Abstract
An application of a multiframe SR (superresolution) algorithm applied to video monitoring is described. The video signal generated by various types of video cameras with different parameters and signal distortions which may be very problematic for superresolution algorithms. The paper focuses on disadvantages in video signal which occur in video surveillance systems. Especially motion estimation and its influence on superresolution effectiveness is analyzed. In proposed initial solution a proper frame shift estimation is shown. Tests of the proposed algorithm performed video frames from real surveillance system in which many described difficulties were found. Result image examples show image resolution enhancement with plate numbers. The improvement of image quality is discussed in reference to further plate recognition.
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References
Elad, M., Feuer, A.: Restoration of a Single Superresolution Image from Several Blurred Noisy and Undersampled Measured Images. IEEE Trans. on Image Proc. 6(12) (1997)
Farsiu, S., Elad, M., Milanfar, P.: Multi-frame Demosaicing and Super-resolution of Color Images. IEEE Trans. on Image Proc. 15(1), 141–159 (2006)
Farsiu, S., Robinson, M.D.: Fast and Robust Multiframe Super Resolution. IEEE Trans. on Image Proc. 13(10) (2004)
Gilman, A., Bailey, D.G., Marshal, S.R.: Interpolation Models for Super-resolution. In: 4th IEEE Int. Symposium on Electronic Design Test & Applications, DELTA (2008)
Krylov, A.S., Lukin, A.S., Nasonov, A.V.: Edge-preserving nonlinear iterative image resampling method. In: 16th IEEE Int. Conf. on Image Proc. (2009)
Lertrattanapanichand, S., Bose, N.K.: High Resolution Image Formation From Low Resolution Frames Using Delaunay Triangulation. IEEE Trans. on Image Process 11(12) (2002)
Park, S.C., Park, M.K., Kang, M.G.: Super-Resolution Image Reconstruction: A Technical Overview. IEEE Signal Proc. Mag. 20, 21–36 (2003)
Sánchez-Beatoand, A., Pajares, G.: Noniterative Interpolation-Based Super-Resolution Minimizing Aliasing in the Reconstructed Image. IEEE Trans. on Image Proc. 17(10) (2008)
Sroubek, F., Cristobal, G., Flusser, J.: Simultaneous super-resolution and blind Deconvolution. In: 4th AIP Int. Conf. and 1st Congress of IPIA J. of Phys. Conf. Ser., vol. 124, 012048 (2008)
Zomet, A., Rav-Acha, A., Peleg, S.: Robust Super-resolution. In: Proc of 2001 IEEE Comp. Soc. Conf. on Computer Vision and Pattern Recognition, vol. 1(1), pp. 645–650 (2001)
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Merta, T., Czyżewski, A. (2010). Superresolution Algorithm to Video Surveillance System. In: Nguyen, N.T., Zgrzywa, A., Czyżewski, A. (eds) Advances in Multimedia and Network Information System Technologies. Advances in Intelligent and Soft Computing, vol 80. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14989-4_10
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DOI: https://doi.org/10.1007/978-3-642-14989-4_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14988-7
Online ISBN: 978-3-642-14989-4
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