Phase error analysis and reduction in phase measuring deflectometry

Wu, Yue; Yue, Huimin; Yi, Jingya; Li, Mingyang; Liu, Yong

doi:10.1117/1.oe.54.6.064103

Cited by 23 publications

(5 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Especially, the classical PMD will amplify the phase errors because the shape data are reconstructed by slope integration and the captured fringe pattern is defocused. Phase error sources mainly arise from the random noise, nonlinear response function, the non-telecentric imaging of the CCD camera, and the nonlinear response function of the LCD screen [ 114 ].…”

Section: Influential Factors On Measurement Resultsmentioning

confidence: 99%

Three-Dimensional Shape Measurements of Specular Objects Using Phase-Measuring Deflectometry

Zhang

Wang

Huang

et al. 2017

Sensors

View full text Add to dashboard Cite

The fast development in the fields of integrated circuits, photovoltaics, the automobile industry, advanced manufacturing, and astronomy have led to the importance and necessity of quickly and accurately obtaining three-dimensional (3D) shape data of specular surfaces for quality control and function evaluation. Owing to the advantages of a large dynamic range, non-contact operation, full-field and fast acquisition, high accuracy, and automatic data processing, phase-measuring deflectometry (PMD, also called fringe reflection profilometry) has been widely studied and applied in many fields. Phase information coded in the reflected fringe patterns relates to the local slope and height of the measured specular objects. The 3D shape is obtained by integrating the local gradient data or directly calculating the depth data from the phase information. We present a review of the relevant techniques regarding classical PMD. The improved PMD technique is then used to measure specular objects having discontinuous and/or isolated surfaces. Some influential factors on the measured results are presented. The challenges and future research directions are discussed to further advance PMD techniques. Finally, the application fields of PMD are briefly introduced.

show abstract

Section: Influential Factors On Measurement Resultsmentioning

confidence: 99%

Three-Dimensional Shape Measurements of Specular Objects Using Phase-Measuring Deflectometry

Zhang

Wang

Huang

et al. 2017

Sensors

View full text Add to dashboard Cite

show abstract

“…Each fringe image from the LCD screen (LILLIPUT, 9.7 , 1024 × 768 pixels, 192 µm pixel size, Lenovo, Beijing, China) was captured by the CCD camera (Blackfly 2.3 MP Mono GigE PoE, 1920 × 1200 pixels, 5 µm pixel spacing, Point Grey, Vancouver, BC, Canada) four times repeatedly, and the surface shape of the mirror under test was reconstructed based on the algorithm [36,37]. During experiment, the acquisition noise could be reduced by averaging the captured images of the repeated measurements [38] and filtering out with an appropriate filtering window in the Fourier transform process [39].…”

Section: Methodsmentioning

confidence: 99%

“…camera (Blackfly 2.3 MP Mono GigE PoE, 1920 × 1200 pixels, 5 μm pixel spacing, Point Grey, Vancouver, Canada) four times repeatedly, and the surface shape of the mirror under test was reconstructed based on the algorithm [36,37]. During experiment, the acquisition noise could be reduced by averaging the captured images of the repeated measurements [38] and filtering out with an appropriate filtering window in the Fourier transform process [39]. In the experiment, the PMD method, a widely verified surface shape measurement method, was set as the comparison to verify the validity and flexibility of the proposed COPMD method.…”

Section: Methodsmentioning

confidence: 99%

Surface Shape Distortion Online Measurement Method for Compact Laser Cavities Based on Phase Measuring Deflectometry

et al. 2022

View full text Add to dashboard Cite

Conventional phase measuring deflectometry (PMD) takes up a large measurement space and is not suitable for compact online measurement, as the liquid crystal display (LCD) has to be placed in parallel with the mirror under test. In this paper, a compact online phase measuring deflectometry (COPMD) with the LCD screen set perpendicular to the mirror under test is presented for surface shape distortion real-time measurement. The configuration of the COPMD in an enclosed laser cavity is proposed, and the principle of the method is theoretically derived by using the vector-form reflection law. Based on the analysis model, the fringe modulation regulation of the LCD is revealed, and the measurement errors caused by misalignments of the components are illustrated. The validity and flexibility of the COPMD method are verified in the experiment by using a single-actuator deformable mirror as the mirror under test and the PMD method as the comparison. The proposed COPMD method remarkably expands the application range of the conventional PMD method, as it could make efficient use of compact space and is applicable for real-time measurement in enclosed laser facilities and assembled laser systems.

show abstract

“…Liu et al [13] proposed a phase averaging method with the temporal phase unwrapping algorithm to compensate for the random errors in phase retrieval. Wu et al [14] analyzed the random noise of the defocused fringe patterns and CCD camera in deflectometry and proposed a phase error compensation method. However, all the above methods can only compensate for the phase errors of each factor.…”

Section: Introductionmentioning

confidence: 99%

Error compensation for phase retrieval in deflectometry based on deep learning

Guan¹,

Li²,

Yang³

et al. 2022

Meas. Sci. Technol.

View full text Add to dashboard Cite

Fringe patterns are widely applied in optical metrology, and phase retrieval is an essential process for decoding surface information. In the field of phase measurement deflectometry (PMD), phase errors in the phase retrieval process have more significant effects for PMD is a slope-based technique and is more sensitive to low-frequency errors. The main factors affecting the quality of the captured fringe images include the gamma effect of the liquid crystal display (LCD) screen, the random noise from the charge-coupled device (CCD) camera, and the random noise amplified by the defocused fringe patterns. Conventional methods compensated the phase errors of these factors separately with different methods, which are inefficient in handling the errors from coupling factors effectively. In this paper, we propose a deep neural network to compensate for the phase errors resulting from the combination of the factors. Experimental results demonstrate that the proposed network can significantly suppress the errors in phase retrieval with non-ideal fringe images. The phase errors can be reduced in both simulated and authentic data for deflectometry, which verifies the robustness and effectiveness of the proposed method.

show abstract

Phase error analysis and reduction in phase measuring deflectometry

Cited by 23 publications

References 24 publications

Three-Dimensional Shape Measurements of Specular Objects Using Phase-Measuring Deflectometry

Three-Dimensional Shape Measurements of Specular Objects Using Phase-Measuring Deflectometry

Surface Shape Distortion Online Measurement Method for Compact Laser Cavities Based on Phase Measuring Deflectometry

Error compensation for phase retrieval in deflectometry based on deep learning

Contact Info

Product

Resources

About