Implementation of Max Principle with PCA in image fusion for Surveillance and Navigation Application
Image fusion is the combination of two or more different images by using suitable algorithms to form an output image. It provides a useful tool to integrate multiple images into a composite image. In this paper, we present an approach that uses the principle component transform along with the selec...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Computer Vision Center Press
2011-07-01
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| Series: | ELCVIA Electronic Letters on Computer Vision and Image Analysis |
| Subjects: | |
| Online Access: | https://elcvia.cvc.uab.es/article/view/353 |
| Summary: | Image fusion is the combination of two or more different images by using suitable algorithms to form an output image. It provides a useful tool to integrate multiple images into a composite image. In this paper, we present an approach that uses the principle component transform along with the selection of maximum pixel intensity to perform pixel level fusion. The entropy, mutual information and the universal index based measure are used to evaluate the performance of this fusion algorithm.
Keywords: Wavelet transformation, pixel level image fusion, PCA
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| ISSN: | 1577-5097 |