Blind restoration for defocus blurred image based on autocorrelation of derivative image

被引：0

作者：

Zhao, Lin ^{[1
]}

Jin, Weiqi ^{[1
]}

Chen, Yinan ^{[1
]}

Su, Binghua ^{[1
]}

机构：

[1] Department of Optical Engineering, School of Information Science and Technology, Beijing Institute of Technology

来源：

Guangxue Xuebao/Acta Optica Sinica | 2008年 / 28卷 / 09期

关键词：

Autocorrelation; Defocus blurred image; Image restoration; Laplacian; Super-resolution;

D O I：

10.3788/AOS20082809.1703

中图分类号：

学科分类号：

摘要：

The research on the blind restoration for the images blurred by defocus effect has important meaning and actual metric. A super-resolution blind restoration algorithm for defocus blurred images was suggested according to the model of optical defocusing by using autocorrelation of derivative image. The autocorrelation of the second-order derivative blurred image received by Laplacian was computed, the radius of defocusing blur was be confirmed via the information contained in the result of the autocorrelation, and the restoration was finally achieved by MPMAP super-resolution method using the estimated defocusing radius as parameter. Experiments illuminate that the proposed algorithm can accurately estimate the radius of defocusing blur and restore clear images. Compared with other methods, the proposed algorithm declines the computation quantity, improves result precision and obtaines more detailed information by using the super-resolution restoration algorithm. It has been successfully applied into judging or appraisal of defocus images in practice works.

引用

页码：1703 / 1709

页数：6

共 12 条

[1]

Liu K., Quan J., Et al., Identification and restoration of images with out-of-focus blurs, Proc. SPIE, 1567, pp. 720-728, (1991)

[2]

Zheng C., Li R., Chang H., Restoration of defocus blurred digital image using Wiener filter in frequency domain, Laser J., 25, 5, pp. 57-58, (2004)

[3]

Fujiwara H., Zhang Z., Miyake T., Defocused image restoration using translation invariant wavelet transform, SICE-ICASE International Joint Conference, (2006)

[4]

Li Z., Su L., Yan J., Et al., Semi-blind defocused image restoration with dual-tree complex wavelet transform, J. Sichuan University (Natural Science Edition), 44, 2, pp. 316-320, (2007)

[5]

Yang X., Gao H., Identification of defocus blurred image based on genetic algorithm and its restoring methods, J. Changchun Normal University (Natural Science), 26, 4, pp. 92-93, (2007)

[6]

Sun J., Yuan Y., Wang C., Comparison and analysis of algorithms for digital image processing in autofocusing criterion, Acta Optica Sinica, 27, 1, pp. 35-39, (2007)

[7]

Su B., Jin W., Niu L., Et al., Poisson-map super-resolution image restoration algorithm markov constraint, Acta Photonica Sinica, 31, 4, pp. 492-496, (2002)

[8]

Liu Y., Jin W., Su B., Et al., Progress of super-resolution reconstructing images schemes and application in remote-sensing image, Infrared and Laser Engineering, 34, 1, pp. 70-73, (2005)

[9]

Liu Y., Jin W., Su B., Et al., Identification of blurred system based on super-resolution reconstructing image schemes, J. Optoelectronics and Laser, 16, 3, pp. 213-216, (2005)

[10]

Gonzalez R.C., Woods R.E., Eddins S.L., Digital Image Processing Using Matlab, pp. 133-134, (2005)

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