计算机科学
杠杆(统计)
计算机视觉
人工智能
编码(社会科学)
数据压缩
空间分析
外部数据表示
光学
遥感
物理
地质学
数学
统计
作者
Kejun Wu,Qiong Liu,Kim–Hui Yap,You Yang
出处
期刊:Optics Letters
[Optica Publishing Group]
日期:2024-01-02
卷期号:49 (3): 562-562
被引量:3
摘要
Multifocal multiview (MFMV) is an emerging high-dimensional optical data that allows to record richer scene information but yields huge volumes of data. To unveil its imaging mechanism, we present an angular–focal–spatial representation model, which decomposes high-dimensional MFMV data into angular, spatial, and focal dimensions. To construct a comprehensive MFMV dataset, we leverage representative imaging prototypes, including digital camera imaging, emerging plenoptic refocusing, and synthesized Blender 3D creation. It is believed to be the first-of-its-kind MFMV dataset in multiple acquisition ways. To efficiently compress MFMV data, we propose the first, to our knowledge, MFMV data compression scheme based on angular–focal–spatial representation. It exploits inter-view, inter-stack, and intra-frame predictions to eliminate data redundancy in angular, focal, and spatial dimensions, respectively. Experiments demonstrate the proposed scheme outperforms the standard HEVC and MV-HEVC coding methods. As high as 3.693 dB PSNR gains and 64.22% bitrate savings can be achieved.
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