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Full-reference image quality assessment by combining global and local distortion measures

机译：通过结合全局和局部失真措施进行全参考图像质量评估

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摘要

Full-reference image quality assessment (FR-IQA) techniques compare a reference and a distorted/test image and predict the perceptual quality of the test image in terms of an objective score. Evaluation of FR-IQA techniques is carried out by comparing the objective score with the image's subjective score obtained through human observer ratings. The goal of an observer is to rate the distortion present in the test images. The goal oriented tasks are processed by the human visual system (HVS) through top-down processing which actively searches for local distortions driven by the goal. Therefore local distortion measurement is important for the top-down processing. Simultaneous bottom-up processing also takes place signifying spontaneous visual functions in the HVS. To account for this, global perceptual features can be used. Therefore, we hypothesize that the objective score for an image can be derived from the combination of local and global distortion measures calculated from the reference and test images. We calculate the local distortion by measuring the local correlation differences from the gradient and contrast information. For global distortion, dissimilarity of the saliency maps computed from a bottom-up model of saliency is used. Experimental analysis conducted in six benchmark databases suggest the effectiveness of the proposed approach.
机译：全参考图像质量评估（FR-IQA）技术将参考图像和失真/测试图像进​​行比较，并根据客观得分预测测试图像的感知质量。 FR-IQA技术的评估是通过将客观评分与通过人类观察者评分获得的图像主观评分进行比较来进行的。观察者的目的是评估测试图像中存在的失真。面向目标的任务由人类视觉系统（HVS）通过自上而下的处理过程进行处理，该过程主动搜索由目标驱动的局部变形。因此，局部失真测量对于自顶向下的处理很重要。同时进行自下而上的处理，表示HVS中的自发视觉功能。为了解决这个问题，可以使用全局感知功能。因此，我们假设可以从参考图像和测试图像计算出的局部和全局失真度量的组合中得出图像的客观得分。我们通过测量来自梯度和对比度信息的局部相关差异来计算局部失真。对于全局失真，使用从自下而上的显着性模型计算出的显着性图的不相似性。在六个基准数据库中进行的实验分析表明了该方法的有效性。

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