Panchromatic and Multispectral Image Fusion Method Based on Nonsubsampled Contourlet Transform

FU Yao; SUN Xue-chen; XUE Xu-cheng; HAN Cheng-shan; ZHAO Yun-long; QU Li-xin

doi:10.3788/YJYXS20132803.0429

您当前的位置：

首页 >

文章列表页 >

Panchromatic and Multispectral Image Fusion Method Based on Nonsubsampled Contourlet Transform

Imaging Technology & Image Processing | 更新时间：2020-08-12

- Panchromatic and Multispectral Image Fusion Method Based on Nonsubsampled Contourlet Transform
- Chinese Journal of Liquid Crystals and Displays Vol. 28, Issue 3, Pages: 429-434(2013)
- 作者机构：
  
  中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
- 作者简介：
- 基金信息：
- DOI：10.3788/YJYXS20132803.0429
  CLC： TP951.1
- Received：15 October 2012，
  
  Revised：04 February 2013，
  
  Published Online：22 March 2013，
  
  Published：15 June 2013
- 稿件说明：
移动端阅览
傅瑶, 孙雪晨, 薛旭成, 韩诚山, 赵运隆, 曲利新. 基于非下采样轮廓波变换的全色图像与多光谱图像融合方法研究[J]. 液晶与显示, 2013,28(3): 429-434

FU Yao, SUN Xue-chen, XUE Xu-cheng, HAN Cheng-shan, ZHAO Yun-long, QU Li-xin. Panchromatic and Multispectral Image Fusion Method Based on Nonsubsampled Contourlet Transform[J]. , 2013,28(3): 429-434
傅瑶, 孙雪晨, 薛旭成, 韩诚山, 赵运隆, 曲利新. 基于非下采样轮廓波变换的全色图像与多光谱图像融合方法研究[J]. 液晶与显示, 2013,28(3): 429-434 DOI： 10.3788/YJYXS20132803.0429.

FU Yao, SUN Xue-chen, XUE Xu-cheng, HAN Cheng-shan, ZHAO Yun-long, QU Li-xin. Panchromatic and Multispectral Image Fusion Method Based on Nonsubsampled Contourlet Transform[J]. , 2013,28(3): 429-434 DOI： 10.3788/YJYXS20132803.0429.

摘要

为了同时改善遥感图像的空间分辨率和光谱分辨率

提高遥感图像信息量

提出了一种基于非下采样轮廓波变换的全色图像与多光谱图像的融合方法。首先

对多光谱图像进行HIS变换

获取其亮度分量;分别对多光谱图像的亮度分量和全色图像进行非下采样轮廓波变换

获取其高低频系数;采用脉冲耦合神经网络算法和加权融合对高低频系数进行选取;最后

经过逆HIS变换和逆非下采样轮廓波变换获得最终融合后图像。实验结果表明

本文融合方法处理后遥感图像的光谱失真少

信息量和清晰度都优于其他传统遥感图像融合方法。

Abstract

A novel panchromatic and multi-spectral image fusion method based on non-subsampled Contourlet Transform(NSCT) was proposed for the purpose of improving spatial and spectral resolution of remote sensing images. Firstly

HIS transformation was applied in multi-spectral image for getting its intensity component. Then

NSCT was used both in the intensity component of multi-spectral image and panchromatic image in order that the high frequency and low frequency coefficients were acquired. Furthermore

pulse-coupled neural network (PCNN) and the weighted fusion were used in the high and low frequency coefficients independently. Finally

inverse HIS transform and inverse NSCT were applied to get the fusion image. The experiment results show that many contrast experiments were made. In conclusion

space resolution and information amount of the fused image were both greatly improved.

关键词

Keywords

references

张永生,巩丹超,刘军. 高分辨率遥感卫星应用——成像模型、处理算法及应用技术 [M].北京:科学出版社, 2007.[2] 闫敬文,屈小波. 超小波分析及应用 [M]. 北京:国防工业出版社,2008.[3] 焦李成,侯彪,王爽,等. 图像多尺度几何分析理论与应用——后小波分析理论与应用 [M]. 西安:西安电子科技大学出版社,2008.[4] QU X B, YAN J W, XIAO H Z, et al. Image fusion algorithm based on spatial frequency-motivated pulse coupled neural networks in nonsubsampled contourlet transform domain [J]. Acta Automatica Sinica, 2008,34(12):1508-1514.[5] 屈小波,闫敬文,杨贵德.改进拉普拉斯能量和的尖锐频率局部化Contourlet域多聚焦图像融合方法 [J]. 光学精密工程, 2009, 17(5):1203-1212.[6] 武治国,王延杰,李桂菊.应用小波变换的自适应脉冲耦合神经网络在图像融合中的应用 [J]. 光学精密工程, 2010,18(3):708-715.[7] Do Minh N, Vetterli Martin. "Contourlets" In Beyond Wavelets [M]. Academic Press, 2002:1-27.[8] Burt P J,Adelson E. The laplacian pyramid as a compact image code [J]. IEEE Trans. Commun, 1983, 31(4):532-540.[9] 林立宇,张友焱,孙涛,等. Contourlet变换——影像处理应用 [M]. 北京:科学出版社,2008.[10] da Cunha A L, Zhou Jianping, Do M N. The non-subsampled contourlet transform:theory, design, and applications in denoising[C]//IEEE Transactions On Image Processing, Genoa, Italy:IEEE, 2005:749-752.[11] Padgett M L,Johnson J L. Pulse coupled neural networks(PCNN) and wavelets: biosensor application[C]//International Conference on Neural Networks, Houston,USA:IEEE,1997:2507-2512.[12] 李云红,伊欣. 基于脉冲耦合神经网络模型的小波自适应斑点噪声滤除算法 [J]. 光学精密工程, 2012,20(9):2060-2067.[13] 姚军财.基于人眼对比度敏感视觉特性的图像质量评价方法 [J]. 液晶与显示, 2011,26(3):390-396.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Robust stitching method for borehole wall images under multi-interference imaging conditions

Image defogging algorithm based on multi-scale residual feature fusion

Infrared and visible image fusion algorithm based on structure-texture decomposition

Laboratory flame image segmentation and recognition by fusing infrared and visible light

Fusion of NSCT infrared and visible images based on improved FT saliency detection

Related Author

ZHAO Yuhang

LUO Qi

XU Wangming

LI Yaoxiang

SUN Mengyu

DI Ruohai

WANG Peng

LI Xiaoyan

Related Institution

School of Information Science and Engineering， Wuhan University of Science and Technology

School of Electronics and Information Engineering， Xi'an Technological University

School of Optoelectronic Engineering， Xi'an Technological University

School of Mechanical and Electrical Engineering， Xi'an Technological University

College of Electronic Information and Artificial Intelligence， Shaanxi University of Science and Technology

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China 130033 Postal code：130033
Tel：0431-86176059 Email：yjxs@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