一种基于尺度最优的极线校正优化方法  

An Optimization Method of Epipolar Rectification Based on Optimal Scale

作　　者：刘仁峰[1] 周华兵[1] 田金文[1] 

机构地区：[1]华中科技大学图像识别与人工智能研究所多谱图像信息处理技术重点实验室,武汉430074

出　　处：《计算机工程》2013年第6期287-289,294,共4页Computer Engineering

基　　金：国家自然科学基金资助项目(61004111)

摘　　要：通过分析校正变换的不唯一性,提出一种基于尺度的极线校正方法。该方法使用尺度不变特征变换算子分析特征点在尺度空间中的分布:在某一特定的尺度下会有更多稳定的特征点,使得图像的局部特征更加突出。对无人机拍摄的照片进行实验,结果表明,该方法能较好地消除垂直误差,且在校正优化最优尺度上能得到满足需要的视差图,从而根据视差恢复三维地形图。An epipolar rectification method based on scale is proposed through analysing the polysemy of rectification transformation. Matching algorithm of Scale Invariant Feature Transform（SIFT） descriptor is used to analyze the distribution of the scale space of the feature points, and that will cause more robust interest points in some particular scales than before of not optimized, and the local features of an image are then enhanced. Experiments are performed on images taken by unmanned aerial vehicle. The results demonstrate that the proposed method has strong application value. It is able to eliminate the perpendicularity errors, and also can generate satisfied disparity map in the optimal scale. Moreover, it can also recover 3D topographic map based on the disparity map.

关 键 词：极线校正 图像匹配 DoG算子 尺度不变特征变换算子 视差图 三维恢复 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]