2.845

2023影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

融合图像质量评价指标的相关性分析及性能评估

张小利 李雄飞 李军

张小利, 李雄飞, 李军. 融合图像质量评价指标的相关性分析及性能评估. 自动化学报, 2014, 40(2): 306-315. doi: 10.3724/SP.J.1004.2014.00306
引用本文: 张小利, 李雄飞, 李军. 融合图像质量评价指标的相关性分析及性能评估. 自动化学报, 2014, 40(2): 306-315. doi: 10.3724/SP.J.1004.2014.00306
ZHANG Xiao-Li, LI Xiong-Fei, LI Jun. Validation and Correlation Analysis of Metrics for Evaluating Performance of Image Fusion. ACTA AUTOMATICA SINICA, 2014, 40(2): 306-315. doi: 10.3724/SP.J.1004.2014.00306
Citation: ZHANG Xiao-Li, LI Xiong-Fei, LI Jun. Validation and Correlation Analysis of Metrics for Evaluating Performance of Image Fusion. ACTA AUTOMATICA SINICA, 2014, 40(2): 306-315. doi: 10.3724/SP.J.1004.2014.00306

融合图像质量评价指标的相关性分析及性能评估

doi: 10.3724/SP.J.1004.2014.00306
基金项目: 

吉林省科技发展计划(20090468,20100508,201105017);长春市科技计划(11KZ24) 资助

详细信息
    作者简介:

    张小利 吉林大学计算机科学与技术学院博士研究生. 主要研究方向为图像处理,信息融合.E-mail:zxl12@mails.jlu.edu.cn

Validation and Correlation Analysis of Metrics for Evaluating Performance of Image Fusion

Funds: 

Supported by Technology Development Plan of Jilin Province (20090468, 20100508, 201105017) and Science and Technology Project of Changchun (11KZ24)

