In this paper we present a wavelet-based coding approach for semi-regular meshes, which spatially adapts the employed wavelet basis in the wavelet transformation of the mesh. The spatially-adaptive nature of the transform requires additional information to be stored in the bit-stream in order to allow the reconstruction of the transformed mesh at the decoder side. In order to limit this overhead, the mesh is first segmented into regions of approximately equal size. For each spatial region, a predictor is selected in a rate-distortion optimal manner by using a Lagrangian rate-distortion optimization technique. When compared against the classical wavelet transform employing the butterfly subdivision filter, experiments reveal that the proposed spatially-adaptive wavelet transform significantly decreases the energy of the wavelet coefficients for all subbands. Preliminary results show also that employing the proposed transform for the lowest-resolution subband systematically yields improved compression performance at low-to-medium bit-rates. For the Venus and Rabbit test models the compression improvements add up to 1.47 dB and 0.95 dB, respectively.
Denis, L, Florea, R-M, Munteanu, A & Schelkens, P 2010, Spatially-adaptive bases in wavelet-based coding of semi-regular meshes. in SPIE Photonics Europe. Optics, Photonics, and Digital Technologies for Multimedia Applications. vol. 7723, Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet, Stockholm, Sweden, 21/09/09.
Denis, L., Florea, R.-M., Munteanu, A., & Schelkens, P. (2010). Spatially-adaptive bases in wavelet-based coding of semi-regular meshes. In SPIE Photonics Europe. Optics, Photonics, and Digital Technologies for Multimedia Applications (Vol. 7723)
@inproceedings{f7e5be429bb0407ab8092f140247e169,
title = "Spatially-adaptive bases in wavelet-based coding of semi-regular meshes",
abstract = "In this paper we present a wavelet-based coding approach for semi-regular meshes, which spatially adapts the employed wavelet basis in the wavelet transformation of the mesh. The spatially-adaptive nature of the transform requires additional information to be stored in the bit-stream in order to allow the reconstruction of the transformed mesh at the decoder side. In order to limit this overhead, the mesh is first segmented into regions of approximately equal size. For each spatial region, a predictor is selected in a rate-distortion optimal manner by using a Lagrangian rate-distortion optimization technique. When compared against the classical wavelet transform employing the butterfly subdivision filter, experiments reveal that the proposed spatially-adaptive wavelet transform significantly decreases the energy of the wavelet coefficients for all subbands. Preliminary results show also that employing the proposed transform for the lowest-resolution subband systematically yields improved compression performance at low-to-medium bit-rates. For the Venus and Rabbit test models the compression improvements add up to 1.47 dB and 0.95 dB, respectively.",
keywords = "Mesh multiresolution analysis, spatially-adaptive wavelet bases, coding of semi-regular meshes",
author = "Leon Denis and Ruxandra-Marina Florea and Adrian Munteanu and Peter Schelkens",
year = "2010",
month = apr,
day = "12",
language = "English",
isbn = "978-0-8194-8196-2",
volume = "7723",
booktitle = "SPIE Photonics Europe. Optics, Photonics, and Digital Technologies for Multimedia Applications",
note = "Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet ; Conference date: 21-09-2009 Through 25-09-2009",
}