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Visible and Infrared Image Fusion Using Low-Frequency Coefficients Mapping Fusion Rule in the LWT

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DOI: 10.23977/ieps.2017.1017

Author(s)

Wang Xiaowei, Lai Guojun, Wang XuDong, Hao wenlong

Corresponding Author

Wang Xiaowei

ABSTRACT

In order to improve the effect of detect object in visible and infrared fusion image, a Low-Frequency Coefficients Mapping fusion rule is proposed. The overall fusion scheme based on lifting wavelet transforms. Firstly, the source images of same scene are decomposed using lifting wavelet transform (LWT). Secondly, a Low-Frequency Coefficients Mapping fusion rule is used to select low frequency lifting wavelet coefficients of the visible and infrared images. The fusion rule of local square maximum is used to combine corresponding high frequency coefficients. After fusing low and high frequency coefficients of the source images, the final fused image is obtained using the inverse LWT. The experiments show that the proposed Low Frequency Coefficients Mapping Fusion Rule in the LWT obtains a good fusion results as compared to previous image fusion rule in the LWT such as local energy weighted average and average gradient maxima.

KEYWORDS

Image Fusion, Lifting Wavelet Transform, Fusion Rules, Local Square Maximum, Weighted Average, Low Frequency Coefficients Mapping

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