基于梯度互信息和改进粒子群算法的图像配准新算法

Laiming Xu, Jun Liu
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引用次数: 1

摘要

由于待配准的两幅图像之间存在较大的曝光程度或噪声污染等差异,常用的基于原始灰度互信息的配准算法容易陷入局部极值,配准精度不理想。针对这种情况,本文提出了一种基于梯度互信息和改进粒子群算法的图像配准新方法。实验结果表明,与传统配准算法相比,该方法在保证配准效率的同时,显著提高了配准精度。
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A New Image Registration Algorithm Based on Mutual Information of Gradient and Improved PSO
Because of the larger difference between the two images to be registered, such as exposure degree or noise pollution, the common registration algorithm that based on mutual information of original gray, is easy to fall into local extreme value, thus the registration accuracy is unsatisfactory. In this case, a new method of image registration algorithm that based on mutual information of gradient and improved PSO is developed in this paper. The experiment result shows the method works well, and comparing with traditional registration algorithm, the registration accuracy is significantly improved while the efficiency is also guaranteed.
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