基于Contourlet变换和IPCNN的融合算法及其在可见光与红外线图像融合中的应用

INFRARED IMAGE FUSION ALGORITHM BASED ON CONTOURLET TRANSFORM AND IMPROVED PULSE COUPLED NEURAL NETWORK

针对多传感器图像融合这一图像处理领域中的研究热点问题,提出了一种基于Contourlet变换和IPCNN的融合方法.该融合方法首先利用Contourlet对输入图像进行多尺度、多方向稀疏分解,准确地捕获图像中的二维或高维奇异信息,然后在Contourlet域充分利用IPCNN的同步激发特性,进行基于IPCNN的融合策略设计,提高了融合效果.仿真结果表明,该算法具有很好的融合效果.

A fusion algorithm based on contourlet transform and improved pulse coupled neural network was proposed. By using the contourlet transform, the input images were firstly decomposed into a number of sub-images with various scale and directional features. Then, based on the IPCNN, a fusion rule in the contourlet domain was given. The fused coefficients could be generated by the IPCNN based fusion rule and the fused image was obtained by performing the inverse contourlet transform to the fused coefficients. The proposed algorithm was successfully applied for the visible image and infrared image fusion. The simulation results confirm the validity of the proposed method.