基于椭圆对称方向矩的可见光与红外图像配准算法

针对图像匹配制导中异源图像匹配难度大的问题,提出一种基于椭圆对称方向矩的可见光与红外图像配准算法.基于最稳定极值区域提取异源图像中具有尺度和仿射不变特性的椭圆区域,利用聚类分割方法从中自动选取具有异源不变性的同质区域特征,用椭圆对称方向矩描述区域特征边界各方向上的相似程度,通过互相关性指标进行特征匹配,获取匹配特征对,利用匹配矫正策略减少误匹配.实验结果表明:较传统算法,进一步提高了可见光与红外图像关联特征的匹配效率,正确率超过了95%,计算时间缩短了近一半.基本满足图像匹配制导对匹配算法实时性好、匹配正确率高、抗干扰能力强等要求.

Registration of visual-infrared images based on ellipse symmetrical orientation moment

For addressing the difficulties in the registration of multimodal images in image-matching guidance, a new visual-infrared image-registration approach based on ellipse symmetrical orientation moment was proposed.Scale and affine invariant maximally stable external regions features were extracted to fit the ellipse area in multimodal images.Cluster segmentation was used to automatically select the homogeneous regional features that were invariant between multimodal images.The ellipse symmetrical orientation moment was used to describe the similarity of the regional feature edges in different orientations.Based on the mutual-correlation criterion, the matching feature pairs of the visual and infrared images were obtained.The matching correction strategy was used to reduce the probability of mismatching.The experiments demonstrate that the matching success rate of the corresponding feature pairs between the visual and infrared image is improved to more than 95%, and the computation time is reduced by nearly half as compared with that required by traditional algorithms.The proposed algorithm can meet the image-registration algorithm requirements of a higher success rate and rapid speed as well as strong anti-jamming and stabilization for image-matching guidance.