Uni-modal versus joint segmentation for region-based image fusion
conference paper
A number of segmentation techniques are compared with regard to their usefulness for region-based image and video fusion. In order to achieve this, a new multi-sensor data set is introduced containing a variety of infra-red, visible and pixel fused images together with manually produced 'ground truth' segmentations. This enables the objective comparison of joint and unimodal segmentation techniques. A clear advantage to using joint segmentation over unimodal segmentation, when dealing with sets of multi-modal images, is shown. The relevance of these results to region-based image fusion is confirmed with task-based analysis and a quantitative comparison of the fused images produced using the various segmentation algorithms.
Topics
TNO Identifier
16684
Source title
2006 9th International Conference on Information Fusion, FUSION, 10 July 2006 through 13 July 2006, Florence
Files
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