Corresponding Feature Extraction Algorithm between Infrared and Visible Images Using MSER
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摘要: 关联特征提取是红外与可见光图像配准、融合和变化检测等应用中的关键步骤。针对同一场景红外与可见光图像间关联特征难以正确提取的问题,基于最稳定极值区域(MSER)算法,提出了一个仿射不变的关联特征提取方法。该方法主要包括3个步骤:(1)提取红外与可见光图像中的最稳定极值区域;(2)对特征区域进行椭圆拟合;(3)规则化处理,消除形变干扰,输出便于描述和匹配的一致性特征。实验结果证明了该算法在红外与可见光图像关联特征提取中的有效性。Abstract: Corresponding feature extraction is a key stage in infrared-visible image registration, fusion, and change detection, etc.. Considering the difficulties in correct extraction of related features between infrared and visible images of the same scene, an affine invariant method is proposed based on Maximally Stable Extremal Regions (MSER) algorithm. The approach includes three steps: (1) to extract the maximally stable extremal regions in infrared and visible images; (2) to fit the feature regions to ellipses; and (3) to regularize the elliptical regions to eliminate the deformation disturbance. The final output is coherent features which are convenient for description and matching. Experimental results show appealing effectiveness of the proposed method in corresponding feature extraction between infrared and visible images.
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