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EAGER: Fabrication of Thin, Lens-Free Cameras for Visible and SWIR Imaging

EAGER: Fabrication of Thin, Lens-Free Cameras for Visible and SWIR Imaging
EAGER:制造用于可见光和短波红外成像的薄型无镜头相机
批准号:
1502875
负责人:
Ashok Veeraraghavan
金额:
$15.0万
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:
2015-02-01 至 2017-01-31

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中文摘要
翻译
图像传感器从半导体制造的稳步发展中受益匪浅,在过去的三十年中,分辨率每十年都会增加一个数量级。摩尔?s定律对计算和图像传感器技术都有类似的影响。然而,除了传感器之外,相机和其他成像设备还需要镜头,其制造工艺没有从摩尔?s定律。因此,成像设备的最终缩放和成本受到物理光学的限制。 该研究项目涉及无透镜相机(LFCs)的开发,这是一种用于可见光,短波红外(SWIR),中波红外(MWIR)和热波长的新型成像架构,利用幅度复用掩模和计算解复用算法来取代传统相机中的镜头。这种无透镜成像技术将生产薄相机,其可以使用当代半导体制造工艺直接制造,从而受益于半导体制造的缩放定律(scalinglaws)JFC由图像传感器和在图像传感器表面上方几百微米处制造的薄幅度调制掩模组成。幅度调制掩模在场景和传感器测量之间创建线性映射。描述LFC的线性系统包含数百万个变量和数百万个测量值。求解这个大的线性方程组将允许从传感器测量重构高分辨率图像。该项目将专注于制造薄无透镜相机。这一制造过程的结果将是世界?他的第一台相机厚度不到一毫米。无透镜相机的进步将更广泛地适用于几个具有挑战性的应用,如显微镜,内窥镜和其他空间受限的成像场景。
英文摘要
Image sensors have benefited immensely from the steady advances in semiconductor fabrication, resulting in an order of magnitude resolution increase every decade for the last three decades. Moore?s law has had a similar impact on both computing and image sensor technology. In addition to the sensor, however, cameras and other imaging devices require lenses whose manufacturing processes has not benefited from Moore?s law. As a result the ultimate scaling and cost of imaging devices is limited by physical optics. This research project involves the development of Lens-Free Cameras (LFCs), a novel imaging architecture for visible, short-wave infrared (SWIR), mid-wave infrared (MWIR) and thermal wavelengths that exploits amplitude multiplexing masks and computational demultiplexing algorithms to replace lenses in traditional cameras. Such lensless imaging technology will produce thin cameras that can be directly fabricated using contemporary semiconductor fabrication processes, thereby benefitting from the scaling laws of semiconductor fabrication.An LFC consists of an image sensor and a thin amplitude modulation mask fabricated at a few hundreds of microns above the image sensor surface. The amplitude modulation mask creates a linear mapping between the scene and the sensor measurements. The linear system describing the LFC contains millions of variables and millions of measurements. Solving this large linear system of equations will allow for the reconstruction of high resolution images from the sensor measurements. This project will focus on the fabrication of a thin lensfree camera. The result of this fabrication process will be the world?s first camera less than a millimeter thick. The advance in lensfree cameras will be more widely applicable to several challenging applications such as microscopy, endoscopy and other space constrained imaging scenarios.
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Collaborative Research: RI: Medium: Thermal Computational Imaging
  • 批准号:
    2107313
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2021
  • 负责人:
    Ashok Veeraraghavan
  • 依托单位:
Collaborative Research: CNS Core: Medium: OneDegree: Foundations and Methods for Imaging in mmWave Wireless Networks
  • 批准号:
    1956297
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $90.0万
  • 财政年份:
    2020
  • 负责人:
    Ashok Veeraraghavan
  • 依托单位:
SaTC: CORE: Medium: Collaborative: Presentation-attack-robust biometrics systems via computational imaging of physiology and materials
  • 批准号:
    1801372
  • 项目类别:
    Standard Grant
  • 资助金额:
    $27.05万
  • 财政年份:
    2018
  • 负责人:
    Ashok Veeraraghavan
  • 依托单位:
CAREER: A Signal Processing Framework for Computational Imaging: From Theory to Applications
  • 批准号:
    1652633
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $54.9万
  • 财政年份:
    2017
  • 负责人:
    Ashok Veeraraghavan
  • 依托单位:
海外基金