In the long-range imaging system, one of the main factors limiting the imaging resolution is the size of the imaging lens aperture, which determines the diffraction limit of the optical system. In the actual Fourier ptychography imaging system, the system errors such as the aberrations of imaging devices and the noise of the detector will be introduced in the actual imaging, which is also one of the important factors to reduce the quality of the reconstructed image. In order to improve the reconstruction accuracy of the Fourier ptychography imaging algorithm, this paper mainly discusses some optimization algorithms in the process of the Fourier ptychography imaging algorithm to improve the high-resolution details of the restored image. The adaptive step size based optimization algorithm is used to update the spectrum and aperture function of the current sub-aperture to obtain the high-resolution spectrum information of the measured target. The optimal spectrum overlap rate is discussed to reduce the number of image acquisition and calculation cost as much as possible. In the reconstruction process, the simulated annealing algorithm is used to correct the positioning error of the sub-aperture, and the optimization algorithm is used to update the sub-aperture, which greatly improves the accuracy of the reconstruction results and achieves the theoretical imaging resolution.
In the long-distance imaging system, one of the main factors limiting the imaging resolution is the size of the imaging lens aperture, which determines the diffraction limit of the optical system. Therefore, we propose a non-interference synthetic aperture super-resolution imaging reconstruction and optimization method. The camera array is used to collect a series of low-resolution sub-aperture images. Combined with Fourier ptychography imaging algorithm, the spectrum and aperture function of the current sub-aperture diameter is updated by using the optimization algorithm based on adaptive step size. to obtain the high-resolution spectrum information of the target to be measured. Meanwhile, the high-resolution spectrum information of the target is obtained. In the reconstruction process, the simulated annealing algorithm is introduced to correct the positioning error of the sub-aperture, and the optimization algorithm is used to update the sub-aperture, which greatly improves the accuracy of the reconstruction results and achieves the theoretical imaging resolution. Moreover, it also has excellent imaging results for complex objects, which verifies the feasibility of the algorithm.
KEYWORDS: Mirrors, Clouds, 3D metrology, Cameras, Imaging systems, Calibration, Projection systems, Data conversion, 3D modeling, Light sources and illumination
In a conventional fringe projection profilometry (FPP) consisted of a camera and a projector, just one-sided 3D data of the tested object can be obtained by a single-shot measurement. Therefore, tools such as turntables are commonly used to obtain 360-degree 3D point cloud data of objects. However, this method requires multiple measurements and point cloud registration, which is time consuming and laborious. With the help of two planar mirrors, this paper proposes an improved system that captures fringe images from three different perspectives including one real camera and two virtual cameras. The information of the planar mirrors (i.e., the mirror calibration) is achieved by artificially attaching the featured pattern to the surface of the mirrors. Using the calibration parameters of the planar mirrors, the 3D point cloud data obtained by the virtual cameras can be converted into the real coordinate system, thereby reconstructing the full-surface 3D point cloud data with relative roughness. Finally, an improved ICP algorithm is introduced to obtain high-precision 360-degree point cloud data. The experimental results demonstrate that with the help of the mirrors, our system can obtain high-quality full-surface 360-degree profile results of the measured object at high speed.
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