HOLBP: Remote Sensing Image Registration Based on Histogram of Oriented Local Binary Pattern Descriptor

Remote. Sens. Pub Date : 2021-06-14 DOI:10.3390/rs13122328
Yameng Hong, Chengcai Leng, Xinyue Zhang, Zhao Pei, I-Fan Cheng, A. Basu
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引用次数: 4

Abstract

Image registration has always been an important research topic. This paper proposes a novel method of constructing descriptors called the histogram of oriented local binary pattern descriptor (HOLBP) for fast and robust matching. There are three new components in our algorithm. First, we redefined the gradient and angle calculation template to make it more sensitive to edge information. Second, we proposed a new construction method of the HOLBP descriptor and improved the traditional local binary pattern (LBP) computation template. Third, the principle of uniform rotation-invariant LBP was applied to add 10-dimensional gradient direction information to form a 138-dimension HOLBP descriptor vector. The experimental results showed that our method is very stable in terms of accuracy and computational time for different test images.
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HOLBP:基于定向局部二值模式描述子直方图的遥感图像配准
图像配准一直是一个重要的研究课题。本文提出了一种新的描述子构造方法——定向局部二值模式描述子直方图(HOLBP),以实现快速、鲁棒的匹配。我们的算法中有三个新的组成部分。首先,我们重新定义了梯度和角度计算模板,使其对边缘信息更加敏感;其次,提出了一种新的HOLBP描述符构建方法,改进了传统的局部二进制模式(LBP)计算模板;第三,应用均匀旋转不变LBP原理,添加10维梯度方向信息,形成138维HOLBP描述子向量;实验结果表明,对于不同的测试图像,我们的方法在精度和计算时间上都非常稳定。
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