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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xuexing Zeng Durrani, T.S. |
| Copyright Year | 2010 |
| Description | Author affiliation: Centre for excellence in Signal and Image Processing, University of Strathclyde, Glasgow, Scotland, UK (Xuexing Zeng; Durrani, T.S.) |
| Abstract | With the ready availability of multiple sensors, the area of information fusion has been receiving increasing attention. For multi-sensor image data, algorithms such as simple average method, Principal Component Analysis (PCA) method, Gradient Pyramid (GP) method, Laplacian Pyramid (LP), Ratio Pyramid (RP) method and Discrete Wavelet Transform (DWT) methods have been successfully applied for image fusion. Another important issue that arises in image fusion: the performance of image fusion is that the performance of the associated algorithms is difficult to evaluate, especially when a clearly defined ground-truth image is not available. Some common measures to assess the performance for image fusion are Mutual information (MI), Tsallis and Renyi divergence based information. However they are difficult to estimate precisely. In this paper, a new approach is proposed for evaluating the performance of image fusion algorithms based on copula functions. To achieve this, copulas are proposed for the estimation of the MI, Tsallis and Renyi divergence based information and these are used to evaluate the quality of image fusion. |
| Starting Page | 756 |
| Ending Page | 759 |
| File Size | 266403 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424458974 |
| e-ISBN | 9781424459001 |
| DOI | 10.1109/ICOSP.2010.5655910 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-10-24 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image fusion Mutual information Principal component analysis Discrete wavelet transforms Joints Probability density function Pixel Image Fusion Copulas Divergence based information Tsallis Renyi Performance Evaluation |
| Content Type | Text |
| Resource Type | Article |
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