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Novel Approach to Estimate Motion Blur Kernel Parameters and Comparative Study of Restoration Techniques

by Kishore R. Bhagat, Puran Gour
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 72 - Number 17
Year of Publication: 2013
Authors: Kishore R. Bhagat, Puran Gour
10.5120/12634-9228

Kishore R. Bhagat, Puran Gour . Novel Approach to Estimate Motion Blur Kernel Parameters and Comparative Study of Restoration Techniques. International Journal of Computer Applications. 72, 17 ( June 2013), 21-26. DOI=10.5120/12634-9228

@article{ 10.5120/12634-9228,
author = { Kishore R. Bhagat, Puran Gour },
title = { Novel Approach to Estimate Motion Blur Kernel Parameters and Comparative Study of Restoration Techniques },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 72 },
number = { 17 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 21-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume72/number17/12634-9228/ },
doi = { 10.5120/12634-9228 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:38:10.307939+05:30
%A Kishore R. Bhagat
%A Puran Gour
%T Novel Approach to Estimate Motion Blur Kernel Parameters and Comparative Study of Restoration Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 72
%N 17
%P 21-26
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Motion blur occurs due to the fact,that during exposure time there is movement of object or camera or both. Removing of blur is always challenging for image processing field because one has to estimate the motion blur which can spatially differ over image. Motion blur is simply an undesired effect. Restoration of blur image is very important in many of the cases like identification of criminal face in blurred image. In restoration of motion blur the knowledge of the point spread function (PSF) plays a vital role. This paper present a novel approach towards estimation of parameters like motion blur angle and the motion blur length which defines the PSF. Both of these parameters are used to restore the blurred image. Furthermore paper discusses the comparative study of different restoration techniques. The experimental result shows estimated blur angle and blur length are very close to theoretical value and the blur images with natural and artificial noise are successfully restored.

References
  1. Yogesh K . meghrajani, HimanshuMazumdar, An Interactive Deblurring Technique for Motion Blur,International Journal of Computer Applications (0975 – 8887) Volume 60– No. 3, December 2012 .
  2. R. Lokhande, K. V. Arya, and P. Gupta. 2006. Identification of parameters and restoration of motion blurred images. In Proceedings of the 2006 ACM symposium on Applied computing (SAC '06). ACM, New York, NY, USA, 301-305.
  3. M. M. Chang, A. M. Tekalp, and A. T. Erdem. Blur identification using the bispectrum. IEEE Trans. Signal Processing, 39(10):2323{2325, 1991.
  4. R. Fabian and D. Malah. Robust identification ofmotion and out-of-focus blur parameters from blurredand noisy images. CVGIP: Graphical, Models andImage Processing, 53:403{412, 1991.
  5. HuiJi, Chaoqiang Liu, Motion Blur Identification from Image Gradients, IEEE-978-1-4244-2243-2/08,2008.
  6. R. C. Gonzalez and R. E. Woods. Digital ImageProcessing. Pearson Education, 2003.
  7. D. B. Gennery. Determination of optical transferfunction by inspection of frequency domain plot. J. Opt. Soc. Amer. , 63(12):1571{1577, 1973.
  8. Taeg Sang Cho, Blur Kernel Estimation using the Radon Transform, Massachusetts Institute of Technology,2010.
  9. Li and Y. Yoshida,'Parameter estimation andrestoration for motion blurred images' IEICE Trans. Fundamentals, E80-A(8), 1997. .
  10. Alex Rav-Acha Shmuel Peleg, School of Computer Science and Engineering, Proceedings of the Fifth IEEE Workshop on Applications of Computer Vision (WACV'00), IEEE--7695-0813-8/00, 2000.
  11. Y. S. Chen and I. S. Choa. An approach to estimatingthe motion parameters for a linear motion blurred image. IEICE Trans. Inf. Syst. , E83-D(7):1601{1603,2000.
  12. R. L. Lagendijk and J. Biemond. Hand Book of Image and Vedio Processing, chapter Basic Methods for Image Restoration and Identfication, pages 125{140. Academic Press, 2000.
  13. J. S. Lim. Image restoration by short space spectralsubtraction. IEEE Trans. Acoust. Speech SignalProcess. , 28(2):191{197, 1980. .
  14. D. G. Childers. The cepstrum: A guide to processing. Proceedings Of The IEEE, 65(10):1428{1443, 1977.
  15. R. Lokhande, K. V. Arya,Identi_cation of Parameters and Restoration of MotionBlurred Images, SAC'06 April 23­27, 2006, Dijon, France.
  16. I. Rekleitis. Visual motion estimation based on motionblur interpretation. Master's thesis, School ofComputer Science, McGill University, 1995.
  17. M. Cannon. Blind deconvolution of spatially invariant image blurs with phase. IEEE Trans. Acoust. Speech Signal Process. , 24(1):56{63, 1976.
Index Terms

Computer Science
Information Sciences

Keywords

Image restoration Image fusion PSF Spectrum Wiener

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