Color image fusion based on simplified pulse coupled neural network and HSV color space

2016 ◽  
Author(s):  
Jin Xin ◽  
Dongming Zhou ◽  
Shaowen Yao ◽  
Rencan Nie ◽  
Chuanbo Yu ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Fusion ◽  
Color Image ◽  
Color Space ◽  
Hsv Color Space ◽  
Pulse Coupled Neural Network

scholarly journals Multifocus Color Image Fusion Based on NSST and PCNN

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Xin Jin ◽  
Rencan Nie ◽  
Dongming Zhou ◽  
Quan Wang ◽  
Kangjian He
Keyword(s):  
Neural Networks ◽  
Image Fusion ◽  
Color Image ◽  
Color Space ◽  
Color Spaces ◽  
Fusion Algorithm ◽  
Hsv Color Space ◽  
Coupled Neural Networks ◽  
Different Color ◽  
Pulse Coupled Neural Networks

This paper proposed an effective multifocus color image fusion algorithm based on nonsubsampled shearlet transform (NSST) and pulse coupled neural networks (PCNN); the algorithm can be used in different color spaces. In this paper, we take HSV color space as an example, H component is clustered by adaptive simplified PCNN (S-PCNN), and then the H component is fused according to oscillation frequency graph (OFG) of S-PCNN; at the same time, S and V components are decomposed by NSST, and different fusion rules are utilized to fuse the obtained results. Finally, inverse HSV transform is performed to get the RGB color image. The experimental results indicate that the proposed color image fusion algorithm is more efficient than other common color image fusion algorithms.

scholarly journals A Novel Image Fusion Framework Based on Sparse Representation and Pulse Coupled Neural Network

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 98290-98305 ◽  
Author(s):  
Li Yin ◽  
Mingyao Zheng ◽  
Guanqiu Qi ◽  
Zhiqin Zhu ◽  
Fu Jin ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Fusion ◽  
Sparse Representation ◽  
Pulse Coupled Neural Network ◽  
Fusion Framework

scholarly journals An Improved Pulse-Coupled Neural Network Model for Pansharpening

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2764 ◽  
Author(s):  
Xiaojun Li ◽  
Haowen Yan ◽  
Weiying Xie ◽  
Lu Kang ◽  
Yi Tian
Keyword(s):  
Neural Network ◽  
Image Fusion ◽  
Multispectral Image ◽  
Transform Domain ◽  
Human Visual Perception ◽  
Pulse Coupled Neural Network ◽  
Proposed Model ◽  
Spectral Fidelity ◽  
Fusion Methods ◽  
Injection Mechanism

Pulse-coupled neural network (PCNN) and its modified models are suitable for dealing with multi-focus and medical image fusion tasks. Unfortunately, PCNNs are difficult to directly apply to multispectral image fusion, especially when the spectral fidelity is considered. A key problem is that most fusion methods using PCNNs usually focus on the selection mechanism either in the space domain or in the transform domain, rather than a details injection mechanism, which is of utmost importance in multispectral image fusion. Thus, a novel pansharpening PCNN model for multispectral image fusion is proposed. The new model is designed to acquire the spectral fidelity in terms of human visual perception for the fusion tasks. The experimental results, examined by different kinds of datasets, show the suitability of the proposed model for pansharpening.

Image fusion scheme based on modified dual pulse coupled neural network

2013 ◽  
Vol 7 (5) ◽  
pp. 407-414 ◽  
Author(s):  
Ghada Sami El-taweel ◽  
Ashraf Khaled Helmy
Keyword(s):  
Neural Network ◽  
Image Fusion ◽  
Pulse Coupled Neural Network ◽  
Fusion Scheme
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