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CID2013: A Database for Evaluating No-Reference Image Quality Assessment Algorithms

机译:CID2013:用于评估无参考图像质量评估算法的数据库

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This paper presents a new database, CID2013, to address the issue of using no-reference (NR) image quality assessment algorithms on images with multiple distortions. Current NR algorithms struggle to handle images with many concurrent distortion types, such as real photographic images captured by different digital cameras. The database consists of six image sets; on average, 30 subjects have evaluated 12–14 devices depicting eight different scenes for a total of 79 different cameras, 480 images, and 188 subjects (67% female). The subjective evaluation method was a hybrid absolute category rating-pair comparison developed for the study and presented in this paper. This method utilizes a slideshow of all images within a scene to allow the test images to work as references to each other. In addition to mean opinion score value, the images are also rated using sharpness, graininess, lightness, and color saturation scales. The CID2013 database contains images used in the experiments with the full subjective data plus extensive background information from the subjects. The database is made freely available for the research community.
机译:本文提出了一个新的数据库CID2013,以解决在多重失真的图像上使用无参考(NR)图像质量评估算法的问题。当前的NR算法难以处理具有许多并发失真类型的图像,例如由不同数码相机捕获的真实摄影图像。该数据库由六个图像集组成;平均而言,有30位受试者评估了12-14种设备,这些设备描绘了8种不同的场景,总共有79种相机,480张图像和188位受试者(女性占67%)。主观评价方法是为本研究开发并在本文中介绍的混合绝对类别评级对比较。该方法利用场景中所有图像的幻灯片显示,以使测试图像相互参照。除了平均意见得分值外,还使用清晰度,颗粒度,亮度和色彩饱和度等级对图像进行评级。 CID2013数据库包含用于实验的图像,其中包含完整的主观数据以及受试者的广泛背景信息。该数据库可免费提供给研究社区。

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