刚性图像配准由裸骨烟花算法

Eva Tuba, I. Strumberger, Dejan Zivkovic, N. Bačanin, M. Tuba
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引用次数: 2

摘要

图像配准广泛应用于天文学、医学、机器人等领域,是一个重要的研究课题。图像配准问题是指图像的对齐问题,它可以通过线性(刚性)变换或非线性变换来定义。找到使两个图像对齐的最优变换是一个很难的优化问题。本文提出了一种新的群智能算法——裸骨烟花算法,用于解决刚性图像配准问题。该方法采用归一化互相关作为相似性度量,并在6幅基准图像上进行了测试。将所得结果与文献中其他方法进行了比较,结果表明本文提出的方法在配准精度方面有更好的提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rigid Image Registration by Bare Bones Fireworks Algorithm
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.
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