基于视觉感知的影像质量评价方法研究
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摘要
影像质量评价旨在寻找精确的计算模型来预测影像视觉质量的变化。影像是利用各种观测系统以不同形式刻画客观世界而获得的视觉实体。它相对于文字和图形所承载的信息更真切、更丰富,正所谓“百闻不如一见”。由于影像数据在采集、压缩、处理、传输和恢复的过程中可能会引入各种失真,这些失真会对后续的影像处理、分析和理解带来困难,不利于人们正确的认识客观世界。因此,需要通过度量影像的视觉失真程度,来设计方法和优化系统,以最少的代价提供最好的视觉质量。
本文针对影像质量评价的基本问题,探索人类视觉系统和数字信息之间的联系,在图像稀疏表示和特征建模的基础上,为影像处理中由未知因素造成的各种失真构建客观评价方法,以度量影像的失真程度和提供信息的能力,从而为视觉质量评价提供合理依据。主要工作概括如下:
(1)针对人类视觉系统的生理学和心理学特性,结合基于仿生学的误差可见度模型,从图像的基本结构和几何特征出发,利用原始图像和待测图像的结构差异和几何相似来度量视觉质量的变化。提出了基于人类视觉系统的全参考型图像质量评价测度。实验结果表明,本方法不仅与视觉感知有较好的一致性,而且算法复杂度很低,取得了预期的效果。
(2)在图像特征提取和稀疏表示的基础上,模拟人类视觉系统的多通道特性,采用多尺度几何分析来获取图像的几何特征。然后利用人类视觉心理物理学的对比敏感度和掩模特性,对图像的几何特征进行感知滤波,进而利用该特征来捕捉由于失真而引起的视觉感知的变化。提出了基于多尺度几何分析的部分参考型图像质量评价测度框架。实验结果表明,利用该框架的各种方法所得到的客观评价结果与主观观测值之间具有很好的一致性,能准确地反映人眼对图像质量的主观感受。
(3)在自然图像统计特性的基础上,利用计算模型来构建图像特征的一般分布规律,采用轮廓波来刻画图像尺度间、尺度内、和方向间的统计相关性,然后对自然图像模型在轮廓波变换域尺度间的变化进行分析,并结合图像模型的变化来捕获不同程度的失真,最后使用这些变化特征的非线性映射来表征图像质量。提出了基于轮廓波变换域的无参考型图像质量评价测度。该算法适用于不同的图像失真类型,且与视觉感知的一致性较好。
(4)针对不同失真类型的特点,根据视觉感知与失真过程的密切关系,从人眼对影像的敏感性和敏锐性出发,结合影像的整体结构和内容的局部结构进行分析,利用影像的结构相似性来度量视觉失真的变化。提出了基于失真模型优化的视频质量评价方法。在VQEG视频数据库上进行测试,获得了较好的评价性能。
(5)深入分析了VQEG视频数据库的优缺点,针对该数据库存在的局限性和网络流媒体发展的紧迫性,结合目前主流视频压缩标准H.264,对大量的内容丰富的视频序列进行各种不同量化尺度以及码率的压缩,并邀请一定数量的非专业人士,利用主观排序方法和自动评分平台对压缩产生的失真序列进行主观打分。完成了面向编码失真的视频质量评价数据库的构建,为视频质量评价研究的深入进行夯实了基础。
上述研究成果是在实际应用中抽象出的科学问题,涉及到影像处理的基础理论,是从新的角度、基于新的条件和应用进行研究的,富有一定的前瞻性和挑战性,具有极其重要的理论意义和应用价值。本论文在理论上有一些突破,技术上有一定创新,为影像质量评价的发展开辟了新的思路,提供了一些有意义的参考。
The aim of the image and video quality assessment is to find a computational model that can predict the perceptual visual quality automatically. An image is a vision entity that can describe the objective world in different forms by variable observation system. Compared with texts and graphics, the image conveys the information more vividly and affluently. Since images are subject to distortions during acquisition, compression, transmission, processing and reproduction, which will bring difficulties to the subsequent process such as image and video processing, analysis and understanding, It is not conducive to the correct understanding of the objective world. Thus, it is necessary to design or optimize an image and video processing method or system by measuring the degradation of the image and video, so that we can get the perfect visual quality with the least cost.
In this dissertation, objecting to essential problems of the image and video quality assessment and exploring the relation between human visual system and digital information, objective assessment methods are built to evaluate some distortions by uncertain factors in process of the image and video, which are based on the image sparse representation and feature modeling for measuring visual quality of distorted image and the ability to provide information of the image, The main contributions of this dissertation can be summarized as follows:
(1) According to the characteristic of the physiology and psychology of human visual system and combining error visibility models based on bottom-up approach, the variation of visual quality is measured by emplying the difference structure and geometrical similarity between reference images and distorted images from the basic structure and geometrical characteristic. A full reference image quality assessment method based on human visual system is proposed. Experimental results illustrate that the proposed has a good consistency with the subjective assessment of human beings, and it can be used to describe the visual perception of the image effectively.
