International Journal of Applied Mathematics and Machine LearningAuthor's: Yuchao Sun, Shaohai Hu, Shuaiqi Liu and Wei Sun
Pages: [197] - [220]
Received Date: December 2, 2014
Submitted by: Jianqiang Gao.
Based on the imaging characteristics of the infrared and visual images and the insufficient information content of the fused images, combined with the benefits of complex shearlet transform and fuzzy logic, a kind of infrared and visual image fusion algorithm based on object extraction via complex shearlet transform is proposed, which fuses the object region and background, respectively. First, the object regions from infrared image are segmented by region growing method. Then, complex shearlet transform is utilized for multiscale geometric decomposition of the source images, the object regions and background region are fused by different rules. The high frequency sub-band coefficients of background region are selected by using the fuzzy logic, and finally, the fused image is reconstructed by the inverse complex shearlet transform. Experimental results demonstrate that the proposed fusion algorithm outperforms typical wavelet-based, contourlet-based and non-subsampled contourlet-based, non-sampled shearlet fusion algorithms in terms of qualitative and quantitative evaluations.
image fusion, object extraction, infrared image, visible image, complex shearlet, fuzzy logic.
