Abstract
In this paper, we describe an image deblurring algorithm for images generated by the baggage inspection system. Baggage inspection images have low-extent blurring, large intensity dependent noise and need line by line processing in real time, which makes most of the existing methods unsuitable. With these special characteristics, we propose a new algorithm by combining the iterative inverse filter and the shock filter. At each iteration of the inverse filter, the constraint borrowed from the shock filter is imposed so that the image is deblurred without ringing artifacts. The algorithm is fairly fast and can process the image line by line, which can satisfy the real-time requirement. It is also easy to program and can be implemented in practice. The algorithm is tested on the synthetic data and real data from the airport. The experiments show that our algorithm has a great improvement on human’s perception and is better than the original algorithms.
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References
Alvarez, L., Mazorra, L.: Signal and image restoration using shock filters and anisotropic diffusion. SIAM Journal on Numerical Analysis 31(2), 590–605 (1994)
Andrews, H.C., Hunt, B.R.: Digital Image Restoration. Prentice-Hall, Englewood Cliffs (1977)
Combettes, P.L., Pesquet, J.C.: Image restoration subject to a total variation constraint. IEEE Trans. Image Processing 13(9), 1213–1222 (2004)
Kundur, D., Hatzinakos, D.: A novel blind deconvolution scheme for image restoration using recursive filtering. IEEE Trans. Signal Processing 26(2), 375–390 (1998)
Dyson, N.A.: X-rays in atomic and nuclear physics, 2nd edn. Longman, Harlow (1990)
Gilboa, G.: Super-Resolution Algorithms Based on Invers Diffusion-type Processes. PhD thesis, Israel Institute of Technology (2004)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Pearson Education, Inc., London (2002)
Lagendijk, R.L., Biemond, J., Mersereau, R.M.: Iterative methods for image deblurring. Proceedings of the IEEE, pp. 856–883 (May 1990)
Katsaggelos, A.K., Efstratiadis, S.N.: A class of iterative signal restoration algorithms. IEEE Trans. Accus. Speech and Signal Processing 38, 778–786 (1990)
Osher, S., Rudin, L.I.: Feature-oriented image enhancement with shock filters. SIAM Journal on Numerical Analysis 27(4), 919–940 (1990)
Perona, P., Malik, J.: Scale-space and edge detection using anisotropic diffusion. IEEE Trans. on Pattern Analysis and Matching Intelligence 12(7), 629–639 (1990)
Lagendijk, R.L., Biemond, J., Boekee, D.E.: Regularized iterative restoration with ringing reduction. IEEE Trans. Accus. Speech and Signal Processing 36(12), 1874–1888 (1988)
Singh, M., Singh, S.: Explosives detection systems (eds) for aviation security. Signal Processing 83, 31–55 (2003)
Sapiro, G.: Geometric partial differential equations and image analysis. Cambridge University Press, Cambridge (2001)
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© 2006 Springer-Verlag Berlin Heidelberg
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Yu, G., Zhang, J., Zhang, L., Chen, Z., Li, Y. (2006). Combining Iterative Inverse Filter with Shock Filter for Baggage Inspection Image Deblurring. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3852. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612704_27
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DOI: https://doi.org/10.1007/11612704_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31244-4
Online ISBN: 978-3-540-32432-4
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