Journal of Computer Applications ›› 2017, Vol. 37 ›› Issue (3): 695-698.DOI: 10.11772/j.issn.1001-9081.2017.03.695

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Objective quality assessment method of high dynamic range image

GUAN Feifan, YU Mei, SONG Yang, SHAO Hua, JIANG Gangyi   

  1. Faculty of Information Science and Engineering, Ningbo University, Ningbo Zhejiang 315211, China
  • Received:2016-07-25 Revised:2016-09-30 Online:2017-03-10 Published:2017-03-22
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61271270), the Natural Science Foundation of Zhejiang Province (LY15F010005).


管非凡, 郁梅, 宋洋, 邵华, 蒋刚毅   

  1. 宁波大学 信息科学与工程学院, 浙江 宁波 315211
  • 通讯作者: 蒋刚毅
  • 作者简介:管非凡(1990-),男,安徽蚌埠人,硕士研究生,主要研究方向:图像与视频质量评价;郁梅(1968-),女,江苏无锡人,教授,博士,主要研究方向:多媒体信号处理、视频压缩与通信;宋洋(1989-),男,浙江宁波人,博士研究生,主要研究方向:图像与视频质量评价;邵华(1979-),男,浙江杭州人,博士研究生,主要研究方向:图像处理、视频编码;蒋刚毅(1964-),男,浙江绍兴人,教授,博士,CCF会员,主要研究方向:数字视频压缩与通信、图像处理、视频编码。
  • 基金资助:

Abstract: Aiming at the problem that High Dynamic Range (HDR) image quality evaluation method does not consider the color and structure information of HDR image, a novel objective quality assessment method of HDR image was proposed. Firstly, the feature of visual fidelity about brightness and contrast was obtained based on the visual model of HDR-VDP-2.2. Then, the HDR image was transformed into the YIQ color space, and the color similarity and structural correlation coefficient were gotten by dealing with the Y, I, Q channel, respectively. Finally, Support Vector Regression (SVR) was used to fuse the features, and the objective evaluation value of the high dynamic range image quality could be obtained by predicting the similarity degree and the structural relevance degree. The experimental results show that compared with HDR-VDP-2.2, the Pearson correlation coefficient and Spearman rank correlation coefficient of the proposed method are increased by 23.09% and 25.34%, respectively; the Root Mean Square Error (RMSE) is reduced by 38.01%. The proposed method has higher consistency with subjective visual perception.

Key words: High Dynamic Range (HDR) image, quality assessment, feature, Support Vector Regression (SVR), visual perception

摘要: 针对当前高动态范围(HDR)图像质量评价方法未考虑图像色度和结构信息的问题,提出了一种新的HDR图像客观质量评价方法。首先,利用HDR-VDP-2.2中的基于视觉感知的模型得到关于亮度与对比度的视觉保真度特征;然后,将HDR图像转换到YIQ彩色空间,对彩色空间中的Y、I、Q通道分别进行处理,求得色度相似度和结构相关度特征;最后,利用支持向量回归(SVR)的方法对特征进行融合,预测得到高动态范围图像质量的客观评价值。实验结果表明,与HDR-VDP-2.2相比,该方法的Pearson相关系数和Spearman等级相关系数分别提升了23.09%和25.34%;均方根误差(RMSE)降低了38.01%。所提出的方法与主观视觉感知具有更高的一致性。

关键词: 高动态范围图像, 质量评价, 特征, 支持向量回归, 视觉感知

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