(2) According to feature extraction and sparse representation of the image and mimicing mutil-channel characteristic of human visual system, multiscale geometric analysis is employed to extract geometrical characteristics of the image. Then these geometrical characteristics are perceptually filtered based on the contrast sensitivity and masking of human visual system. The degradation of perceptual quality can be captured by these filtered features. So a framework of reduced reference image quality assessment based on multiscale geometric analysis is proposed, thorough empirical studies are carried out upon the LIVE database against subjective mean opinion score and demonstrate that the proposed framework has good consistency with subjective perception values and the objective assessment results can well reflect the visual quality of images.
(3) On the basis of natural image statistic characteristics and making use of computational model to construct a generalized distribution of image features. Contourlet transform is introduced to decompose images and produce coefficients at difference subbands, relationship of whose coefficients are reflected by the mutual information among scale, direction and adjacent. By analyzing the variance between different scales of the image model and combing the diversification of the model , the variation degree of distortion is measured, and then a nonlinear mapping of the diversification of the features is used as the quality of the distorted image. A no reference image quality metric based on contourlet domain is proposed. This algorithm is demonstrated to be fit for various types of distortion, and is well consistent with the subjective perceptive results.
(4) According to the features of different types of artifacts and the relation between visual perception and degradation process, we designed a new metric derived from the acuity and sensitivity of human eyes to image quality, analyzing the image global structure and local structure, to determine the degree of visual distortion which is based on the structure similarity of images. The experimental results have good correlation with visual perception. This method is extended to the video quality assessment based on the optimal distortion model. It also gives good performance.
(5) The strengths and weaknesses of the VQEG video database have been well analyzed. In order to compensate the limitations of the database and catch up with the development of the current streaming media, a new video database is constructed based on the H.264 standard of the advanced video compression. Great deals of videos with rich content are compressed in different quantification scales and bit rates. A number of non-expert persons give the subjective scores for these videos on an automatic platform by subjective sorting methods. The new database offers a good beginning for further video quality assessment research.
The research results above are scientific problems abstracted from practical application, referred to the basic theory of image and video processing. They are studied from new angles and based on new conditions and application, which are forward-looking and full of challenges and have extremely important theoretical significance and application value. The dissertation have some breakthrough in theory, some innovation in technology and some reference in methodology, it opens up a new way for image and video quality assessment.
本文针对影像质量评价的基本问题,探索人类视觉系统和数字信息之间的联系,在图像稀疏表示和特征建模的基础上,为影像处理中由未知因素造成的各种失真构建客观评价方法,以度量影像的失真程度和提供信息的能力,从而为视觉质量评价提供合理依据。主要工作概括如下:
(1)针对人类视觉系统的生理学和心理学特性,结合基于仿生学的误差可见度模型,从图像的基本结构和几何特征出发,利用原始图像和待测图像的结构差异和几何相似来度量视觉质量的变化。提出了基于人类视觉系统的全参考型图像质量评价测度。实验结果表明,本方法不仅与视觉感知有较好的一致性,而且算法复杂度很低,取得了预期的效果。
(2)在图像特征提取和稀疏表示的基础上,模拟人类视觉系统的多通道特性,采用多尺度几何分析来获取图像的几何特征。然后利用人类视觉心理物理学的对比敏感度和掩模特性,对图像的几何特征进行感知滤波,进而利用该特征来捕捉由于失真而引起的视觉感知的变化。提出了基于多尺度几何分析的部分参考型图像质量评价测度框架。实验结果表明,利用该框架的各种方法所得到的客观评价结果与主观观测值之间具有很好的一致性,能准确地反映人眼对图像质量的主观感受。
(3)在自然图像统计特性的基础上,利用计算模型来构建图像特征的一般分布规律,采用轮廓波来刻画图像尺度间、尺度内、和方向间的统计相关性,然后对自然图像模型在轮廓波变换域尺度间的变化进行分析,并结合图像模型的变化来捕获不同程度的失真,最后使用这些变化特征的非线性映射来表征图像质量。提出了基于轮廓波变换域的无参考型图像质量评价测度。该算法适用于不同的图像失真类型,且与视觉感知的一致性较好。
(4)针对不同失真类型的特点,根据视觉感知与失真过程的密切关系,从人眼对影像的敏感性和敏锐性出发,结合影像的整体结构和内容的局部结构进行分析,利用影像的结构相似性来度量视觉失真的变化。提出了基于失真模型优化的视频质量评价方法。在VQEG视频数据库上进行测试,获得了较好的评价性能。
(5)深入分析了VQEG视频数据库的优缺点,针对该数据库存在的局限性和网络流媒体发展的紧迫性,结合目前主流视频压缩标准H.264,对大量的内容丰富的视频序列进行各种不同量化尺度以及码率的压缩,并邀请一定数量的非专业人士,利用主观排序方法和自动评分平台对压缩产生的失真序列进行主观打分。完成了面向编码失真的视频质量评价数据库的构建,为视频质量评价研究的深入进行夯实了基础。
上述研究成果是在实际应用中抽象出的科学问题,涉及到影像处理的基础理论,是从新的角度、基于新的条件和应用进行研究的,富有一定的前瞻性和挑战性,具有极其重要的理论意义和应用价值。本论文在理论上有一些突破,技术上有一定创新,为影像质量评价的发展开辟了新的思路,提供了一些有意义的参考。
The aim of the image and video quality assessment is to find a computational model that can predict the perceptual visual quality automatically. An image is a vision entity that can describe the objective world in different forms by variable observation system. Compared with texts and graphics, the image conveys the information more vividly and affluently. Since images are subject to distortions during acquisition, compression, transmission, processing and reproduction, which will bring difficulties to the subsequent process such as image and video processing, analysis and understanding, It is not conducive to the correct understanding of the objective world. Thus, it is necessary to design or optimize an image and video processing method or system by measuring the degradation of the image and video, so that we can get the perfect visual quality with the least cost.
