Multisensor image fusion using the wavelet transform
Graphical Models and Image Processing
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
2-D and 3-D Image Registration: for Medical, Remote Sensing, and Industrial Applications
2-D and 3-D Image Registration: for Medical, Remote Sensing, and Industrial Applications
Topographic Independent Component Analysis
Neural Computation
Image Processing, Analysis, and Machine Vision
Image Processing, Analysis, and Machine Vision
Fast and robust fixed-point algorithms for independent component analysis
IEEE Transactions on Neural Networks
A remote sensing image fusion algorithm based on ordinal fast independent component analysis
Proceedings of the 1st international conference on Forensic applications and techniques in telecommunications, information, and multimedia and workshop
Medical image fusion via an effective wavelet-based approach
EURASIP Journal on Advances in Signal Processing
Pixel-level image fusion with simultaneous orthogonal matching pursuit
Information Fusion
A regional image fusion based on similarity characteristics
Signal Processing
An efficient algorithm for multi-focus image fusion using PSO-ICA
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
MIRF: A Multimodal Image Registration and Fusion Module Based on DT-CWT
Journal of Signal Processing Systems
Mutual spectral residual approach for multifocus image fusion
Digital Signal Processing
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The task of enhancing the perception of a scene by combining information captured by different sensors is usually known as image fusion. The pyramid decomposition and the Dual-Tree Wavelet Transform have been thoroughly applied in image fusion as analysis and synthesis tools. Using a number of pixel-based and region-based fusion rules, one can combine the important features of the input images in the transform domain to compose an enhanced image. In this paper, the authors test the efficiency of a transform constructed using Independent Component Analysis (ICA) and Topographic Independent Component Analysis bases in image fusion. The bases are obtained by offline training with images of similar context to the observed scene. The images are fused in the transform domain using novel pixel-based or region-based rules. The proposed schemes feature improved performance compared to traditional wavelet approaches with slightly increased computational complexity.