Time-Multiplexed Coded Aperture and Coded Focal Stack -Comparative Study on Snapshot Compressive Light Field Imaging
Time-Multiplexed Coded Aperture and Coded Focal Stack -Comparative Study on Snapshot Compressive Light Field Imaging
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DOI：
10.1587/transinf.2022pcp0003
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发表时间：
2022-10
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影响因子：
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通讯作者：
Kohei Tateishi;Chihiro Tsutake;Keita Takahashi;T. Fujii
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文献类型：
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作者：
Kohei Tateishi;Chihiro Tsutake;Keita Takahashi;T. Fujii
摘要光场（LF）被表示为一组密集的多视图图像，已被用于各种3D应用中。为了使LF采集更有效，研究人员通过将某些编码功能并入相机来研究压缩感知方法。在本文中，我们专注于一个具有挑战性的情况下，称为快照压缩LF成像，其中整个LF重建从只有一个单一的采集图像。为了在单个图像中嵌入大量的LF信息，我们考虑了两种基于单次曝光期间快速光学控制的有前途的方法：时分复用编码孔径（TMCA）和编码焦点堆栈（CFS），这两种方法在以前的工作中分别被提出。TMCA和CFS可以统一的艾德方式分别解释为编码孔径（CA）和焦点叠加（FS）方法的扩展。通过开发基于深度神经网络的TMCA和CFS的统一艾德算法管道，我们评估了它们相对于其他可能成像方法的性能。我们发现，TMCA和CFS可以实现更好的重建质量比其他快照方法，他们也表现得相当不错的方法相比，使用多个采集图像。据我们所知，我们是第一个全面讨论TMCA和CFS，并在压缩LF成像的背景下比较和验证其有效性的机构。
SUMMARY A light field (LF), which is represented as a set of dense, multi-view images, has been used in various 3D applications. To make LF acquisition more e ffi cient, researchers have investigated compressive sensing methods by incorporating certain coding functionalities into a camera. In this paper, we focus on a challenging case called snapshot compressive LF imaging, in which an entire LF is reconstructed from only a single acquired image. To embed a large amount of LF information in a single image, we consider two promising methods based on rapid optical con-trol during a single exposure: time-multiplexed coded aperture (TMCA) and coded focal stack (CFS), which were proposed individually in previous works. Both TMCA and CFS can be interpreted in a unified manner as extensions of the coded aperture (CA) and focal stack (FS) methods, respectively. By developing a unified algorithm pipeline for TMCA and CFS, based on deep neural networks, we evaluated their performance with respect to other possible imaging methods. We found that both TMCA and CFS can achieve better reconstruction quality than the other snapshot methods, and they also perform reasonably well compared to methods us-ing multiple acquired images. To our knowledge, we are the first to present an overall discussion of TMCA and CFS and to compare and validate their e ff ectiveness in the context of compressive LF imaging.