Two-dimensional signal and image processing
Two-dimensional signal and image processing
Multisensor image fusion using the wavelet transform
Graphical Models and Image Processing
A fast, non-iterative and exact histogram matching algorithm
Pattern Recognition Letters
A framework for multi-source data fusion
Information Sciences: an International Journal - Special issue: Soft computing data mining
Cognitive high level information fusion
Information Sciences: an International Journal
A driver fatigue recognition model based on information fusion and dynamic Bayesian network
Information Sciences: an International Journal
An EM algorithm for wavelet-based image restoration
IEEE Transactions on Image Processing
Random weighting estimation for fusion of multi-dimensional position data
Information Sciences: an International Journal
Sequential covariance intersection fusion Kalman filter
Information Sciences: an International Journal
A variational Bayesian approach to robust sensor fusion based on Student-t distribution
Information Sciences: an International Journal
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Image fusion of multi-spectral images and panchromatic images has been widely applied to imaging sensors. Multi-spectral images are rich in spectral information whereas panchromatic images have relatively higher spatial resolution. In this paper, we consider the image fusion as an estimation problem, that is to estimate the ideal scene of multi-spectral images at the resolution of panchromatic images. We propose a method of combining the covariance intersection (CI) principle with the expectation maximization (EM) algorithm to develop a novel image fusion approach. In contrast to other fusion methods, the proposed scheme takes cross-correlation among data sources into account, and thus provides consistent and accurate estimates through convex combinations. Since the covariance information is usually unknown in practice, the EM method is employed to provide a maximum likelihood estimate (MLE) of the covariance matrix. Real multi-spectral and panchromatic images are used to evaluate the effectiveness of the proposed EM-CI method. The proposed algorithm is found to preserve both the spectral information of the multi-spectral image and the high spatial resolution information of the panchromatic image more effectively than the conventional image fusion techniques.