基于图像色貌和梯度特征的图像质量客观评价  

Objective image quality assessment based on image color appearance and gradient features

作　　者：史晨阳 林燕丹[1,2] Shi Chen-Yang;Lin Yan-Dan(Department of Light Sources and Illuminating Engineering,School of Information Science and Technology,Fudan University,Shanghai 200433,China;Institute of Future Lighting,Academy for Engineering&Technology,Fudan university,Shanghai 200433,China)

机构地区：[1]复旦大学信息科学与工程学院,光源与照明工程系,上海200433 [2]复旦大学工程与应用技术研究院,超越照明研究所,上海200433

出　　处：《物理学报》2020年第22期395-406,共12页Acta Physica Sinica

基　　金：国家重点研发计划(批准号:2017YFB0403700)资助的课题。

摘　　要：图像质量评价(IQA)方法需要考虑如何从主观视觉度量结果出发,设计出符合该结果的客观图像质量评价方法,应用到相关实际问题中.本文从视觉感知特性出发,量化色度和结构特征信息,提出了基于色貌和梯度两个图像特征的图像质量客观评价模型.两个色貌新指标(vividness和depth)是色度特征信息提取算子;梯度算子用来提取结构特征信息.其中, vividness相似图一方面作为特征提取算子计算失真图像局部质量分数,另一方面作为图像全局权重系数反应每个像素的重要程度.为了量化所提模型的主要参数,根据通用模型性能评价指标,使用Taguchi实验设计方法进行优化.为了验证该模型的性能,使用4个常用图像质量数据库中的94幅参考图像和4830幅失真图像进行对比测试,从预测精度、计算复杂度和泛化性进行分析.结果表明,所提模型的精度PLCC值在4给数据库中最低实现0.8455,最高可以达到0.9640,综合性能优于10个典型和近期发表的图像质量评估(IQA)模型.研究结果表明,所提模型是有效的、可行的,是一个性能优异的IQA模型.With the rapid development of color image contents and imaging devices in various kinds of multimedia communication systems,conventional grayscale counterparts are replaced by chromatic ones.Under such a transition,the image quality assessment(IQA)model needs to be built by subjective visual measurement,designed in accordance with the results,and applied to the related practical problems.Based on the visual perception characteristics,chromaticity and the structure feature information are quantified,and an objective IQA model combining the color appearance and the gradient image features is proposed in this paper,namely color appearance and gradient similarity(CAGS)model.Two new color appearance indices,vividness and depth,are selected to build the chromatic similarity map.The structure information is characterized by gradient similarity map.Vividness map plays two roles in the proposed model.One is utilized as feature extractor to compute the local quality of distorted image,and the other is as a weight part to reflect the importance of local domain.To quantify the specific parameters of CAGS,Taguchi method is used and four main parameters,i.e.,KV,KD,KG and a,of this model are determined based on the statistical correlation indices.The optimal parameters of CAGS are KV=KD=0.02,KG=50,and a=0.1.Furthermore,the CAGS is tested by utilizing 94 reference images and 4830 distorted images from the four open image databases(LIVE,CSIQ,TID2013 and IVC).Additionally,the influences of the 35 distortion types on IQA are analyzed.Massive experiments are performed on four publicly available benchmark databases between CAGS and other 10 state-of-the-art and recently published IQA models,for the accuracy,complexity and generalization performance of IQA.The experimental results show that the accuracy PLCC of the CAGS model can achieve 0.8455 at lowest and 0.9640 at most in the four databases,and the results about commonly evaluation criteria prove that the CAGS performs higher consistency with the subjective evaluations.Among the 3

关 键 词：图像质量评价 人类视觉特性 色貌 梯度 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]