摘要
针对目前图像拼接算法存在对于图像配准过程中对应特征点对难以准确匹配的问题,提出了一个通过改进的SURF算法提取图像特征点,然后对得到的特征点进行描述,利用快速RANSAC算法配准图像,最后采用像素加权的方法进行图像融合。实验结果表明,提出的改进SURF方法有效地提高了特征点提取的准确性,去除了错误的匹配点对,将整个拼接过程的效率从之前的13.03对/秒提升到15.20对/秒。
Image stitching is mainly used in aerial image processing, medical image analysis, virtual reality technology, computer vision, etc. For image registration, the difficult is to accurately extract the corresponding feature points. This paper puts forward a kind of algorithm based on improved SURF algorithm to extract image feature points, and then describes the feature points, using the RANSAC algorithm to registration the image. Finally, it uses the method of weighted pixel in image fusion. The experiment results show that this method improved the accuracy of feature extract, wipe out the wrong matching points, and improved the processing of stitching from 13.03/s to 15.20/s.
出处
《微型机与应用》
2014年第24期45-47,共3页
Microcomputer & Its Applications
