摘要
以图像间的互信息为基础,通过计算图像的信息熵来获得2幅图像的匹配区域。利用互信息量测度函数作为蚁群算法的适应值函数,通过蚁群迭代寻找最优的匹配区域。与SIFT拼接算法进行比对实验。实验结果表明,本文算法具有良好的拼接效果和较高的拼接效率。
Image mosaic can obtain greater vision and improve image resolution by stitching algorithm mainly. It has broad application prospects and commercial value at present. In this paper, we can get the matching area of the two images by calculating the comentropy based on the mutual information between images. Then, we used the mutual information measure function as the fitness function of ACA and found the optimal matching region by iteration. Finally, compared with stitching method based on SIFT features by using a series of mosaic experiments, the result showed that the proposed algorithm has better stitching effect and higher splicing efficiency.
出处
《重庆理工大学学报（自然科学）》
CAS
2013年第1期76-81,共6页
Journal of Chongqing University of Technology：Natural Science
关键词
互信息
蚁群算法
图像拼接
mutual information
ant colony algorithm
image mosaic
