Visual Quality Assessment of Video and Image Sequences-A Human-based Approach
Visual Quality Assessment of Video and Image Sequences-A Human-based Approach
复制标题
视频和图像序列的视觉质量评估——基于人的方法
DOI：
10.1007/s11265-008-0289-0
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
Al-Najdawi A
中科院分区：
文献类型：
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作者：
Al-Najdawi A
大多数当前的质量评估技术将图像质量解释为其与另一参考图像的保真度的度量，假设该“完美”图像的可用性。基于人眼视觉感知的图像序列质量评价算法一直是国内外众多研究者关注的问题。本文提出了一种新的技术，用于定量评估图像序列的质量，而不需要一个参考图像，并在某种程度上，准确地与人类的质量判断。这项研究是一个更大框架的一部分，该框架结合了多目标优化算法，以优化自动驾驶汽车获取的压缩视频的质量指标，并通过低带宽通信信道传输。我们的系统在一个数据集上进行了训练，该数据集涉及5个不同类别的700个视频。我们验证了我们的模型的性能，并表明它高度相关的人的主观质量评估。
Most of the current quality assessment techniques interpret an image quality as a measure of its fidelity with another reference image, assuming the availability of that “perfect” image. It has been the concern of many researchers around the world to algorithmically assess the quality of image sequences based on human visual perception. This paper presents a novel technique for quantitatively assessing the quality of image sequences without the need for a reference image and in a way that precisely correlates to human judgement on quality. This research is a part of a larger framework that incorporates multi-objective optimisation algorithms to optimise the quality metrics of compressed videos acquired by autonomous vehicles and transmitted over low-bandwidth communication channels. Our system was trained on a dataset that involved 700 videos of 5 different categories. We validate the performance of our model and show that it highly correlates to the human subjective quality assessment.