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Interactive Editing of Massive Imagery Made Simple: Turning Atlanta into Atlantis

机译:大规模图像的交互式编辑变得简单:将亚特兰大变成亚特兰蒂斯

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The Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112;The Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112;Lawrence Livermore National Laboratory, Livermore, CA 94551 -0808;Lawrence Livermore National Laboratory, Livermore, CA 94551 -0808;The Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112;%This article presents a simple framework for progressive processing of high-resolution images with minimal resources. We demonstrate this framework's effectiveness by implementing an adaptive, multi-resolution solver for gradient-based image processing that, for the first time, is capable of handling gigapixel imagery in real time. With our system, artists can use commodity hardware to interactively edit massive imagery and apply complex operators, such as seamless cloning, panorama stitching, and tone mapping. We introduce a progressive Poisson solver that processes images in a purely coarse-to-fine manner, providing near instantaneous global approxi-mations for interactive display (see Figure 1). We also allow for data-driven adaptive refinements to locally emulate the effects of a global solution. These techniques, combined with a fast, cache-friendly data access mechanism, allow the user to interactively explore and edit massive imagery, with the illusion of having a full solution at hand. In particular, we demonstrate the interactive modification of gigapixel panoramas that previously required extensive offline processing. Even with massive satellite images surpassing a hundred gigapixels in size, we enable repeated interactive editing in a dynamically changing environment. Images at these scales are significantly beyond the purview of previous methods yet are processed interactively using our techniques. Finally our system provides a robust and scalable out-of-core solver that consistently offers high-quality solutions while maintaining strict control over system resources.
机译:犹他州大学盐湖城科学计算与成像研究所,犹他州84112;犹他大学盐湖城盐湖大学科学计算与成像研究所,UT 84112;劳伦斯利弗莫尔国家实验室,加利福尼亚州利弗莫尔94551 -0808;劳伦斯利弗莫尔国家实验室,利弗莫尔,加利福尼亚州94551 -0808;犹他大学科学计算与成像研究所,盐湖城,犹他州84112;%本文提供了一个简单的框架,可以用最少的资源逐步处理高分辨率图像。我们通过为基于梯度的图像处理实现自适应,多分辨率求解器来证明此框架的有效性,该解决器首次能够实时处理千兆像素图像。使用我们的系统,艺术家可以使用商品硬件交互式地编辑海量图像并应用复杂的运算符,例如无缝克隆,全景拼接和色调映射。我们介绍了一种渐进式Poisson求解器,它以一种从粗到精的方式处理图像,为交互式显示提供近乎瞬时的全局逼近(见图1)。我们还允许数据驱动的自适应优化来本地模拟全局解决方案的效果。这些技术与快速,易于缓存的数据访问机制相结合,使用户可以以手头有完整解决方案的错觉来交互式地浏览和编辑海量图像。特别是,我们演示了以前需要大量离线处理的千兆像素全景图的交互式修改。即使拥有超过一百亿像素的巨大卫星图像,我们也可以在动态变化的环境中进行重复的交互式编辑。这些比例的图像远远超出了先前方法的范围,但使用我们的技术进行了交互式处理。最终,我们的系统提供了强大且可扩展的核外求解器,该求解器始终提供高质量的解决方案,同时保持对系统资源的严格控制。

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