A Spectral Analysis of Light Field Signal for Plenoptic Sampling and Rendering
Shan Zhang, Weiyan Chen, Changjian Zhu · 2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP) · 2022
Light field rendering (LFR) has been widely used for generating multiview images in Image-Based Rendering. However, to ensure the quality of novel views, this conventional rendering technology, requires a mass of manually captured light field images as input, which contains complete light field signal information and is highly time-consuming. Depth information of 3D scene and light field spectrum analysis are fundamental to light field reconstruction. The depth information was acquired with spectrum statistical analysis. This study aims to provide a broad applicability and robust depth layered scene mapping method by extending the traditional plenoptic sampling theory to reasonably determine the number of necessary captured images. A mathematical function was derived on the basis of overlapped spectrum, to decide the optimal mapping layer. Then, an optimal reconstruction filter is designed to reconstruct novel views. The proposed method exhibited a larger PSNR value in a variety of scenes. The depth layered scene mapping method showed potential for light field rendering without the need for complete multiview images requiring continuous sampling.