Quality Assessment of Thumbnail and Billboard Images on Mobile Devices

Zeina Sinno, Anush K. Moorthy, J. D. Cock, Zhi Li, A. Bovik
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引用次数: 1

Abstract

Objective image quality assessment (IQA) research entails developing algorithms that predict human judgments of picture quality. Validating performance entails evaluating algorithms under conditions similar to where they are deployed. Hence, creating image quality databases representative of target use cases is an important endeavor. Here we present a database that relates to quality assessment of billboard images commonly displayed on mobile devices. Billboard images are a subset of thumbnail images, that extend across a display screen, representing things like album covers, banners, or frames or artwork. We conducted a subjective study of the quality of billboard images distorted by processes like compression, scaling and chroma-subsampling, and compared high-performance quality prediction models on the images and subjective data.
移动设备上缩略图和广告牌图像的质量评估
客观图像质量评估(IQA)研究需要开发预测人类对图像质量判断的算法。验证性能需要在与部署算法相似的条件下评估算法。因此,创建代表目标用例的图像质量数据库是一项重要的工作。在这里,我们提出了一个数据库,涉及到通常显示在移动设备上的广告牌图像的质量评估。广告牌图像是缩略图图像的一个子集,它在显示屏幕上延伸,代表诸如专辑封面、横幅、框架或艺术品之类的东西。我们对经过压缩、缩放和色度子采样等处理后的广告牌图像进行了主观质量研究,并比较了基于图像和主观数据的高性能质量预测模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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