关键词: 图像融合, 多聚焦图像, Brenner函数, 景深扩展

Abstract: In order to eliminate the aliasing phenomena of the spectrum in each direction subband of the fusion algorithm in contourlet domain and to improve the accuracy of extracting effective coefficients, a multifocus image fusion method was proposed based on the Brenner function and the New Contourlet Transform with Sharp Frequency Localization (NCT-SFL). Firstly, the new contourlet transform was used to decompose the multifocus images which to be fused. And then the traditional arithmetic mean fusion rule was used to fuse the low-frequency coefficients and the maximum local energy based on the Brenner function to fuse the high-frequency coefficients. Finally, the inverse new contourlet transform was used to obtain fused images. Using the proposed fusion method, the experimental results demonstrate that the algorithm can effectively extract the contour information of the images which to be fused, and under the premise of obtaining a better performance in terms of subjective vision, objective evaluation criterions of mutual information and transferred edge information have improved by 99.34% and 77.95% respectively. In addition, the more levels of the new contourlet decomposition, the more obvious advantages of the algorithm will show.

Key words: image fusion, multi-focus image, Brenner function, Extended Depth of Focus