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Table 1: Basic Multiresolution Optimization Algorithm (OF-Basic). Essential parameters are the coarse scale jmax, the motion eld smoothness parameter , and the quantizer step size at scale jmax.

in Multiscale Modeling and Estimation of Motion Fields for Video Coding
by Pierre Moulin, John Woods 1997
"... In PAGE 12: ... Such algorithms usually converge very rapidly [29, 31, 36, 39, 40, 41], and the motion estimation application is no exception. Our algorithm is summarized in Table1 ; de- tailed explanations and derivations may be found in Appendix C. The steps of the algorithm are outlined as follows.... In PAGE 16: ... The algorithm begins by creating the lowpass pyramids for the current and previous frames. The motion eld at the coarsest level, dimax, is estimated and encoded using the multiscale representation (4) and the basic algorithm in Table1 . At every level (0 i lt; imax), the following steps are performed.... In PAGE 17: ...otion were used to encode the DFD. The overall bit-rate converted to approximately 24 kbit/s. The adaptive arithmetic coder described in [45] was used to entropy-code the quantizer outputs and obtain the quoted bit-rates. Our OF-CP algorithm used two levels in the control pyramid (imax = 1), and the following parameters for the basic motion estimator ( Table1 ) at each level: jmax = 4, = 500 and = 0:125. All coe cients at the nest level (j = 0) of the HFE pyramid were set to zero.... ..."
Cited by 16

Table 1: Filters for biorthogonal wavelets upto order 4. 6 REFERENCES [1] S. G. Mallat. A theory for multiresolution signal decomposition: The wavelet representation. IEEE Trans. on Pattern Analysis and Machine Intelligence, 11, 1989. [2] M. Vetterli and J. Kovacevic. Wavelets and Subband Coding. Prentice Hall, 1995. [3] G. Battle. A block spin construction of ondelettes, part 1: Lemarie functions. Commn. Math. Physics, 110, 1987. [4] I. Daubechies. Ten lectures on wavelets. Springer Verlag, Pennsylvania, 1992. [5] C. de Boor. A Practical Guide to Splines. Springer Verlag, 1978.

in Wavelets Based on Splines: An Application
by Pramila Srinivasan, Leah H. Jamieson 1996
Cited by 1

TABLE I MULTI-RESOLUTION COLOR FEATURES.

in unknown title
by unknown authors 2003
Cited by 48

TABLE I MULTI-RESOLUTION COLOR FEATURES.

in unknown title
by unknown authors 2003
Cited by 48

Table 1: Curve multiresolution Africa Tiger

in Multiresolution for Algebraic Curves and Surfaces Using Wavelets
by Jordi Esteve, Pere Brunet, Alvar Vinacua 1998
Cited by 2

Table 2: Wavelet-based multiresolution analysis

in Resource-aware mining with variable granularities in data streams
by Wei-guang Teng, Ming-syan Chen, Philip S. Yu
Cited by 2

TABLE 3 Performance of Algorithm for Various Multiresolution Levels

in Automated 3-Dimensional Registration of Stand- Alone 18 F-FDG Whole-Body PET with CT
by unknown authors

Table 1: MN without multiresolution compared to DF

in Multiresolution bayesian approach for brain electrical tomography: application to reconstructing the cortical representation of hand from MEG data
by Gavit Baillet Mangin

Table 2: MN with multiresolution compared to DF

in Multiresolution bayesian approach for brain electrical tomography: application to reconstructing the cortical representation of hand from MEG data
by Gavit Baillet Mangin

Table 3: Surface multiresolution: Mechanical part

in EUROGRAPHICS ’0x / N.N. and N.N. (Guest Editors) Volume xxx, (200x), Number yyy Multiresolution for Algebraic Curves and Surfaces using
by Jordi Esteve, Pere Brunet, Alvar Vinacua
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