一种基于线点结合特征的多源图像配准算法

Yi Yang, Yuanli Liu
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摘要

针对含有典型线目标的图像,提出了一种基于线点结合特征的多源图像配准算法。首先,利用视觉显著性和线段检测方法提取图像控制线特征进行粗配准;视觉显著性是人类的视觉特征。LSD具有旋转不变性、光照变化不敏感性和抗噪声能力。其次,利用基于多分辨率分析的尺度不变特征变换(SIFT)提取具有尺度和旋转不变特征的点特征;然后利用特征点实现精细配准。最后对仿真结果进行了分析,从主观效果和客观评价指标两方面验证了算法的有效性。
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A multi-source image registration algorithm based on combined line and point features
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.
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