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首页> 外文期刊>Journal of Imaging Science and Technology >A Novel Weight Pooling Method for Objective Image Quality Assessment with the Luminance Adaptation Effect in the Pixel Intensity Domain
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A Novel Weight Pooling Method for Objective Image Quality Assessment with the Luminance Adaptation Effect in the Pixel Intensity Domain

机译：像素强度域中具有亮度自适应效应的客观图像质量评估的新权重池方法

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摘要

Human Visual System (HVS) contains some important psychophysical characteristics and the most important among those are the contrast sensitivity function and luminance adaptation (LA) effect, that can potentially be used for modeling better image quality assessment (IQA) methods. As a result, some existing IQA methods have intrinsically adopted the Weber's law model to reflect the LA effects. But the authors have found that the way of adopting the LA effect was inappropriate. Recent psychophysical studies reveal that the Weber's law model is unable to be precisely fitted in the measured data for the LA effect. Furthermore, most IQA methods attempt to measure the quality in the pixel intensity domain, while the Weber's law works in the luminance domain and pixel intensity domain has a nonlinear relationship with the luminance domain. To address these problems, the authors derive a new LA effect model in the pixel intensity domain. Based on their derived LA effect model, the authors propose a new weight pooling method for the LA effect, denoted as LA-based Local weight Function (LALF). Their comprehensive experimental results prove that LALF can easily be applied in existing FR-IQA methods and it significantly improves the performance of the base methods in which LALF is applied. (C) 2019 Society for Imaging Science and Technology.
机译：人类视觉系统（HVS）包含一些重要的心理物理特征，其中最重要的是对比度敏感度函数和亮度适应（LA）效果，可潜在地用于建模更好的图像质量评估（IQA）方法。结果，一些现有的IQA方法本质上采用了韦伯定律模型来反映LA效应。但是作者发现采用洛杉矶效应的方法是不合适的。最近的心理物理学研究表明，韦伯定律模型无法精确地拟合到LA效应的测量数据中。此外，大多数IQA方法尝试在像素强度域中测量质量，而韦伯定律在亮度域中起作用，而像素强度域与亮度域具有非线性关系。为了解决这些问题，作者在像素强度域中导出了一个新的LA效应模型。基于他们导出的LA效应模型，作者提出了一种新的LA效应权重合并方法，称为基于LA的局部权重函数（LALF）。他们的综合实验结果证明，LALF可以轻松地应用于现有的FR-IQA方法中，并且显着提高了应用LALF的基本方法的性能。 （C）2019影像科学与技术学会。

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