中文摘要：

对于具有病变的眼底图像,血管结构不够清晰,采用基于血管分割和血管分支点、交叉点等眼底图像配准方法具有一定的局限性。为了解决这个问题,提出一种基于不变特征的眼底图像配准方法。提取眼底图像的尺度不变特征（SIFT）作为特征点,提出双边＂或＂的Best-Bin-First（BBF）算法进行特征点匹配,并根据特征点具有旋转不变性的方向特征和空间斜率及空间距离等几何特性的一致性检测去除误匹配,精化匹配特征,利用得到的匹配特征进行M估计得到眼底图像的变换关系。通过对不同程度病变的眼底图像数据进行配准实验,观察配准结果,对比匹配特征的正确匹配数量和分析衡量配准精度的均方根误差。结果表明,该方法实现了良好的细节对齐,保留了足够的正确匹配对,对实验的病变眼底图像配准成功后的均方根误差均小于1,且浮动于0.5左右,验证了方法的精确性和有效性。

英文摘要：

It is quite difficult to register two pathological retinal images owing to the vague vascular network existence.Moreover,general registration methods based on detecting the crossovers,bifurcations of the vascular network have certain drawbacks.In this paper,a retinal image registration method based on invariant feature is proposed.We recognize the extracted invariant feature as feature point and proposed bilateral ＂or＂ the best-bin-first（BBF） algorithm to match feature point.In addition,we use the feature points′ orientations and the geometrical property to exclude the error matches and utilize the refined matching features pair to estimate transformation by M-estimation for retinal image.The registration results are observed,the correct matches are compared and the root of mean square error is analyzed by experiments of registering various degrees of pathological retinal images.Results show that the proposed method achieves fine detail alignment,reserves sufficient correct matches and the root of mean square error is less than 1 and around 0.5 for pathological retinal images of registration success.Experimental results validate the accuracy and effectiveness of the proposed method.