摘要
全景图拼合的预处理主要包括对样本图像的特征提取以及相邻图像的特征匹配。本文首先改进Harris角点检测算子,以便准确提取样本图像的特征点并赋予特征描述符;提出一种基于小波系数的特征索引算法,实现了图像特征点对的快速搜索和两幅图像之间的匹配。实验结果表明,该算法得到的匹配点精确,搜索效率高,能够实现全景图的无缝拼接。
The preprocessing to panoramic stitching mainly includes extracting features form sample images and matching. Then to images of overlapping. In this approach,an extended Harris corner detector is proposed by us to accurately extract feature points from an image and to assign a feature descriptor for each of them. After that,we suggests a new feature indexing algorithm based on wavelet coefficients which enables comparing features in neighboring images more efficiently. Experiments show that feature matches are accurate and efficient,and seamless panoramic image stitching can be produced.
出处
《光电子．激光》
EI
CAS
CSCD
北大核心
2007年第6期746-749,共4页
Journal of Optoelectronics·Laser
基金
天津自然科学基金资助项目(033600211)
天津教委基金资助项目(2004BA09)
关键词
特征点
小波变换
K-近邻
图像拼接
feature point
wavelet transformation
panoramic image stitching
