Advanced Search

ISSN1001-3806 CN51-1125/TN Map

Volume 40 Issue 6
Sep.  2016
Article Contents
Turn off MathJax

Citation:

Infrared and visible light images fusion of fuzzy logic on NSST domain

  • Received Date: 2015-08-17
    Accepted Date: 2015-11-03
  • In order to retain more detail information and reduce the algorithm complexity when fusing the infrared and visible light images, a fusion algorithm based on non-subsampled shearlet transform (NSST) and improved fuzzy logic was proposed to decompose source images sparsely on multi-direction and multi-scale. Low-frequency subband coeffients and high-frequency subband coeffients were obtained. The improved average fusion method of fuzzy Cauchy membership function was adopted in low-frequency subband coeffients. The fusion rule of the combination of energy compatibility and visual sensitivity coefficient was used in high-frequency subband coeffients. Finally, fusion image was obtained after NSST inverse transformation. Experimental results show that the fusion method can not only guarantee the definition of fused image, but also shorten the running time of algorithm.
  • 加载中
  • [1]

    LI J Sh, YANG W, ZHANG X M. Infrared image processing, analysis and fusion[M]. Beijing:Science Press, 2009:174-182(in Chinese).
    [2]

    ZHENG W, SUN X Q, LI Zh. Image fusion based on shearlet transform and region characteristics[J]. Laser Technology, 2015, 39(1):50-56(in Chinese).
    [3]

    FENG X, WANG X M. Fusion of infrared and visible images based on Shearlet transform[J].Journal of OptoelectronicsLaser, 2013, 24(2):384-390(in Chinese).
    [4]

    XING X X. Research the image fusion algorithm based on non-subsampled shearlet transform[D]. Changchun:Jilin University, 2014:69-77(in Chinese).
    [5]

    SHI Zh, ZHANU Zh, YUE Y G. Adaptive image fusion algorithm based on Shearlet transform[J]. Acta Photonica Sinica, 2013, 42(1):115-120(in Chinese).
    [6]

    XIE Y H. Multi-focus image fusion by improved shearlet transform[D]. Xi'an:Xidian University, 2013:37-43(in Chinese).
    [7]

    KONG W W, LEI Y J. Technique for image fusion based on NSST domain and human visual characteristics[J]. Journal of Harbin Engineer University, 2013, 34(6):777-782(in Chinese).
    [8]

    ZHANG L, LUO Ch G, ZHANG Y Y, et al. Fusion algorithm of infrared and visible images based on support value transform[J]. Laser Technology, 2015, 39(3):428-431(in Chinese).
    [9]

    LI G, WANG L, ZHANG R B. Infrared and visible image fusion based on feature energy[J]. Opto-Electronic Engineering, 37(3):83-87(in Chinese).
    [10]

    CHEN M Sh, CAI Zh Sh. Study on fusion of visual and infrared images based on NSCT[J]. Laser Optoelectronics Progress, 2015, 52(6):114-119(in Chinese).
    [11]

    HUANG X Q. Infrared and visible image fusion technology based on fuzzy logic[D]. Chongqing:Chongqing University, 2012:39-41(in Chinese).
    [12]

    ZHANG Y K. Research on shearlet-based SAR/IR image fusion[D]. Nanjing:Nanjing University of Aeronautics and Astronautics, 2011:28-41(in Chinese).
    [13]

    WANG L Q, AN J W. Image fusion based on nonsubsampled Contourlet transform[J]. Computer Engineering and Application, 2008, 44(12):189-191(in Chinese).
    [14]

    DO M N, VETTERLI M. Contourlets:a directional multiresolution image representation[C]//International Conference on Image Processing.New York,USA:IEEE, 2002:357-360(in Chinese).
    [15]

    EASLEYG R, LABAT E D, LIM W Q. Optimally sparse image representations using shearlets[C]//Fortieth Asilomar Conference on Signal, Systems and Computers. New York, USA:IEEE, 2006:974-978.
    [16]

    YUAN Y H, ZHANG J J, CHANG B K, et al. Objective quality evaluation of visible and infrared color fusion image[J]. Optical Engineering, 2011, 50(3):33-45.
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Article views(6557) PDF downloads(247) Cited by()

Proportional views

Infrared and visible light images fusion of fuzzy logic on NSST domain

  • 1. Department of Electronic Engineering, School of Electronics and Information Engineering, Shenyang Aerospace University, Shenyang 110136, China

Abstract: In order to retain more detail information and reduce the algorithm complexity when fusing the infrared and visible light images, a fusion algorithm based on non-subsampled shearlet transform (NSST) and improved fuzzy logic was proposed to decompose source images sparsely on multi-direction and multi-scale. Low-frequency subband coeffients and high-frequency subband coeffients were obtained. The improved average fusion method of fuzzy Cauchy membership function was adopted in low-frequency subband coeffients. The fusion rule of the combination of energy compatibility and visual sensitivity coefficient was used in high-frequency subband coeffients. Finally, fusion image was obtained after NSST inverse transformation. Experimental results show that the fusion method can not only guarantee the definition of fused image, but also shorten the running time of algorithm.

Reference (16)

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return