Please wait a minute...
img

官方微信

遥感技术与应用  2011, Vol. 26 Issue (5): 670-676    DOI: 10.11873/j.issn.1004-0323.2011.5.670
图像与数据处理     
一种基于结构相似度的IHS变换融合算法
王晓艳,刘勇,蒋志勇
(兰州大学资源与环境学院,甘肃 兰州730000)
An IHS Fusion Method based on Structural Similarity
Wang Xiaoyan,Liu Yong,Jiang Zhiyong
(College of Earth and Environmental Sciences,Lanzhou University,Lanzhou 730000,China)
 全文: PDF(4005 KB)  
摘要:

由于IHS色彩空间表现的颜色更加符合人眼的视觉规律,因此,IHS变换在遥感影像融合中被广泛应用。针对传统的IHS变换融合算法进行融合实验时有较大的色彩畸变问题,提出了一种基于结构相似度(Strucral Similarity SSIM)的IHS变换融合算法。对影像进行IHS变换之后,计算原始多光谱影像I分量与全色波段影像的SSIM矩阵,并由该SSIM矩阵确定对应不同区域的新的亮度分量I。实验结果表明,该算法在增强影像空间分辨率的同时,能很好地保持其光谱特征。

关键词: 图像融合IHS变换SSIM遥感    
Abstract:

IHS(Intensity-Hue-Saturation) color space is more consistent with human visual system than RGB color space,so IHS transform has been used widely in image fusion.The most significant problem of the traditional IHS transform fusion method is that the fused image usually has a notable deviation in visual appearance and in spectral values from the original image.In this paper,we propose a new IHS transform fusion method based on Structural Similarity (SSIM).First,the multispectral image was transform from RGB color space to IHS color space,then we calculate the SSIM matrix between the intensity component of the multispectral image and the panchromatic image.The new intensity component is determined based on the SSIM.Experimental results indicate that this method is effective in preserving spectral and spatial information.

Key words: Image fusion    IHS transform    SSIM    Remote sensing
收稿日期: 2011-03-03 出版日期: 2011-11-01
:  TP 753  
基金资助:

中央高校基本科研业务费专项资金自由探索项目(lzujbky-2010-178) 。

作者简介: 王晓艳(1973-),女,山东沂南人,博士研究生,主要从事遥感数字图像处理及环境遥感研究。Email:wangxiaoy@lzu.edu.cn。
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  

引用本文:

王晓艳,刘勇,蒋志勇. 一种基于结构相似度的IHS变换融合算法[J]. 遥感技术与应用, 2011, 26(5): 670-676.

Wang Xiaoyan,Liu Yong,Jiang Zhiyong. An IHS Fusion Method based on Structural Similarity. Remote Sensing Technology and Application, 2011, 26(5): 670-676.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2011.5.670        http://www.rsta.ac.cn/CN/Y2011/V26/I5/670

