A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multifocus image fusion using artificial neural networks
Pattern Recognition Letters
On multi-feature integration for deformable boundary finding
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
A fusion scheme of visual and auditory modalities for event detection in sports video
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
A pixel-level multisensor image fusion algorithm based on fuzzy logic
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
A multivalued image wavelet representation based on multiscale fundamental forms
IEEE Transactions on Image Processing
Wavelet thresholding of multivalued images
IEEE Transactions on Image Processing
Fusing images with different focuses using support vector machines
IEEE Transactions on Neural Networks
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A multivalued wavelet transform (MWT) is proposed to fuse multisensor images in feature space. First, feature space is constructed using image-derived features, and then the MWT is introduced. The multisensor images are then fused in the MWT domain using a voting and electing fuser based on the cross-feature scale guideline and the posterior probability of the MWT coefficient. The performance of the MWT is estimated using metric measures regarding various aspects of image quality. A fusion experiment using Thematic Mapper (TM) multispectral and SPOT panchromatic images of south China demonstrates that MWT outperforms smoothing filter-based intensity modulation (SFM) in terms of the fidelity to spectral properties and the injection of salient information. The experimental results confirm that the MWT is a superior fusion method for enhancing spatial quality of multispectral images with their spectral properties reliably preserved.