.png){kind=icon}
返回
Scene-adaptive coded aperture imaging
.png){kind=icon}
PRE
AI
DOI：10.1007/s11042-017-5520-1.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Coded aperture imaging systems have recently shown great success in recovering scene depth and extending the depth-of-field. Tremendous efforts have been focused on designing good coded patterns. The ideal pattern, however, would have to serve two conflicting purposes: 1) it should be broadband to ensure robust deconvolution and 2) it should have sufficient zero-crossings for a high depth discrepancy. This paper presents a simple but effective scene-adaptive coded aperture solution to bridge this gap. We observe that natural scenes often exhibit a dominant edge direction that can be caused by structure, texture, shading, etc. We therefore apply depth-discriminative codes along the dominant direction and broadband codes along its orthogonal direction. To physically implement this scheme, we adopt a two-shot scheme. Firstly, we capture a scene image with a pinhole aperture and analyze image content to determine the dominant direction. Secondly, we apply the proposed coding scheme using the programmable Liquid Crystal on Silicon (LCoS). Experiments on a broad range of synthetic and real scenes show that our technique is able to combine advantages of the state-of-the-art patterns for recovering better quality depth map and all-focus images.
Keyword:
Computational imaging
Coded-aperture
Depth-from-defocus
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3
论文数:
2.0W
被引数:
3.2W
机构
引用论文
Surgery Treatment Improved the Overall Survival Rate in Locoregional Myxoid Leiomyosarcoma than Other Myxosarcomas in the United States手术治疗提高了美国局部区域黏液样平滑肌肉瘤的整体生存率，优于其他黏液样肉瘤。
OAAI
.png){kind=icon}
OAAI分享收藏Response of Woody Plant Communities in Power‐Line Corridors to Frequent Anthropogenic Disturbance
PREAI
分享收藏分享收藏
查看更多内容