Abstract

When the measured object is fast moving online, the captured deformed pattern may appear as motion blur, and some phase information will be lost. Therefore, the frame rate has to be improved by adjusting the image acquisition mode of the camera to adapt to a fast-moving object, but the resolution of the captured deformed pattern will be sacrificed. So a super-resolution image reconstruction method based on maximum a posteriori (MAP) estimation is adopted to obtain high-resolution deformed patterns, and in this way, the reconstructed high-resolution deformed patterns also have a good effect on noise suppression. Finally, all the reconstructed high-resolution equivalent phase shifting deformed patterns are used for online three-dimensional (3D) reconstruction. Experimental results prove the effectiveness of the proposed method. The proposed method has a good application prospect in high-precision and fast online 3D measurement.

Highlights

  • With the development of optics, computer and information technology, 3D measurement technology plays an important role in reverse engineering, industrial 3D testing, medical diagnosis, cultural relic protection and so on [1,2,3]

  • Common 3D measurement based on phase measurement profilometry (PMP) requires the fixed position of the object, but the object is moving in online 3D measurement, which will cause the object coordinates in the captured multiple frames of deformed patterns not to correspond, and lead to the error in the PMP phase demodulation

  • In order to obtain high-resolution deformed patterns and improve the measurement precision, we proposed an online phase measurement profilometry method based on super-resolution image reconstruction [12,13], which combines high-resolution image from multiple frames of low-resolution images with sub-pixel [14] shifts among them

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Summary

Introduction

With the development of optics, computer and information technology, 3D measurement technology plays an important role in reverse engineering, industrial 3D testing, medical diagnosis, cultural relic protection and so on [1,2,3]. In order to obtain high-resolution deformed patterns and improve the measurement precision, we proposed an online phase measurement profilometry method based on super-resolution image reconstruction [12,13], which combines high-resolution image from multiple frames of low-resolution images with sub-pixel [14] shifts among them. This paper adopts a super-resolution reconstruction method based on the maximum a posteriori (MAP) [15,16], using Gauss and Markov–Gibbs [17,18] random field models to construct posteriori probability of the high-resolution deformed pattern, the optimal estimation of high-resolution deformed pattern is obtained by minimizing the objective function. The potential function ρα(dic) is chosen according to the penalty degree of removing features of image, such as the Huber equation and linear equation

Iterative Solution
Experiment and Analysis
Conclusions
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