350 rub
Journal Radioengineering №12 for 2015 г.
Article in number:
Linear blur
Authors:
A.V. Bogoslovsky - Dr. Sc. (Eng.), Professor, Д, MESC «Zhukovsky-Gagarin Air Force Academy» (Voronezh). E-mail: p-digim@mail.ru E.A. Bogoslovsky - Ph. D. (Eng.), Professor, Д, MESC «Zhukovsky-Gagarin Air Force Academy» (Voronezh). E-mail: qro76@yandex.ru I.V. Zhigulina - Ph. D. (Eng.), Associate Professor, Д, MESC «Zhukovsky-Gagarin Air Force Academy» (Voronezh). E-mail: p-digim@mail.ru V.V. Vasilyev - Post-graduate Student, MESC «Zhukovsky-Gagarin Air Force Academy» (Voronezh). E-mail: warner88@mail.ru A.V. Ponomarev - Ph. D. (Eng.), Associate Professor, Head of Department, MESC «Zhukovsky-Gagarin Air Force Academy» (Voronezh). E-mail: cycloida@mail.ru
Abstract:
The model of linear blurring the image, based on the processes of forming video signals, is presented. The model is based on the dis-cretization of the input light flux and the accumulation of signal in the process of moving. The systems of equations prepared for use reverse Gaussian elimination and allow us to obtain unbiased samples of the video signal corresponding to the moving object. It is shown that the proposed model leads to differences in the description of the rise and fall of the pulse signal corresponding to the object compared with the models that does not consider the processes of formation of signal distortions. An example of reconstruction of the real image is shown.
Pages: 147-154
References

 

  1. Gonsales R., Vuds R. Cifrovaja obrabotka izobrazhenijj. M.: Tekhnosfera. 2006 1072 s.
  2. Gruzman I.S., Kirichuk V.S., Kosykh V.P., Peretjagin G.I., Spektor A.A. Cifrovaja obrabotka izobrazhenijj v informacionnykh sistemakh: Ucheb. posobie. Novosibisrk: Izd-vo NGTU. 2000. 168 s.
  3. Vasilenko G.I., Taratorin A.M. Vosstanovlenie izobrazhenijj. M.: Radio i svjaz. 1986. 304 s.
  4. Pereslavceva E.E., Filippov M.V. Metod uskorennogo vosstanovlenija izobrazhenijj, smazannykh pri dvizhenii // EHlektronnoe nauchno-tekhnich. izdanie «Nauka i obrazovanie». 2012. № 77-30569/340562.
  5. Kokoshkin A.V., Korotkov V.A., Korotkov K.V., Novichikhin E.P. Slepoe vosstanovlenie izobrazhenijj, iskazhennykh smazom i defokusirovkojj, pri neizvestnojj forme i parametrakh AF // ZHurnal radioehlektroniki. 2014. № 9. EHlektronnyjj resurs: http://jre.cplire.ru/jre/sep14/8/text.pdf.
  6. Jiann-Ming Wu, Hsiao-Chang Chen, Chun-Chang Wu, Pei-Hsun Hsu. Blind image deconvolution by neural recursive function approximation // World Academy of Science, Engineering and Technology. 2010. V. 4. 2010-10-22.
  7. Martinello M., Favaro P. Single image blind deconvolution with higher-order texture statistics. 2011. D. Cremers et al. (Eds.). Video Processing and Computional Video. LNCS 7082. P. 124−151. 2011. © Springer-VerlagBerlinHeidelberg. 2011.
  8. Ayers G.R., Dainty J.C. Iterative blind deconvolution method and its applications // Optic letters. July 1988. V. 13. № 7.
  9. Holmes T.J., Biggs D., Abu-Tarif A. Blind deconvolution. Handbook of biological confocal microscopy. Third edition / Edited by J.B. Pawler. Springer Science+Business Media, LLC. NewYork. 2006.
  10. Bhuiyan M.I., Sacchi M.D. Two-stage blind deconvolution. GeoConvention 2013: Integration.
  11. Kwon T.M. Blind deconvolution of vehicle inductance signatures for travel-time estimation. EHlektronnyjj resurs: http://www/rrb.org/PDF/200606.pdf.
  12. Hirsch M., Harmeling S., Sra S., Schölkopf B. Online multi-frame blind deconvolution with super-resolution and saturation correction. Astronomy@Astrophysics. A@A 531. A9 (2011).
  13. Bell A.J., Sejnowski T.J. An information-maximization approach to blind deconvolution. NeuralComputation. 7. 6. 1004−1034 (1995).
  14. Ohba K., Ohara K. Microvision. VisionSystems: Applications. 2007.
  15. Shan Q., Jia J., Agarwala A. High-quality motion deblurring from a single image // ACM Transactions on Graphics. V. 27. № 3. Article 73. Aug. 2008 [EHlektronnyjj resurs: http://cse.cuhk.edu.hk/%7eleojia/projects/motion%5fdeblurring/].
  16. Bando Y., Chen B.-Y., Nishita T. Motion deblurring from a single image using circular sensor motion // Computer Graphics Forum. 2011. TheEurographicsAssociationandBlackwellPublishingLTD. V. 30. № 7. 2011.
  17. Bogoslovskijj E.A., Vasilev V.V., CHetvertakov A.N. Osnovnye podkhody, ispolzuemye pri modelirovanii i ustranenii smaza izobrazhenija // Materialy Vseros. NTK slushatelejj, kursantov i molodykh uchenykh, posvjashhennojj Dnju obrazovanija vojjsk svjazi «IV Nauchnye chtenija imeni A.S. Popova». 15 oktjabrja 2015 g. Voronezh: VUNC VVS «Voenno-vozdushnaja akademija imeni prof. N.E. ZHukovskogo i JU.A. Gagarina».
  18. Andreev A.L. Avtomatizirovannye sistemy nabljudenija. CH. 1. Apparatnye sredstva i ehlementnaja baza: Ucheb. posobie dlja kursovogo i diplomnogo proektirovanija. SPb: SPbGUITMO. 2005. 88 s.
  19. Obnaruzhenie, raspoznavanie i opredelenie parametrov obrazov obektov. Metody i algoritmy / Pod red. A.V. Korennogo. M.: Radiotekhnika. 2012. 112 s.