Phase shifting profilometry (PSP) has been commonly used in three-dimensional shape measurement with the advantages of high-precision and non-contact. However, it is still challenging to measure high-reflective surface because image saturation will lead to absolute phase errors and reconstruction errors. In this paper, a dual-view multi-intensity projection method was proposed. Compared with the single-view method, the proposed method can reconstruct more points at each projection intensity especially for pixels around the specular angle and reduce the number of projections to reduce the time consumption. First, we established the dual-view structured light system consisting of two monocular systems that share the same projector. Subsequently, a dual-view saturated pixel judging method was proposed that enables the reconstruction results under two views to be combined without duplicate points. The multi-intensity projection method was adopted by reducing the input projection intensity step by step and reconstructing the remaining pixels around the specular angle. Finally, the reconstruction result can be obtained by stitching point clouds at each projection intensity. Experiments verified that the proposed method could improve the integrity of reconstructed point clouds and measurement efficiency.

The image deconvolution technique can recover potential sharp images from blurred images affected by aberrations. Obtaining the point spread function (PSF) of the imaging system accurately is a prerequisite for robust deconvolution. In this paper, a computational imaging method based on wavefront coding is proposed to reconstruct the wavefront aberration of a photographic system. Firstly, a group of images affected by local aberration is obtained by applying wavefront coding on the optical system’s spectral plane. Then, the PSF is recovered accurately by pupil function synthesis, and finally, the aberration-affected images are recovered by image deconvolution. After aberration correction, the image’s coefficient of variation and mean relative deviation are improved by 60% and 30%, respectively, and the image can reach the limit of resolution of the sensor, as proved by the resolution test board. Meanwhile, the method’s robust anti-noise capability is confirmed through simulation experiments. Through the conversion of the complexity of optical design to a post-processing algorithm, this method offers an economical and efficient strategy for obtaining high-resolution and high-quality images using a simple large-field lens.

No abstract

No abstract

No abstract