Paper Info
Title
Hierarchical blur identification from severely out-of-focus images
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.
Year
DOI
Venue
2006
10.1007/11949534_135
PSIVT
Keywords
Field
DocType
out-of-focus image,reconstructed psf,proposed blur identification algorithm,blur identification method,proposed hierarchical algorithm,psf estimation,hierarchical approach,hierarchical blur identification,feasible psf,proposed algorithm,regularized psf reconstruction algorithm,image resolution,image restoration,point spread function,sampling methods
Iterative reconstruction,Computer vision,Pattern recognition,Computer science,Image processing,Digital image,Reconstruction algorithm,Artificial intelligence,Image restoration,System identification,Point spread function,Image resolution
Conference
Volume
ISSN
ISBN
4319
0302-9743
3-540-68297-X
Citations 
PageRank 
References 
1
0.38
4
Authors
4
Name
Order
Citations
PageRank
Jung-soo Lee1196.91
Yoonjong Yoo2212.33
Jeongho Shin312417.26
Joonki Paik461171.87