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Image Compression with Anisotropic Geodesic Triangulations

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Date
2009
Link to item file
https://hal.archives-ouvertes.fr/hal-00366933
Dewey
Probabilités et mathématiques appliquées
Sujet
geodesic; Image compression; farthest point; Fast Marching; anisotropy; triangulation
DOI
http://dx.doi.org/10.1109/ICCV.2009.5459425
Conference country
JAPAN
Book title
12th IEEE International Conference on Computer Vision (ICCV 2009)
Publisher
IEEE
Publisher city
Piscataway, NJ
Year
2009
ISBN
978-1-4244-4420-5
URI
https://basepub.dauphine.fr/handle/123456789/2953
Collections
  • CEREMADE : Publications
Metadata
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Author
Bougleux, Sébastien
Peyré, Gabriel
Cohen, Laurent D.
Type
Communication / Conférence
Abstract (EN)
We propose a new image compression method based on geodesic Delaunay triangulations. Triangulations are generated by a progressive geodesic meshing algorithm which exploits the anisotropy of images through a farthest point sampling strategy. This seeding is performed according to anisotropic geodesic distances which force the anisotropic Delaunay triangles to follow the geometry of the image. Geodesic computations are performed using a Riemannian Fast Marching, which recursively updates the geodesic distance to the seed points. A linear spline approximation on this triangulation allows to approximate faithfully sharp edges and directional features in images. The compression is achieved by coding both the coefficients of the spline approximation and the deviation of the geodesic triangulation from an Euclidean Delaunay triangulation. Numerical results show that taking into account the anisotropy improves the approximation by isotropic triangulations of complex images. The resulting geodesic encoder competes well with wavelet-based encoder such as JPEG-2000 on geometric images.

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