Multisensor image fusion using the wavelet transform
Graphical Models and Image Processing
Algorithms for simultaneous sparse approximation: part I: Greedy pursuit
Signal Processing - Sparse approximations in signal and image processing
Digital Signal Processing
Objectively adaptive image fusion
Information Fusion
Subjective tests for image fusion evaluation and objective metric validation
Information Fusion
Guest editorial: Image fusion: Advances in the state of the art
Information Fusion
Pixel- and region-based image fusion with complex wavelets
Information Fusion
Pixel-based and region-based image fusion schemes using ICA bases
Information Fusion
Image Fusion Using Nonsubsampled Contourlet Transform
ICIG '07 Proceedings of the Fourth International Conference on Image and Graphics
Applied Multi-Dimensional Fusion
The Computer Journal
Compression of facial images using the K-SVD algorithm
Journal of Visual Communication and Image Representation
Non-parametric and region-based image fusion with Bootstrap sampling
Information Fusion
MRI and PET image fusion by combining IHS and retina-inspired models
Information Fusion
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
Matching pursuits with time-frequency dictionaries
IEEE Transactions on Signal Processing
An EM algorithm for wavelet-based image restoration
IEEE Transactions on Image Processing
Gradient-based multiresolution image fusion
IEEE Transactions on Image Processing
The Nonsubsampled Contourlet Transform: Theory, Design, and Applications
IEEE Transactions on Image Processing
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
IEEE Transactions on Image Processing
Sparse Representation for Color Image Restoration
IEEE Transactions on Image Processing
A regional image fusion based on similarity characteristics
Signal Processing
A reconstruction method for electrical capacitance tomography based on image fusion techniques
Digital Signal Processing
Human visual system inspired multi-modal medical image fusion framework
Expert Systems with Applications: An International Journal
OMP or BP? a comparison study of image fusion based on joint sparse representation
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
Simultaneous image fusion and super-resolution using sparse representation
Information Fusion
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Pixel-level image fusion integrates the information from multiple images of one scene to get an informative image which is more suitable for human visual perception or further image-processing. Sparse representation is a new signal representation theory which explores the sparseness of natural signals. Comparing to the traditional multiscale transform coefficients, the sparse representation coefficients can more accurately represent the image information. Thus, this paper proposes a novel image fusion scheme using the signal sparse representation theory. Because image fusion depends on local information of source images, we conduct the sparse representation on overlapping patches instead of the whole image, where a small size of dictionary is needed. In addition, the simultaneous orthogonal matching pursuit technique is introduced to guarantee that different source images are sparsely decomposed into the same subset of dictionary bases, which is the key to image fusion. The proposed method is tested on several categories of images and compared with some popular image fusion methods. The experimental results show that the proposed method can provide superior fused image in terms of several quantitative fusion evaluation indexes.