Suppr超能文献

一种基于像素迁移的多传感器图像配准优化算法。

A refined algorithm for multisensor image registration based on pixel migration.

作者信息

Yao Jianchao, Goh Kian Liong

机构信息

Center for Automation Research, University of Maryland, College Park, USA.

出版信息

IEEE Trans Image Process. 2006 Jul;15(7):1839-47. doi: 10.1109/tip.2006.873451.

Abstract

Multimodality image registration via pixel migration is a powerful approach. However, it suffers from a serious problem--the global maximum on the sum of squared gradient magnitude (SSG) surface does not correspond to the correct solution of registration. To solve the problem, we partition the search space into feasible and infeasible regions. The genetic algorithm (global optimizer) is used to obtain a good initial estimate of registration parameters and followed by a fast refining with Powell's approach (local optimizer). The experimental results demonstrate that the use of this modified pixel migration algorithm on multisensor image registration is very effective.

摘要

通过像素迁移的多模态图像配准是一种强大的方法。然而,它存在一个严重的问题——平方梯度幅值总和(SSG)表面上的全局最大值并不对应于配准的正确解。为了解决这个问题,我们将搜索空间划分为可行区域和不可行区域。遗传算法(全局优化器)用于获得配准参数的良好初始估计,然后使用鲍威尔方法(局部优化器)进行快速细化。实验结果表明,这种改进的像素迁移算法在多传感器图像配准中非常有效。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验