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Multidimensional Analysis Reveals Importance of Color for Image Quality

机译:多维分析揭示了图像质量颜色的重要性

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A psychophysical experiment was performed to determine the psychological dimensions involved in judging image quality. Seven different prints for each of two images, a portrait and a landscape, were produced using a combination of 5 printers and different paper types. The experiment consisted of two parts that were run concurrently. In the first part, paired-comparison was used to evaluate image preference. In the second part, judgments of similarity and dissimilarity were made using triad presentations. The paired-comparison data were analyzed using Thurstone's Law of Comparative Judgment and Dual Scaling, a multidimensional statistical technique that reveals the independent dimensions used in categorical judgments. The judgments of similarity and dissimilarity were analyzed using nonmetric multidimensional scaling. The results indicate that the psychological stimulus space can be characterized well in two dimensions. An ideal point model can be used to identify preference in this space. Variation in subjects' preferences can be characterized predominantly in one dimension and the subjects are fairly consistent in their response along this dimension. The psychological stimulus space correlated highly with color variation in the images. We conclude that multidimensional techniques can be used to analyze image preference and find relationships between psychological and physical variables relating to image quality. Specifically, our results indicate that color is of primary importance for judging image quality in our particular situation.
机译:进行了一个心理物理实验,以确定判断图像质量的心理维度。使用5个打印机和不同的纸张类型的组合生产两个图像,肖像和景观中的每一个的七种不同的印刷品。实验包括两部分,同时运行。在第一部分中,配对 - 比较用于评估图像偏好。在第二部分中,使用三合会介绍进行了相似性和异化的判断。使用Thursthone的比较判断和双缩放定律分析配对的比较数据,一种多维统计技术,揭示了分类判断中使用的独立尺寸。使用非化多数多维缩放分析了相似性和异化性的判断。结果表明,心理刺激空间可以在两个维度中表征良好。可以使用理想点模型来识别在该空间中的偏好。受试者偏好的变化可以主要在一个维度中表征,并且受试者在沿着该尺寸的响应中相当一致。心理刺激空间高度相关的图像中的颜色变化。我们得出结论,多维技术可用于分析图像偏好,并找到与图像质量有关的心理和物理变量之间的关系。具体而言,我们的结果表明,在我们的特定情况下,颜色对判断图像质量的重要性是重要的。

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