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首页> 外文期刊>ACM Transactions on Graphics >Adaptive Image Synthesis for Compressive Displays
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Adaptive Image Synthesis for Compressive Displays

机译:压缩显示的自适应图像合成

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摘要

Recent years have seen proposals for exciting new computational display technologies that are compressive in the sense that they generate high resolution images or light fields with relatively few display parameters. Image synthesis for these types of displays involves two major tasks: sampling and rendering high-dimensional target imagery, such as light fields or time-varying light fields, as well as optimizing the display parameters to provide a good approximation of the target content. In this paper, we introduce an adaptive optimization framework for compressive displays that generates high quality images and light fields using only a fraction of the total plenoptic samples. We demonstrate the framework for a large set of display technologies, including several types of auto-stereoscopic displays, high dynamic range displays, and high-resolution displays. We achieve significant performance gains, and in some cases are able to process data that would be infeasible with existing methods.
机译:近年来,已经提出了一些令人兴奋的提议,这些提议令人兴奋,它们具有压缩性,因为它们会生成具有相对较少显示参数的高分辨率图像或光场。这些类型的显示器的图像合成涉及两个主要任务:采样和渲染高维目标图像,例如光场或随时间变化的光场,以及优化显示参数以提供目标内容的良好近似。在本文中,我们介绍了一种用于压缩显示的自适应优化框架,该框架仅使用全部全光样本的一小部分即可生成高质量的图像和光场。我们演示了用于多种显示技术的框架,包括几种类型的自动立体显示器,高动态范围显示器和高分辨率显示器。我们获得了显着的性能提升,并且在某些情况下能够处理现有方法无法实现的数据。

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