An infrastructure for analysing the performance of computational imaging algorithms on modern hardware

用于分析现代硬件上计算成像算法性能的基础设施

• 批准号: 500612-2016
• 负责人: Moshovos, Andreas
• 金额: $ 1.82万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=608194
• 关键词: infrastructure; analysing; performance; computational; imaging

Numerous applications, such as those in medical imaging, film production, automotive and robotics, use imaging sensors (IS) to convert light to signals appropriate for further processing and storage by digital devices. IS output is imperfect and requires significant processing in the digital domain to yield acceptable results. For example, lens imperfections result in distorted output, while sensor sensitivity may yield output that is underexposed or overexposed at places and thus missing crucial information. Computational Imaging (CI) is the processing in the digital domain of IS output can compensate for these limitations. However, further advances in CI sophistication are severely limited by hardware performance. Specifically, at the heart of every computing device, there are one or more processing cores that manipulate data values and move them among storage devices or devices that interact with the physical world such as displays and touch screens. Existing general purpose processing cores are not keeping pace with the computational power demands of CI applications. For several decades, core performance, that is the rate at which data values could be manipulated or moved around, has doubled every two years. This has enabled advances in application sophistication and breadth. Application developers could rely on this trend of performance increase and plan ahead innovations to

许多应用，例如医学成像、电影制作、汽车和机器人技术中的应用，使用成像传感器（IS）将光转换为适合于数字设备进一步处理和存储的信号。IS输出是不完美的，并且需要在数字域中进行大量处理以产生可接受的结果。例如，透镜缺陷导致失真的输出，而传感器灵敏度可能产生在某些地方曝光不足或曝光过度的输出，从而丢失关键信息。计算成像（CI）是IS输出的数字域处理，可以弥补这些限制。然而，CI复杂性的进一步发展受到硬件性能的严重限制。具体地说，在每个计算设备的核心，都有一个或多个处理核心，它们操纵数据值并在存储设备或与物理世界交互的设备（如显示器和触摸屏）之间移动它们。现有的通用处理核不能跟上CI应用的计算能力需求。几十年来，核心性能，即数据值可以被操纵或移动的速度，每两年翻一番。这使得应用程序的复杂性和广度得以提高。应用程序开发人员可以依靠这种性能提高的趋势，并提前计划创新，