VSI: A Visual Saliency-Induced Index for Perceptual Image Quality Assessment
VSI: A Visual Saliency-Induced Index for Perceptual Image Quality Assessment
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VSI：用于感知图像质量评估的视觉显着性诱导指数
DOI：
10.1109/tip.2014.2346028
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发表时间：
2014-10-01
影响因子：
10.6
通讯作者：
Li, Hongyu
中科院分区：
文献类型：
--
作者：
Zhang, Lin;Shen, Ying;Li, Hongyu
感知图像质量评估（IQA）的目的是使用计算模型来衡量图像质量与主观评价一致。视觉显着性（VS）在过去的十年中已经被心理学家，神经生物学家和计算机科学家广泛研究，以调查图像的哪些区域会吸引人类视觉系统的注意力。直觉上，VS与IQA密切相关，因为阈上失真可以在很大程度上影响图像的VS图。考虑到这一点，我们提出了一个简单但非常有效的全参考IQA方法使用VS。在我们提出的IQA模型中，VS的作用是双重的。首先，VS被用作计算失真图像的局部质量图时的特征。第二，当池化质量分数时，采用VS作为加权函数以反映局部区域的重要性。建议的IQA指数被称为视觉显着性为基础的指数（VSI）。几个突出的计算VS模型已经在IQA的上下文中进行了研究，并选择了最好的一个用于VSI。在四个大型基准数据库上进行的大量实验表明，所提出的IQA指数VSI在预测精度方面比我们可以找到的所有最先进的IQA指数都要好，同时保持适度的计算复杂度。VSI的MATLAB源代码和评估结果可在http://sse.tongji.edu.cn/linzhang/IQA/VSI/VSI.htm在线公开获得。
Perceptual image quality assessment (IQA) aims to use computational models to measure the image quality in consistent with subjective evaluations. Visual saliency (VS) has been widely studied by psychologists, neurobiologists, and computer scientists during the last decade to investigate, which areas of an image will attract the most attention of the human visual system. Intuitively, VS is closely related to IQA in that suprathreshold distortions can largely affect VS maps of images. With this consideration, we propose a simple but very effective full reference IQA method using VS. In our proposed IQA model, the role of VS is twofold. First, VS is used as a feature when computing the local quality map of the distorted image. Second, when pooling the quality score, VS is employed as a weighting function to reflect the importance of a local region. The proposed IQA index is called visual saliency-based index (VSI). Several prominent computational VS models have been investigated in the context of IQA and the best one is chosen for VSI. Extensive experiments performed on four largescale benchmark databases demonstrate that the proposed IQA index VSI works better in terms of the prediction accuracy than all state-of-the-art IQA indices we can find while maintaining a moderate computational complexity. The MATLAB source code of VSI and the evaluation results are publicly available online at http://sse.tongji.edu.cn/linzhang/IQA/VSI/VSI.htm.