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基于对比度增强与多尺度边缘保持分解的红外与可见光图像融合

朱浩然 刘云清 张文颖

朱浩然, 刘云清, 张文颖. 基于对比度增强与多尺度边缘保持分解的红外与可见光图像融合[J]. 电子与信息学报, 2018, 40(6): 1294-1300. doi: 10.11999/JEIT170956
引用本文: 朱浩然, 刘云清, 张文颖. 基于对比度增强与多尺度边缘保持分解的红外与可见光图像融合[J]. 电子与信息学报, 2018, 40(6): 1294-1300. doi: 10.11999/JEIT170956
ZHU Haoran, LIU Yunqing, ZHANG Wenying. Infrared and Visible Image Fusion Based on Contrast Enhancement and Multi-scale Edge-preserving Decomposition[J]. Journal of Electronics and Information Technology, 2018, 40(6): 1294-1300. doi: 10.11999/JEIT170956
Citation: ZHU Haoran, LIU Yunqing, ZHANG Wenying. Infrared and Visible Image Fusion Based on Contrast Enhancement and Multi-scale Edge-preserving Decomposition[J]. Journal of Electronics and Information Technology, 2018, 40(6): 1294-1300. doi: 10.11999/JEIT170956

基于对比度增强与多尺度边缘保持分解的红外与可见光图像融合

doi: 10.11999/JEIT170956

Infrared and Visible Image Fusion Based on Contrast Enhancement and Multi-scale Edge-preserving Decomposition

  • 摘要: 在低照度环境下拍摄的可见光图像可视性较差,若将其与红外图像直接融合会导致融合结果清晰度不理想。针对这一问题,该文提出一种基于对比度增强与多尺度边缘保持分解的图像融合方法。首先,在融合之前采用基于导向滤波的自适应增强算法提高可见光图像中暗区内容的可视性。其次,通过一种尺度感知边缘保持滤波器对输入图像进行多尺度分解。再次,应用频率调谐滤波构造显著图。最后,利用由导向滤波生成的权重图重构融合图像。实验结果表明,所提方法不仅可以使细节信息更突出,而且还能够有效地抑制伪影。
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出版历程
  • 收稿日期:  2017-10-18
  • 修回日期:  2018-01-15
  • 刊出日期:  2018-06-19

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