用于遥感图像拼接的改进SURF算法  

Improved SURF algorithm used in image mosaic

作　　者：董强[1,2] 刘晶红[1] 周前飞[1,2] 

机构地区：[1]中国科学院长春光学精密机械与物理研究所,长春130033 [2]中国科学院大学,北京100049

出　　处：《吉林大学学报（工学版）》2017年第5期1644-1652,共9页Journal of Jilin University:Engineering and Technology Edition

基　　金：吉林省重大科技攻关项目(11ZDGG001);装备预研项目;国家林业公益性行业科研专项项目(201204515)

摘　　要：经典的SURF算法存在许多不足,如特征描述符维度高、运算量大,对于旋转和拍射视角变换角度过大时,匹配精度低等。针对以上问题,提出了一种改进算法,首先通过Hessian矩阵提取特征点,然后采用特征点圆形邻域进行特征描述,使用Haar小波响应为每个特征点建立描述符,同时计算邻域内归一化的灰度差分及二阶梯度,形成新的特征描述符,最后采用RANSAC算法剔除误匹配点。该算法不仅较经典SURF算法具有速度优势,同时充分利用了灰度信息和细节信息,具有更高的精度。实验结果表明:该算法对图像的模糊、光照差异、角度旋转、视场变换等均有良好的鲁棒性和稳定性。将该算法应用于遥感图像拼接,得到无明显几何移位、边缘衔接良好的拼接图像。该算法是一种耗时短、精度高的图像配准算法,能够满足遥感图像拼接对配准的要求。To overcome the redundant feature descpriptor,high computational complexity,low matching precision when the angle of rotation or view spends greatly in image registration method based on SURF algorithm,an improved SURF algorithm is proposed.First,the feature points are extracted using Hessian matrix.Then,the feature descriptor for each keypoint in the circular neighborhood is constructed using Haar wavelet response;meanwhile,the normalized gray values difference and second-order gradient of this region are computed.Finally,RANSAC algorithm is applied to eliminate false matches.This method not only performs faster than SURF algorithm,but also fully employs the image gray information and details to acquire higher accuracy.Results indicate that the proposed method has strong robustness and stability for blur,illumination difference,angle rotation and viewpoint change.A well-edge mosaic image is obtained without obvious geometric misalignment in the remote sensing image mosaicking process.This method is an effective image registration algorithm with high-speed and precision,and it satisfies the need of registration in the remote sensing image mosaic.

关 键 词：计算机应用 图像配准 特征提取 SURF算法 二阶梯度 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]