改进的ISH变换和小波变换相结合的图像融合
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摘要
在分析IHS变换时发现,IHS变换中亮度分量的计算是从红绿蓝三种颜色中平均提取三分之一作为总亮度,而人眼对绿色最敏感(占60%)、其次是红色(占30%)、再者是蓝色(占10%),故本文对亮度分量的计算公式做了修改。在此基础上,提出了一种改进的IHS变换和小波变换相结合的图像融合方法。首先对多光谱图像进行改进的IHS变换,然后利用小波变换分别对I分量和全色高分辨率图像做小波分解,并对小波低频系数基于局部能量进行融合,小波高频系数基于局部方差进行融合,最后进行IHS逆变换,得到融合结果图像。结果表明,本文提出的方法在保持光谱源图像特性方面有优势,也较多地保留了源图像的空间细节信息,融合图像的扭曲程度小。
In the analysis and IHS transform we found that total intensity is obtained through a third from each red, green and blue in calculation of intensity of IHS transformation. As the human eye is the most sensitive to green(60%), followed by red(30%), moreover is blue(10%), therefore, the formula of intensity component has been modified in this paper. On this basis, a image fusion method of combined the improved IHS transform with wavelet transform has been presented. First, the improved IHS transform for multispectral image is conducted, and the I component and high-resolution panchromatic image are decomposed using wavelet transform, respectively, and the low frequency and high frequency coefficient of high-resolution panchromatic image are fused with those of the I component based on local energy and on local variance, respectively. Finally, IHS inverse transformation is conducted, and the fusion result images are obtained. Results show that the proposed method in this paper has an advantage in keeping the source image spectral characteristics and also keep the spatial fine structure of the source image, and decrease distortion degree of fused image.
In the analysis and IHS transform we found that total intensity is obtained through a third from each red, green and blue in calculation of intensity of IHS transformation. As the human eye is the most sensitive to green(60%), followed by red(30%), moreover is blue(10%), therefore, the formula of intensity component has been modified in this paper. On this basis, a image fusion method of combined the improved IHS transform with wavelet transform has been presented. First, the improved IHS transform for multispectral image is conducted, and the I component and high-resolution panchromatic image are decomposed using wavelet transform, respectively, and the low frequency and high frequency coefficient of high-resolution panchromatic image are fused with those of the I component based on local energy and on local variance, respectively. Finally, IHS inverse transformation is conducted, and the fusion result images are obtained. Results show that the proposed method in this paper has an advantage in keeping the source image spectral characteristics and also keep the spatial fine structure of the source image, and decrease distortion degree of fused image.
引文
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[10]崔永胜.基于改进的áTrous小波与IHS变换法遥感影像融合研究[D].济南:山东科技大学,2009.Cui YS.Remote sensing image fusion research based on the improved a Trous wavelet and IHS transform method[D].Jinan:Shandong University of Science and Technology,2009.
[11]范文涛.基于小波变换的图像融合技术研究[D].郑州:河南大学,2010.Fan WT.Image fusion technology research based on wavelet transform[D].Zhengzhou:Henan University,2010.
[12]王宇庆.局部方差在图像质量评价中的应用[J].中国光学,2005,13(2):1-6.Wang YQ.The application of local variance on image quality assessment[J].China Optics,2005,13(2):1-6.
[13]龚建周,刘彦随,夏北成,等.小波基及其参数对遥感影像融合图像质量的影响[J].地理与地理信息科学,2010,26(2):6-8.Gong JZ,Liu YS,Xia BC,et al.Influence of wavelet base and its parameters on the quality of the remote sensing image fusion[J].Geography and Geo-Information Science,2010,26(2):6-8.
[14]朱俊杰.高分辨率光学和SAR遥感数据融合及典型目标提取方法研究[D].北京:中国科学院遥感应用研究所,2005.Zhu JJ.High resolution optical and SAR remote sensing data fusion method and typical target extraction[D].Beijing:Institute of Remote Sensing Applications Chinese Academy of Sciences,Beijing,2005.
[15]杨飒.医学图像融合中最佳小波分解层数的选择[J].计算机工程与设计,2008,29(20):5265-5268.Yang S.The choice of best wavelet decomposition layers in the medical image fusion[J].Computer Engineering&Design,2008,29(20):5265-5268.
[16]秦定宇,王敬东,李鹏.图像融合中小波基的选择分析[J].光电子技术,2006,26(3):203-207.Qin DY,Wang JD,Li P.Wavelet basis selection and evaluation for image fusion[J].Optoelectronic Technology,2006,26(3):203-207.
[17]程坚,王敬东,李鹏.SAR与可见光图像融合中小波基选择的研究[J].红外技术,2008,30(3):158-162.Cheng J,Wang JD,Li P.Research on wavelet basis selection in the image fusion in SAR and visual[J].Infrared Technology,2008,30(3):158-162.
[18]李晖晖,郭雷,刘航.基于不同类型小波变换的SAR与可见光图像融合研究[J].光子学报,2006,35(8):1263-1267.Li HH,Guo L,Liu H.Research on SAR and optical image fusion based on different types of wavelet transform[J].Acta Photonica Sinica,2006,35(8):1263-1267.
