Image fusion algorithm based on contrast pyramid and its performance evaluation

被引:8
|
作者
Dong, Yubing [1 ]
Li, Mingjing [1 ]
Li, Jie [1 ]
机构
[1] Changchun Univ, Coll Elect & Informat Engn, Changchun 130022, Peoples R China
来源
DEVELOPMENT OF INDUSTRIAL MANUFACTURING | 2014年 / 525卷
关键词
image fusion; pyramid decomposition; contrast pyramid; performance evaluation;
D O I
10.4028/www.scientific.net/AMM.525.711
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Contrast pyramid algorithm is put forward in this paper. The human visual system is sensitive to contrast information of image, so contrast pyramid algorithm would outstanding the contrast of image. The algorithm consists of creation process of Gauss Pyramid, the process of creating contrast Pyramid and reconstruction process of clear image. Simulation by MATLAB was completed in multi-focus image, multi-modality image and color image. Objective evaluation index such as mean, standard deviation, entropy and average gradient was calculated Simulation results and index show that the contrast pyramid algorithm has advantage of projecting the contrast of image, especially in color image fusion.
引用
收藏
页码:711 / 714
页数:4
相关论文
共 50 条
  • [21] Fusion performance measures and a lifting wavelet transform based algorithm for image fusion
    Ramesh, C
    Ranjith, T
    PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOL I, 2002, : 317 - 320
  • [22] Performance Evaluation of Image Fusion by using Copulas
    Zeng, Xuexing
    Durrani, Tariq S.
    2010 IEEE 10TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS (ICSP2010), VOLS I-III, 2010, : 756 - 759
  • [23] Fusion Algorithm of Infrared and TV Image Based On Image Quality Evaluation Method
    Zhou, Bin
    Luo, Xiaohui
    APPLIED SCIENCE, MATERIALS SCIENCE AND INFORMATION TECHNOLOGIES IN INDUSTRY, 2014, 513-517 : 570 - 574
  • [24] Performance evaluation approach to image fusion based on ordering approximate to ideal solution
    Zhou P.-C.
    Wang F.
    Cui X.-X.
    Xue M.-G.
    Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2011, 33 (03): : 681 - 684
  • [25] Benchmarking Image Fusion Algorithm Performance
    Howell, Christopher L.
    INFRARED IMAGING SYSTEMS: DESIGN, ANALYSIS, MODELING, AND TESTING XXIII, 2012, 8355
  • [26] An assessment of pyramid-based multisensor image data fusion
    Aiazzi, B
    Alparone, L
    Baronti, S
    Carlá, R
    IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING IV, 1998, 3500 : 237 - 248
  • [27] Image Fusion at Pixel and Feature Levels Based on Pyramid Imaging
    Ashalatha, B.
    Reddy, M. Babu
    2017 IEEE INTERNATIONAL CONFERENCE ON SMART TECHNOLOGIES AND MANAGEMENT FOR COMPUTING, COMMUNICATION, CONTROLS, ENERGY AND MATERIALS (ICSTM), 2017, : 258 - 263
  • [28] A Perceptual Quality Metric for Performance Evaluation of Image Fusion
    Jian, Muwei
    Ma, Ping
    Jia, Jianfeng
    IITSI 2009: SECOND INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY AND SECURITY INFORMATICS, 2009, : 148 - +
  • [29] Performance Assessment of Gaussian Filter-Based Image Fusion Algorithm
    Bhageerath, Kesari Eswar
    Marndi, Ashapurna
    Harini, D. N. D.
    FOURTH CONGRESS ON INTELLIGENT SYSTEMS, VOL 1, CIS 2023, 2024, 868 : 41 - 50
  • [30] Multiscale contrast image fusion scheme with performance measures
    Zhang, XM
    Han, JQ
    OPTICA APPLICATA, 2004, 34 (03) : 453 - 461