Wavelets and subband coding
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SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Multiresolution analysis for surfaces of arbitrary topological type
ACM Transactions on Graphics (TOG)
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Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Progressive geometry compression
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Optimal bit allocation for biorthogonal wavelet coding
DCC '96 Proceedings of the Conference on Data Compression
Geometry compression of normal meshes using rate-distortion algorithms
Proceedings of the 2003 Eurographics/ACM SIGGRAPH symposium on Geometry processing
Unlifted Loop Subdivision Wavelets
PG '04 Proceedings of the Computer Graphics and Applications, 12th Pacific Conference
Biorthogonal loop-subdivision wavelets
Computing - Geometric modelling dagstuhl 2002
Modeling, analysis, and optimum design of quantized M-band filterbanks
IEEE Transactions on Signal Processing
A multiscale relaxation algorithm for SNR maximization in nonorthogonal subband coding
IEEE Transactions on Image Processing
Technical Section: Temporal wavelet-based compression for 3D animated models
Computers and Graphics
A new error metric for geometric shape distortion using depth values from orthographic projections
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
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The objective of this paper is to propose an efficient model-based bit allocation process optimizing the performances of a wavelet coder for semiregular meshes. More precisely, this process should compute the best quantizers for the wavelet coefficient subbands that minimize the reconstructed mean square error for one specific target bitrate. In order to design a fast and low complex allocation process, we propose an approximation of the reconstructed mean square error relative to the coding of semiregular mesh geometry. This error is expressed directly from the quantization errors of each coefficient subband. For that purpose, we have to take into account the influence of the wavelet filters on the quantized coefficients. Furthermore, we propose a specific approximation for wavelet transforms based on lifting schemes. Experimentally, we show that, in comparison with a "naïve” approximation (depending on the subband levels), using the proposed approximation as distortion criterion during the model-based allocation process improves the performances of a wavelet-based coder for any model, any bitrate, and any lifting scheme.