Submit Manuscript  

Article Details


Image Fusion Method Based on Multi-scale Directional Fast Guided Filter and Convolutional Sparse Representation

Author(s):

Liu Xian-Hong and Chen Zhi-Bin*   Pages 1 - 7 ( 7 )

Abstract:


Background: A multi-scale multidirectional image fusion method is proposed, which introduces the Nonsubsampled Directional Filter Bank (NSDFB) into the multi-scale edge-preserving decomposition based on the fast guided filter.

Method: The proposed method has the advantages of preserving edges and extracting directional information simultaneously. In order to get better-fused sub-bands coefficients, a Convolutional Sparse Representation (CSR) based approximation sub-bands fusion rule is introduced and a Pulse Coupled Neural Network (PCNN) based detail sub-bands fusion strategy with New Sum of Modified Laplacian (NSML) to be the external input is also presented simultaneously.

Results: Experimental results have demonstrated the superiority of the proposed method over conventional methods in terms of visual effects and objective evaluations.

Keywords:

Image fusion, Fast guided filter, Convolutional Sparse Representation, Nonsubsampled Directional Filter Bank, Pulse Coupled Neural Network, Sum of Modified Laplacian.

Affiliation:

Department of Electronics and Optics engineering, Army Engineering University, Shijiazhuang 050003, No. 32181 Troop, Chinese People`s Liberation Army, P.O. Box: 050000, Shijiazhuang



Read Full-Text article