Braids of partitions for the hierarchical representation and segmentation of multimodal images. (November 2019)

• Record Type: Journal Article
• Authors: Tochon, Guillaume; Dalla Mura, Mauro; Veganzones, Miguel Angel; Géraud, Thierry; Chanussot, Jocelyn
• Is Part Of: Pattern recognition. Volume 95(2019:Nov.)
• Page Start: 162
• Page End: 172
• Publication Date: 2019-11
• Subjects: Hierarchical representation -- Multimodal image -- Braid of partitions -- Energy minimization -- Image segmentation; Pattern perception -- Periodicals; Perception des structures -- Périodiques; Patroonherkenning; 006.4
• DOI: 10.1016/j.patcog.2019.05.029
• Languages: English
• ISSNs: 0031-3203

Abstract

Highlights: We propose a methodology for the hierarchical representation of multimodal images. The hierarchical representation relies on the novel concept of braids of partitions. We introduce a braid-based method to conduct multimodal image segmentation. The segmentation method is based on an energy minimization procedure. The proposed approach is validated on different multimodal images. Abstract: Hierarchical data representations are powerful tools to analyze images and have found numerous applications in image processing. When it comes to multimodal images however, the fusion of multiple hierarchies remains an open question. Recently, the concept of braids of partitions has been proposed as a theoretical tool and possible solution to this issue. In this paper, we demonstrate the relevance of the braid structure for the hierarchical representation of multimodal images. We first propose a fully operable procedure to build a braid of partitions from two hierarchical representations. We then derive a framework for multimodal image segmentation, relying on an energetic minimization scheme conducted on the braid structure. The proposed approach is investigated on different multimodal images scenarios, and the obtained results confirm its ability to efficiently handle the multimodal information to produce more accurate segmentation outputs.