Yao Chuanwei, Shen Yibing
State Key Laboratory of Modern Optical Instrumentation, Zhejiang University, Hangzhou 310027, China.
Sensors (Basel). 2021 Jun 10;21(12):4011. doi: 10.3390/s21124011.
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.
图像去卷积技术可以从受像差影响的模糊图像中恢复潜在的清晰图像。准确获取成像系统的点扩散函数(PSF)是进行稳健去卷积的前提条件。本文提出一种基于波前编码的计算成像方法来重建摄影系统的波前像差。首先,通过在光学系统的光谱平面上应用波前编码获得一组受局部像差影响的图像。然后,通过光瞳函数合成精确恢复PSF,最后,通过图像去卷积恢复受像差影响的图像。经像差校正后,图像的变异系数和平均相对偏差分别提高了60%和30%,并且如分辨率测试板所证明的,图像可以达到传感器的分辨率极限。同时,通过仿真实验证实了该方法具有强大的抗噪声能力。通过将光学设计的复杂性转换为后处理算法,该方法为使用简单的大视场镜头获得高分辨率和高质量图像提供了一种经济高效的策略。