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Orthogonal Spatial Binary Coding Method for High-Speed 3D Measurement

delete2024-01-01
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PRE
AI
H
Haitao Wu
Y
Yiping Cao *
Y
Yongbo Dai
Z
Zhimi Wei
DOI:10.1109/TIP.2024.3381773delete
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摘要

摘要

En 中文
Temporal phase unwrapping based on single auxiliary binary coded pattern has been proven to be effective for high-speed 3D measurement. However, in traditional spatial binary coding, it often leads to an imbalance between the number of periodic divisions and codewords. To meet this challenge, a large codewords orthogonal spatial binary coding method is proposed in this paper. By expanding spatial multiplexing from 1D to 2D orthogonal direction, it goes beyond the traditional 8 codewords to 27 codewords at three-level periodic division. In addition, a novel full-period connected domain segmentation technique based on local localization is proposed to avoid the time-consuming global iterative erosion and complex anomaly detection in traditional methods. For the decoding process, a purely spatial codewords recognition and a spatial-temporal hybrid codewords recognition methods are established to better suppress the percentage offset caused by static defocusing and dynamic motion, respectively. Obviating the need for intricate symbol recognition, the decoding process in our proposed method encompasses a straightforward analysis of statistical distribution. Building upon the development of special spatial binary coding, we have achieved a well-balance between low periodic division and large codewords for the first time. The experimental results verify the feasibility and validity of our proposed whole image processing method in both static and dynamic measurements.
Keyword:
Image coding
Three-dimensional displays
Phase measurement
Optical variables measurement
Encoding
Shape
Periodic structures
Temporal phase unwrapping
spatial binary coding
connected domain segmentation
spatial-temporal decoding
image processing

期刊

IEEE Transactions on Image Processing 封面图
IEEE Transactions on Image Processing
IF:
13.7
论文数:
1.0W
被引数:
8.4W

机构

S
sichuan university
学者数:
12.1W
论文数: 7.8W
被引数: 100
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