Multi-scale image segmentation in a hierarchy of partitions

In this paper, we propose a new multi-scale image segmentation relying on a hierarchy of partitions. First of all, we review morphological methods based on connections which produce hierarchical image segmentations and introduce a new way of generating fine segmentations. From connection-based fine partitions, we focus on producing hierarchical segmentations. Multi-scale segmentations obtained by scale-space or region merging approaches have both benefits and drawbacks, therefore we propose to integrate a scale-space approach in the production of a hierarchy of partitions which merges similar regions. Starting from an initial over-segmented fine partition, a region adjacency graph is alternatively simplified and decimated. The simplification of graph nodes models tends to produce similar ones and this is used to merge them. The algorithm can be used to simplify the image at low scales and to segment it at high scales.