Extraction and compression of hierarchical isocontours from image data

In this work, we introduce a new scheme to extract hierarchical isocontours from regular and irregular 2D sampled data and to encode it at single rate or progressively. A dynamic tessellation is used to represent and adapt the 2D data to the isocontour. This adaptation induces a controlled multi-resolution representation of the isocontour. This representation can then be encoded while controlling the geometry and topology of the decoded isocontour. The resulting algorithms form an efficient and flexible isocontour extraction and compression scheme.