Sparsity-based optimization of two lifting-based wavelet transforms for semi-regular mesh compression

Aymen Kammoun (1) , Frédéric Payan (1) , Marc Antonini (1)

1 Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe IMAGES-CREATIVE

This paper describes how to optimize two popular wavelet transforms for semi-regular meshes, using a lifting scheme. The objective is to adapt multiresolution analysis to the input mesh to improve its subsequent coding. Considering either the Butterfly- or the Loop-based lifting schemes, our algorithm finds at each resolution level an optimal prediction operator P such that it minimizes the L1 norm of the wavelet coefficients. The update operator U is then recomputed in order to take into account the modifications to P. Experimental results show that our algorithm improves on state-of-the-art wavelet coders.

Mots clés: Wavelets; Lifting scheme; Semi-regular mesh; Compression; Butterfly; Loop; Sparsity; Optimization

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Aymen Kammoun, Frédéric Payan, Marc Antonini. Sparsity-based optimization of two lifting-based wavelet transforms for semi-regular mesh compression. Computers and Graphics, 2012, 36 (4), pp.272-282. ⟨10.1016/j.cag.2012.02.004⟩. ⟨hal-00687445⟩