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首页> 外文期刊>IEEE Transactions on Pattern Analysis and Machine Intelligence >Groupwise Geometric and Photometric Direct Image Registration
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Groupwise Geometric and Photometric Direct Image Registration

机译：分组几何和光度直接图像配准

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摘要

Image registration consists in estimating geometric and photometric transformations that align two images as best as possible. The direct approach consists in minimizing the discrepancy in the intensity or color of the pixels. The inverse compositional algorithm has been recently proposed by Baker et al. for the direct estimation of groupwise geometric transformations. It is efficient in that it performs several computationally expensive calculations at a pre-computation phase. Photometric transformations act on the value of the pixels. They account for effects such as lighting change. Jointly estimating geometric and photometric transformations is thus important for many tasks such as image mosaicing. We propose an algorithm to jointly estimate groupwise geometric and photometric transformations while preserving the efficient pre-computation based design of the original inverse compositional algorithm. It is called the dual inverse compositional algorithm. It uses different approximations than the simultaneous inverse compositional algorithm and handles groupwise geometric and global photometric transformations. Its name stems from the fact that it uses an inverse compositional update rule for both the geometric and the photometric transformations. We demonstrate the proposed algorithm and compare it to previous ones on simulated and real data. This shows clear improvements in computational efficiency and in terms of convergence.
机译：图像配准在于估计几何和光度转换，以尽可能最佳地对齐两个图像。直接方法在于使像素的强度或颜色的差异最小化。 Baker等人最近提出了逆合成算法。用于直接估计逐组几何变换。它的高效之处在于，它在预计算阶段执行了一些计算量大的计算。光度转换作用于像素值。它们考虑了灯光变化等影响。因此，联合估计几何和光度转换对于许多任务（例如图像镶嵌）很重要。我们提出了一种算法，可以在保持有效的基于预计算的原始逆合成算法设计的基础上，共同估算分组几何和光度变换。它被称为双重逆合成算法。与同时逆组合算法相比，它使用不同的近似值，并处理成组的几何和全局光度转换。它的名称源于它对几何和光度转换都使用逆成分更新规则的事实。我们演示了所提出的算法，并将其与先前的算法进行了仿真和真实数据比较。这显示出计算效率和收敛性方面的明显改善。

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