Image and Signal Processing: 4th International Conference, by Kaori Kataoka, Shingo Ando, Akira Suzuki, Hideki Koike

By Kaori Kataoka, Shingo Ando, Akira Suzuki, Hideki Koike (auth.), Abderrahim Elmoataz, Olivier Lezoray, Fathallah Nouboud, Driss Mammass, Jean Meunier (eds.)

This ebook constitutes the refereed complaints of the 4th foreign convention on photo and sign Processing, ICISP 2010, held in Québec, Canada June 30 - July 2, 2010. The sixty nine revised complete papers have been rigorously chosen from one hundred sixty five submissions. The papers offered are geared up in topical sections on photograph Filtering and Coding, development attractiveness, Biometry, sign Processing, Video Coding and Processing, Watermarking and record Processing, computing device imaginative and prescient and Biomedical functions.

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Additional info for Image and Signal Processing: 4th International Conference, ICISP 2010, Trois-Rivières, QC, Canada, June 30-July 2, 2010. Proceedings

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IEEE Trans. Patt. Ana. & Mach. Intel. 22, 950–955 (2000) 19. : Learning based coarse-to-fine image registration. In: IEEE ICCVPR, pp. 1–7 (2008) 20. : Numerical optimization. Springer, New York (1999) 21. edu/registration/satellite/ (accessed January 2009) 22. pt/~ aguiar/mosaics/ (accessed January 2009) 23. : Image quality assessment: From error visibility to structural similarity. IEEE Trans. Image Proc. 13, 600–612 (2004) 24. : A class of algorithms of fast digital image registration. IEEE Trans.

As traditionally defined, a two-dimensional wavelet decomposition produces dyadic native spatial resolutions, related to the original size of the image by a factor (1/2)k , where k is an integer. Few works in the literature have investigated the inclusion of spatial scalability by non-dyadic ratios with wavelet-based approaches. In [1], a post-processing stage is used in addition to a full decomposition tree obtained by extending the two-dimensional wavelet decomposition filter bank. While the scheme allows for dyadic and non-dyadic spatial scalability, the post-processing stage at the A.

R. Alsharif, and K. Yamashita low pass subband and a high pass subband. Then a nonsubsampled DFB decomposes the high pass subband into several directional subbands. The scheme is iterated repeatedly on the low pass subband outputs of nonsubsampled pyramids. The multiscale property of the NSCT is obtained from a shift invariant filtering structure that achieves subband decomposition similar to that of the Laplacian pyramid. The block diagram of the nonsubsampled pyramid is shown in Figure 2(a) and subband on the 2-D frequency plane is shown in Figure 2(b).

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