红外与激光工程
紅外與激光工程
홍외여격광공정
INFRARED AND LASER ENGINEERING
2013年
9期
2547-2552
,共6页
图像融合%均匀离散曲波变换%伪Gibbs现象
圖像融閤%均勻離散麯波變換%偽Gibbs現象
도상융합%균균리산곡파변환%위Gibbs현상
image fusion%uniform discrete curvelet transform%pseudo-Gibbs phenomena
利用均匀离散曲波变换(UDCT)多尺度、多方向、低冗余等特征,提出了一种新的多聚焦图像融合方法。首先使用UDCT对源图像进行多频带分解;然后根据多聚焦图像的特点,对分解后的低频子带系数运用一种基于改进拉普拉斯和算子的方案进行融合,对高频方向子带系数运用基于局部能量的融合规则进行融合,并对融合系数做一致性检测;最后重建各子带系数得到融合图像。实验结果表明:所提方法可以有效地融合源图像中的方向信息和细节特征,同时抑制了融合图像中的伪Gibbs现象;与基于拉普拉斯金字塔分解、小波变换以及轮廓波变换的图像融合方法相比,该方法取得了更好的视觉效果和量化结果。
利用均勻離散麯波變換(UDCT)多呎度、多方嚮、低冗餘等特徵,提齣瞭一種新的多聚焦圖像融閤方法。首先使用UDCT對源圖像進行多頻帶分解;然後根據多聚焦圖像的特點,對分解後的低頻子帶繫數運用一種基于改進拉普拉斯和算子的方案進行融閤,對高頻方嚮子帶繫數運用基于跼部能量的融閤規則進行融閤,併對融閤繫數做一緻性檢測;最後重建各子帶繫數得到融閤圖像。實驗結果錶明:所提方法可以有效地融閤源圖像中的方嚮信息和細節特徵,同時抑製瞭融閤圖像中的偽Gibbs現象;與基于拉普拉斯金字塔分解、小波變換以及輪廓波變換的圖像融閤方法相比,該方法取得瞭更好的視覺效果和量化結果。
이용균균리산곡파변환(UDCT)다척도、다방향、저용여등특정,제출료일충신적다취초도상융합방법。수선사용UDCT대원도상진행다빈대분해;연후근거다취초도상적특점,대분해후적저빈자대계수운용일충기우개진랍보랍사화산자적방안진행융합,대고빈방향자대계수운용기우국부능량적융합규칙진행융합,병대융합계수주일치성검측;최후중건각자대계수득도융합도상。실험결과표명:소제방법가이유효지융합원도상중적방향신식화세절특정,동시억제료융합도상중적위Gibbs현상;여기우랍보랍사금자탑분해、소파변환이급륜곽파변환적도상융합방법상비,해방법취득료경호적시각효과화양화결과。
A novel fusion algorithm for multi-focus images was proposed using Uniform Discrete Curvelet Transform (UDCT) for its characteristics of multi-scale; multi-direction and low redundancy. First, the source images were decomposed into several subbands using UDCT. Then, according to the characteristics of multi-focus images, the coefficients of low-frequency subband were fused with a scheme based on the sum-modified-laplacian; the coefficients of high-frequency subbands were fused with the fusion rule based on local energy; and the consistency of the fused coefficients was verified. Finally, the subband coefficients were reconstructed, and the fused image was obtained. The experiment results indicate that the proposed method can effectively fuse the directional information and detailed features of source images, and suppress pseudo-Gibbs phenomena of fused image; compared with other fusion methods, such as those based on Laplacian pyramid transform, discrete wavelet transform and contourlet transform, this method obtains better fusion quality in terms of both visual and quantified measure.