Hyperspectral multi-band image fusion algorithm by using pulse coupled neural networks

Considering hyperspectral images with multi-band and large data amount, a novel fusion algorithm of hyperpsectral multi-band images based on pulse coupled neural networks (PCNN) was proposed. Firstly, the original PCNN model was expanded according to the multi-input characteristics of the hyperspectral images, and a multi-channel PCNN model was applied to fuse the multiple input images in a nonlinear manner. Then, the modified variable threshold exponent increasing attenuation model was proposed to improve fusion effect and reduce time complexity by analyzing the characteristics and shortage of the traditional variable threshold attenuation model. Finally, the fusion image with a certain degree of enhancement effect was obtained by the time matrix which recorded the ignition time. The experiment results show that the proposed algorithm outperforms the traditional fusion algorithms based on principle component analysis (PCA) and wavelet transform.