Sub-Regional Infrared-Visible Image Fusion Using Multi-Scale Transformation

Journal of Beijing Institute of Technology ›› 2022, Vol. 31 ›› Issue (6) : 535 -550.

PDF (4452KB)
Journal of Beijing Institute of Technology ›› 2022, Vol. 31 ›› Issue (6) : 535 -550. DOI: 10.15918/j.jbit1004-0579.2021.096

Sub-Regional Infrared-Visible Image Fusion Using Multi-Scale Transformation

Author information +
History +
PDF (4452KB)

Abstract

Infrared-visible image fusion plays an important role in multi-source data fusion, which has the advantage of integrating useful information from multi-source sensors. However, there are still challenges in target enhancement and visual improvement. To deal with these problems, a sub-regional infrared-visible image fusion method (SRF) is proposed. First, morphology and threshold segmentation is applied to extract targets interested in infrared images. Second, the infrared background is reconstructed based on extracted targets and the visible image. Finally, target and background regions are fused using a multi-scale transform. Experimental results are obtained using public data for comparison and evaluation, which demonstrate that the proposed SRF has potential benefits over other methods.

Keywords

image fusion / infrared image / visible image / multi-scale transform

Cite this article

Download citation ▾
null. Sub-Regional Infrared-Visible Image Fusion Using Multi-Scale Transformation. Journal of Beijing Institute of Technology, 2022, 31(6): 535-550 DOI:10.15918/j.jbit1004-0579.2021.096

登录浏览全文

4963

注册一个新账户 忘记密码

References

AI Summary AI Mindmap
PDF (4452KB)

938

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/