[19]樊华,刘明军,赵国春.基于Matlab平台GUI的地震走时层析成像快速实现[J].CT理论与应用研究,2014,23(2):121-130.Fan H,Liu MJ,Zhao GC.Implementation of GUI software for seismic travel-time tomography[J].CT Theory and Applications,2014,23(2):121-130.
[2]Haydn R,Dalke GW,Henkel J,et a1.Application of the IHS color transform to the processing of multisensor data and image enhancement[C]//Proceedings of the International Symposium on Remote Sensing of Arid and Semi-Arid Lands.Cairo,Egypt,1982:599-616.
[3]张喜乐,黄静,刘楠,等.基于小波变换的低剂量CT投影数据滤波方法研究[J].CT理论与应用研究,2011,20(2):163-171.Zhang XL,Huang J,Liu N,et al.Wavelet-transform based low-dose CT projection filtering[J].CT Theory and Applications,2011,20(2):163-171.
[4]董方,胡亮,李柏林,等.基于小波变换尺度相关性的轮廓数据去噪[J].CT理论与应用研究,2008,17(4):62-66.Dong F,Hu L,Li BL,et al.The outline data denoising based on the scale correlation of wavelet transform[J].CT Theory and Applications,2008,17(4):62-66.
[5]Hassainia F,Magafia I,Langevin F,et al.Image fusion by an orthogonal wavelet transformand comparison with other methods[J].Engineering in Medicine and Biology Society,l992,14(10):l246-l247.
[6]Zhou J,Civco DL.Silander JAA wavelet transform method to merge landsat TM and SPOT panchromatic data[J].Journal of Remote Sensing,1998,(19):43-757.
[7]季弼程,魏俊,彭天强.基于IHS变换与小波变换的遥感图像融合[J].数据采集与处理,2003,18(3):268-272.Ji BC,Wei J,Peng TJ.Remote sensing image fusion based on IHS transform and wavelet transform[J].Data Acquisition and Processing,2003,19(3):268-272.
[8]Kaewpijit S,Moigne J,EL-Ghazawi T.A wavelet-based PCA reduction for hyperspectral Imagery[A].IEEE International Geoscience and Remote Sensing Symposium(IEEE IGARSS’02)[C]//Toronto,Canada,2002:24-28.
[9]王仁礼,戚铭尧,王慧.用于图像融合的IHS变换方法的比较[J].测绘学院学报,2000,17(4):269-272.Wang RL,Qi MY,Wang H.Comparison of IHS transform methods for image fusion[J].Journal of Institute of Surveying and Mapping,2000,17(4):269-272.
[10]崔永胜.基于改进的áTrous小波与IHS变换法遥感影像融合研究[D].济南:山东科技大学,2009.Cui YS.Remote sensing image fusion research based on the improved a Trous wavelet and IHS transform method[D].Jinan:Shandong University of Science and Technology,2009.
[11]范文涛.基于小波变换的图像融合技术研究[D].郑州:河南大学,2010.Fan WT.Image fusion technology research based on wavelet transform[D].Zhengzhou:Henan University,2010.
[12]王宇庆.局部方差在图像质量评价中的应用[J].中国光学,2005,13(2):1-6.Wang YQ.The application of local variance on image quality assessment[J].China Optics,2005,13(2):1-6.
[13]龚建周,刘彦随,夏北成,等.小波基及其参数对遥感影像融合图像质量的影响[J].地理与地理信息科学,2010,26(2):6-8.Gong JZ,Liu YS,Xia BC,et al.Influence of wavelet base and its parameters on the quality of the remote sensing image fusion[J].Geography and Geo-Information Science,2010,26(2):6-8.
[14]朱俊杰.高分辨率光学和SAR遥感数据融合及典型目标提取方法研究[D].北京:中国科学院遥感应用研究所,2005.Zhu JJ.High resolution optical and SAR remote sensing data fusion method and typical target extraction[D].Beijing:Institute of Remote Sensing Applications Chinese Academy of Sciences,Beijing,2005.
[15]杨飒.医学图像融合中最佳小波分解层数的选择[J].计算机工程与设计,2008,29(20):5265-5268.Yang S.The choice of best wavelet decomposition layers in the medical image fusion[J].Computer Engineering&Design,2008,29(20):5265-5268.
[16]秦定宇,王敬东,李鹏.图像融合中小波基的选择分析[J].光电子技术,2006,26(3):203-207.Qin DY,Wang JD,Li P.Wavelet basis selection and evaluation for image fusion[J].Optoelectronic Technology,2006,26(3):203-207.
[17]程坚,王敬东,李鹏.SAR与可见光图像融合中小波基选择的研究[J].红外技术,2008,30(3):158-162.Cheng J,Wang JD,Li P.Research on wavelet basis selection in the image fusion in SAR and visual[J].Infrared Technology,2008,30(3):158-162.
[18]李晖晖,郭雷,刘航.基于不同类型小波变换的SAR与可见光图像融合研究[J].光子学报,2006,35(8):1263-1267.Li HH,Guo L,Liu H.Research on SAR and optical image fusion based on different types of wavelet transform[J].Acta Photonica Sinica,2006,35(8):1263-1267.
[19]樊华,刘明军,赵国春.基于Matlab平台GUI的地震走时层析成像快速实现[J].CT理论与应用研究,2014,23(2):121-130.Fan H,Liu MJ,Zhao GC.Implementation of GUI software for seismic travel-time tomography[J].CT Theory and Applications,2014,23(2):121-130.
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