遥感图像拼接系统

提出和实现了一种图像配准方法，利用OpenCV库开发了一个低空遥感图像拼接系统. 将SIFT作为图像拼接特征向量，实现了图像局部尺度空间中极值点的计算和SIFT特征点的提取. 使用特征向量的欧氏距离实现特征点的粗匹配，结合随机抽样一致RANSAC算法对匹配点进行优化，并精确估算出投影变换矩阵，实现两幅图像的拼接. 最后实现对重合区域的图像融合. 实验结果表明本文方法较好的解决了遥感图像中常出现的图像的平移、缩放、旋转等变换下的配准问题，达到较好的拼接效果.

Remote Sensing Image Mosaicking System

An image registration method is proposed. A low altitude remote sensing image mosaicking system is development by using OpenCV library. We use the scale invariant feature transform (SIFT) points as the feature vector for image mosaicking. Local extreme points in scale space of the image are calculated. The SIFT feature points are extracted. The feature points' rough matching is performed based on the vectors Euclidean distance. We use random sample consensus (RANSAC) algorithm to optimize feature points matching. The image transform matrix is accurately estimated. Image fusion of overlap region is realized. The experimental results show that this method can solve the image registration problems which often occur in remote sensing images such as translation, scaling and rotation transform. Good mosaic results are achieved using the proposed method.