SAR and multispectral image fusion algorithm based on pulse coupled neural networks and non-subsampled Contourlet transform
非下采样Contourlet变换与脉冲耦合神经网络相结合的SAR与多光谱图像融合

SAR and optical images have large differences in imaging-mechanism and spectral characteristics. Moreover, SAR images are always severe contaminated by speckle noise. Consequently, it is very difficult to obtain satisfying results while fusing SAR and optical images. Considering the advantage of non-sampled Contourlet transform(NSCT) comparing with other multiscale decomposition methods, a method of image fusion based on pulse coupled neural networks(PCNN) and NSCT is proposed. The source images are first decomposed in the NSCT domain. Energy of log in the NSCT domain is the input to motivate PCNN and coefficients in NSCT domain with high firing frequency are selected as coefficients of the fused image. Then the final fused image is obtained by NSCT reconstruction. Experimental results demonstrate that the proposed algorithm outperforms many other algorithms in both objective criteria and visual appearance.