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Coded image quality assessment based on a new contrast masking model

机译:基于新对比度掩盖模型的编码图像质量评估

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摘要

The use of computational metrics to control and assess the visual quality of digital images is we/I known. This paper presents a quality metric including a visual channels representation and a new contrast masking model. Based on the measure of maximum quantization steps without visual impairments, the model considers both intrachannel and interchannel masking and is derived from extensive experiments conducted on noise and texture images instead of simple sinusoidal stimuli. The metric parameters are optimized in order to maximize the linear correlation coefficient as well as the Spearman rank-order correlation between the computed quality measures and the mean opinion score.
机译:使用计算指标来控制和评估数字图像的视觉质量是我们已知的。本文提出了一种质量指标,其中包括视觉通道表示和新的对比度蒙版模型。基于没有视觉障碍的最大量化步长的度量,该模型同时考虑了通道内和通道间的掩盖,并且是根据对噪声和纹理图像(而不是简单的正弦刺激)进行的广泛实验得出的。对度量参数进行了优化,以使线性相关系数以及计算的质量度量和平均意见得分之间的Spearman等级相关性最大化。

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