结合全局和局部变换模型的多焦点图像配准

I. De, B. Chanda
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引用次数: 0

摘要

图像配准是多焦点图像融合的必要先决条件,因为在融合之前,各组成图像必须相对于共同坐标系进行正确定位。本文提出了一种两步配准方法。首先,通过最大化源图像和参考图像的互信息来确定全局平移,然后将其应用于源图像。第二步,对翻译后的源图像进行逐块局部缩放。全局和局部变换构成了一种混合技术,通过迭代得到最优结果。该方法易于实现,无需人工干预,效果良好。给出了该方法在不同多聚焦图像集上得到的结果。对系统的性能进行了评价,并与两种不同的方法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Registration of multi-focus images by combining global and local transformation models
Image registration is a necessary pre-requisite for multi-focus image fusion because before fusion the constituent images must be positioned properly with respect to a common coordinate system. A two-step registration method is proposed in this work. In first step, a global translation is determined by maximizing the mutual information of the source and the reference images and then it is applied on the source image. In second step, a block-wise local scaling is applied on the translated source image. The global and local transformations constitute a hybrid technique which is iterated to obtain the optimal result. Proposed method is easy to implement, requires no manual intervention and gives good results. Results obtained by the method on different sets of multi-focus images are provided with. Performance of the system is also evaluated and is compared with two different methods.
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