Paper
8 December 2011 SAR and panchromatic image fusion based on contourlet hidden markov tree model
Huihui Li, Kun Liu
Author Affiliations +
Proceedings Volume 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis; 80021Q (2011) https://doi.org/10.1117/12.902806
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
Abstract
Contourlet-domain hidden markov tree(HMT) model can reflect the coefficients' dependencies of different scales and directions, then a SAR and optical image fusion algorithm based on it is proposed. Firstly source images are decomposed by Contourlet transform, low frequency and high frequency subband coefficients are obtained; secondly, the high frequency subband coefficients are modeled using hidden markov tree and the model is trained using Expectation-Maximization(EM) algorithm to get the posterior probability of the coefficients; Thirdly, using the posterior probability to guide the fusion rules' design of high frequency subband coefficients in order to preserve the salient features of original images well and obtain good noise suppression; Finally, the fusion coefficients are inversed to get the final fusion result. SAR and Panchromatic images were taken to fuse, and the results were evaluated by Difference Coefficient, Correlation Coefficient and Signal-Noise Ration. The experimental result shows that the proposed algorithm is better than traditional fusion algorithms based on Contourlet and wavelet-domain hidden markov tree model.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Huihui Li and Kun Liu "SAR and panchromatic image fusion based on contourlet hidden markov tree model", Proc. SPIE 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, 80021Q (8 December 2011); https://doi.org/10.1117/12.902806
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KEYWORDS
Image fusion

Synthetic aperture radar

Expectation maximization algorithms

Signal to noise ratio

Image processing

Wavelets

Image analysis

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