计算机工程与应用Issue(15)：157-163,7.DOI:10.3778/j.issn.1002-8331.1208-0480
改进多尺度特征提取的图像配准算法研究
Image registration algorithm research using improved multi-scale feature extraction
摘要
Abstract
Detected corner points using Harris-Laplace in multiple scales cause the problem that the same structure is detected in certain range of scales, which leads to finding many redundant points. Those points increase the complexity of computing in the later corner point description and matching procedure. Meanwhile, the difference of those points in scales and locations also causes mismatch. An improved Harris-Laplace method is proposed, which selects one character-istic point to represent the same local structure. With the improved Harris-Laplace method and SIFT descriptor, through setting the threshold of maximum and second maximum of distance, the auto image registration is realized. The results of many experiments compared with the original method indicate that the improved method not only has better invariant per-formance in image rotation transform illumination change and scale transform, but also can obtain stable matching pairs. Except that, for getting rid of many redundant points in detecting procedure, the consumed time of image registration and mismatch probability are also reduced.关键词
Harris-Laplace/冗余点/尺度不变特征变换(SIFT)描述子/图像配准Key words
Harris-Laplace/redundant points/Scale-Invariant Feature Transform(SIFT)descriptor/image registration分类
信息技术与安全科学引用本文复制引用
杨宇光,滕义伟..改进多尺度特征提取的图像配准算法研究[J].计算机工程与应用,2014,(15):157-163,7.基金项目
国家自然科学基金（No.61003290）；教育部博士学科点专项科研基金（No.20091103120014）；北京市自然科学基金（No.4122008，No.1102004）；ISN开放基金。 （）
