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论文:2017,Vol:35,Issue(4):698-703 |
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引用本文: |
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王峰, 程咏梅. 基于NSST变换域KFE与DUM-PCNN的伪彩色图像融合[J]. 西北工业大学学报 |
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Wang Feng, Cheng Yongmei. A False Color Image Fusion Method Based on KFE and DUM-PCNN in NSST Domain[J]. Northwestern polytechnical university |
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基于NSST变换域KFE与DUM-PCNN的伪彩色图像融合 |
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王峰, 程咏梅 |
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西北工业大学 自动化学院, 陕西 西安 710129 |
摘要: |
针对夜视图像融合过程中,目标信息不突出、色彩信息显示不自然等问题,提出了一种新的基于NSST变换域的伪彩色融合方法,采用Kirsch特征能量(KFE)和所构造的双通道单链接记忆性脉冲耦合神经网络(DUM-PCNN)设计了新融合方案,在NSST变换域内完成红外(IR)与可见光(VIS)的融合;将融合后的图像与IR及VIS进行线性组合并将其分配至YUV彩色空间,合成伪彩色(FC)图像。最后,利用色彩空间的信息转换技术获得染色后的夜视图像。基于不同数据集的对比实验结果表明,文中所提出的FC图像融合方法,能得到突出的目标信息,呈现出与自然图像相近的外观。 |
关键词:
图像融合
非下采样的剪切波变换
Kirsch特征能量
双通道单链接记忆性脉冲耦合神经网络
膜厚度
像素
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A False Color Image Fusion Method Based on KFE and DUM-PCNN in NSST Domain |
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Wang Feng, Cheng Yongmei |
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School of Automation, Northwestern Polytechnical University, Xi'an 710129, China |
Abstract: |
The target information is not prominent in the process of night vision image fusion, color information display unnatural. A novle false color image fusion method based on the nonsubsampled shearlet transform (NSST) is proposed.Using Kirsh feature energy(KFE) and constructing the dual channel unit link memristive pulse coupled neural network (DUM-PCNN) design the new fusion scheme, completing the infrared (IR) and visible (VIS) image fusion in the NSST domain. The fused image,IR and VIS carried on the linea combination and it assiged the YUV color space, synthesis the false color image (FCI). Finally, Applied color space conversion technology to obtain the pseudo-color image. Experimental results based on different data sets show that the proposed the fusion method can obtain the prominent target information and present the similar to natural images color appearance. |
Key words:
image fusion
non-subsampled shearlet transform
Kirsch feature energy
dual-channel unit-linking memristive pulse coupled neural networks
film thinkness
pixels
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收稿日期: 2017-02-28
修回日期:
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DOI: |
基金项目: 西安市科技计划项目(CXY1436(9)、CXY1350(2))与国家自然科学基金(61135001)资助 |
通讯作者:
Email: |
作者简介: 王峰(1981—),西北工业大学博士研究生,主要从事智能信息处理及机器学习研究。
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作者相关文章 |
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王峰 在本刊中的所有文章 |
程咏梅 在本刊中的所有文章 |
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参考文献: |
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