论文标题
部分可观测时空混沌系统的无模型预测
3DVSR: 3D EPI Volume-based Approach for Angular and Spatial Light field Image Super-resolution
论文作者
论文摘要
捕获场景的空间和角度信息的光场（LF）成像无疑对众多应用有益。尽管已经提出了各种技术来获取LF，但在角度和空间高分辨率的LF上都达到了技术挑战。在本文中，提出了一种基于学习的方法，用于重建高分辨率LF。通过2阶段的超分辨率框架，提出的方法有效地解决了各种LF超分辨率（SR）问题，即空间SR，Angular SR和Angular-Spatial SR。虽然第一阶段为提出的分辨率提供了灵活的选项，但第二阶段由新型的基于EPI的精炼网络（EVRN）组成，但大大提高了高分辨率EPI体积的质量。 An extensive evaluation on 90 challenging synthetic and real-world light field scenes from 7 published datasets shows that the proposed approach outperforms state-of-the-art methods to a large extend for both spatial and angular super-resolution problem, i.e., an average peak signal to noise ratio improvement of more than 2.0 dB, 1.4 dB, and 3.14 dB in spatial SR $\times 2$, spatial SR $ \ times 4 $和Angular SR。重建的4D光场在所有透视图像上都表现出平衡的性能分布，并且与以前的作品相比，具有较高的视觉质量。
Light field (LF) imaging, which captures both spatial and angular information of a scene, is undoubtedly beneficial to numerous applications. Although various techniques have been proposed for LF acquisition, achieving both angularly and spatially high-resolution LF remains a technology challenge. In this paper, a learning-based approach applied to 3D epipolar image (EPI) is proposed to reconstruct high-resolution LF. Through a 2-stage super-resolution framework, the proposed approach effectively addresses various LF super-resolution (SR) problems, i.e., spatial SR, angular SR, and angular-spatial SR. While the first stage provides flexible options to up-sample EPI volume to the desired resolution, the second stage, which consists of a novel EPI volume-based refinement network (EVRN), substantially enhances the quality of the high-resolution EPI volume. An extensive evaluation on 90 challenging synthetic and real-world light field scenes from 7 published datasets shows that the proposed approach outperforms state-of-the-art methods to a large extend for both spatial and angular super-resolution problem, i.e., an average peak signal to noise ratio improvement of more than 2.0 dB, 1.4 dB, and 3.14 dB in spatial SR $\times 2$, spatial SR $\times 4$, and angular SR respectively. The reconstructed 4D light field demonstrates a balanced performance distribution across all perspective images and presents superior visual quality compared to the previous works.
