Image Processing Reference
In-Depth Information
17. Borman, S.: Topics in multiframe superresolution restoration. Ph.D. thesis, University of
Notre Dame (2004)
18. Boykov, Y., Huttenlocher, D.: A new Bayesian framework for object recognition. In: Pro-
ceedings of Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 637-663,
Ft. Collins, USA (1999)
19. Buades, A., Coll, B., Morel, J.M.: A non-local algorithm for image denoising. In: Proceedings
of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2,
pp. 60-65, San Diego, USA (2005)
20. Burt, P., Kolczynski, R.: Enhanced image capture through fusion. In: Proceedings of Interna-
tional Conference on Computer Vision, pp. 173-182, Berlin, Germany (1993)
21. Burt, P.J.: The Pyramid as a Structure for Efficient Computation. Rensselaer Polytechnic
Institute, Troy (1983)
22. Cai, S., Du, Q., Moorhead, R.: Hyperspectral imagery visualization using double layers. IEEE
Trans. Geosci. Remote Sens. 45 (10), 3028-3036 (2007)
23. Candès, E.J., Donoho, D.: Curvelets: a surprisingly effective nonadaptive representation for
objects with edges. In: Proceedings of International Conference on Curves and Surfaces, vol.
2, pp. 1-7, San Malo, France (1999)
24. Cao, W., Li, B., Zhang, Y.: A remote sensing image fusion method based on PCA transform
and wavelet packet transform. In: Proceedings of the International Conference on Neural
Networks and Signal Processing, vol. 2, pp. 976-981, Nanjing, China (2003)
25. Carmona, R., Zhong, S.: Adaptive smoothing respecting feature directions. IEEETrans. Image
Process. 7 (3), 353-358 (1998)
26. Chai, Y., He, Y., Ying, C.: CT and MRI image fusion based on contourlet using a novel rule.
In: Proceedings of International Conference on Bioinformatics and Biomedical Engineering,
pp. 2064-2067, Shanghai, China (2008)
27. Chambolle, A., Lions, P.L.: Image recovery via total variation minimization and related prob-
lems. Numer. Math. 76 (2), 167-188 (1997)
28. Chan, T.F., Golub, G.H., Mulet, P.: A nonlinear primal-dual method for total variation-based
image restoration. SIAM J. Sci. Comput. 20 (6), 1964-1977 (1999)
29. Chang, C.I. (ed.): Hyperspectral Data Exploitation: Theory and Applications, 1st edn. Wiley-
Interscience, Hoboken (2007)
30. Chaudhuri, S.: Super-resolution Imaging. Kluwer Academic, Boston (2001)
31. Chaudhuri, S., Joshi, M.V.: Motion-free Super-resolution. Springer, New York (2005)
32. Chaudhury, K., Sage, D., Unser, M.: Fast O(1) bilateral filtering using trigonometric range
kernels. IEEE Trans. Image Process. 20 (12), 3376-3382 (2011)
33. Chavez, P., Sises, S., Anderson, J.: Comparison of three different methods to merge mul-
tiresolution and multispectral data: Landsat TM and SPOT panchromatic. Photogram. Eng.
Remote Sens. 57 (3), 295-303 (1991)
34. Chen, K.: Adaptive smoothing via contextual and local discontinuities. IEEE Trans. Pattern
Anal. Mach Intell. 27 (10), 1552-1567 (2005)
35. Chen, T., Guo, R., Peng, S.: Image fusion using weighted multiscale fundamental form.
In: Proceedings of International Conference on Image Processing, vol. 5, pp. 3319-3322,
Singapore (2004)
36. Chen, T., Zhang, J., Zhang, Y.: Remote sensing image fusion based on ridgelet transform. In:
Proceedings of International Geoscience and Remote Sensing Symposium, vol. 2, pp. 1150-
1153, Seoul, Korea (2005)
37. Chen, Y., Xue, Z., Blum, R.: Theoretical analysis of an information-based quality measure
for image fusion. Inf. Fusion 9 (2), 161-175 (2008)
38. Cho, M., Skidmore, A., Corsi, F., vanWieren, S.E., Sobhan, I.: Estimation of green grass/herb
biomass from airborne hyperspectral imagery using spectral indices and partial least squares
regression. Int. J. Appl. Earth Obs. Geoinf. 9 (4), 414-424 (2007)
39. Choi, M., Kim, R., Kim, M.: The curvelet transform for image fusion. In: Proceedings of
Congress of the International Society for Photogrammetry and Remote Sensing, vol. B8,
pp. 59-64, Istanbul, Turkey (2004)
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