In this dissertation, objecting to essential problems of the image and video quality assessment and exploring the relation between human visual system and digital information, objective assessment methods are built to evaluate some distortions by uncertain factors in process of the image and video, which are based on the image sparse representation and feature modeling for measuring visual quality of distorted image and the ability to provide information of the image, The main contributions of this dissertation can be summarized as follows:
(1) According to the characteristic of the physiology and psychology of human visual system and combining error visibility models based on bottom-up approach, the variation of visual quality is measured by emplying the difference structure and geometrical similarity between reference images and distorted images from the basic structure and geometrical characteristic. A full reference image quality assessment method based on human visual system is proposed. Experimental results illustrate that the proposed has a good consistency with the subjective assessment of human beings, and it can be used to describe the visual perception of the image effectively.
(2) According to feature extraction and sparse representation of the image and mimicing mutil-channel characteristic of human visual system, multiscale geometric analysis is employed to extract geometrical characteristics of the image. Then these geometrical characteristics are perceptually filtered based on the contrast sensitivity and masking of human visual system. The degradation of perceptual quality can be captured by these filtered features. So a framework of reduced reference image quality assessment based on multiscale geometric analysis is proposed, thorough empirical studies are carried out upon the LIVE database against subjective mean opinion score and demonstrate that the proposed framework has good consistency with subjective perception values and the objective assessment results can well reflect the visual quality of images.
(3) On the basis of natural image statistic characteristics and making use of computational model to construct a generalized distribution of image features. Contourlet transform is introduced to decompose images and produce coefficients at difference subbands, relationship of whose coefficients are reflected by the mutual information among scale, direction and adjacent. By analyzing the variance between different scales of the image model and combing the diversification of the model , the variation degree of distortion is measured, and then a nonlinear mapping of the diversification of the features is used as the quality of the distorted image. A no reference image quality metric based on contourlet domain is proposed. This algorithm is demonstrated to be fit for various types of distortion, and is well consistent with the subjective perceptive results.
(4) According to the features of different types of artifacts and the relation between visual perception and degradation process, we designed a new metric derived from the acuity and sensitivity of human eyes to image quality, analyzing the image global structure and local structure, to determine the degree of visual distortion which is based on the structure similarity of images. The experimental results have good correlation with visual perception. This method is extended to the video quality assessment based on the optimal distortion model. It also gives good performance.
(5) The strengths and weaknesses of the VQEG video database have been well analyzed. In order to compensate the limitations of the database and catch up with the development of the current streaming media, a new video database is constructed based on the H.264 standard of the advanced video compression. Great deals of videos with rich content are compressed in different quantification scales and bit rates. A number of non-expert persons give the subjective scores for these videos on an automatic platform by subjective sorting methods. The new database offers a good beginning for further video quality assessment research.
The research results above are scientific problems abstracted from practical application, referred to the basic theory of image and video processing. They are studied from new angles and based on new conditions and application, which are forward-looking and full of challenges and have extremely important theoretical significance and application value. The dissertation have some breakthrough in theory, some innovation in technology and some reference in methodology, it opens up a new way for image and video quality assessment.
引文
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