Multifocus image fusion using artificial neural networks
Pattern Recognition Letters
Guest editorial: Image fusion: Advances in the state of the art
Information Fusion
A Novel Wavelet Image Fusion Algorithm Based on Chaotic Neural Network
FAW '08 Proceedings of the 2nd annual international workshop on Frontiers in Algorithmics
Enhancing geophysical signals from archaeological sites trough the use of wavelet transforms
WSEAS TRANSACTIONS on SYSTEMS
Capture and fusion of 3d surface texture
Multimedia Tools and Applications
Infrared and visible image fusion using fuzzy logic and population-based optimization
Applied Soft Computing
Multi-focus image fusion based on SOFM neural networks and evolution strategies
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
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An image fusion algorithm based on multiscale analysis along arbitrary orientations is presented. After a steerable dyadic wavelet transform decomposition of multi-sensor images is carried out, the maximum local oriented energy is determined at each level of scale and spatial position. Maximum local oriented energy and local dominant orientation are used to combine transform coefficients obtained from the analysis of each input image. Reconstruction is accomplished from the modified coefficients, resulting in a fused image. Examples of multi-sensor fusion and fusion using different settings of a single sensor are demonstrated.