Patent ID: 11906286
Assignee: NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 4:
5. According to claim 1, a deep learning-based temporal phase unwrapping method for fringe projection profilometry is characterized by step three wherein the distribution range of the absolute phase map with unit frequency is [0,2π], so the wrapped phase map with unit frequency is an absolute phase map; by using a multi-frequency temporal phase unwrapping (MF-TPU) algorithm, an absolute phase map with a frequency of 8 is unwrapped with the aid of the absolute phase map with unit frequency; an absolute phase map with a frequency of 32 is wrapped with the aid of the absolute phase map with a frequency of 8; an absolute phase map with a frequency of 64 is unwrapped with the aid of the absolute phase map with a frequency of 32; the absolute phase map is calculated by the following formula:, k
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            ), where fh is a frequency of high-frequency fringe images; f1 is a frequency of low-frequency fringe images; Φh(x, y) is a wrapped phase map of high-frequency fringe images; kh(x, y) is a fringe order map of high-frequency fringe images; Φh(x, y) is the absolute phase map of high-frequency fringe images; Φl(x,y) is the absolute phase map of low-frequency fringe images; round( )is the rounding operation.