Image fusion scheme based on modified dual pulse coupled neural network

El-taweel G.S.; Helmy A.K.

首页> 外文期刊>Image Processing, IET >Image fusion scheme based on modified dual pulse coupled neural network

【24h】

Image fusion scheme based on modified dual pulse coupled neural network

机译：基于改进双脉冲耦合神经网络的图像融合方案

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

Image fusion combines information from multiple images of the same scene to obtain a composite image which is more suitable for further image processing tasks. This study presented an image fusion scheme based on the modified dual pulse coupled neural network (PCNN) in non-subsampled contourlet transform (NSCT) domain. NSCT can overcome the lack of shift invariance in contourlet transform. Original images were decomposed to obtain the coefficients of low-frequency subbands and high-frequency subbands. In this fusion scheme, a new sum-modified Laplacian of the low-frequency subband image, which represents the edge-feature of the low-frequency subband image in NSCT domain, is presented and input to motivate modified dual PCNN. For fusion of high-frequency subband coefficients, spatial frequency will be used as the gradient features of images to motivate dual channel PCNN and to overcome Gibbs phenomena. Experimental results show that the proposed scheme can significantly improve image fusion performance, performs very well in fusion and outperforms conventional methods such as traditional discrete wavelet transform, dual tree complex wavelet and PCNN in terms of objective criteria and visual appearance.

机译：图像融合结合了来自同一场景的多个图像的信息，以获得更适合于进一步图像处理任务的合成图像。这项研究提出了一种基于非双采样轮廓波变换（NSCT）域中的改进的双脉冲耦合神经网络（PCNN）的图像融合方案。 NSCT可以克服Contourlet变换中缺少移位不变性的问题。分解原始图像以获得低频子带和高频子带的系数。在该融合方案中，提出了表示低频子带图像在NSCT域中的边缘特征的低频子带图像的总和修正拉普拉斯算子，并将其输入以激发修正的双PCNN。为了融合高频子带系数，空间频率将用作图像的梯度特征，以激发双通道PCNN并克服吉布斯现象。实验结果表明，该方案可以显着提高图像融合性能，融合效果很好，并且在客观标准和视觉外观上均优于传统的离散小波变换，双树复小波和PCNN等传统方法。

著录项

来源
《Image Processing, IET》 |2013年第5期|407-414|共8页
作者
El-taweel G.S.; Helmy A.K.;
展开▼
作者单位

Computer Science, Faculty of Computers and Informatics, Suez Canal University, Ismailia, Egypt|c|;

展开▼
收录信息
原文格式 PDF
正文语种 eng
中图分类
关键词

相似文献

外文文献
中文文献
专利

1. Research on infrared image segmentation and fusion of substation based on modified unit‐linking‐pulse coupled neural networks and affine speeded up robust feature [J] . Peng Daogang, Wang Lanqing, Chen Yuewei, Microwave and optical technology letters . 2019,第6期

机译：基于改进的单位连接脉冲耦合神经网络和仿射加速强大特征的变电站红外图像分割和融合研究
2. Multi-focus image fusion algorithm based on pulse coupled neural networks and modified decision map [J] . Du Chaoben, Gao Shesheng Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic . 2018,第期

机译：基于脉冲耦合神经网络和修改决策地图的多聚焦图像融合算法
3. A region-based multi-sensor image fusion scheme using pulse-coupled neural network [J] . Min Li, Wei Cai, Zheng Tan Pattern recognition letters . 2006,第16期

机译：基于脉冲耦合神经网络的基于区域的多传感器图像融合方案
4. Image Fusion Using Pulsed Coupled Neural Network with Modified Spatial Frequency based on NSCT [C] . N Archana, R Menaka, R Dhanagopal International Conference on Electronics, Communication and Aerospace Technology . 2020

机译：基于NSCT的修改空间频率脉冲耦合神经网络的图像融合
5. Physiologically-based vision modeling applications and gradient descent-based parameter adaptation of pulse coupled neural networks. [D] . Broussard, Randy Paul. 1997

机译：基于生理的视觉建模应用和基于梯度下降的脉冲耦合神经网络参数自适应。
6. Pulse Coupled Neural Network-Based Multimodal Medical Image Fusion via Guided Filtering and WSEML in NSCT Domain [O] . Liangliang Li, Hongbing Ma 2021

机译：基于脉冲耦合的基于神经网络的多媒体医学图像融合通过导向滤波和NSCT域WSEML
7. Fusion of Medical Images Using Adaptive Pulse Coupled Neural Networks Based on QCSA Optimization [O] . Pydi Kavita 2021

机译：使用基于QCSA优化的自适应脉冲耦合神经网络的医学图像融合

Image fusion scheme based on modified dual pulse coupled neural network

摘要

著录项

相似文献

相关主题

期刊订阅