文献详情
Adaptive foveated single-pixel imaging with dynamic supersampling
文献类型期刊
作者Phillips, David B.[1];Sun, Ming-Jie[2];Taylor, Jonathan M.[3];Edgar, Matthew P.[4];Barnett, Stephen M.[5];Gibson, Graham M.[6];Padgett, Miles J.[7]
机构
通讯作者Phillips, DB; Sun, MJ (reprint author), Univ Glasgow, Sch Phys & Astron, Glasgow G12 8QQ, Lanark, Scotland.
2017
期刊名称SCIENCE ADVANCES
来源信息年:2017  卷:3  期:4  页码范围:e1601782  
3
期刊信息SCIENCE ADVANCES  ISSN:2375-2548
4
页码范围e1601782
增刊正刊
摘要In contrast to conventional multipixel cameras, single-pixel cameras capture images using a single detector that measures the correlations between the scene and a set of patterns. However, these systems typically exhibit low frame rates, because to fully sample a scene in this way requires at least the same number of correlation measurements as the number of pixels in the reconstructed image. To mitigate this, a range of compressive sensing techniques have been developed which use a priori knowledge to reconstruct images from an undersampled measurement set. Here, we take a different approach and adopt a strategy inspired by the foveated vision found in the animal kingdom-a framework that exploits the spatiotemporal redundancy of many dynamic scenes. In our system, a high-resolution foveal region tracks motion within the scene, yet unlike a simple zoom, every frame delivers new spatial information from across the entire field of view. This strategy rapidly records the detail of quickly changing features in the scene while simultaneously accumulating detail of more slowly evolving regions over several consecutive frames. This architecture provides video streams in which both the resolution and exposure time spatially vary and adapt dynamically in response to the evolution of the scene. The degree of local frame rate enhancement is scene-dependent, but here, we demonstrate a factor of 4, thereby helping to mitigate one of the main drawbacks of single-pixel imaging techniques. The methods described here complement existing compressive sensing approaches and may be applied to enhance computational imagers that rely on sequential correlation measurements.
收录情况SCIE(WOS:000401954800013)  
所属部门仪器科学与光电工程学院
链接地址http://advances.sciencemag.org/content/3/4/e1601782
DOI10.1126/sciadv.1601782
百度学术Adaptive foveated single-pixel imaging with dynamic supersampling
语言外文
ISSN2375-2548
被引频次77
人气指数1526
浏览次数1525
基金Royal Academy of Engineering; UK Quantum Technology Hub in Quantum Enhanced Imaging [EP/M01326X/1]; Wolfson Foundation; Royal Society; National Natural Foundation of China [61675016, 61307021]; China Scholarship Council [201306025016]
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