论文标题
茎噪声在视觉感知和图像质量测量中的作用
The Role of Stem Noise in Visual Perception and Image Quality Measurement
论文作者
论文摘要
本文考虑了扭曲和嘈杂图像的免费参考质量评估。具体而言，它考虑了可以评估任何图像的茎噪声的一阶和二阶统计。在图像质量评估（IQA）的研究领域中，茎噪声定义为自动回归（AR）过程的输入，从中可以恢复低能量和脱离相关版本的图像。为了估计AR模型参数和相关的茎噪声能量，使用Yule-Walker方程，以便可以将随附的自动相关函数（ACF）系数视为图像重建的模型参数。为了表征系统的信号依赖性和信号无关扭曲，可以通过图像评估茎噪声的平均值和方差。至关重要的是，本文表明，这些统计数据与人类图像质量等级有关。此外，在某些类型的图像失真下，茎噪声统计数据显示与已建立的图像质量衡量的相关性非常显着。
This paper considers reference free quality assessment of distorted and noisy images. Specifically, it considers the first and second order statistics of stem noise that can be evaluated given any image. In the research field of Image quality Assessment (IQA), the stem noise is defined as the input of an Auto Regressive (AR) process, from which a low-energy and de-correlated version of the image can be recovered. To estimate the AR model parameters and associated stem noise energy, the Yule-walker equations are used such that the accompanying Auto Correlation Function (ACF) coefficients can be treated as model parameters for image reconstruction. To characterize systematic signal dependent and signal independent distortions, the mean and variance of stem noise can be evaluated over the image. Crucially, this paper shows that these statistics have a predictive validity in relation to human ratings of image quality. Furthermore, under certain kinds of image distortion, stem noise statistics show very significant correlations with established measures of image quality.
