改进NSCT和IHS变换相结合的遥感影像融合

Remote sensing image fusion based on an improved NSCT and IHS transformation

目的目的为了增强多光谱和全色影像融合质量,提出基于脉冲耦合神经网络(PCNN)的非下采样Contoulet变换(NSCT)和IHS变换相结合的融合方法。方法先对多光谱图像进行IHS变换提取亮度I分量,采用主成分分析增强I分量得到新的I+分量;然后通过NSCT变换分别对I+分量和全色图像进行分解,并采用边缘梯度信息激励的PCNN得到融合图像的低频和高频分量;最后进行NSCT逆变换、IHS逆变换得到融合图像。结果利用资源一号02C卫星数据进行实验,结果表明该算法在保留光谱信息的同时提高了图像空间分辨率,获得了较好的融合效果。结论结合NSCT和IHS变换的融合方法在视觉效果和客观评价指标上都优于常用的图像融合方法。

Objective In order to improve the quality of the multispectral and panchromatic satellite images fusion, a meth- od to combine the non-subsampled contourlet transform （NSCT） based on the pulse coupled neural network （PCNN） with the IHS （intensity-hue-saturation） transformation is proposed. Method First, the IHS transformation of the multispeetral images is conducted to extract the I component. Then it is enhanced using the Principal Component Analysis to gaina new component I ＋ ; Second, the panchromatic image and the I ~ component are decomposed by NSCT and then the edge gradient information is used to trigger on the PCNN to obtain the coefficient of the low-frequencies and high-frequencies of the fusion images; Finally, a fused imagecan be obtained by taking the inversed NSCT and inversed IHS to reconstruct the images. Result Experimental resuhs on the ZY-I0 2C satellite data show that the proposed method can improve the spatial resolution while preserving spectral information, and obtain better fusion effect. Conclusion The fusion method based on NSCT and IHS transformhas has more advantage than the common image fusion methods in the aspects of visual effect and objective evaluation.