【作者】 张桦；

【导师】 陈耀武；

【作者基本信息】 浙江大学 ， 电子信息技术及仪器， 2009， 博士

【摘要】 图像质量评价方法是指通过设计数学模型,对图像进行智能分析,并按照设计的质量尺度进行自动评分的客观评价方法。根据对原始图像的依赖程度,图像质量评价方法可分为全参考型、部分参考型和无参考型三种类型。图像质量评价方法是分析图像压缩和处理效果、反馈图像传输质量的关键技术,是多媒体系统中不可或缺的重要组成部分。同时,由于图像是视频的基本单位,视频是图像在时间域上的连续序列。因此,对图像质量评价方法的研究也是视频质量评价方法研究的重要基础。传统的依靠人工观察的主观方法对图像进行质量评价不但费时费力,而且评价的结果受到评价环境、评价人员工作背景等因素的影响,无法客观反映图像的质量。因此开发能准确反映人对图像的主观感受,并且能在多媒体系统中广泛应用的图像质量评价方法,成为当前国际性的研究热点。人类视觉系统(HVS)是人获取图像信息的唯一手段。心理物理学研究表明,HVS对图像的感知是有选择性的,不同的区域具有不同的视觉显著性。然而,已有的图像质量评价方法并未充分考虑HVS对图像感知的多样性。因此,研究基于视觉感知的图像质量评价方法,进一步提高图像质量评价的准确性,具有重要的理论意义和应用价值。本文正是在这样的背景下,展开了基于视觉感知的全参考型、部分参考型和无参考型图像质量评价方法的研究,并在此研究基础上开展了视频质量评价方法的讨论。第一章绪论部分首先阐述了选题的意义,然后综述了国内外研究现状并作了相应的总结,最后介绍了本课题的主要研究内容和论文结构。第二章对全参考型图像质量评价方法进行研究,提出了一种基于视觉感知的结构相似度图像质量评价方法。该方法首先利用空间域视觉特征生成视觉感知图,并通过计算块结构相似度生成失真感知图。然后根据视觉感知图和失真感知图分别确定视觉特征显著区域和失真严重区域,并进一步考虑了由视觉特征显著或失真严重引起的视觉注意焦点转移对视觉感知的影响,生成视觉注意焦点转移后的视觉感知图。最后利用视觉感知图和视觉注意焦点转移后的视觉感知图对块结构相似度进行加权,获得图像的客观质量。第三章对部分参考型图像质量评价方法进行研究,提出了一种基于小波域水印的部分参考型图像质量评价方法。该方法利用掩盖效应这一视觉感知特性生成水印嵌入指示图,确定合适的水印嵌入位置,并且设计量化参数自动调节系统,确定合适的水印嵌入强度。同时利用子带图像受损时敏感程度不一样的特点,选择在合适的子带内嵌入水印,并通过提取水印恢复率获得图像的客观质量。第四章对无参考型图像质量评价方法进行研究,提出了一种基于视觉感知的无参考型图像块效应评价方法和一种基于正交最小二乘法径向基函数(OLS-RBF)的无参考型图像模糊和振铃效应评价方法。该块效应评价方法利用空间域视觉特征生成视觉感知图,对块效应失真和块平坦度进行加权,获得图像的客观质量。该模糊和振铃效应评价方法利用结构纹理区域内的边缘特征和图像主观质量训练基于OLS-RBF的网络,得到无参考型图像客观质量评价模型。第五章在对图像质量评价方法的研究基础上,展开对视频质量评价方法的研究,提出了一种全参考型视频质量评价方法。该方法首先设计基于视觉感知的视觉注意模型生成视觉感知图和失真感知图。然后根据失真感知图确定失真严重区域,并进一步考虑了由失真严重引起的视觉注意焦点转移对视觉感知的影响,生成视觉注意焦点转移后的视觉感知图。再利用该视觉感知图对结构相似度进行帧内质量加权,获得单帧视频图像的客观质量。最后模拟突发性严重失真对序列质量的影响,设计帧质量贡献度曲线,对单帧视频图像进行帧间质量加权,获得视频序列的整体客观质量。第六章总结了本论文的研究成果和创新点,并提出了进一步研究的方向和任务。更多还原

【Abstract】 Image quality assessment is to analyze the image intelligently and predict the perceived image quality automatically based on designing a mathematical model. It can be classified into full reference, reduced reference and no reference according to the availability of the original image. It becomes one of the key technologies for benchmarking the image compression or processing algorithms and plays an important role in the multimedia application system. Meanwihle, the image is the basic unit of the video, and the video composes of the images which are arranged with time sequence. The research on the image quality assessment is the important basis of the one on the video quality assessment. However, the traditional subjective image quality assessment which depends on the observation of human beings is impractical, slow and expensive for most applications. Researches focusing on developing the new generation of image quality assessment which can reflect the subjective feeling of human beings precisely and can also be applied in the practical multimedia systems become a necessity. Currently, Human Visual System (HVS) is the only way to access the image information. The perception of HVS for the image is selective, and different regions or objects in the image have diverse levels of visual importance. However, the current image quality assessment ignores this diversity of perception mechanism. Therefore, it is of theoretical significance and practical value to take an in-depth research on the improvement of the prediction accuracy of image quality assessment by applying the principle of the visual perception.In chapter 1, the significance of the research work is presented together with a brief summary of the present research status.In chapter 2, a structural similarity quality metric based on the visual perception is proposed, which is a full reference metric. The spatial features are combined to produce the visual perceptual map. The focus of attention is shifted because of the most visual saliency or a serious distortion; it results in the reproduction of the visual perceptual map. The structural similarity is weighted by the above two visual perceptual maps, and the objective quality of the image is acquired.In chapter 3, an image quality assessment based on watermarking in the wavelet domain is proposed, which is a reduced reference metric. The watermark is embedded into the selected frequency sub-bands according to the different distortion sensitivity. Meanwhile, the watermark embedded map and the adaptive adjustment of quantization parameter are applied to decide the position and the strength of the watermark, which ensure the watermark’s invisibility effectively. The image objective quality is acquired through the watermark recovery rate.In chapter 4, a perceptual blockiness metric and an Orthogonal Least Squares Radial Basis Function (OLS-RBF) based blurring and ringing metric are proposed; they are both no reference metrics. The blockiness metric calculates the spatial visual features to produce the visual perceptual map. Then, it weighs the blockiness to acquire the image objective quality. The blurring and ringing metric extracts the generalized features of the edge points in the structure-texture region; the objective quality of the JPEG2000 image is evaluated by training an OLS-RBF network model from the generalized features and the subjective scores.In chapter 5, a video structural similarity quality assessment based on the visual perception is proposed, which is a full reference metric. A distortions-weighing spatiotemporal visual attention model is designed. The visual perceptual map which is produced based on this model and the structural similarity map are used for the objective quality of the single video frame. Then, the objective quality of the whole video sequence is calculated by introducing a frame quality contribution function which weighs the qualities of each frame and gives a much heavier weighting factor to the extremely damaged frames to takes the case of burst-of-error into account.The final chapter concludes the new achievements of the whole research and the prospect of the future research.更多还原