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A Graph-Based Approach for Data Fusion and Segmentation of Multimodal Images | IEEE Journals & Magazine | IEEE Xplore

A Graph-Based Approach for Data Fusion and Segmentation of Multimodal Images


Abstract:

In the past few years, graph-based methods have proven to be a useful tool in a wide variety of energy minimization problems. In this article, we propose a graph-based al...Show More

Abstract:

In the past few years, graph-based methods have proven to be a useful tool in a wide variety of energy minimization problems. In this article, we propose a graph-based algorithm for feature extraction and segmentation of multimodal images. By defining a notion of similarity that integrates information from each modality, we create a fused graph that merges the different data sources. The graph Laplacian then allows us to perform feature extraction and segmentation on the fused data set. We apply this method in a practical example, namely, the segmentation of optical and LiDAR images. The results obtained confirm the potential of the proposed method.
Published in: IEEE Transactions on Geoscience and Remote Sensing ( Volume: 59, Issue: 5, May 2021)
Page(s): 4419 - 4429
Date of Publication: 25 September 2020

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