Fringe pattern inpainting based on dual-exposure fused fringe guiding CNN denoiser prior

• Autorzy: Peng Guangze , Chen Wenjing

Identyfikatory

DOI

10.37190/oa220203

• Języki publikacji: EN

Abstrakty

EN

The intensity of some pixels of the captured fringe will be saturated when fringe projection profilometry is used to measure objects with high reflectivity, which will significantly affect the reconstruction of the measured object. In this paper, we propose a fringe pattern inpainting method based on the convolutional neural network (CNN) denoiser prior guided by additional information from a fringe captured in short exposure time. First, a binary mask obtained by Otsu algorithm from the modulation information of the short exposure fringe is used to detect the high-saturation region in the normal exposure fringe. Then, the corrected gray-scales of the region of the short exposure fringe selected by the mask are inserted in the saturated region of the normal fringe to form an initial fringe for iteration. At last, fringe pattern inpainting is achieved by using a CNN denoiser prior. The correct phase can be reconstructed from the inpainted fringes. The computer simulation and experiments verify the effectiveness of the proposed method.

Słowa kluczowe

EN

fringe projection profilometry; phase calculation; convolutional neural network; denoiser prior

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Optica Applicata
• Rocznik: 2022
• Tom: Vol. 52, nr 2
• Strony: 179--193
• Opis fizyczny: Bibliogr. 23 poz., rys., tab.

Twórcy

autor

Peng Guangze

• Department of Optic-Electronic, College of Electronics and Information Engineering, Sichuan University, Chengdu, Sichuan 610065, China

autor

Chen Wenjing

• Department of Optic-Electronic, College of Electronics and Information Engineering, Sichuan University, Chengdu, Sichuan 610065, China

Bibliografia

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