CIF: Small: Lens-Free Imaging: Can Signal Processing Replace Lenses?
CIF: Small: Lens-Free Imaging: Can Signal Processing Replace Lenses?
批准号:
1527501
负责人:
Richard Baraniuk
金额:
$50.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-09-01 至 2018-08-31
中文摘要
照相机的基本设计几个世纪以来一直没有改变。为了获取图像,来自场景的光线通过镜头聚焦到图像传感器上。这种设计在广泛的应用中为用户提供了良好的服务,镜头形成了当前成像实践的基石。不幸的是,镜头也带来了一些限制。首先,虽然图像传感器通常很薄,但由于镜头的复杂性和镜头与传感器之间实现对焦所需的较大距离,相机最终会变得很厚。其次,摩尔?随着时间的推移,Law已经指数级地降低了图像传感器的成本,镜头和相机并没有从这种指数级的缩减中受益,特别是在红外和紫外线的波长上,廉价的玻璃和塑料无法使用。第三,基于镜头的相机总是需要后期组装,导致制造效率低下。在这个项目中,pi开发了完全不需要镜头的新相机架构。无镜头相机保留了基于镜头的相机的高光吞吐量,具有薄的外形因素,并且可以在宽光谱范围内工作时直接制造。该设计用一系列编码掩模取代了镜头,这些掩模几乎立即放置在裸露的传统传感器上,并使用计算算法从传感器测量中恢复图像。该项目的目标是一个基于现代信号处理的框架,用于设计、优化和开发无透镜和无折射光学成像系统,这将确定此类系统成像的基本限制。这将彻底改变成像能力,并首次使薄相机可以直接使用传统的半导体制造工具制造。
英文摘要
The basic design of the camera has remained unchanged for centuries. To acquire an image, light from the scene is focused using a lens onto an image sensor. This design has served users well in a broad range of applications, with lenses forming the bedrock of current imaging practice. Unfortunately, lenses also introduce a number of limitations. First, while image sensors are typically thin, cameras end up being thick due to the lens complexity and the large distance between the lens and sensor required to achieve focus. Second, while Moore?s Law has cut the cost of image sensors exponentially over time, lenses, and thus cameras, do not benefit from this exponential scaling, particularly at wavelengths further into the infrared and ultraviolet, where inexpensive glass and plastics cannot be used. Third, lens-based cameras invariably require post-fabrication assembly, resulting in manufacturing inefficiencies.In this project, the PIs develop new camera architectures that dispense with lenses completely. Lens-free cameras retain the high light-throughput of lens-based cameras, have a thin form factor, and are amenable to direct fabrication while operating over a wide spectral range. The design replaces the lens with a series of coded masks placed almost immediately atop a bare conventional sensor and uses a computational algorithm to recover the image from the sensor measurements. The goal of this project is a modern signal processing based framework for the design, optimization and development of lens free and refractive optics-free imaging systems that will establish the fundamental limits of imaging with such systems. This will revolutionize imaging capabilities and, for the first time, enable thin, cameras that can directly be fabricated using traditional semiconductor fabrication tools.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
DOI:
10.1364/oe.25.031096
发表时间:
2017-12-11
期刊:
OPTICS EXPRESS
影响因子:
3.8
作者:
[Li, Fengqiang, Chen, Huaijin, Cossairt, Oliver]
通讯作者:
Cossairt, Oliver
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NCS-FO: Collaborative Research: Operationalizing Students' Textbooks Annotations to Improve Comprehension and Long-Term Retention
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DIP: Collaborative Research: A Personalized Cyberlearning System Based on Cognitive Science
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批准号:1124535
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项目类别:Standard Grant
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项目类别:Standard Grant
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资助金额:$48.13万
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负责人:Richard Baraniuk
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依托单位:
Collaborative Research: Design and Analysis of Compressed Sensing DNA Microarrays
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项目类别:Continuing Grant
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资助金额:$30.0万
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财政年份:2007
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负责人:Richard Baraniuk
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依托单位:
NeTS-NOSS: Adaptivity in Sensor Networks for Optimized Distributed Sensing and Signal Processing
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批准号:0520280
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项目类别:Continuing Grant
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资助金额:$0.0万
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财政年份:2005
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依托单位:
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项目类别:Standard Grant
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资助金额:$3.5万
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财政年份:2004
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负责人:Richard Baraniuk
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依托单位:
Multiscale Geometric Analysis for Higher Dimensional Signal Processing
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批准号:0431150
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项目类别:Standard Grant
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资助金额:$0.0万
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财政年份:2004
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依托单位:
NeTS NOSS: AssimNet
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批准号:0435425
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项目类别:Continuing Grant
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资助金额:$0.0万
-
财政年份:2004
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负责人:Richard Baraniuk
-
依托单位:
Multiscale Signal and Image Processing using Singularity Grammars
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批准号:9973188
-
项目类别:Standard Grant
-
资助金额:$17.02万
-
财政年份:1999
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负责人:Richard Baraniuk
-
依托单位:
NYI: Signal Analysis and Processing in Matched Coordinate Systems
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批准号:9457438
-
项目类别:Continuing Grant
-
资助金额:$32.75万
-
财政年份:1994
-
负责人:Richard Baraniuk
-
依托单位:
国内基金
海外基金
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