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A Detail Based Method for Linear Full Reference Image Quality Prediction

机译:基于细节的线性全参考图像质量预测方法

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摘要

In this paper, a novel Full Reference method is proposed for image quality assessment, using the combination of two separate metrics to measure the perceptually distinct impact of detail losses and of spurious details. To this purpose, the gradient of the impaired image is locally decomposed as a predicted version of the original gradient, plus a gradient residual. It is assumed that the detail attenuation identifies the detail loss, whereas the gradient residuals describe the spurious details. It turns out that the perceptual impact of detail losses is roughly linear with the loss of the positional Fisher information, while the perceptual impact of the spurious details is roughly proportional to a logarithmic measure of the signal to residual ratio. The affine combination of these two metrics forms a new index strongly correlated with the empirical Differential Mean Opinion Score (DMOS) for a significant class of image impairments, as verified for three independent popular databases. The method allowed alignment and merging of DMOS data coming from these different databases to a common DMOS scale by affine transformations. Unexpectedly, the DMOS scale setting is possible by the analysis of a single image affected by additive noise.
机译:在本文中,提出了一种新颖的完全参考方法来进行图像质量评估,该方法使用两个单独的指标的组合来测量细节损失和虚假细节在感知上的明显影响。为此,将受损图像的梯度局部分解为原始梯度的预测版本,再加上梯度残差。假设细节衰减标识了细节损失,而梯度残差描述了虚假细节。事实证明,细节损失的感知影响与位置Fisher信息的损失大致成线性关系,而虚假细节的感知影响与信号与残差比的对数度量大致成比例。这两个指标的仿射组合形成了一个新的指数,该指数与显着类别的图像损伤的经验差分平均观点得分(DMOS)密切相关,这已针对三个独立的流行数据库进行了验证。该方法允许通过仿射变换将来自这些不同数据库的DMOS数据对齐和合并到通用DMOS规模。出乎意料的是,通过分析受加性噪声影响的单个图像,可以设置DMOS标度。

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