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首页> 外文会议>Image Quality and System Performance IV; Proceedings of SPIE-The International Society for Optical Engineering; vol.6494; Electronic Imaging Science and Technology >Investigation of two Methods to quantify Noise in digital Images based on the Perception of the human Eye
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Investigation of two Methods to quantify Noise in digital Images based on the Perception of the human Eye

机译：基于人眼感知的两种量化数字图像噪声的方法的研究

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摘要

Since the signal to noise measuring method as standardized in the normative part of ISO 15739:2002(E) does not quantify noise in a way that matches the perception of the human eye, two alternative methods have been investigated which may be appropriate to quantify the noise perception in a physiological manner:- the model of visual noise measurement proposed by Hung et al (as described in the informative annex of ISO 15739:2002 ) which tries to simulate the process of human vision by using the opponent space and contrast sensitivity functions and uses the CIEL*u*v*1976 colour space for the determination of a so called visual noise value.- The S-CIELab model and CIEDE2000 colour difference proposed by Fairchild et al which simulates human vision approximately the same way as Hung et al but uses an image comparison afterwards based on CIEDE2000. With a psychophysical experiment based on just noticeable difference (JND), threshold images could be defined, with which the two approaches mentioned above were tested. The assumption is that if the method is valid, the different threshold images should get the same 'noise value'.The visual noise measurement model results in similar visual noise values for all the threshold images. The method is reliable to quantify at least the JND for noise in uniform areas of digital images. While the visual noise measurement model can only evaluate uniform colour patches in images, the S-CIELab model can be used on images with spatial content as well. The S-CIELab model also results in similar colour difference values for the set of threshold images, but with some limitations: for images which contain spatial structures besides the noise, the colour difference varies depending on the contrast of the spatial content.
机译：由于ISO 15739：2002（E）规范部分中标准化的信噪比测量方法无法以与人眼感知相匹配的方式对噪声进行量化，因此已研究了两种适合量化噪声的方法。以生理方式进行噪声感知：-Hung等人提出的视觉噪声测量模型（如ISO 15739：2002的信息性附录中所述），该模型试图通过使用对手空间和对比敏感度函数来模拟人类视觉的过程并使用CIEL * u * v * 1976色彩空间来确定所谓的视觉噪声值。-Fairchild等人提出的S-CIELab模型和CIEDE2000色差与Hung等人的模拟方法大致相同但之后基于CIEDE2000使用图像比较。通过仅基于显着差异（JND）的心理物理实验，就可以定义阈值图像，并用其测试上述两种方法。假设如果该方法有效，则不同的阈值图像应获得相同的“噪声值”。视觉噪声测量模型对所有阈值图像产生相似的视觉噪声值。该方法可靠地至少量化JND以消除数字图像均匀区域中的噪声。视觉噪声测量模型只能评估图像中的均匀色块，而S-CIELab模型也可以用于具有空间内容的图像。 S-CIELab模型对于阈值图像集也产生相似的色差值，但有一些限制：对于除噪声外还包含空间结构的图像，色差会根据空间内容的对比度而变化。

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