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Rigid Image Registration by Bare Bones Fireworks Algorithm

机译:通过裸骨头烟花算法进行刚性图像配准

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摘要

Image registration is widely used in various applications in astronomy, medicine, robotics, and others which makes it an important research topic. Image registration problem refers to image alignments and it can be defined by linear (rigid) or non-linear transformation. Finding the optimal transformation that aligns two images is a hard optimization problem. In this paper, we propose a recent swarm intelligence algorithm, bare bones fireworks algorithm, for solving rigid image registration problem. The proposed method uses normalized cross-correlation as similarity metrics and it was tested on six benchmark images. Obtained results were compared to other approaches from literature and it has been shown that the proposed technique is better in term of registration accuracy.
机译:图像配准广泛用于天文学,医学,机器人技术等领域,这使其成为重要的研究课题。图像配准问题是指图像对齐,可以通过线性(刚性)或非线性变换来定义。找到对齐两个图像的最佳变换是一个困难的优化问题。在本文中,我们提出了一种新的群体智能算法,即裸露的烟火算法,用于解决刚性图像配准问题。所提出的方法使用归一化互相关作为相似性度量标准,并在六个基准图像上进行了测试。将获得的结果与文献中的其他方法进行了比较,结果表明所提出的技术在套准精度方面更好。

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