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A multi-source image registration algorithm based on combined line and point features

机译:一种基于组合线和点特征的多源图像配准算法

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A multi-source image registration algorithm based on combined line and point features is proposed for images containing typical line objects. Firstly, the image control line features are extracted for coarse registration by the use of visual saliency and Line Segment Detection (LSD). Visual saliency represents human visual characteristics. LSD has attributes including rotation invariance, illumination changes insensitivity and noise resistant ability. Secondly, Scale Invariant Feature Transform (SIFT) based on multi-resolution analysis is used to extract the point features with scale and rotation invariant characteristics. Then the feature points are used to realize the fine registration. Finally, the simulation results are analyzed, and the validity of the algorithm is verified from subjective effect and objective evaluation indices.
机译:提出了一种基于组合线和点特征的多源图像配准算法,用于包含典型线对象的图像。首先,通过使用视力显着性和线段检测(LSD)来提取图像控制线特征以粗略配准。视觉显着表示人类视觉特征。 LSD具有包括旋转不变性的属性,照明改变不敏感性和抗噪能力。其次,基于多分辨率分析的级别不变特征变换(SIFT)用于提取具有比例和旋转不变特性的点特征。然后,要素要点用于实现精细的注册。最后,分析了仿真结果,并从主观效果和客观评估指标验证了算法的有效性。

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