scholarly journals Fusion of Thermal Infrared and Visible Images Based on Multi-scale Transform and Sparse Representation

2021 ◽  
Vol 8 (3) ◽  
pp. 39-59
Author(s):  
mohammad fallah ◽  
mohsen Azadbakht ◽  
◽  
Keyword(s):  
Sparse Representation ◽  
Thermal Infrared ◽  
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.

scholarly journals A Thermal Infrared and Visible Images Fusion Based Approach for Multitarget Detection under Complex Environment

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Xinnan Fan ◽  
Pengfei Shi ◽  
Jianjun Ni ◽  
Min Li
Keyword(s):  
Thermal Infrared ◽  
Basic Belief ◽  
Measured Signal ◽  
Complex Environment ◽  
Distance Distribution Function ◽  
Detection Approach ◽  
Efficiency And Effectiveness ◽  
Visible Images ◽  
Belief Theory ◽  
Update Process

Multitarget detection under complex environment is a challenging task, where the measured signal will be submerged by noise. D-S belief theory is an effective approach in dealing with Multitarget detection. However, there are some limitations of the general D-S belief theory under complex environment. For example, the basic belief assignment is difficult to establish, and the subjective factors will influence the update process of evidence. In this paper, a new Multitarget detection approach based on thermal infrared and visible images fusion is proposed. To easily characterize the defected heterogeneous image, a basic belief assignment based on the distance distribution function of heterogeneous characteristics is presented. Furthermore, to improve the discrimination and effectiveness of the Multitarget detection, a concept of comprehensive credibility is introduced into the proposed approach and a new update rule of evidence is designed. Finally, some experiments are carried out and the experimental results show the efficiency and effectiveness of the proposed approach in the Multitarget detection task.

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
Sign in / Sign up

Export Citation Format

Share Document