Information Technology Reference
In-Depth Information
20. Griffin, L.D., Lillholm, M.: Hypotheses for image features, icons and textons. Interna-
tional Journal of Computer Vision 70(3), 213-230 (2006)
21. Cheung, V., Frey, B.J., Jojic, N.: Video epitomes. In: Proceedings of Computer Vision
and Pattern Recognition, CVPR 2005, pp. 42-49 (2005), ieeexplore.ieee.org
22. Lauze, F., Nielsen, M.: A Variational Algorithm for Motion Compensated Inpainting. In:
Hoppe, S.B.A., Ellis, T. (eds.) British Machine Vision Conference, BMVA, vol. 2, pp.
777-787 (2004)
23. Keller, S.H., Lauze, F., Nielsen, M.: Deinterlacing using variational methods. IEEE
Transactions on Image Processing 17(11), 2015-2028 (2008)
24. Keller, S.H.: Video Upscaling Using Variational Methods. Ph.D. thesis, Faculty of
Science, University of Copenhagen (2007), http://image.diku.dk/sunebio/
Afh/SuneKeller.pdf (accessed November 16, 2009)
25. Mumford, D.: Bayesian rationale for the variational formulation. In: ter Haar Romeny,
B.M. (ed.) Geometry-Driven Diffusion In Computer Vision, pp. 135-146. Kluwer Aca-
demic Publishers, Dordrecht (1994)
26. Horn, B., Schunck, B.: Determining Optical Flow. Artificial Intelligence 17, 185-203
(1981)
27. Papenberg, N., Bruhn, A., Brox, T., Didas, S., Weickert, J.: Highly Accurate Optic Flow
Computation With Theoretically Justified Warping. International Journal of Computer
Vision 67(2), 141-158 (2006)
28. Rudin, L., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algo-
rithms. Physica D 60, 259-268 (1992)
29. Lauze, F., Nielsen, M.: On Variational Methods for Motion Compensated Inpainting.
Tech. rep., Dept. of Computer Science, Copenhagen University, DIKU (2009), http:
//image.diku.dk/francois/seqinp (accessed November 16, 2009)
30. Lauze, F.: Computational methods for motion recovery, motion compensated inpainting
and applications. Ph.D. thesis, IT University of Copenhagen (2004)
31. Bruhn, A., Weickert, J., Feddern, C., Kohlberger, T., Schnorr, C.: Variational Optic Flow
Computation in Real-Time. IEEE Trans. on Image Processing 14(5), 608-615 (2005)
32. Keller, S.H.: Selected electronic results of TSR experiments (2007), http://image.
diku.dk/sunebio/TSR/TSR.zip (accessed November 16, 2009)
33. ITU: ITU-R recommendation BT.500-11: Methodology for the subjective assessment of
the quality of television pictures (2002)
34. Bruhn, A., Weickert, J., Schnorr, C.: Lucas/Kanade Meets Horn/Schunck: Combining
Local and Global Optic Flow Methods. International Journal of Computer Vision 61(3),
211-231 (2005)
Search WWH ::




Custom Search