摘要
该文提出一种将遗传搜索策略应用于多聚焦图像融合子块寻优的算法,对同一场景两幅严格配准的多聚焦图像的清晰恢复进行了深入研究。该方法把图像子块大小作为遗传染色体,经过杂交、变异等操作,以便得到全局意义上的最优解。利用3种评价参量,即均方根误差、熵和互信息进行不同图像融合方法的分析及效果评价,文中讨论了两种情形,并通过大量的图像实验表明:当聚焦目标无交叉模糊区域时,该方法能实现多聚焦图像对参考源图像的重构或优化融合效果;当聚焦目标有交叉模糊区域时,该方法也取得了很好的效果,超过Laplacian算法和小波变换法。
An adaptive genetic search algorithm is developed for fusion of two spatially registered images of the same scene, In this method, the size of block is defined as chromosome, after crossover and mutation, the global optimal image will be got. Three evaluation criteria such as root mean square error, entropy and mutual information are used on the analysis and effect evaluation of different fused images. Two cases are discussed and extensive experiments demonstrate that in one case the method achieves reconstruction or optimized fusion result to the reference image when the focus objectives are not overlapping blurred, and in another case this method performs better outperforming Laplacian and wavelet methods when the focus objectives are overlapping blurred.
出处
《电子与信息学报》
EI
CSCD
北大核心
2006年第11期2054-2057,共4页
Journal of Electronics & Information Technology
关键词
图像重构
遗传搜索
多聚焦图像
图像融合
Image reconstruction, Genetic search, Multifocus images, Image fusion
