Registration of visual-infrared images based on ellipse symmetrical orientation moment
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摘要: 針對圖像匹配制導中異源圖像匹配難度大的問題,提出一種基于橢圓對稱方向矩的可見光與紅外圖像配準算法.基于最穩定極值區域提取異源圖像中具有尺度和仿射不變特性的橢圓區域,利用聚類分割方法從中自動選取具有異源不變性的同質區域特征,用橢圓對稱方向矩描述區域特征邊界各方向上的相似程度,通過互相關性指標進行特征匹配,獲取匹配特征對,利用匹配矯正策略減少誤匹配.實驗結果表明:較傳統算法,進一步提高了可見光與紅外圖像關聯特征的匹配效率,正確率超過了95%,計算時間縮短了近一半.基本滿足圖像匹配制導對匹配算法實時性好、匹配正確率高、抗干擾能力強等要求.Abstract: For addressing the difficulties in the registration of multimodal images in image-matching guidance, a new visualinfrared 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.
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參考文獻
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