• DocumentCode
    2940076
  • Title

    Improving Image Enhancement by Gradient Fusion

  • Author

    Xu, Xin ; Chen, Qiang ; Xia, Deshen

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Nanjing Univ. of Sci. & Technol., Nanjing, China
  • fYear
    2010
  • fDate
    19-21 June 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    We present a fusion approach in the gradient domain to combine complementary advantages between image enhancement results for visualization improvement. A weighted structure tensor is employed to capture significant details of each input channel, and local contrast is incorporated in the design of fusion weights. Experimental results demonstrate that the fused image can preserve significant detail and structural information of each input image, and the visual effect is improved.
  • Keywords
    data visualisation; gradient methods; image enhancement; image fusion; gradient fusion; image enhancement; visualization improvement; weighted structure tensor; Computer science; Data mining; Dynamic range; Frequency domain analysis; Histograms; Humans; Image enhancement; Image fusion; Lighting; Tensile stress;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Photonics and Optoelectronic (SOPO), 2010 Symposium on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-4963-7
  • Electronic_ISBN
    978-1-4244-4964-4
  • Type

    conf

  • DOI
    10.1109/SOPO.2010.5504345
  • Filename
    5504345