Fusion of Infrared and Visible Images Based on Multi-Scale Edge-Preserving Decomposition and Sparse Representation

2018 ◽  
Author(s):  
Chuanzhen Rang ◽  
Yongxing Jia ◽  
Yu Yang ◽  
Ying Zhu ◽  
Yuan Wang
Keyword(s):  
Sparse Representation ◽  
Edge Preserving ◽  
Multi Scale ◽  
Visible Images

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

2019 ◽  
Vol 12 (3) ◽  
pp. 263-269
Author(s):  
Liu Xian-Hong ◽  
Chen Zhi-Bin
Keyword(s):  
Image Fusion ◽  
Sparse Representation ◽  
Filter Bank ◽  
Guided Filter ◽  
Fusion Method ◽  
Edge Preserving ◽  
Directional Information ◽  
Multi Scale ◽  
Directional Filter ◽  
Image Fusion Method

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. Methods: 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. Conclusion: In this paper, combining fast guided filter and nonsubsampled directional filter bank, a multi-scale directional edge-preserving filter image fusion method is proposed. The proposed method has the features of edge-preserving and extracting directional information.

Fusion of infrared and visible images combined with NSDTCT and sparse representation

2016 ◽  
Vol 24 (7) ◽  
pp. 1763-1771 ◽  
Author(s):  
殷 明 YIN Ming ◽  
段普宏 DUAN Pu-hong ◽  
褚 标 CHU Biao ◽  
梁翔宇 LIANG Xiang-yu
Keyword(s):  
Sparse Representation ◽  
Visible Images
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