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基于MSSTO與NSCT變換的可見光與紅外圖像增強(qiáng)融合

發(fā)布時間:2018-05-20 23:29

  本文選題:圖像融合 + 非下采樣輪廓波變換; 參考:《控制與決策》2017年02期


【摘要】:針對紅外與可見光圖像融合結(jié)果中邊緣區(qū)域失真嚴(yán)重、對比度差的問題,提出一種基于多尺度順序翻轉(zhuǎn)算子(MSSTO)和非下采樣輪廓波變換(NSCT)的圖像增強(qiáng)融合算法.首先,采用NSCT將圖像分解成高低頻系數(shù);其次,利用MSSTO從低頻系數(shù)中提取出有效的亮、暗信息,并將其注入到融合低頻系數(shù)中以合成最終低頻系數(shù);再次,高頻系數(shù)采用局部空間頻率加權(quán)(LFSW)與區(qū)域能量取大的融合方案;最后,對合成的高低頻系數(shù)進(jìn)行反NSCT得到融合圖像.實驗結(jié)果驗證了所提出算法的有效性.
[Abstract]:Aiming at the serious edge distortion and poor contrast in infrared and visible image fusion, an image enhancement fusion algorithm based on multi-scale sequential flipping operator (MSSTO) and non-downsampling profilometry transform (NSCT) is proposed. Firstly, the image is decomposed into high and low frequency coefficients by NSCT. Secondly, the effective bright and dark information is extracted from the low frequency coefficients by MSSTO and injected into the fusion low frequency coefficients to synthesize the final low frequency coefficients. The high frequency coefficients are fused with the local spatial frequency weighted NSCT and the region energy is increased. Finally, the fusion image is obtained by inverse NSCT of the synthesized high and low frequency coefficients. Experimental results show that the proposed algorithm is effective.
【作者單位】: 西北工業(yè)大學(xué)自動化學(xué)院;
【基金】:國家自然科學(xué)基金重點(diǎn)項目(61135001) 西安市科技計劃項目(CXY1436(9);CXY1350(2))
【分類號】:TP391.41

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本文編號:1916726


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