基于特征的序列图像拼接方法

Yihua Lan, H. Ren, Cunhua Li, Xuefeng Zhao, Zhifang Min
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引用次数: 2

摘要

图像拼接是传统图像处理的重要组成部分。针对图像拼接系统,提出了一种基于特征的序列图像拼接方法。该方法将整个图像配准过程分为特征点检测、特征描述子提取、特征点匹配、运动模型参数估计和拼接五个步骤。在这些步骤中,利用高斯图像的差值得到极值点作为特征点,然后使用SIFT描述符算子对特征进行描述,最后使用随机样本一致性方法对运动参数进行估计。我们对人工图像和真实图像两种序列图像进行了测试。结果表明,该方法具有较好的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Feature Based Sequence Image Stitching Method
Image mosaic is useful for the traditional image process. We proposed a novel feature based sequence image stitching method for the image mosaic system. In this method, the whole image registration process has five steps, which includes feature point detection, feature descriptor extraction, feature points matching, estimation of the motion model parameters and stitching process. In these steps, difference of Gaussian image is used to get the extreme points as the feature points, then the SIFT descriptor operator is used to describe the feature, finally random sample consensus method is used for estimating the motion parameters. We test our method on two kinds of sequence images, the artificial images and the real images. The results show the stitching method is robust.
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