Image Registration Algorithm Based on Super pixel Segmentation and SURF Feature Points

Weiyi Wei, Chengfeng A, Yufei Zhao, Guicang Zhang
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引用次数: 4

Abstract

In the current image registration technology, feature points detection and matching feature points have lower accuracy. Based on the analysis of SURF feature point detection and information entropy for image registration, an image registration algorithm based on SURF feature points is proposed. Firstly, the image is divided into super-pixels, and the information entropy of each image area is calculated. The redundant points in feature points are eliminated by using the value of information quantity. The problem that the SURF operator distributes densely is improved and the number of feature points is reduced. Experimental results show that the improved algorithm can improve the accuracy of image feature point pairs, and effectively improve the quality of registration.
基于超像素分割和SURF特征点的图像配准算法
在目前的图像配准技术中,特征点的检测和匹配精度较低。在分析SURF特征点检测和图像配准信息熵的基础上,提出了一种基于SURF特征点的图像配准算法。首先,将图像分割成多个超像素,计算每个图像区域的信息熵;利用信息量值消除特征点中的冗余点。改进了SURF算子分布密集的问题,减少了特征点的数量。实验结果表明,改进后的算法可以提高图像特征点对的精度,有效提高配准质量。
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