应用光学, 2019, 40 (2): 259, 网络出版: 2019-03-26  

基于局部哈希学习的大面阵CCD航拍图像匹配方法

Matching method of large array CCD aerial images based on local hashing learning
作者单位
南京信息工程大学 江苏省气象探测与信息处理重点实验室,江苏 南京 210044
摘要
为实现大面阵CCD航拍图像准确快速匹配, 提出一种局部多特征哈希学习LMFH(local multi-feature hashing)方法。依据航向重叠率构建预测区域, 在预测区域内检测特征点并进行多特征描述, 以现有上万幅航拍图像为训练样本, 通过哈希函数将高维的特征描述向量映射为紧凑的二进制哈希编码, 在汉明空间通过汉明距离实现特征点的快速匹配。实验结果表明, 相对于SURF算子, LMFH算法在准确度上提高了10%, 匹配时间上减少了0.2 s。LMFH算法可更快更准确地实现CCD航拍图像的匹配。
Abstract
In order to realize the fast and accurate matching of large array charge coupled-device (CDD) aerial images, a local multi-feature hashing (LMFH) method is proposed. Firstly, the prediction area is constructed according to the course overlap rate, and the feature points detected in the area are described by multi-feature. Then, the hash functions are learned by tens of thousands of existing aerial images. Finally, the high-dimensional feature description vectors are mapped to compact binary hash codes by the learned hash functions. Fast hashing matching is achieved according to the Hamming distance in the Hamming space. Experiments show that compared to the classical speeded up robust features (SURF) algorithm, accuracy is improved about 10%, meanwhile, the matching time is decreased 0.2s. The proposed LMFH algorithm for aerial images matching is much more efficient.

陈苏婷, 郭子烨, 张艳艳. 基于局部哈希学习的大面阵CCD航拍图像匹配方法[J]. 应用光学, 2019, 40(2): 259. CHEN Suting, GUO Ziye, ZHANG Yanyan. Matching method of large array CCD aerial images based on local hashing learning[J]. Journal of Applied Optics, 2019, 40(2): 259.

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!