基于区域特征的非下采样Contourlet变换卫星云图融合

对不同的卫星云图进行融合处理,可为灾害性天气的监测和预警提供更为全面的信息,提出一种基于区域特征的非下采样Contourlet变换(NSCT)卫星云图融合新方法。首先,采用NSCT对卫星云图进行多尺度和多方向分解,得到低通子带系数和各带通方向子带系数;然后,对低通子带系数采用基于图像区域相关系数和区域能量的自适应融合规则,对各带通方向子带系数采用加权和区域方差相结合的融合规则;最后,对融合系数进行NSCT逆变换得到融合云图。实验结果表明,该算法在增强融合云图的纹理及边缘等细节信息的同时,能更好地保留源红外云图的红外信息,融合效果更好。

Satellite cloud image fusion based on regional feature with nonsubsampled contourlet transform

The fusion of different satellite cloud images can provide more comprehensive information for surveillance and early warning of disastrous weather.A satellite cloud image fusion algorithm based on regional feature with NonSubsampled Contourlet Transform(NSCT) was proposed.Firstly,the source images were decomposed at multi-scale and multi-direction by NSCT.Then the self-adaptive fusion rule based on regional correlation coefficient and regional energy was used to fuse the low frequency coefficients,and the fusion rule of regional variance in combination with weighting was used for the fusion of the high frequency coefficients.Finally,the fused image was obtained by performing the inverse NSCT on the fused coefficients.The experimental results illustrate that while the texture and edge feature of the fused cloud image are enriched,the infrared information are preserved as much as possible and the proposed algorithm acquires better fusion result.