基于色貌的感知对比度评价方法及建模研究
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摘要
随着科技的进步和人们生活水平的提高,各种类型的显示设备在日常生活和工作中得到了广泛应用,而其颜色特性的评价已成为各种显示技术在激烈竞争中取胜的关键。其中,对比度更是显示设备性能评价的指标性参数。但是,传统的对比度评价方法大多侧重于亮度的物理测量,往往不能反映人眼视觉系统(HVS)的真实感知,也不适应于变化的观察条件。因此,本研究利用心理物理学实验方法获取简单图样的视觉亮度阈值以及亮度感知对比度评估数据,基于色貌模型建立了相应的亮度感知对比度模型。进而,通过对亮暗及彩色条纹对比灵敏度函数(CSF)的视觉测量,分析了空间频率及颜色特性对感知对比度的影响。最后,基于色貌模型和CSF,提出了复杂图像的感知对比度模型,并利用图像颜色外貌感知实验的视觉数据进行了测试和验证。
在视觉实验之前,首先对显示器的颜色特性进行了详细的测量与分析。对于不完全满足色品恒定性和通道相加性假设的大尺寸液晶显示器(LCD),采用局域三维查找法实现其颜色特征化,并提出了一种自适应实时搜索算法以提高其变换效率,特征化精度优于0.5△E*ab。对于阴极射线管(CRT)显示器,采用色品坐标变化的分段线性插值(PLVC)方法并结合抖动技术进行颜色特征化,特征化精度高达0.31AE*ab。对于近似满足两个假设条件的专业级Eizo LCD,采用了色品坐标不变的分段线性插值(PLCC)方法,特征化精度达到0.98AE*ab。
通过恒常刺激视觉评价实验方法并采用数据处理的概率分析法,分别获得9种不同观察条件下对均匀中性色背景下不同亮度水平的19个目标刺激的视觉亮度阈值,并采用四种不同的颜色属性量进行表征,即以cd/m2为单位的亮度L、CIELAB的明度L*、CIECAM02的明度J和视明度Q。由变异系数CV对其相应的阈值对比度表征方程的预测性能进行评价,结果表明,基于色貌属性量的表征方程在不同观察条件下与视觉数据有更好的一致性,为建立感知对比度模型提供了实验和理论支持。
基于幅值估计的心理物理学方法,分别实施了参考色样与测试色样观察条件相同(实验一)和参考色样观察条件固定(实验二)的感知对比度视觉评价实验,并通过视觉数据的拟合建立了亮度的感知对比度模型。建模的途径分为两类,一类是基于感知属性量特别是色貌属性量的对比度表征,另一类是基于恰可察觉亮度阶数的对比度表征。通过标准化残差平方和(STRESS)及F-test对不同模型预测性能的检验和比较可知,基于CIECAM02视明度Q的对比度模型CQ相比其他模型更加符合人眼视觉系统的非线性感知特性,并且对不同观察条件的适应性较好,因此可以推荐为实际应用中所采用的感知对比度模型,以取代传统的亮度对比率公式。为了方便地应用CQ模型于LCD对比度性能的评价,设计了圆斑测试图样,并提出了结合LCD色度预测模型的感知对比度评价流程,最后经视觉数据的实际测试,验证了其预测过程的可行性和预测性能的有效性。
利用交叉阶梯法在CRT显示器上分别测得灰色中心及有彩颜色中心在0.5-11.7cpd空间频率范围内的亮度/明度及彩色对比度阈值,并拟合得到不同颜色中心的CSF以及不同空间频率下的彩色对比度阈值色度椭圆,分析了空间频率及颜色特性对对比度感知的影响。其间,提出了基于色差定义的统一量度的明度CSF和彩度CSF,并基于Barten模型建立了不同明度水平的明度CSF数学模型。
采用类别判断的心理物理学实验方法对包含空间频率信息和颜色信息的复杂图像的颜色外貌属性进行了视觉评估,包括图像质量、对比度、色彩度、锐度、自然性以及全局对比度和局部对比度。在对图像感知对比度及其影响因素进行分析的基础上,提出了基于CSF空间频率适应和色貌模型的图像感知对比度模型S-PBCDR-Ⅰ和S-PBCDR-Ⅱ并与相对单图像感知对比度模型△SIPk和基于像素色差比的PBCDR模型进行了比较。经过视觉数据的检验,S-PBCDR-Ⅰ模型表现出相对最优的图像感知对比度预测性能,更加简便实用。
最后,对本论文的主要内容以及所取得的主要研究成果予以概括总结,并对今后进一步的研究工作进行了展望。
Various types of display devices have been extensively applied in daily life and work with the development of science and technology and the improvement of the living standard. And the evaluations of their color characteristics have become the key to win in the hot competition among different display technologies. Hereinto, contrast is the representative parameter for the performance evaluation of displays. However, the traditional evaluation methods of contrast emphasize more on the physical measurement of luminance, which usually deviate from the real perception of the human visual system (HVS) and do not adapt to the variations of viewing conditions. Hereby, by performing the psychophysical experiments in this study, plenty of data were obtained for the visual threshold and perceptual contrast via simple neutral color patterns, so that the corresponding perceptual contrast models were built based on the color appearance model. Then the impact of spatial frequency and color on the perceptual contrast were analyzed through the visual measurements of the contrast sensitivity functions (CSF) of luminance and color grating patterns. Lastly, on the basis of the color appearance model and CSF, the perceptual contrast model of complex image was proposed, which was tested and verified using the visual data of image color appearance perception experiments.
