An infared polarization image fusion method based on NSCT and fuzzy C-means clustering segmentation algorithms

2014 ◽  
Author(s):  
Xuelian Yu ◽  
Qian Chen ◽  
Guohua Gu ◽  
Weixian Qian ◽  
Mengxi Xu
Keyword(s):  
Image Fusion ◽  
Fusion Method ◽  
Fuzzy C Means ◽  
Segmentation Algorithms ◽  
Polarization Image ◽  
Fuzzy C Means Clustering ◽  
Image Fusion Method

Polarization Image Fusion Method Using Color Transfer and Clustering-Based Segmentation

2011 ◽  
Vol 40 (1) ◽  
pp. 149-153 ◽  
Author(s):  
周浦城 ZHOU Pu-cheng ◽  
张洪坤 ZHANG Hong-kun ◽  
薛模根 XUE Mo-gen
Keyword(s):  
Image Fusion ◽  
Fusion Method ◽  
Color Transfer ◽  
Polarization Image ◽  
Image Fusion Method

A new polarization image fusion method based on Choquet fuzzy integral

2013 ◽  
Author(s):  
Hong-wu Yuan ◽  
Qin-chao Huang ◽  
Guo-ming Xu ◽  
Cheng-liang Yin
Keyword(s):  
Image Fusion ◽  
Fuzzy Integral ◽  
Fusion Method ◽  
Polarization Image ◽  
Image Fusion Method

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.

Gradient-based multi-focus image fusion method using convolution neural network

2021 ◽  
Vol 92 ◽  
pp. 107174
Author(s):  
Yang Zhou ◽  
Xiaomin Yang ◽  
Rongzhu Zhang ◽  
Kai Liu ◽  
Marco Anisetti ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Fusion ◽  
Convolution Neural Network ◽  
Fusion Method ◽  
Gradient Based ◽  
Focus Image ◽  
Image Fusion Method
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