 2.Department of Web Information EngineeringHankyong National UniversityAnsung-cityKorea

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