The color characteristics of displays were first measured and analyzed in detail before the visual experiments. For the large size liquid crystal displays (LCD) which do not fully meet the two assumptions of chromaticity constancy and channel additivity, the method of local three-dimension look-up table was adopted for their colorimetric characterization, and an auto-adaptation real-time searching algorithm was developed to promote the transformation efficiency with the characterization accuracy being better than0.5CIELAB color difference unit (△E*ab). For the cathode ray tube (CRT) display, the method of piecewise linear interpolation assuming variation in chromaticity coordinates (PLVC) combined with the dithering technique was implemented to achieve the high colorimetric characterization accuracy of0.31 △E*ab. The professional Eizo LCD. which approximately satisfies the two mentioned assumptions, was colorimetrically characterized using the method of piecewise linear interpolation assuming constant chromaticity coordinates (PLCC) to result in the characterization accuracy of0.98△E ab.
The visual thresholds of19target stimuli with different lightness levels on the uniform neutral color background under9viewing conditions were measured using the psychophysical method of constant stimuli and data processing technique of probit analysis, which were represented by four different color attributes, i.e. luminance L in cd/m2, CIELAB lightness L*, CIECAM02lightness J and brightness Q. The prediction performances of different representation equations for visual threshold contrast were tested via the coefficient of variation (CV). which results indicated that the representation equations based on color appearance attributes were in better agreement with the visual data under different viewing conditions. This provided the experimental and theoretical supports for modeling the perceptual contrast.
Based on the principle of the magnitude estimation method, two perceptual contrast assessment experiments were carried out, respectively, i.e. Experiment No.1with the reference and the test patterns under the same viewing condition and Experiment No.2with the reference pattern under the fixed viewing condition. Then two categories of perceptual contrast models were established through the fitting of visual data. One category is represented using the perceptual attributes especially the color appearance attributes, and another representation is based on the steps of the just noticeable difference (JND) of luminance. The prediction performance of these models were tested and compared by the ways of standardized residual sum of squares (STRESS) and F-test, and the results showed that the contrast model CQ adopting the CIECAM02brightness Q agreed better with the nonlinear perception characteristics of HVS than the other models and was well adaptive to different viewing conditions. Therefore, the CQ model may be suggested as the perceptual contrast model in practical applications to replace the traditional luminance ratio. In order to apply the CQ conveniently into the contrast evaluation of LCD. the spot test patterns were designed and the evaluation workflow involving the chromaticity prediction model of LCDs was proposed, of which the feasibility of the prediction procedure and the validity of the prediction performance were verified via the practical test of visual data.
Utilizing the psychophysical method of interleaved staircase, the luminance/lightness and color contrast thresholds were measured, respectively, at gray and chromatic color centers with the spatial frequency ranged from0.5to11.7cpd on the CRT display. And the CSFs of different color centers and the chromaticity ellipses for color contrast thresholds at different spatial frequencies were obtained by fitting with the visual data. Then the influences of spatial frequency and chromacity on the contrast perception were analyzed. Meanwhile, the lightness and chromatic CSFs defined in the same scale by color difference were proposed, and the mathematic model of lightness CSF of different lightness levels at gray center was built from the Barten model.
