Quality assessment methods for perceptual video compression
Quality assessment methods for perceptual video compression
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DOI：
10.1109/icip.2013.6738009
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发表时间：
2013-09
期刊：
影响因子：
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通讯作者：
Fan Zhang;D. Bull
中科院分区：
文献类型：
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作者：
Fan Zhang;D. Bull
本文描述了一种用于感知视频压缩应用（PVM）的质量评估模型，该模型使用明显失真和模糊伪影的自适应组合来刺激视觉掩蔽和失真伪影感知。该方法比现有的基于VQEG数据库的质量指标有了显著的改进，并且由于其延迟和复杂性的属性，它提供了对下一代视频编解码器的环内速率质量优化的兼容性。性能比较针对一系列不同的失真类型进行验证。
This paper describes a quality assessment model for perceptual video compression applications (PVM), which stimulates visual masking and distortion-artefact perception using an adaptive combination of noticeable distortions and blurring artefacts. The method shows significant improvement over existing quality metrics based on the VQEG database, and provides compatibility with in-loop rate-quality optimisation for next generation video codecs due to its latency and complexity attributes. Performance comparison are validated against a range of different distortion types.