Abstract
Image super-resolution (SR) is a process to reconstruct a high-resolution (HR) image by fusing multiple low-resolution (LR) images. A critical step in image SR is accurate registration of the LR images, however the larger inter-frame motion can significantly affect the sub-pixel image registration, then it can also affect the output of HR reconstruction. So a novel Adaptive Frame Selection method is proposed in this paper for the reconstruction of multi-frame SR. It devises a framework to resolve the image SR reconstruction problem into two steps. Firstly, using the Optical flow algorithm to calculate the inter-frame motion estimation, designing an adaptive frame selection method to discard some of the larger inter-frame motion frames, then the less inter-frame motion of successive frames is obtained. Secondly, using the maximum a posteriori (MAP) based SR algorithm for the SR reconstruction. The experimental results indicate that the proposed algorithm has considerable effectiveness in terms of both objective measurements and visual evaluation.
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References
Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: International Joint Conference on Artificial Intelligence, pp. 674–679 (1981)
Irani, M., Peleg, S.: Improving resolution by image registration. CHIP: Graphical Models and Image Processing 53(3), 231–239 (1991)
Hardie, R.C., Barnard, K.J., Bognar, J.G., Armstrong, E.E., Watson, E.A.: High-resolution image reconstruction from a sequence of rotated and translated frames and its application to an infrared imaging system. Optical Engineering 37(1), 247–260 (1998)
Tsai, R.Y., Huang, T.S.: Multiframe image restoration and registration. In: Huang, T.S. (ed.) Advances in Computer Vision and Image Processing, vol. 1, pp. 317–339. JAI Press, Greenwich (1984)
Kim, S.P., Bose, N.K., Valenzuela, H.M.: Recursive reconstruction of high resolution image from noisy undersampled multiframes. IEEE Transactions on Acoustics, Speech, Signal Processing 38(6), 1013–1027 (1990)
Kim, S.P., Su, W.Y.: Recursive high-resolution reconstruction of blurred multiframe images. IEEE Transactions on Image Processing 2(4), 534–539 (1993)
Narayanan, B., Hardie, R.C., Barner, K.E., Shao, M.: A computationally efficient super-resolution algorithm for video processing using partition filters. IEEE Transactions on Circuits and Systems for Video Technology 17(5), 621–634 (2007)
Farsiu, S., Robinson, M.D., Elad, M., Milanfar, P.: Fast and robust multiframe super resolution. IEEE Transactions on Image Processing 13, 1327–1344 (2004)
Zhang, L., Zhang, H., Shen, H., Li, P.: A super-resolution reconstruction algorithm for surveillance images. Signal Processing 90, 848–859 (2010)
Zhang, Z., Wang, R.-S.: Frame selection in multi-frame image super-resolution restoration. Signal Processing 25, 1775–1780 (2009)
Jillela, R.R., Ross, A.: Adaptive Frame Selection for Improved Face Recognition in Low-Resolution Videos. Appeared in Proc. of International Joint Conference on Neural Networks (IJCNN), Atlanta, USA (June 2009)
Lucas, B.D., Kanade, T.: An iterative image registration technique with an applicatioin to stereo vision. In: Proceedings of DARPA Image Understanding, pp. 121–130 (1981)
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© 2012 Springer-Verlag GmbH Berlin Heidelberg
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Xue, C., Yu, M., Jia, C., Shi, S., Zhai, Y. (2012). Adaptive Frame Selection for Multi-frame Super Resolution. In: Jin, D., Lin, S. (eds) Advances in Future Computer and Control Systems. Advances in Intelligent and Soft Computing, vol 159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29387-0_7
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DOI: https://doi.org/10.1007/978-3-642-29387-0_7
Publisher Name: Springer, Berlin, Heidelberg
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