The complex images usually involve plenty of spatial and color information. Through the psychophysical method of category judgments, the image color appearance attributes were visually estimated, including image quality, contrast, colorfulness, sharpness, naturalness, global contrast and local contrast. On the top of the analysis of the image perceptual contrast and its influence factors, two image perceptual contrast models S-PBCDR-Ⅰ and S-PBCDR-Ⅱ were proposed, respectively. based on the CSF spatial adaptation and the color appearance model, and they were further compared with the relative single-image perceived contrast model△SIPk and the pixel-based color difference ratio model PBCDR. Through the test of visual data, the model S-PBCDR-Ⅰ exhibited best prediction performance in the perception of image contrast among all the models and was more simple and convenient as well in applications.
Finally, the main contents and research achievements of this dissertation were summarized, and the perspectives of the future study were also forecasted.
在视觉实验之前,首先对显示器的颜色特性进行了详细的测量与分析。对于不完全满足色品恒定性和通道相加性假设的大尺寸液晶显示器(LCD),采用局域三维查找法实现其颜色特征化,并提出了一种自适应实时搜索算法以提高其变换效率,特征化精度优于0.5△E*ab。对于阴极射线管(CRT)显示器,采用色品坐标变化的分段线性插值(PLVC)方法并结合抖动技术进行颜色特征化,特征化精度高达0.31AE*ab。对于近似满足两个假设条件的专业级Eizo LCD,采用了色品坐标不变的分段线性插值(PLCC)方法,特征化精度达到0.98AE*ab。
通过恒常刺激视觉评价实验方法并采用数据处理的概率分析法,分别获得9种不同观察条件下对均匀中性色背景下不同亮度水平的19个目标刺激的视觉亮度阈值,并采用四种不同的颜色属性量进行表征,即以cd/m2为单位的亮度L、CIELAB的明度L*、CIECAM02的明度J和视明度Q。由变异系数CV对其相应的阈值对比度表征方程的预测性能进行评价,结果表明,基于色貌属性量的表征方程在不同观察条件下与视觉数据有更好的一致性,为建立感知对比度模型提供了实验和理论支持。
基于幅值估计的心理物理学方法,分别实施了参考色样与测试色样观察条件相同(实验一)和参考色样观察条件固定(实验二)的感知对比度视觉评价实验,并通过视觉数据的拟合建立了亮度的感知对比度模型。建模的途径分为两类,一类是基于感知属性量特别是色貌属性量的对比度表征,另一类是基于恰可察觉亮度阶数的对比度表征。通过标准化残差平方和(STRESS)及F-test对不同模型预测性能的检验和比较可知,基于CIECAM02视明度Q的对比度模型CQ相比其他模型更加符合人眼视觉系统的非线性感知特性,并且对不同观察条件的适应性较好,因此可以推荐为实际应用中所采用的感知对比度模型,以取代传统的亮度对比率公式。为了方便地应用CQ模型于LCD对比度性能的评价,设计了圆斑测试图样,并提出了结合LCD色度预测模型的感知对比度评价流程,最后经视觉数据的实际测试,验证了其预测过程的可行性和预测性能的有效性。
利用交叉阶梯法在CRT显示器上分别测得灰色中心及有彩颜色中心在0.5-11.7cpd空间频率范围内的亮度/明度及彩色对比度阈值,并拟合得到不同颜色中心的CSF以及不同空间频率下的彩色对比度阈值色度椭圆,分析了空间频率及颜色特性对对比度感知的影响。其间,提出了基于色差定义的统一量度的明度CSF和彩度CSF,并基于Barten模型建立了不同明度水平的明度CSF数学模型。
采用类别判断的心理物理学实验方法对包含空间频率信息和颜色信息的复杂图像的颜色外貌属性进行了视觉评估,包括图像质量、对比度、色彩度、锐度、自然性以及全局对比度和局部对比度。在对图像感知对比度及其影响因素进行分析的基础上,提出了基于CSF空间频率适应和色貌模型的图像感知对比度模型S-PBCDR-Ⅰ和S-PBCDR-Ⅱ并与相对单图像感知对比度模型△SIPk和基于像素色差比的PBCDR模型进行了比较。经过视觉数据的检验,S-PBCDR-Ⅰ模型表现出相对最优的图像感知对比度预测性能,更加简便实用。
最后,对本论文的主要内容以及所取得的主要研究成果予以概括总结,并对今后进一步的研究工作进行了展望。
Various types of display devices have been extensively applied in daily life and work with the development of science and technology and the improvement of the living standard. And the evaluations of their color characteristics have become the key to win in the hot competition among different display technologies. Hereinto, contrast is the representative parameter for the performance evaluation of displays. However, the traditional evaluation methods of contrast emphasize more on the physical measurement of luminance, which usually deviate from the real perception of the human visual system (HVS) and do not adapt to the variations of viewing conditions. Hereby, by performing the psychophysical experiments in this study, plenty of data were obtained for the visual threshold and perceptual contrast via simple neutral color patterns, so that the corresponding perceptual contrast models were built based on the color appearance model. Then the impact of spatial frequency and color on the perceptual contrast were analyzed through the visual measurements of the contrast sensitivity functions (CSF) of luminance and color grating patterns. Lastly, on the basis of the color appearance model and CSF, the perceptual contrast model of complex image was proposed, which was tested and verified using the visual data of image color appearance perception experiments.
