Fast restoration of a blurred image obtained by a horizontally rotating camera
Kozak A.V., Steinberg B.Y., Steinberg O.B.

 

Southern Federal University, Rostov-on-Don, Russia

 PDF

Abstract:
A problem of restoration of  a blurred image obtained by a horizontally rotating camera is considered in this paper. The mathematical model of this problem is the convolution equation on a cyclic group. In the previous papers of the authors, the case of a non-singular equation was considered. The general case that admits the degeneracy of the convolution equation is considered in this paper. An algorithm is developed based on which a fast program for recovering blurred images is written. The complexity of the algorithm presented in this paper for the degenerate convolution equation is the same as for the non-singular case. The analysis of calculation errors affecting the image quality is given. The influence of the errors of the algorithm's initial data for a degenerate equation is not higher than for a non-singular case.

Keywords:
optical devices, image processing, machine vision, blurred image, computation errors, convolution.

Citation:
Kozak AV, Steinberg BY, Steinberg OB. Fast restoration of a blurred image obtained by a horizontally rotating camera. Computer Optics 2018; 42(6): 1046-1053. DOI: 10.18287/2412-6179-2018-42-6-1046-1053.

References:

  1. Lucy LB. An iterative technique for the rectification of observed distributions. The Astronomical Journal 1974; 79: 745. DOI: 10.1086/111605.
  2. Richardson WH. Bayesian-based iterative method of image restoration. J Opt Soc Am 1972; 62(1): 55-59. DOI: 10.1364/JOSA.62.000055.
  3. Whyte O, Sivic J, Zisserman A, Ponce J. Non-uniform deblurring for shaken images. Int J Comput Vis 2012; 98(2): 168-186. DOI: 10.1007/s11263-011-0502-7.
  4. Kornilova A, Kirilenko Ia. MEMS-sensors in Computer Vision: we underestimate them. Software Engineering Conference Russia CEE-SECR '17. Source: áhttp://2017.secr.ru/program/submitted-presentations/mems-sensors-in-computer-visionñ.
  5. Fursov VA, Yakimov PYu. Internet technology for correcting dynamic distortions on images in mobile devices. 2017. Source: áhttp://keldysh.ru/abrau/2017/09.pdfñ. DOI: 10.20948/abrau-2017-09.
  6. Fursov VA. Restoration of images by FIR-filters constructed by direct identification of the inverse tract. Computer Optics 1996; 16: 103-108.
  7. Dronnikova SA, Gurov IP. Image quality enhancement by processing of video frames with different exposure time. Scientific and Technical Journal of Information Technologies, Mechanics and Optics 2017; 17(3): 424-430. DOI: 10.17586/2226-1494-2017-17-3-424-430.
  8. Gurov IP, Smirnov DS. Improving the quality of images by the method of Van Zittert. Sci Tech J Inf Technol Mech Opt 2002; 6: 178-182.
  9. Gruzman IS, Kirichuk ВС, Kosykh VP, Peretyagin GI, Spektor AA. Digital processing of images in information systems. Novosibirsk: Publishing house of NSTU; 2000.
  10. Cho S, Lee S. Fast motion deblurring. ACM Transactions on Graphics 2009; 28(5): 145. DOI: 10.1145/1618452.1618491.
  11. Kozak AV, Steinberg BY, Steinberg OB. The discrete convolution equation with the characteristic function of a segment and its application. In Book: Transactions of Scientific School of I.B. Simonenko. Issue 2. Rostov-on-Don: Publishing House of the Southern Federal University; 2015: 157-167.
  12. Kozak AV, Steinberg BY, Steinberg OB. Estimation of errors in solving the convolution equation for reconstructing blurred images. Abstracts of the International Conference «Modern Methods, Problems and Applications of Operator Theory and Harmonic Analysis VI», Rostov-on-Don. 2016.
  13. Kozak AV, Steinberg BY, Steinberg OB. Development of studies on the fast reconstruction of a blurred image. Abstracts of the international conference «Modern methods, problems and applications of operator theory and harmonic analysis VII», Rostov-on-Don, April 23-28 2017: 28-29.
  14. Kozak AV, Steinberg BY, Steinberg OB. Fast and accurate restoration of blurred image obtained by rotating the camera. Proceedings of the 12th Central and Eastern European Software Engineering Conference in Russia CEE-SECR '16. 2016: 11. DOI: 10.1145/3022211.3022222.
  15. Graham SL, Snir M, Patterson CA. Getting up to speed: The future of supercomputing. Washington: National Academies Press, 2005. ISBN: 978-0-309-09502-0.

© 2009, IPSI RAS
151, Molodogvardeiskaya str., Samara, 443001, Russia; E-mail: journal@computeroptics.ru ; Tel: +7 (846) 242-41-24 (Executive secretary), +7 (846) 332-56-22 (Issuing editor), Fax: +7 (846) 332-56-20