  • 摘要: 图像融合质量评价指标研究旨在提供一种高效、准确的方法,为融合模型 选择、参数优化等问题提供支持. 本文通过对现有指标的机理分析、指标性能检验与 指标间相关性分析,提出一种客观评价指标集的遴选策略. 本文首先将现有客观评价 指标归为三类:基于统计的、基于信息的和基于人类视觉系统的;之后列举了类别内经典指标和最新指标;并在标准数据集上,使用正确排序指标对各图 像融合客观评价指标的性能进行验证. 结果表明,基于视觉系统类的指标性能普遍优于前两类. 最后,利用Spearman相关系数挖掘各指 标间的相关程度. 实验表明,通过指标性能和相 关系数可以选取合适的客观评价指标集.
  • [1] Goshtasby A A, Nikolov S. Image fusion: advances in the state of the art. Information fusion, 2007, 8(2): 114-118
    [2] Yang B, Li S T. Pixel-level image fusion with simultaneous orthogonal matching pursuit. Information fusion, 2012, 13(1): 10-19
    [3] Hu Liang-Mei, Gao Jun, He Ke-Feng. Research on quality measures for image fusion. Acta Electronica Sinica, 2004, 32(12A): 218-221(胡良梅, 高隽, 何柯峰. 图像融合质量评价方法的研究. 电子学报, 2004, 32(12A): 218-221)
    [4] Petrović V. Subjective tests for image fusion evaluation and objective metric validation. Information Fusion, 2007, 8(2): 208-216
    [5] Toet A, Franken E M. Perceptual evaluation of different image fusion schemes. Displays, 2003, 24(1): 25-37
    [6] Qu G H, Zhang D L, Yan P F. Information measure for performance of image fusion. Electronics Letters, 2002, 38(7): 313-315
    [7] Petrović V, Cootes T. Information representation for image fusion evaluation. In: Proceedings of the 9th International Conference on Information Fusion. Florence, Italy: IEEE, 2006. 1-7
    [8] Hossny M, Nahavandi S, Creighton D. Comments on “Information measure for performance of image fusion”. Electronics Letters, 2008, 44(18): 1066-1067
    [9] Xydeas C S, Petrović V. Objective image fusion performance measure. Electronics Letters, 2000, 36(4): 308-309
    [10] Wang Z, Bovik A C. A universal image quality index. IEEE Signal Processing Letters, 2002, 9(3): 81-84
    [11] Wang Z, Simoncelli E P, Bovik A C. Multiscale structural similarity for image quality assessment. In: Conference Record of the 37th Asilomar Conference on Signals, Systems and Computers. Pacific Grove, CA, USA: IEEE, 2003. 1398-1402
    [12] Sampat M P, Wang Z, Gupta S, Bovik A C, Markey M K. Complex wavelet structural similarity: a new image similarity index. IEEE Transactions on Image Processing, 2009, 18(11): 2385-2401
    [13] Piella G, Heijmans H. A new quality metric for image fusion. In: Proceedings of the 2003 IEEE International Conference on Acoustics, Speech and Signal Processing. Barcelona, Spain: IEEE, 2003. 173-176
    [14] Yang C, Zhang J Q, Wang X R, Liu X. A novel similarity based quality metric for image fusion. Information Fusion, 2008, 9(2): 156-160
    [15] Luo X Y, Zhang J, Dai Q H. Saliency-based geometry measurement for image fusion performance. IEEE Transactions on Instrumentation and Measurement, 2012, 61(4): 1130-1132
    [16] Zheng Y Z, Qin Z. Objective image fusion quality evaluation using structural similarity. Tsinghua Science and Technology, 2009, 14(6): 703-709
    [17] Zhang X Q. A novel quality metric for image fusion based on color and structural similarity. In: Proceedings of the 2009 International Conference on Signal Processing Systems. Singapore, Singapore: IEEE, 2009. 258-262
    [18] Chen H, Varshney P K. A human perception inspired quality metric for image fusion based on regional information. Information Fusion, 2007, 8(2): 193-207
    [19] Han Y, Cai Y Z, Cao Y, Xu X M. A new image fusion performance metric based on visual information fidelity. Information Fusion, 2013, 14(2): 127-135
    [20] Wang Z, Bovik A C, Lu L G. Why is image quality assessment so difficult? In: Proceedings of the 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing. Orlando, FL, USA: IEEE, 2002. 3313-3316
    [21] Wang Z, Bovik A C. Mean squared error: love it or leave it? A new look at signal fidelity measures. IEEE Signal Processing Magazine, 2009, 26(1): 98-117
    [22] Wang Z, Bovik A C, Sheikh H R, Simoncelli E P. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 2004, 13(4): 600-612
    [23] Cvejic N, Canagarajah C N, Bull D R. Image fusion metric based on mutual information and Tsallis entropy. Electronics Letters, 2006, 42(11): 626-627
    [24] Wang Z, Bovik A C. A universal image quality index. Signal Processing Letters, 2002, 9(3): 81-84
    [25] Wang Z, Bovik A C. Modern image quality assessment. Synthesis Lectures on Image, Video, and Multimedia Processing. USA: Morgan Claypool Publishers, 2006, 2(1): 1-156
    [26] Cheng Guang-Quan, Zhang Ji-Dong, Cheng Li-Zhi, Huang Jin-Cai, Liu Zhong. Image quality assessment based on geometric structural distortion model. Acta Automatica Sinica, 2011, 37(7): 811-819(程光权, 张继东, 成礼智, 黄金才, 刘忠. 基于几何结构失真模型的图像质量评价研究. 自动化学报, 2011, 37(7): 811-819)
  • 加载中
计量
  • 文章访问数:  3103
  • HTML全文浏览量:  163
  • PDF下载量:  2126
  • 被引次数: 0
出版历程
  • 收稿日期:  2012-09-12
  • 修回日期:  2013-01-28
  • 刊出日期:  2014-02-20

目录

    /

    返回文章
    返回