An image fusion algorithm based on likelihood function of HMT in Contourlet domain

作者：Liu Kun^*; Li Hui Hui

来源：Journal of Optoelectronics - Laser, 2013, 24(10): 2031-2037.

• Contourlet coefficients
• Contourlet transform
• Different frequency
• Feasible algorithms
• Hidden Markov tree model
• Image fusion algorithms
• Image fusion methods
• Likelihood functions

Traditional image fusion method based Contourlet transform always ignores the relationship of the Contourlet coefficients. This paper proposes a novel image fusion method based on Contourlet domain hidden Markov tree (HMT) model. The fusion method can strengthen the relationship among Contourlet coefficients and extract more detailed and exact information from the original images. Firstly, the original images are decomposed using Contourlet transform. Secondly, different frequency bands have different characteristics, so this paper designs the different fusion rules in different frequencies. The proposed method calculates likelihood function according to the parameters of Contourlet HMT. Finally the fused coefficients are reconstructed to obtain fusion results. Two sets of images are taken as experimental data, and subjective and objective standards are used to evaluate the results. Experimental results have verified the simplicity and effectiveness of the method. The results show that the proposed method can preserve much more information. The proposed fusion rule based on likelihood function can extract much more and exact characteristics for fused images. And it is an effective and feasible algorithm.

• 出版日期2013
• 单位上海海事大学; 西北工业大学