利用焦叠对称的光场深度恢复

Haiting Lin, Can Chen, S. B. Kang, Jingyi Yu
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引用次数: 134

摘要

我们描述了一种利用光场焦叠的两个特征从光场(LF)中恢复深度的技术。其中一个特征是,非遮挡像素沿聚焦切片为中心的焦深度维度呈现对称性。另一个是基于合成分析的数据一致性度量,即给定假设深度图的合成震源叠加与LF的震源叠加之间的差异。这些术语在迭代优化框架中用于提取场景深度。在Lytro和Raytrix实际数据上的实验结果表明,我们的技术优于最先进的解决方案,并且对噪声和欠采样的鲁棒性更强。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Depth Recovery from Light Field Using Focal Stack Symmetry
We describe a technique to recover depth from a light field (LF) using two proposed features of the LF focal stack. One feature is the property that non-occluding pixels exhibit symmetry along the focal depth dimension centered at the in-focus slice. The other is a data consistency measure based on analysis-by-synthesis, i.e., the difference between the synthesized focal stack given the hypothesized depth map and that from the LF. These terms are used in an iterative optimization framework to extract scene depth. Experimental results on real Lytro and Raytrix data demonstrate that our technique outperforms state-of-the-art solutions and is significantly more robust to noise and under-sampling.
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