红外技术Issue(9)：546-550,5.
基于区域的二维经验模式分解的图像融合算法
Region-based Image Fusion Algorithm Using Bidimensional Empirical Mode Decomposition
摘要
Abstract
In order to improve the effect of the image fusion, a region-based image fusion algorithm using bidimensional empirical mode decomposition(BEMD)was put forward. This algorithm can be used to fuse the infrared image and low-level-light or visible image. First of all, decompose the source images by BEMD and fuse the residue of the images by weighted average. Secondly, segment the fused image by fuzzy C-means(FCM)and use the result to map the intrinsic mode function(IMF)images. Then fuse the IMF images by some fusion criterion. Finally, reconstruct the fusion images. The simulation results and objective evaluation data show that such algorithm can enhance the information in the fused image and highlight the image details. And this algorithm has certain advantages compared with others.关键词
图像融合/二维经验模式分解/模糊C均值聚类/区域分割Key words
image fusion/bidimensional empirical mode decomposition/fuzzy c-means/region segmentation分类
信息技术与安全科学引用本文复制引用
韩博,张鹏辉,许辉,陆刘兵,张俊举..基于区域的二维经验模式分解的图像融合算法[J].红外技术,2013,(9):546-550,5.基金项目
国家自然科学基金，编号61101195；江苏省产学研联合创新项目，编号20120017。 （）
