控制点/控制点对最优能量解析的图像配准

 针对遥感图像配准中匹配同名点少、配准精度低等问题，提出了一种基于控制点/控制点对最优能量解析的图像配准方法。在控制点提取中，通过多尺度曲波变换，实现不同尺度下图像质量的灰关联分析和噪声抑制，并根据灰关联能量值，自动调整尺度不变特征变换配准参数，提高匹配同名点数量；为保证控制点选择的均匀性和准确性，创建了控制点对能量模型，采用马尔科夫蒙特卡洛优化算法实现分布、匹配能量最优的控制点筛选，提高了图像配准精度。实验结果表明，本方法对遥感图像匹配同名点少、控制点分布不均匀、图像配准精度低等问题有很大改善，具有较高的应用价值。

An Algorithm of Image Registration Based on Optimized Energy Analysis of Control Points/Correspondences

An crucial problem of feature-based image registration is how to get enough and accurate correspondent features to increase the accuracy of registration. An automatic remote sensing image registration method based on optimized energy analysis of control points/correspondences is presented to improve the traditional algorithm.First,a multi-scale segment method based on digital curvelet transform is used to evaluate the quality of sensed images, then parameters of SIFT feature-matching algorithm is automatically adjusted according to multi-scale grey relation energy of image quality  to increase the feature matching points and the correspondences.At last, to make sure the accuracy of geometrical transform parameters, a method of selecting optimized correspondences based on the distribution and matching energy model of control points is developed. Experimental results demonstrate that the proposed method works well in increasing control points and the correspondences of low quality remote sensing images.