Title :
Uni-Modal Versus Joint Segmentation for Region-Based Image Fusion
Author :
Lewis, J.J. ; Nikolov, S.G. ; Canagarajah, C.N. ; Bull, D.R. ; Toet, A.
Author_Institution :
Centre for Commun. Res., Univ. of Bristol
Abstract :
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
Keywords :
image fusion; image segmentation; infra-red image; joint segmentation technique; multisensor data set; pixel fused image; region-based image fusion; task-based analysis; unimodal segmentation technique; video fusion; visible image; Algorithm design and analysis; Human factors; Image analysis; Image databases; Image fusion; Image segmentation; Infrared imaging; Pixel; Visual databases; Visual system; evaluation of segmentation; human segmentation; image fusion; multi-modal segmentation; region-based;
Conference_Titel :
Information Fusion, 2006 9th International Conference on
Conference_Location :
Florence
Print_ISBN :
1-4244-0953-5
Electronic_ISBN :
0-9721844-6-5
DOI :
10.1109/ICIF.2006.301565
