Autocorrelation phase retrieval function of light field for improving rendering quality
Mengqin Bai, Changjian Zhu · 2023
In this paper, we show an autocorrelation phase retrieval function (APRF) of light field to improve the rendering quality of novel views for light field rendering (LFR) technology. The phase of light field signal carries more abundant scene information, such as for scenes with occlusion, non-Lambertian, complex geometry and color texture. We apply the autocorrelation theory to convert the phase retrieval of the light field signal into the phase retrieval of the light field signal autocorrelation function, so as to facilitate the phase retrieval in the frequency domain. Therefore, we first derive the autocorrelation function of the light field signal and the influence of scene attributes. Based on the autocorrelation function of the light field, the phase retrieval of the light field signal is performed in the frequency domain for multiple iterations. By the phase retrieval optimization of the light field, the estimation and recovery of the scene information carried by the phase are realized, and the rendering quality of multi-view images is optimized. Additionally, to verify the effectiveness of this method, we compare the APRF with other reconstruction algorithms. The experimental results show the effectiveness of APRF in improving the reconstruction quality.