基于Harris角点和改进SURF描述子的图像快速拼接

Image fast mosaic based on Harris corner points and improved SURF descriptor

针对SURF算法计算量大、对应点匹配时间长的不足,以Harris角点取代SURF斑点作为特征点,改进了描述子生成区域的子块划分方式,使区域面积减小40%。同时,引入尺度因子s以弥补采样区域减小的影响,形成一种计算量小、独特性好的描述子。以该方法构造的角点特征矢量参与同名点匹配,可实现较好的匹配快速性和准确性。匹配完成后,分别使用RANSAC方法和L-M方法获取变换矩阵并进行非线性优化,最后根据图像的不同区域采用不同方法完成图像融合。实验结果表明,该图像拼接方法与传统SURF法相比,图像匹配时间可节约35%以上,整体图像的拼接时间可节约30%左右,大幅提高了图像拼接的效率。

Since the shortages of SURF algorithm are the large amount of calculations and long matching time of corresponding points,the Harris corner points are taken as the feature points instead of the SURF spots. The sub-block dividing mode of de-scriptor generated region is improved,and the region areas are reduced by 40%. The descriptor with little calculated quantity and good peculiarity is shaped by the introduced scale factor s to eliminate the influence of sample region decrease. The corner point characteristic vector parameter structured by the proposed method is matched with the same name point,so rapidity and ac-curacy of matching are well realized. After matching,RANSAC method and L-M method are respectively adopted to obtain the transformation matrix,and execute nonlinear optimization. Image fusion is accomplished with different methods according to different image regions. The experimental results show that the image mosaic method,compared with the traditional SURF method, can save more than 35% image matching time and about 30% mosaic time of the whole image. The efficiency of image mosaic is greatly improved.