A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Alignment by maximization of mutual information
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Image Sequence Fusion Using a Shift-Invariant Wavelet Transform
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 3 - Volume 3
Automatic Registration of Multi-Sensor Airborne Imagery
AIPR '05 Proceedings of the 34th Applied Imagery and Pattern Recognition Workshop
Pixel-based and region-based image fusion schemes using ICA bases
Information Fusion
Region-based Image Fusion Using Energy Estimation
SNPD '07 Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01
Image Registration by Template Matching Using Normalized Cross-Correlation
ACT '09 Proceedings of the 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies
A multi-modal automatic image registration technique based on complex wavelets
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Efficient Least Squares Multimodal Registration With a Globally Exhaustive Alignment Search
IEEE Transactions on Image Processing
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Image Fusion is a powerful and necessary tool to incorporate the relevant visual information provided by multiple sensors simultaneously. The quality of the results however, is bounded not only by the quality of the algorithm, but also by the outcome of the required image registration algorithm. Despite this dependency, images are always assumed to be pre-aligned. With 3rd Generation surveillance systems, centralized computations are shifted to distributed visual nodes low on computational and power resources. This article presents a combined approach that is able to register and fuse multimodal images, dubbed MIRF. Combining both algorithms into one image domain not only offers a reduction in complexity making it a better fit for a resource constrained embedded platform, but also improves the response time of the system. Two algorithms for area-based image registration and object-based image fusion are proposed. They are based on Dual-Tree Complex Wavelet Transform. Qualitative and quantitative experimental results show that the proposed registration approach achieves comparable accuracies to its counterparts, with lower-complexity. On the other hand, the developed fusion scheme exhibits higher accuracy and proves its immunity to minor errors in registration