Next Generation Imaging using Sparse Single-Photon Data

使用稀疏单光子数据的下一代成像

• 批准号: EP/N003446/1
• 负责人: Gerald Buller
• 金额: $ 180.68万
• 依托单位: Heriot-Watt University
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FN003446%2F1
• 关键词: Next; Generation; Imaging; using; Sparse

Over the last three decades, our lives have been revolutionized by the availability of inexpensive CMOS-based CCD cameras whose ubiquitous nature has changed key aspects of security, communications, data handling, healthcare, commerce and leisure for almost all sections of society, regardless of wealth or geographical location. For example, it is estimated that over one half of all adults in the UK own a smartphone with imaging/video capability - a statistic considered unthinkable less than 10 years ago. The next revolution in imaging will almost certainly be spearheaded by sparse photon and three dimensional imaging, ultimately using the effects of quantum entanglement. Such a revolution will necessarily require fast timing of the single-photon detection, in the form of arrayed detectors or single-pixel cameras. The use of fast timing will permit effective time-of-flight based depth profiling at remote distances, and the effects of quantum entanglement could be utilised effectively in critical niche examples, such as imaging below the diffraction limit, wavelength transmutation or quantum secure imaging. These revolutionary changes represent a paradigm shift in terms of functionality, but present significant challenges in algorithm development and data processing, as well as data fusion with other imaging platforms, for example multispectral and regular video. This Fellowship will allow me to bridge the gap between the enabling quantum technology and the image processing community in order to improve the scope and overall performance of next generation imaging systems based on quantum technology.

在过去的三十年里，我们的生活已经彻底改变了廉价的CMOS CCD相机的可用性，其无处不在的性质已经改变了安全，通信，数据处理，医疗保健，商业和休闲的关键方面，几乎所有的社会阶层，无论财富或地理位置。例如，据估计，英国超过一半的成年人拥有一部具有成像/视频功能的智能手机-这在不到10年前被认为是不可想象的统计数据。下一次成像革命几乎肯定会由稀疏光子和三维成像带头，最终利用量子纠缠效应。这样的革命必然需要单光子探测的快速定时，以阵列探测器或单像素相机的形式。使用快速定时将允许在远程进行有效的基于飞行时间的深度分析，并且量子纠缠的效果可以有效地用于关键的利基示例，例如低于衍射极限的成像，波长嬗变或量子安全成像。这些革命性的变化代表了功能方面的范式转变，但在算法开发和数据处理以及与其他成像平台（例如多光谱和常规视频）的数据融合方面存在重大挑战。这个奖学金将使我能够弥合量子技术和图像处理社区之间的差距，以提高基于量子技术的下一代成像系统的范围和整体性能。

项目成果

Efficient Range Estimation and Material Quantification from Multispectral Lidar Waveforms

根据多光谱激光雷达波形进行有效的范围估计和材料量化

• DOI: 10.1109/sspd.2016.7590596
• 发表时间: 2016
• 作者: Altmann Y

Photon-sparse microscopy: visible light imaging using infrared illumination

• DOI: 10.1364/optica.2.001049
• 发表时间: 2015-12-20
• 期刊: OPTICA
• 影响因子: 10.4
• 作者: Aspden, Reuben S.;Gemmell, Nathan R.;Padgett, Miles J.
• 通讯作者: Padgett, Miles J.

Robust Bayesian Target Detection Algorithm for Depth Imaging From Sparse Single-Photon Data

• DOI: 10.1109/tci.2016.2618323
• 发表时间: 2016-01
• 期刊: IEEE Transactions on Computational Imaging
• 影响因子: 5.4
• 作者: Y. Altmann;Ximing Ren;A. Mccarthy;G. Buller;S. Mclaughlin

Target detection for depth imaging using sparse single-photon data

使用稀疏单光子数据进行深度成像的目标检测

• DOI: 10.1109/icassp.2016.7472279
• 发表时间: 2016
• 作者: Altmann Y

Single-photon Depth Imaging in Free-space and Underwater Environments

自由空间和水下环境中的单光子深度成像

• DOI: 10.1364/lsc.2015.lm3d.1
• 发表时间: 2015
• 作者: Buller G