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基于非抽樣Shearlet變換的紅外與可見光圖像融合方法
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西北農(nóng)林科技大學(xué)人才基金資助項目


Infrared and Visible Light Images Fusion Algorithm Based on Non-subsampled Shearlet Transform
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    摘要:

    針對同一場景紅外圖像與可見光圖像的融合問題,提出了一種基于非抽樣Shearlet變換(NSST)的融合算法。首先對源圖像進行多尺度、多方向NSST分解,得到低頻子帶系數(shù)和各帶通方向子帶系數(shù);然后,在局部區(qū)域結(jié)構(gòu)相似度的基礎(chǔ)上,采用基于局部區(qū)域能量的方法選擇融合圖像的低頻子帶系數(shù);基于脈沖耦合神經(jīng)網(wǎng)絡(luò)(PCNN)對帶通方向子帶空間頻率(SF)的響應(yīng)而得到的點火次數(shù)選擇融合圖像的帶通方向子帶系數(shù),得到融合圖像的NSST系數(shù);最后經(jīng)過非抽樣Shearlet逆變換得到融合圖像。實驗結(jié)果表明:與其他5種相關(guān)的融合方法相比,該方法可獲得具有更好視覺效果和更優(yōu)量化指標(biāo)的融合圖像。

    Abstract:

    Focusing on the fusion problem of infrared and visible light images in the same scene, a novel multirsensor image fusion algorithm based on the non subsampled Shearlet transform was proposed. Firstly, the NSST was performed on the source images at different scales and directions, thus the low frequency subband coefficients and varieties of directional bandpass subband coefficients were obtained. Secondly, the low frequency subband coefficients of the fused image were selected based on the local structural similarity and local energy of the two source images, and the bandpass subband coefficients of the fused image were selected based on the firing times of the pulse coupled neural network(PCNN), so the NSST coefficients of fused image was got. Finally, the fused image was obtained by performing the inverse NSST on the combined coefficients. Quantitative and qualitative analysis of the experimental results demonstrated that the proposed method performs significantly better than the other five related methods.

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高國榮,劉艷萍.基于非抽樣Shearlet變換的紅外與可見光圖像融合方法[J].農(nóng)業(yè)機械學(xué)報,2014,45(3):268-274. Gao Guorong, Liu Yanping. Infrared and Visible Light Images Fusion Algorithm Based on Non-subsampled Shearlet Transform[J]. Transactions of the Chinese Society for Agricultural Machinery,2014,45(3):268-274.

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  • 收稿日期:2013-04-16
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  • 在線發(fā)布日期: 2014-03-10
  • 出版日期: 2014-02-10