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Absolute Phase Retrieval With a Single Large-Range Gray-Level Coding Pattern

delete2024-01-01
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PRE
AI
Y
Yingchun Wu *
N
Na Yang
L
Li Liu
Z
Zihao Wang
A
Anhong Wang
DOI:10.1109/TIM.2024.3378259delete
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摘要

摘要

En 中文
Phase retrieval is a very important procedure in fringe projection-based 3-D shape measurement. Gray-level coding has become the focus of investigation due to its excellent phase order calculation ability. However, most of these methods have to trade off the quantity of additional projected fringe patterns against the precision of phase orders computation. For this reason, an absolute phase retrieval method based on a single large-range gray-level coding pattern is proposed. By adopting two different arctangent functions that have different principal intervals, two truncated phases can be calculated. Based on the signs of the two truncated phases, the fringe period is further subdivided into four sub-regions. Finally, different codewords are assigned to the corresponding sub-regions to form the coding pattern. Compared with the existing algorithms, a larger range of phase order can be represented by the proposed single coding pattern, and the coding pattern only involves two gray levels (black and white), which is helpful in suppressing the quantization error. Additionally, to further improve the accuracy of absolute phase calculation, an error codes correction method based on nearest-neighborhood prediction is proposed. Through measurements on different objects (involving simple, complex, isolated, and standard objects), the results of the experiment show that the method proposed in this article can obtain more accurate reconstruction results while using fewer coding patterns than the other methods.
Keyword:
Encoding
Quantization (signal)
Phase measurement
Reflective binary codes
Codes
Three-dimensional displays
Shape measurement
3-D measurement
absolute phase retrieval
fringe projection profilometry (FPP)
gray-level coding
wrong codes correction

期刊

IEEE Transactions on Instrumentation and Measurement 封面图
IEEE Transactions on Instrumentation and Measurement
IF:
5.9
论文数:
1.9W
被引数:
5.8W

机构

T
taiyuan university of science & technology
学者数:
3.5K
论文数: 2.3K
被引数: 3
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