首页> 外文会议>SPIE Conference on Human Vision and Electronic Imaging >Application of a visual model to the design of an ultra-high definition upscaler
【24h】

Application of a visual model to the design of an ultra-high definition upscaler

机译:视觉模型在超高清Umscaler设计中的应用

获取原文

摘要

A Visual Model (VM) is used to aid in the design of an Ultra-high Definition (UHD) upscaling algorithm that renders High Definition legacy content on a UHD display. The costly development of such algorithms is due, in part, to the time spent subjectively evaluating the adjustment of algorithm structural variations and parameters. The VM provides an image map that gives feedback to the design engineer about visual differences between algorithm variations, or about whether a costly algorithm improvement will be visible at expected viewing distances. Such visual feedback reduces the need for subjective evaluation. This paper presents the results of experimentally verifying the VM against subjective tests of visibility improvement versus viewing distance for three upscaling algorithms. Observers evaluated image differences for upscaled versions of high-resolution stills and HD (Blu-ray) images, viewing a reference and test image, and controlled a linear blending weight to determine the image discrimination threshold. The required thresholds vs. viewing distance varied as expected, with larger amounts of the test image required at further distances. We verify the VM by comparison of predicted discrimination thresholds versus the subjective data. After verification, VM visible difference maps are presented to illustrate the practical use of the VM during design.
机译:视觉模型(VM)用于帮助设计超高清(UHD)UPSCING算法,该算法在UHD显示器上呈现高清遗留内容。这些算法的昂贵开发部分是部分地到期,到了主观评估算法结构变化和参数调整的时间。 VM提供了一个图像映射,其向设计工程师提供关于算法变化之间的视觉差异的反馈,或者关于在预期的观看距离下是否可见昂贵算法改进。这种视觉反馈减少了对主观评估的需求。本文提出了通过实验验证VM免受可见性改善的主观测试的结果,而是三个upcaling算法的观看距离。观察者评估用于查看参考和测试图像的高分辨率剧性和HD(蓝光)图像的上部版本的图像差异,并控制线性混合重量以确定图像辨别阈值。所需的阈值与观看距离如预期的变化,具有更大的测试图像,需要进一步距离。通过比较预测的辨别阈值与主观数据的比较,我们验证VM。验证后,提出了VM可见差异图,以说明VM在设计期间的实际使用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号