采用抗混叠移不变Contourlet变换的云图融合

摘要

Fusion multi-channel satellite cloud images can provide a more comprehensive and reliable information for monitoring and forecasting weather conditions. A fusion method for satellite cloud images using Aliasing-suppression and Shift-invariance Contourlet Transform (AS&SICT) is presented. Firstly, in order to deal with the frequency aliasing and shift-variance problems of the original Contourlet transform, the aliasing-free filter bank is combined with non-subsampled directional filer banks (NDFB) to construct AS&SICT. Then, two channels of satellite images (infrared and visible) are decomposed into low-frequency and high-frequency directional sub-bands by AS&SICT. Next, low-frequency sub-band coefficients are fused by weighted regional energy rule while high-frequency sub-bands coefficients are fused by weighted regional variance rule. Finally, we get the fused cloud image by taking the inverse AS&SICT on the fusion coefficients. Experimental results show that the proposed fusion method can not only improve the resolution of infrared cloud image by joining the texture details of visible cloud image, but also keep the original brightness temperature information of infrared cloud image better.%融合多通道的卫星云图可为监测和预报天气状况提供更加全面可靠的信息。本文提出一种采用抗混叠移不变Contourlet变换(Aliasing-suppression and Shift-invariance Contourlet Transform，AS&SICT)的卫星云图融合方法。首先，为了克服原始Contourlet变换的频谱混叠及移变问题，将抗混叠滤波器组与非下采样方向滤波器组相结合，构造出AS&SICT；然后，对两通道卫星云图(红外与可见光)采用AS&SICT分解成低频及若干高频方向子带，对低频子带系数采取加权区域能量融合规则，而对高频子带系数采取加权区域方差融合规则进行融合处理；最后，对融合后系数进行抗混叠移不变 Contourlet 逆变换，得到融合云图。实验结果表明，本文方法融合的云图，由于增添了可见光云图的纹理细节信息，不仅提高了原始红外云图的分辨率，而且较好地保留了红外云图的亮温信息。