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首页> 外文期刊>Journal of visual communication & image representation >Spatial pooling for measuring color printing quality attributes
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Spatial pooling for measuring color printing quality attributes

机译：用于测量彩色打印质量属性的空间合并

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摘要

Many objective image quality assessment algorithms firstly apply quality metrics in local regions that results in a quality map, and then pool the quality values in the quality map into a single quality score. The simplest pooling method is the average of quality values, which assumes that all the quality values are independent and equally important. However, visual perception is so complex that the assumption underlying average pooling might be too strict. There is an agreement that some regions in the images might be more perceptually significant, which leads to more advanced spatial pooling methods. In this work we evaluate existing spatial pooling methods for five important quality attributes, which are proposed to reduce the complexity of image quality assessment. The results show that: (1) more advanced spatial pooling methods are generally better than simple average; (2) spatial pooling depends on both image quality metrics and the attributes of the image.
机译：许多客观的图像质量评估算法首先在局部区域应用质量度量，从而生成质量图，然后将质量图中的质量值合并为一个质量得分。最简单的合并方法是质量值的平均值，它假定所有质量值都是独立且同等重要的。但是，视觉感知是如此复杂，以至于平均池化的假设可能过于严格。达成共识，图像中的某些区域可能在感知上更重要，这导致了更高级的空间合并方法。在这项工作中，我们评估了五个重要质量属性的现有空间池化方法，这些方法旨在降低图像质量评估的复杂性。结果表明：（1）更先进的空间池化方法通常要优于简单平均法； （2）空间汇集取决于图像质量指标和图像属性。

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