中文摘要：

针对现有光场图像存在混叠的问题，提出一种多尺度抗混叠绘制光场图像的方法.首先分析了光场角度降采样引起图像混叠的原因，然后给出角度采样率与图像混叠关系的数学描述，并且指出了影响图像混叠的相关因素.在此基础上，提出采用多尺度光场图像梯度融合的方法降低图像混叠，其优点在于无需场景深度先验信息.分别在虚拟光场数据和真实光场数据集上进行了抗混叠绘制实验，结果表明该方法优于经典光场绘制方法，能够得到与已知深度绘制方法相近的结果.

英文摘要：

As aliasing artifacts can significantly reduce the quality of light field imaging, we propose a multi-scale anti-aliasing rendering algorithm to alleviate these artifacts. First, we explain that the angular under-sampling is an essential cause of aliasing artifacts. Then, we model the relationship between the aliasing and angular under-sampling. Distinct from existing methods, we address angular aliasing in the light field rendering stage, and the proposed algorithm does not need scene depth as the rendering prior. To avoid boundary problem, we introduce a multi-scale gradient field fusion algorithm, which can seam different level of non-aliased image parts together to reduce the light field aliasing. We test the proposed algorithm on both synthetic data and real scene data sets. In the experiments, the proposed rendering approach can significantly outperform the traditional light field rendering and can obtain similar results as the depth prior based rendering method.