Appl Opt. 2023 Apr 20;62(12):3016-3027. doi: 10.1364/AO.484909.
In this paper, we make full advantage of the information correlation of subaperture images and propose a new super-resolution (SR) reconstruction method based on spatiotemporal correlation to achieve SR reconstruction for light-field images. Meanwhile, the offset compensation method based on optical flow and spatial transformer network is designed to realize accurate compensation between adjacent light-field subaperture images. After that, the obtained light-field images with high resolution are combined with the self-designed system based on phase similarity and SR reconstruction to realize accurate 3D reconstruction of a structured light field. Finally, experimental results demonstrate the validity of the proposed method to perform accurate 3D reconstruction of light-field images from the SR data. Generally, our method makes full use of the redundant information between different subaperture images, hides the upsampling process in the convolution, provides more sufficient information, and reduces time-consuming procedures, which is more efficient to realize the accurate 3D reconstruction of light-field images.
在本文中，我们充分利用子孔径图像的信息相关性，提出了一种新的基于时空相关性的超分辨率（SR）重建方法，以实现光场图像的 SR 重建。同时，设计了基于光流和空间变换网络的偏移补偿方法，以实现相邻光场子孔径图像之间的精确补偿。之后，将获得的高分辨率光场图像与基于相位相似性和 SR 重建的自设计系统相结合，实现结构光场的精确 3D 重建。最后，实验结果验证了该方法从 SR 数据准确重建光场图像的有效性。总的来说，我们的方法充分利用了不同子孔径图像之间的冗余信息，将上采样过程隐藏在卷积中，提供了更充分的信息，减少了耗时的步骤，更高效地实现了光场图像的精确 3D 重建。
