Abstract
The recent years have seen an increasing interest in developing algorithms for image fusion and several algorithms have been proposed in the literature. However, a process for assessing several fusion algorithms and coming up with the best solution for a given set of images has not been sufficiently explored so far. In this paper, a system is proposed that performs intelligent decision making in image fusion. The system uses the concepts of adaptive learning and inherent knowledge to present the best fusion solution for a given set of images. By automating the selection process, the system can analyze and exhibit intrinsic details of the images and adapt this knowledge to provide better solutions for varying types of images to provide better solutions for varying types of images.
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Kumar, A., Kumar, P.U., Shelar, A., Naidu, V. (2013). Multi-agent Based Intelligent System for Image Fusion. In: Nagamalai, D., Kumar, A., Annamalai, A. (eds) Advances in Computational Science, Engineering and Information Technology. Advances in Intelligent Systems and Computing, vol 225. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00951-3_10
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DOI: https://doi.org/10.1007/978-3-319-00951-3_10
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-00950-6
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