• Title of article

    One color contrast enhanced infrared and visible image fusion method

  • Author/Authors

    Yin، نويسنده , , Songfeng and Cao، نويسنده , , Liangcai and Ling، نويسنده , , Yongshun and Jin، نويسنده , , Guofan، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2010
  • Pages
    5
  • From page
    146
  • To page
    150
  • Abstract
    Color constancy (Toet and Franken, 2003 [2]; Toet, 2003 [7]) and color contrast (Scribner et al., 2000 [21]; Lee et al., 2005 [23]) are two important topics for color image fusion. The paper focuses on the low color contrast problem of linear fusion algorithms with color transfer method. Color transfer technology is popular in infrared (IR) and visible image fusion to give the fused image a natural day-time color appearance (Toet, 2003 [7]; Wang et al., 2007 [8]; Zheng and Essock, 2008 [9]). However, in the color transfer step, all three channels of the color space are processed with the same linear mapping without color enhancement, resulting in low color contrast between the target and the background (Wang et al., 2007 [8]). Based on the characteristics of the IR image, we introduce a ratio of local to global divergence of the IR image to improve the color contrast. The enhancement ratios for both hot and cold targets are larger than one, while it tends to one for the background. As a result, the proposed method pops out both hot and cold targets in color, where hot targets will appear intense red, and cold targets will appear cyan. Subjective results show visible color contrast enhancement effects. Target detection experiments through hue and saturation components of the fused image show an improvement in the hit rate for target detection, owing to larger color distance between the target and the background.
  • Keywords
    Target Detection , Color transfer , Color contrast enhancement , image fusion
  • Journal title
    Infrared Physics & Technology
  • Serial Year
    2010
  • Journal title
    Infrared Physics & Technology
  • Record number

    2375772