| 引用本文: | 刘红亮,陈维义,许中胜.曲面拟合法和梯度法相结合的图像亚像素配准算法.[J].国防科技大学学报,2015,37(5):180-185.[点击复制] |
| LIU Hongliang,CHEN Weiyi,XU Zhongsheng.An image sub-pixel registration algorithm based on combination of curved surface fitting method and gradient method[J].Journal of National University of Defense Technology,2015,37(5):180-185[点击复制] |
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| 曲面拟合法和梯度法相结合的图像亚像素配准算法 |
| 刘红亮1, 陈维义1, 许中胜2 |
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(1.海军工程大学 兵器工程系, 湖北 武汉 430033;2.海军驻中南地区光电系统军事代表室, 湖北 武汉 430073)
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| 摘要: |
| 针对传统亚像素配准算法存在精度不高、计算复杂的问题，提出了一种曲面拟合法和梯度法相结合的图像亚像素配准算法。采用9点相关系数曲面拟合法对图像进行粗配准，求得一个相对粗略的亚像素配准位置；在两幅图像中选取相同尺寸的子区图像，在粗略的亚像素配准位置基础上，采用梯度法最终获得精确的亚像素配准位置。不同平移关系下的样本图像亚像素配准对比实验结果表明，该算法实现了曲面拟合法和梯度法的优势互补，有效提高了图像配准的精度，最大配准绝对误差由0.17像素降低为0.02像素。 |
| 关键词: 图像配准 亚像素 曲面拟合法 梯度法 泰勒展开 |
| DOI：10.11887/j.cn.201505028 |
| 投稿日期：2014-10-12 |
| 基金项目:国家部委资助项目(9140A09031213JB11123) |
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| An image sub-pixel registration algorithm based on combination of curved surface fitting method and gradient method |
| LIU Hongliang1, CHEN Weiyi1, XU Zhongsheng2 |
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(1. Department of Weaponry Engineering, Naval University of Engineering, Wuhan 430033, China;2. Navy Representative Office of Electro-Optics Systems in Zhongnan Area, Wuhan 430073, China)
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| Abstract: |
| In order to overcome the disadvantages of the low registration accuracy and the computational complexity of traditional algorithms, a new sub-pixel registration algorithm based on combination of curved surface fitting method and gradient method was proposed. Firstly, curved surface fitting method based on 9 correlation coefficients was used to achieve the image rough registration. Secondly, subimages were extracted from the reference images according to a predefined selection method. At last, gradient method based on the rough registration was proposed to achieve the accurate sub-pixel registration. Test results among experimental images with different translational relations show that the new algorithm has the advantages of both curved surface fitting method and gradient method, and greatly improves the accuracy of image sub pixel registration．The maximum absolute error of registration accuracy is reduced from 0.17 pixel to 0.02 pixel. |
| Keywords: image registration sub pixel curved surface fitting method gradient method Taylor expansion |
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