A High-Accuracy and Reliable End-to-End Phase Calculation Network and Its Demonstration in High Dynamic Range 3D Reconstruction

Abstract In fringe projection profilometry 3D measurement systems, the measurement of surfaces with high variability in reflectivity poses a challenge due to the limited dynamic range of cameras. The main solution involves using multiple exposures to modulate fringe intensity; however, it is inefficient. In this study, we introduce an attention-guided end-to-end phase calculation network to accelerate the multi-exposure structured light process for high dynamic range (HDR) measurements. We use attention modules to guide feature selection, enhancing relevant features and suppressing irrelevant features. Using the 12-step phase-shifting profilometry (PSP) as ground truth, our method accurately extracts the sine and cosine components of the fundamental frequency from a single pattern to retrieve the absolute phases. Tested on our metallic dataset requiring HDR imaging, our method achieves an absolute phase error of 0.084, close to that of the six-step PSP method (0.069), while using only 16.7% of the time. On the ceramic dataset, our method achieves 0.021 phase error, close to that of the four-step PSP (0.012). In quantitative measurements, our method achieves an accuracy of approximately 40 $$\upmu\text{m}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>μ</mml:mi> <mml:mtext>m</mml:mtext> </mml:mrow> </mml:math> on standard spheres and plates. Overall, our method preserves the accuracy of multi-exposure PSP methods while significantly accelerating the 3D reconstruction process.