基于结构光和ct的背部点云配准算法

Shen Chunmei, 沈春梅; Liu Fan, 刘凡; Zhu Jiale, 朱佳乐

doi:10.3788/lop231456

激光与光电子学进展

2023

DOI: 10.3788/lop231456

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基于结构光和ct的背部点云配准算法

沈春梅 Shen Chunmei,

刘凡 Liu Fan,

朱佳乐 Zhu Jiale

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2024

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Cited by 1 publication

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基于无监督学习的风洞压敏漆图像配准算法

Liu Kang,

Sun Xiongwei,

Shi Hailiang

et al. 2024

光学学报

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structure and a coarsetofine registration strategy to address the issue of large offsets and nonrigid deformations in wind tunnel environments. Additionally, it incorporates a novel loss function paradigm based on image similarity, which enhances image registration in featuresparse scenarios. Comparing with typical alignment methods such as MI -Spline and Voxelmorph on two sets of PSP images, the experimental results prove that our method achieves a far better registration performance than the existing methods in visual evaluation and RMSE, NCC, and TRE metrics, under the premise of ensuring the performance of the algorithm. This method provides a reliable solution to the PSP image registration problem .

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基于无监督学习的风洞压敏漆图像配准算法

Liu Kang,

Sun Xiongwei,

Shi Hailiang

et al. 2024

光学学报

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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基于结构光和ct的背部点云配准算法

Cited by 1 publication

References 13 publications

基于无监督学习的风洞压敏漆图像配准算法

基于无监督学习的风洞压敏漆图像配准算法

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