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首页> 外文期刊>Optics Letters >Robust visual correspondence computation using monogenic curvature phase based mutual information
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Robust visual correspondence computation using monogenic curvature phase based mutual information

机译:使用基于单曲曲率相位的互信息进行鲁棒的视觉对应计算

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摘要

Visual correspondence has been a major research topic in the fields of image registration, 3D reconstruction, and object tracking for some decades. However, due to the radiometric variations of images, conventional approaches fail to produce robust matching results. The traditional method of intensity-based mutual information performs very good for global variations between images, however, its performance degrades in the case of local radiometric variations. Monogenic curvature phase information, as an important local feature of the image, has the advantage of being robust against brightness variation. Hence, in this Letter, we propose an approach to compute the visual correspondence by coupling the advantages of mutual information and monogenic curvature phase. Experimental results demonstrate that the proposed approach can work robustly under radiometric variations.
机译:几十年来,视觉对应一直是图像配准,3D重建和对象跟踪领域的主要研究主题。但是,由于图像的辐射度变化,常规方法无法产生可靠的匹配结果。基于强度的互信息的传统方法对于图像之间的全局变化非常有效,但是,在局部辐射度变化的情况下,其性能会下降。单调曲率相位信息作为图像的重要局部特征,具有对亮度变化具有鲁棒性的优势。因此,在这封信中,我们提出了一种通过耦合互信息和单基因曲率相位的优势来计算视觉对应关系的方法。实验结果表明,所提出的方法可以在辐射变化下可靠地工作。

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