用于图像配准的累积水平线匹配

S. Bouchafa, B. Zavidovique
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引用次数: 3

摘要

提出了一种新的用于图像变换估计的水平线配准技术。这种方法对对比度变化具有鲁棒性,不需要对图像之间的未知转换进行任何估计,并且可以处理通常导致配对模糊的非常具有挑战性的情况,例如图像中的重复模式。注册本身是通过基于多阶段原语选举过程的有效水平行累积匹配来执行的。每个阶段都提供了下一阶段要细化的转换的粗略估计。虽然我们处理相似变换(旋转、缩放和平移),但我们的方法可以很容易地适应更一般的变换。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cumulative level-line matching for image registration
A new level-line registration technique is proposed for image transform estimation. This approach is robust towards contrast changes, does not require any estimate of the unknown transformation between images and tackles very challenging situations that usually lead to pairing ambiguities, such as repetitive patterns in the images. The registration itself is performed through an efficient level-line cumulative matching based on a multistage primitive election procedure. Each stage provides a coarse estimate of the transformation that the next stage gets to refine. Although we deal with similarity transforms (rotation, scale and translation), our approach can be easily adapted to more general transformations.
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