CCRI: Planning: Development of a Community Resource for Digital Image Research

这个项目是关于超大数字图像的研究。虽然图像识别工具对于标准清晰度图像来说已经很常见了，但是对于分析非常高分辨率的图像（每个图像数亿像素），仍然缺乏工具和技术。如果能够自动搜索这样的图像，那么许多重要的应用程序都可以得到很好的服务，特别是在搜索目标的属性甚至还不完全知道的情况下。这种性质的研究是复杂的，因为这种大小的图像不适合在标准分辨率图像处理技术（如手写或面部识别）中成功的软件工具。数据量本身就是一个主要限制；训练一个强大的图像识别工具可能需要数以万计的图像；每张图像有1亿像素，庞大的数据量成为存储、共享和处理的一个问题。机器学习、数据来源和仓储、云计算和图像压缩等领域都需要新的创新，所有这些都将符合国家利益。该项目的具体目的是(a)建立一个对高分辨率图像处理创新有既得利益的利益相关者社区，以及(b)为未来的研究制定路线图。具体来说，研究人员将接触到学术界、工业界和非营利联盟的相关团体，目标是建立一个具有不同期望的强大社区。该社区将参与一系列研讨会，以确定高清晰度图像处理联盟的目标和范围。研讨会将寻求定义数据标准、图像处理目标、标准化数据集以及在拍字节规模上共享和计算图像的最佳实践。这些发现将被利用到未来的项目中，其目标将是实际构建工具并执行该项目所规划的研究。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project is concerned with research on very large digital images. Although image recognition tools are now commonplace for standard definition images, there is a lack of tools and techniques for analyzing very high resolution images (hundreds of millions of pixels per image). There are many important applications that would be well-served by the ability to automatically search such images, especially in cases where the properties of the search target aren't even fully known. Research of this nature is complicated by the fact that images of this size do not lend themselves well to the type of software tools that have been successful in standard-resolution image processing techniques such as handwriting or facial recognition. Data quantity alone is a major limitation; training a robust image recognition tool may require tens of thousands of images; at 100 million pixels per image, the sheer quantity of data becomes an issue for storing, sharing, and processing. New innovations will be required in machine learning, data provenance and warehousing, cloud computing, and image compression, all of which will serve the national interest.The specific purpose of this project is to (a) build a community of stakeholders who have vested interests in innovations in high resolution image processing and (b) create a roadmap for future research. Specifically, the researchers will reach out to relevant groups across academia, industry, and not-for-profit consortia with the goal of building a robust community with diverse expectations. This community will engage in a series of workshops to define the goals and scope of a high definition image processing consortium. The workshops will seek to define data standards, image processing goals, standardized data sets, and best practices for sharing and computing images at the petabyte scale. These findings will be leveraged into a future project whose goal will be to actually build the tools and perform the research that has been road-mapped by this project.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.