The color characteristics of displays were first measured and analyzed in detail before the visual experiments. For the large size liquid crystal displays (LCD) which do not fully meet the two assumptions of chromaticity constancy and channel additivity, the method of local three-dimension look-up table was adopted for their colorimetric characterization, and an auto-adaptation real-time searching algorithm was developed to promote the transformation efficiency with the characterization accuracy being better than0.5CIELAB color difference unit (△E*ab). For the cathode ray tube (CRT) display, the method of piecewise linear interpolation assuming variation in chromaticity coordinates (PLVC) combined with the dithering technique was implemented to achieve the high colorimetric characterization accuracy of0.31 △E*ab. The professional Eizo LCD. which approximately satisfies the two mentioned assumptions, was colorimetrically characterized using the method of piecewise linear interpolation assuming constant chromaticity coordinates (PLCC) to result in the characterization accuracy of0.98△E ab.
The visual thresholds of19target stimuli with different lightness levels on the uniform neutral color background under9viewing conditions were measured using the psychophysical method of constant stimuli and data processing technique of probit analysis, which were represented by four different color attributes, i.e. luminance L in cd/m2, CIELAB lightness L*, CIECAM02lightness J and brightness Q. The prediction performances of different representation equations for visual threshold contrast were tested via the coefficient of variation (CV). which results indicated that the representation equations based on color appearance attributes were in better agreement with the visual data under different viewing conditions. This provided the experimental and theoretical supports for modeling the perceptual contrast.
Based on the principle of the magnitude estimation method, two perceptual contrast assessment experiments were carried out, respectively, i.e. Experiment No.1with the reference and the test patterns under the same viewing condition and Experiment No.2with the reference pattern under the fixed viewing condition. Then two categories of perceptual contrast models were established through the fitting of visual data. One category is represented using the perceptual attributes especially the color appearance attributes, and another representation is based on the steps of the just noticeable difference (JND) of luminance. The prediction performance of these models were tested and compared by the ways of standardized residual sum of squares (STRESS) and F-test, and the results showed that the contrast model CQ adopting the CIECAM02brightness Q agreed better with the nonlinear perception characteristics of HVS than the other models and was well adaptive to different viewing conditions. Therefore, the CQ model may be suggested as the perceptual contrast model in practical applications to replace the traditional luminance ratio. In order to apply the CQ conveniently into the contrast evaluation of LCD. the spot test patterns were designed and the evaluation workflow involving the chromaticity prediction model of LCDs was proposed, of which the feasibility of the prediction procedure and the validity of the prediction performance were verified via the practical test of visual data.
Utilizing the psychophysical method of interleaved staircase, the luminance/lightness and color contrast thresholds were measured, respectively, at gray and chromatic color centers with the spatial frequency ranged from0.5to11.7cpd on the CRT display. And the CSFs of different color centers and the chromaticity ellipses for color contrast thresholds at different spatial frequencies were obtained by fitting with the visual data. Then the influences of spatial frequency and chromacity on the contrast perception were analyzed. Meanwhile, the lightness and chromatic CSFs defined in the same scale by color difference were proposed, and the mathematic model of lightness CSF of different lightness levels at gray center was built from the Barten model.
The complex images usually involve plenty of spatial and color information. Through the psychophysical method of category judgments, the image color appearance attributes were visually estimated, including image quality, contrast, colorfulness, sharpness, naturalness, global contrast and local contrast. On the top of the analysis of the image perceptual contrast and its influence factors, two image perceptual contrast models S-PBCDR-Ⅰ and S-PBCDR-Ⅱ were proposed, respectively. based on the CSF spatial adaptation and the color appearance model, and they were further compared with the relative single-image perceived contrast model△SIPk and the pixel-based color difference ratio model PBCDR. Through the test of visual data, the model S-PBCDR-Ⅰ exhibited best prediction performance in the perception of image contrast among all the models and was more simple and convenient as well in applications.
Finally, the main contents and research achievements of this dissertation were summarized, and the perspectives of the future study were also forecasted.
引文
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