S. Mallat, "A compact multiresolution representation: the wavelet model," in Proc. IEEE Comput. Soc. Workshop Computer Vision, 1987, pp. 2--7.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....The zoom phenomenon of the WT offers high temporal localization for high frequencies while offering good frequency resolution for low frequencies. Consequently, the WT is especially well suited to analyze local variations such as those in still images. By introducing multiresolution, Mallat [Mal87] made an important contribution to the application of wavelet theory to multimedia: the transition from mathematical theory to filters. Multiresolution analysis is implemented via high pass filters, resp. band pass filters (i.e. wavelets) and low pass filters (i.e. scaling functions) In this ....

Stephane Mallat. A Compact Multiresolution Representation: The Wavelet Model. IEEE Computer Society Workshop on Computer Vision (WCV), 87:2--7, 1987.

....a transition from colored foreground to black background) will be analyzed by short, high amplitude wavelets. Lowvariations (e.g. color within the same object) will be analyzed by long, low amplitude wavelets. 3. 1 Wavelet Transform and Filter Banks By introducing multiresolution, Mallat [14][15] made an important stride in the application of wavelet theory in multimedia, the transition from mathematical theory to lters. Amultiresolution analysis is implemented via high pass lters, resp. band pass lters (i.e. wavelets) and low pass lters (i.e. scaling functions) Low pass lters let ....

Stephane Mallat, \A Compact Multiresolution Representation: The Wavelet Model," IEEE Computer Society Workshop on Computer Vision (WCV),vol. 87, pp. 2-7, 1987.

....from bright foreground to black background) will be analyzed by short, high amplitude wavelets. Low variations (e.g. gray value within the same object) will be analyzed by long, low amplitude wavelets. 3. 1 Wavelet Transform and Filter Banks By introducing multiresolution, Mallat [Mal98] [Mal87] made an important contribution to the application of wavelet theory to multimedia: the transition from mathematical theory to lters. Multiresolution analysis is implemented via high pass lters, resp. band pass lters (i.e. wavelets) and low pass lters (i.e. scaling functions) In this ....

Stephane Mallat. A Compact Multiresolution Representation: The Wavelet Model. IEEE Computer Society Workshop on Computer Vision (WCV), 87:2-7, 1987.

.... image data, redundancy of wavelet coefficients 1 Introduction Publications about wavelets are including a broad spectrum of themes like the development of different wavelet types, their applications on different types of images, the boundary value solution problem and their mathematical properties [4, 8, 10, 11, 12] . This kind of work is mainly concerned with one effect of the multiresolution property: the redundancy of wavelet coefficients and the attempt to reduce it by the exploratory analysis of similarities between them. Similarity analyses can be conducted by heuristic classification approaches which ....

Mallat, St. G., 1987, A compact multiresolution representation: the wavelet model, Proc. IEEE Workshop Comput. Vision, Miami, Florida

....unequal zero as like the analysis filters H and G. For the set of all solutions L(n Gamma tap)n=2i;i2N;i1 one can show, that it is indefinite. The analysis filters H and G (respectively the synthesis filters H and G ) are interpreted with respect to the definition of wavelets (after [Mal87]) as pairs of quadrature mirror filters. For instance, two equations with four unknowns for L(2tap) and six equations with eight unknowns for L(4 tap) are obtained as results with the condition for quadrature mirror filter. In addition to the six equations for L(4tap) one can takes the finite sums ....

S.G.Mallat, A Compact Multiresolution Representation: The Wavelet Model, GRASP LAB, Dept. of Computer and Inf. Science, 23p., 1987

....In general this requires the computation of a large number of scalar products. Besides the inherent instabilties this leads to very long computation times. A breakthrough was acchieved in 1988 when the notion of a multiresolution analysis, introduced by S. Mallat as a tool for compressing images [56, 55], was merged with the wavelet idea. This resulted in the construction of orthogonal 1 d wavelets with compact support by I. Daubechies [19] A compactly supported orthogonal 1 d wavelet is a function 2 L 2 (IR) such that Phi 2 m=2 (2 m x Gamma k) j m; k 2 ZZ Psi (3) is an ....

....neighboring pixels of a digitized image f by storing a smooth background picture f N and adding only the most pronounced smaller details. Algorithms of this type for image processing were first introduced in [73, 10] but the breakthrough of this idea was triggered by the articles of S. Mallat [56, 55]. L 2 (IR) F NaN r F NaN r F NaN r F NaN r F NaN r F NaN r F NaN V Gamma1 F NaN V 0 F NaN V 1 F NaN F NaN F NaN R W 0 F NaN F NaN F NaN R W 1 F NaN r F NaN r F NaN r F NaN r F NaN r F NaN r F NaN F NaN f0g f0g He gave a precise definition of a ....

S. Mallat; A compact multiresolution representation: the wavelet model, Proc. IEEE Workshop Comput. Vision, Miami Fl., 1987

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S. Mallat, "A compact multiresolution representation: the wavelet model," in Proc. IEEE Comput. Soc. Workshop Computer Vision, 1987, pp. 2--7.

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S. Mallat, "A Compact Multiresolution Representation: The Wavelet Model," Proceedings IEEE Computer Society Workshop on Computer Vision, IEEE Computer Society Press, Washington, D.C., pp. 2-7, 1987

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