基于图像特征提取的红外影像动态配准方法研究

Research on Dynamic Registration Method of Infrared Image Based on Image Feature Extraction

为了提高红外影像动态配准的配准概率,提出基于图像特征提取的红外影像动态配准方法。采用尺度不变特征变换算法提取红外影像关键点的方向、坐标及其尺度特征,结合特征点的邻域梯度信息生成SIFT特征向量,并确定SIFT向量的特征区域,引入加权因子去除非稳定关键点,得出相位一致性特征(稳定关键点);根据稳定关键点之间的最佳旋转角度获取精准匹配子集,修正匹配点配准关系,完成红外影像动态配准。测试结果表明,该方法获取的红外图像像素点灰度值均方根差均低于0.45,DICE系数均高于0.93,在发生旋转或者灰度信息变化时,配准概率均在93%以上,可较好地完成红外影像动态配准。

In order to improve the registration probability of infrared image dynamic registration,an infrared image dynamic registration method based on image feature extraction is proposed.The scale invariant feature transformation algorithm is used to extract the direction,coordinates and scale features of key points in infrared image.Combined with the neighborhood gradient information of feature points,the SIFT feature vector is generated,the feature region of sift vector is determined,and the weighting factor is introduced to remove unstable key points and obtain the phase consistency feature(stable key points).According to the optimal rotation angle between the stable key points,the accurate matching subset is obtained,the matching point registration relationship is modified,and the dynamic infrared image registration is completed.The test results show that the root mean square difference of gray values of infrared image pixels obtained by this method is lower than 0.45,and the DICE coefficients are all higher than 0.93.When rotation or gray information changes,the registration probability is more than 93%,which can better complete the dynamic registration of infrared image.