Spectral Analysis of Aerial Light Field for Optimization Sampling and Rendering of Unmanned Aerial Vehicle

Qiuming Liu, Yichen Wang, Ying Wei, Lei Xie, Changjian Zhu, Ruoxuan Zhou
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Abstract

The aerial light field (ALF) can render higher quality images of large-scale 3D scenes. In this paper, we apply the ALF technology to study the image captured and novel view rendering of unmanned aerial vehicle (UAV), which exists some problems, such as large scene and depth of field. First, we design an ALF sampling model using spectral analysis of Fourier theory. Based on the ALF sampling model, the exact expression of ALF spectrum is derived. By the spectral support of ALF, we analyze the influence of pitch angle on light field sampling and its bandwidth. Particularly, the bandwidth of ALF can be applied to determine the minimum sampling rate for UAV. Additionally, we design a reconstruction filter that is related to pitch angle to render novel views of UAV. Finally, our experiments show that our sampling and rendering methods can improve the rendering quality of UAV novel view rendering.
面向无人机优化采样与绘制的航空光场光谱分析
航空光场(ALF)可以渲染高质量的大尺度三维场景图像。本文将ALF技术应用于无人机的图像捕获和新视图绘制,解决了无人机场景大、景深大等问题。首先,我们利用傅立叶理论的频谱分析设计了ALF采样模型。在ALF采样模型的基础上,导出了ALF谱的精确表达式。利用ALF的光谱支持,分析了俯仰角对光场采样及其带宽的影响。特别是,ALF的带宽可以用于确定无人机的最小采样率。此外,我们设计了一个与俯仰角相关的重建滤波器,以呈现无人机的新视角。最后,实验表明,我们的采样和绘制方法可以提高无人机新颖视图绘制的绘制质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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