An Automatic PC-SIFT-Based Registration of Multi-source Images from Optical Satellites
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摘要: 针对多源光学卫星影像几何校正过程中同名点匹配率低、配准过程自动化差等问题,本文采用相位一致性代替原始尺度不变特征变换(scale invitation feature transform,SIFT)算法中的像素灰度值梯度对主方向和特征向量进行描述,提升特征描述的正确率;以频率域下相位分析结果为约束条件对匹配结果进行优化,抑制错误匹配同名点;同时,提出了一种基于随机采样一致性(RANSAC)的自适应选择策略,提高参数估计阶段的自动化水平;最后,实现多源光学卫星影像间的配准。多组数据实验结果表明了该方法在辐射非线性畸变多源光学卫星影像间配准中的有效性和适用性。Abstract: In order to solve the problems like low corresponding points matching rate，poor automatic registration process of multi-source optical satellite imagery in geometric correction. We described the principal direction and feature vector by phase congruency instead of the original SIFT algorithm gray level of pixel gradient to ascending accuracy of feature description.Optimizing the matching results with constraints of phase analysis results under the frequency domain，inhibition of error matching points;meanwhile，put forward a adaptive selection strategy to improve parameter estimation phase level of automation RANSAC-based;the ultimate realization of automatic image registration between the multi-source optical satellite imagery. The experimental results of multiple sets of data show that the validity and applicability of this schema to image registration between multi-source optical satellite image with radiation and nonlinear distortion.
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Keywords:
- multi-source images /
- image registration /
- PC-SIFT /
- phase equalization /
- phase correlation
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