太阳高分辨观测图像与全日面像的高精度配准方法
High-accuracy Registration Method of Solar High-resolution Observation Images and Full-disk Solar Images
查看参考文献17篇
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文摘
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在太阳观测研究中,高分辨图像与全日面像的配准是一项非常有意义的工作,但由于他们之间存在着旋转、缩放和平移,因此很难高精度地进行匹配。提出一种结合局部统计信息和控制点匹配的图像配准方法,核心思想为将视场等间隔划分为大量重叠的局部区域,通过相关匹配在全日面像上寻找对应的局部区域,然后计算每一对局部区域间的亚像元偏移,根据偏移量确定每一对特征点的坐标位置,据此作为点匹配中的特征控制点;最后根据控制点建立仿射变换的转换方程,采用最小二乘求解整个视场的转换参数,根据解出的参数重新对图像进行迭代,得到收敛后的结果并进行配准。通过对高分辨观测图像和全日面SDO/HMI连续谱图像进行配准,拟合结果的偏差在0.25″以内。 |
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其他语种文摘
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In the research of the solar observation,the registration between high-resolution observation images and full-disk solar images is a greatly meaningful work. However,it is difficult to register with high accuracy due to the rotation,scaling and translation between them. This paper presents an image registration method combining local statistical information and control point matching: At first,between the high-resolution observation image and the full-disk solar image parameters are preliminarily estimated about the orientation, scale,and positional parameters. Then the images are pretreated based on the estimated parameters. And then the pretreatment of the field of view is divided into a large number of overlapping local regions equally. Each corresponding local area is determined by the Correlation matching on the full-disk after preprocessing. Next, the sub-pixel offset between each pair of local regions is then measured,and the coordinate positions of the feature point are determined according to the sub-pixel offset between each pair of local regions,which is used as the feature control point in the point matching. Finally,the conversion equations of the affine transformation are established according to the control point,then the least-square method is used to solve the entire field of view of the transformation parameters. The image is reiterated according to the parameters, and the transformation parameters are obtained after the final iteration to register images. By registering the highresolution observation images and the full-disk Solar SDO/HMI continuous spectrum,the deviation of fitting results is within 0.25 arc-seconds. |
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来源
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天文研究与技术
,2018,15(1):69-77 【核心库】
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关键词
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太阳图像配准
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高分辨图像
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全日面图像
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地址
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1.
昆明理工大学, 云南省计算机技术应用重点实验室, 云南, 昆明, 650500
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中国科学院云南天文台, 云南, 昆明, 650011
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1672-7673 |
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学科
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天文学 |
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基金
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国家自然科学基金
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文献收藏号
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CSCD:6153484
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参考文献 共
17
共1页
|
|
1.
Zitova B. Image registration methods:a survey.
Image and Vision Computing,2003,21(11):977-1000
|
CSCD被引
574
次
|
|
|
|
|
2.
Mikolajczyk K. Scale & affine invariant interest point detectors.
International Journal of Computer Vision,2004,60(1):63-86
|
CSCD被引
4681
次
|
|
|
|
|
3.
Lowe D G. Distinctive image features from scale-invariant keypoints.
International Journal of Computer Vision,2004,60(60):91-110
|
CSCD被引
4681
次
|
|
|
|
|
4.
Yan K. PCA-SIFT:a more distinctive representation for local image descriptors.
IEEE Computer Society Conference on Computer Vision & Pattern Recognition,2004:506-513
|
CSCD被引
2
次
|
|
|
|
|
5.
Hou J. Image matching based on representative local descriptors.
International Conference on Advances in Multimedia Modeling,2010:303-313
|
CSCD被引
1
次
|
|
|
|
|
6.
Alhwarin F. VF-SIFT:Very Fast SIFT feature matching.
Dagm Conference on Pattern Recognition,2010:222-231
|
CSCD被引
1
次
|
|
|
|
|
7.
Bay H. SURF:speeded up robust features.
Computer Vision & Image Understanding,2006,110(3):404-417
|
CSCD被引
82
次
|
|
|
|
|
8.
张开玉. 基于改进SURF的图像配准关键算法研究.
科学技术与工程,2013,13(10):2875-2879
|
CSCD被引
6
次
|
|
|
|
|
9.
Pluim J P W. Multual-information-based registration of medical images:a survey.
IEEE Transactions on Medical Imaging,2003,22(8):986-1004
|
CSCD被引
161
次
|
|
|
|
|
10.
Lewis J P. Fast normalized crossed-correlation.
Circuits Systems & Signal Processing,2001,82(2):144-156
|
CSCD被引
1
次
|
|
|
|
|
11.
Lee S U. Robust stereo matching using adaptive normalized cross-correlation.
IEEE Transactions on Pattern Analysis & Machine Intelligence,2011,33(4):807-822
|
CSCD被引
15
次
|
|
|
|
|
12.
高军. 基于模板匹配的图像配准算法.
西安交通大学学报,2007(3):307-311
|
CSCD被引
12
次
|
|
|
|
|
13.
Sarvaiya J N. Image registration using log-polar transform and phase correlation.
Tencon IEEE Region 10 Conference,2009:1-5
|
CSCD被引
1
次
|
|
|
|
|
14.
辛登松. SAR图像的改进相位相关配准方法.
计算机与数字工程,2011,39(8):126-128
|
CSCD被引
2
次
|
|
|
|
|
15.
Reddy B S. An FFT-based technique for translation,rotation,and scale-invariant image registration.
IEEE Transactions on Image Processing,1996,5(8):1266-1271
|
CSCD被引
199
次
|
|
|
|
|
16.
Guo X X. An application of Fourier-Mellin transform in image registration.
International Conference on Computer & Information Technology,2005:619-623
|
CSCD被引
1
次
|
|
|
|
|
17.
王亮. 基于Fourier-Mellin变换的气象卫星光谱图像配准.
光谱学与光谱分析,2013,33(3):855-858
|
CSCD被引
4
次
|
|
|
|
|
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