闫敬文教授作为通讯作者的论文《A Novel Algorithm for Image Fusion Based on Orthogonal Grouplet Transform and Pulse Coupled Neural Network》发表到SCI期刊 Jounal of Electronic Imaging，刊登在2013年第3期。

Orthogonal grouplet transformation is a kind of weighted multi-scale Haar transform. It can effectively approximate the geometric structure of any shape in a small region or that with long association. PCNN, a simplified neural network, is able to extract useful information from complex background without learning or training. In order to get better fusion effect, grouplet transform is applied for its the advantage of describing complex edges or texture, and then coefficients are fused by PCNN. In this paper, a novel algorithm named GT-PCNN based on grouplet transform and PCNN is proposed. It defines a coefficient fusion rule based on fire times and an association field fusion rule based on regional fire variance. The image fused by GT-PCNN has clear edges and texture and the overall effect looks well. Indicators of average grey, entropy and mutual information are all better than those of the average algorithm, the PCA algorithm and the algorithm based on wavelet transform and PCNN.

论文链接：http://electronicimaging.spiedigitallibrary.org/article.aspx?articleid=1738035