Real-time optical reconstruction for a three-dimensional light-field display based on path-tracing and CNN super-resolution

Three-Dimensional (3D) light-field display plays a vital role in realizing 3D display. However, the real-time high quality 3D light-field display is difficult, because super high-resolution 3D light field images are hard to be achieved in real-time. Although extensive research has been carried out on fast 3D light-field image generation, no single study exists to satisfy real-time 3D image generation and display with super high-resolution such as 7680×4320. To fulfill real-time 3D light-field display with super high-resolution, a two-stage 3D image generation method based on path tracing and image super-resolution (SR) is proposed, which takes less time to render 3D images than previous methods. In the first stage, path tracing is used to generate low-resolution 3D images with sparse views based on Monte-Carlo integration. In the second stage, a lite SR algorithm based on a generative adversarial network (GAN) is presented to up-sample the low-resolution 3D images to high-resolution 3D images of dense views with photo-realistic image quality. To implement the second stage efficiently and effectively, the elemental images (EIs) are super-resolved individually for better image quality and geometry accuracy, and a foreground selection scheme based on ray casting is developed to improve the rendering performance. Finally, the output EIs from CNN are used to recompose the high-resolution 3D images. Experimental results demonstrate that real-time 3D light-field display over 30fps at 8K resolution can be realized, while the structural similarity (SSIM) can be over 0.90. It is hoped that the proposed method will contribute to the field of real-time 3D light-field display.