Infrared and Visible Images Fusion Based on Contourlet-domain Hidden Markov Tree Model

摘要：

According to the fusion problem of infrared and visible images, the algorithm based on Contourletdomain Hidden Markov Tree model (CHMT) is proposed in this paper. After the contourlet transform on the images, contourlet coefficients of the source images are trained to Contourlet-domain HMT model using the Expectation Maximization (EM) algorithm. Because the Contourlet-domain HMT model efficiently captures all dependencies across scales, space and directions through a tree structured dependence network, it can give more accurate description of images. Then a new fusion rule for the high frequency is built based on the window energy ratio, and weight average is adopted for low frequency. Experimental results show that the proposed algorithm provides more satisfying fusion results in terms of visual effect and objective evaluations, such as standard deviation, standard variance and clarity.

关键词： image fusion contourlet-domain HMT model window energy ratio

作者: Zejing Guang Zhenbing Zhao Qiang Gao Sasa Wang

作者单位: School of Electrical and Electronic Engineering, North China Electric Power University Baoding, China

会议类型: 国际会议

会议名称: 2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)

会议地点: 上海

会议语种:英文

页码: 1951-1955

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）