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A Novel Approach for Computing Quality Map of Visual Information Fidelity Index

机译:一种用于计算视觉信息保真度指数质量图的新方法

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The visual information fidelity (VIF) index gained widespread popularity as a tool to assess the quality of images and to evaluate the performance of image processing algorithms and systems. But VIF is not a map-based quality metric if its quality map is calculated by traditional sliding window approach. This map-based property is owned by the other quality metrics such as structural similarity (SSIM) and mean-squared error (MSE). In this article, we first construct a novel VIF quality map in pixel domain, which makes VIF become a Minkowski norm of its quality map. Furthermore, we deduce the gradient of VIF by taking the derivative of VIF index with respect to the reference image. The gradient of VIF is easy to calculate and has many useful applications. Experimental results show that the proposed quality map can provide useful guidance on how local image quality is similar to reference image.
机译:Visual Information Fidelity(VIF)指数获得了广泛的流行度作为评估图像质量的工具,并评估图像处理算法和系统的性能。但如果通过传统的滑动窗口方法计算其质量图,VIF不是基于地图的质量指标。基于地图的属性由其他质量指标所拥有,例如结构相似度(SSIM)和均值平方错误(MSE)。在本文中,我们首先在像素域中构建一个新的VIF质量图,它使VIF成为其质量图的Minkowski标准。此外,我们通过参考图像的VIF指数的衍生来推导VIF的梯度。 VIF的梯度易于计算,并且具有许多有用的应用。实验结果表明,所提出的质量图可以提供有关局部图像质量如何与参考图像相似的有用指导。

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