Color Image Segmentation Based on Improved Internal Activity Multi-Channel Pulse Coupled Neural Networks

2015 ◽  
Vol 52 (12) ◽  
pp. 121001
Author(s):  
王蒙军 Wang Mengjun ◽  
郭林 Guo Lin ◽  
王霞 Wang Xia ◽  
郝宁 Hao Ning
Keyword(s):  
Neural Networks ◽  
Image Segmentation ◽  
Color Image ◽  
Color Image Segmentation ◽  
Coupled Neural Networks ◽  
Pulse Coupled Neural Networks

Underwater Laser Image Segmentation Method based on Adaptive Pulse Coupled Neural Networks

2015 ◽  
Vol 35 (4) ◽  
pp. 0410004
Author(s):  
王博 Wang Bo ◽  
万磊 Wan Lei ◽  
李晔 Li Ye ◽  
张铁栋 Zhang Tiedong
Keyword(s):  
Neural Networks ◽  
Image Segmentation ◽  
Segmentation Method ◽  
Coupled Neural Networks ◽  
Underwater Laser ◽  
Pulse Coupled Neural Networks

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.

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