Image Fusion Algorithm Based on Adaptive Weighted Coefficients

摘要：

Image fusion is a very important step for image mosaic. Fusion algorithms affect the visual effect and quality of the mosaic images directly. This paper presents an adaptive weighted coefficients algorithm for image fusion. The algorithm can adjust weighted coefficients adaptively along with changes of the range and shape of the overlapping regions. First, Harris operator is used to detect feature points. Then, we use normalized cross correlation (NCC) and random sample consensus (RANSAC) algorithm to carry out coarse matching and precise matching respectively, and to obtain the transformation matrix. Finally, the proposed algorithm is used to fuse images. Compared with other fusion algorithms, the experiment results indicate that the proposed fusion algorithm eliminates stitching seams more effectively, and has better fusion effect.

关键词： image fusion Harris normalized cross correlation (NCC) random sample consensus (RANSAC) adaptive weighted coefficients

作者: Haifeng Liu Mike Deng Chuangbai Xiao Xiao Xu

作者单位: College of Computer Science and Technology Beijing University of Technology Beijing, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 748-751

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）