Skip Navigation

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences 2008 E91-A(6):1416-1425; doi:10.1093/ietfec/e91-a.6.1416
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Request Permissions
Google Scholar
Right arrow Articles by PATANUKHOM, K.
Right arrow Articles by NISHIHARA, A.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Copyright © 2008 The Institute of Electronics, Information and Communication Engineers

Special Section on Image Media Quality - Papers

Identification of Piecewise Linear Uniform Motion Blur

Karn PATANUKHOM1 and Akinori NISHIHARA2

1 The author is with the Department of Communications and Integrated Systems, Tokyo Institute of Technology, Tokyo, 152-8552 Japan. E-mail: karn{at}nh.cradle.titech.ac.jp, 2 The author is with the Center for Research and Development of Educational Technology, Tokyo Institute of Technology, Tokyo, 152-8552 Japan.

A motion blur identification scheme is proposed for non-linear uniform motion blurs approximated by piecewise linear models which consist of more than one linear motion component. The proposed scheme includes three modules that are a motion direction estimator, a motion length estimator and a motion combination selector. In order to identify the motion directions, the proposed scheme is based on a trial restoration by using directional forward ramp motion blurs along different directions and an analysis of directional information via frequency domain by using a Radon transform. Autocorrelation functions of image derivatives along several directions are employed for estimation of the motion lengths. A proper motion combination is identified by analyzing local autocorrelation functions of non-flat component of trial restored results. Experimental examples of simulated and real world blurred images are given to demonstrate a promising performance of the proposed scheme.

Key Words: blur identification, motion blur, image restoration


Manuscript received July 2, 2007. Manuscript revised November 26, 2007.

References

[1] D.B. Gennery, "Determination of optical transfer function by inspection of frequency-domain plot," J. Optical Society of America, vol.63, no.12, pp.1571–1577, Dec. 1973.

[2] Y. Yoshida, K. Horike, and K. Fujita, "Parameter estimation of uniform image blur using DCT," IEICE Trans. Fundamentals, vol.E76-A, no.7, pp.1154–1157, July 1993.

[3] Y. Yitzhaky and N.S. Kopeika, "Identification of blur parameters from motion blurred images," CVGIP: Graphical models and image processing, vol.59, no.5, pp.310–320, Sept. 1997.

[4] Y. Jianchao, "Motion blur identification based on phase change experienced after trial restorations," 1999 IEEE Inter. Conf. on Image Processing, vol.1, pp.180–184, Oct. 1999.

[5] W. Tan, J. Zhang, G. Rong, and H. Chen, "Identification of motion blur direction based on analysis of intentional restoration errors," 2004 IEEE Inter. Conf. on Networking, Sensing and Control, vol.2, pp.1253–1258, 2004.

[6] Y. Chen and I. Choa, "An approach to estimating the motion parameters for a linear motion blurred image," IEICE Trans. Inf. & Syst., vol.E83-D, no.7, pp.1601–1603, July 2000.

[7] A.K. Katsaggelos and K.T. Lay, "Maximum likelihood blur identification and image restoration using the EM algorithm," IEEE Trans. Signal Process., vol.39, no.3, pp.729–733, March 1991.

[8] M.A.T. Figueriredo and R.D. Nowak, "An EM algorithm for wavelet-based image restoration," IEEE Trans. Image Process., vol.12, no.8, pp.906–916, Aug. 2003.

[9] K. Panchapakesan, D.G. Sheppard, M.W. Marcellin, and B.R. Hunt, "Blur identification from vector quantizer encoder distortion," IEEE Trans. Image Process., vol.10, no.3, pp.465–470, March 2001.

[10] R. Nakagaki and A.K. Katsaggelos, "A VQ-based blind image restoration algorithm," IEEE Trans. Image Process., vol.19, no.9, pp.1024–1053, Sept. 2003.

[11] M. Ben-Ezra and S.K. Nayar, "Motion-based motion deblurring," IEEE Trans. Pattern Anal. Mach. Intell., vol.26, no.6, pp.689–698, June 2004.

[12] M. Tico, M. Trimeche, and M. Vehvilainen, "Motion blur identification based on differently exposed images," IEEE International Conference on Image Processing, 2006, pp.2021–2024, Oct. 2006.

[13] L. Liang and Y. Xu, "Adaptive landweber method to deblur images," IEEE Trans. Signal Process., vol.10, no.5, pp.129–132, May 2003.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?



This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Request Permissions
Google Scholar
Right arrow Articles by PATANUKHOM, K.
Right arrow Articles by NISHIHARA, A.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?