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Compression of 3D shape data using SA-WT

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4 Author(s)
E. Inoue ; Fac. of Sci. & Technol., Sophia Univ., Tokyo, Japan ; T. Kawashima ; T. Otake ; A. Kawanaka

A data compression method applying a wavelet transform and hierarchical quantization for geometry data structured by a quadrilateral mesh is proposed. The geometry data is transformed into multi-scale wavelet coefficients of the same number as the original data by applying a shape-adaptive wavelet transform along two axes of the quadrilateral mesh. The wavelet coefficients are entropy coded by an optimal method called combined zero tree quantization, which takes into account dependency of the coefficients at similar positions in each scale, with scalar quantization of the remained coefficients. The performance of the proposed method is evaluated using two metrics based on shape distortion and normal vector distortion of reconstructed geometry data, and the experimental results show that the new method performs remarkably well compared to conventional methods

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Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on  (Volume:3 )

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