[1]Ehlers M.Multisensor Image Fusion Techniques in Remote Sensing[J].ISPRS Journal of Photogrammetry and Remote Sensing,1991,46(1):19-30.
[2]Chen C M,Hepner G F,Forster R R.Fusion of Hyperspectral and Radar Data Using the IHS Transformation to Enhance Urban Surface Features[J].ISPRS Journal of Photogrammetry and Remote Sensing,2003,58(1):19-30.
[3]Cliche G,Bonn F,Teillet P.Integration of the SPOT Pan Channel into its Multispectral Mode for Image Sharpness Enhancement[J].Photogrammetric Engineering and Remote Sensing,1985,51(3):311-316.
[4]Li S,Kwok J T,Wang Y.Using the Discrete Wavelet Transform to Merge Landsat TM and SPOT Panchromatic Images[J].Information Fusion,2002,3(1):17-23.
[5]Chen Y,Blum R S.A New Automated Quality Assessment Algorithm for Image Fusion[J].Image and Vision Computing,2009,27:1421-1432.
[6]Miao Q G,Shi C,Xu P F,et al.A Novel Algorithm of Image Fusion Using Shearlets[J].Optics Communications,2011,284:1540-1547.
[7]Yang S Y,Wang M,Jiao L C,et al.Image Fusion based on a New Contourlet Packet[J].Information Fusion,2010,11:78-84.
[8]Yin S F,Cao L C,Ling Y S,et al.One Color Contrast Enhanced Infrared and Visible Image Fusion Method[J].Infrared Physics & Technology,2010,53:146-150.
[9]Guo Q,Chen S Y,Leung H,et al.Covariance Intersection based Image Fusion Technique with Application to Pansharpening in Remote Sensing[J].Information Sciences,2010,180:3434-3443.
[10]Ling Y,Ehkers M.FFT-Enhanced IHS Transform Method for Fusing High-resolution Satellite Images[J].ISPRS Journal of Photogrammetry and Remote Sensing,2007,61(6):381-392.
[11]Zhang Y,Hong G.An IHS and Wavelet Integrated Approach to Improve Pan-sharpening Visual Quality of Natural Colour Ikonos and QuickBird Images[J].Information Fusion,2005,6(3):225-234.
[12]Di Hongwei,Liu Xianfeng.Image Fusion Quality Assessment based on Structural Similarity[J].Acta Photonica Sinca,2006,35(5):766-771.[狄红卫,刘显峰.基于结构相似度的图像融合质量评价[J].光子学报,2006,35(5):766-771.]
[13]Wang Z,Bovik A C.A Universal Image Quality Index[J].IEEE Signal Processing Letters,2002,9(3):81-84.
[14]Wang Z,Bovik A C,Sheikh H R,et al.Image Quality Assessment:From Error Visibility to Structural Similarity[J].IEEE Transaction on Image Processing,2004,13(4):600-612.
[15]Yang C,Zhang J Q,Wang X L,et al.A Novel Similarity based Quality Metric for Image Fusion[J].Information Fusion,2008,9:156-160.
[16]Zheng Y,Qin Z.Objective Image Fusion Quality Evaluation Using Structural Similarity[J].Tsinghua Science & Technology,2009,14:703-709.
[17]Liu Tingxiang,Huang Limei,Bao Wendong.Stady on Texture Information Evaluation of Image Fused by CBERS-02B and SPOT-5 Panchromatic Data[J].Remote Sensing Technology and Application,2009,24(1):103-108.[刘廷祥,黄丽梅,鲍文东.基于CBERS-02B和SPOT-5全色波段的图像融合纹理信息评价研究[J].遥感技术与应用,2009,24(1):103-108.]
[18]Jing Juanjuan,Lv Qunbo.Research on the Assessment of Fusion Image[J].Acta Photonica Sinca,2007,36:313-317.[景娟娟,吕群波.图像融合效果评价方法研究[J].光子学报,2007,36:313-317.]

[1] 王卷乐, 程凯, 边玲玲, 韩雪华, 王明明. 面向SDGs和美丽中国评价的地球大数据集成框架与关键技术[J]. 遥感技术与应用, 2018, 33(5): 775-783.
[2] 王恺宁,王修信,黄凤荣,罗涟玲. 喀斯特城市地表温度遥感反演算法比较[J]. 遥感技术与应用, 2018, 33(5): 803-810.
[3] 张晓峰,吕晓琪,张信雪,张继凯,王月明,谷宇,樊宇. 多时刻海色遥感数据融合及其可视化[J]. 遥感技术与应用, 2018, 33(5): 873-880.
[4] 谢旭,陈芸芝. 基于PSO-RBF神经网络模型反演闽江下游水体悬浮物浓度[J]. 遥感技术与应用, 2018, 33(5): 900-907.
[5] 迟文峰,匡文慧,贾静,刘正佳. 京津风沙源治理工程区LUCC及土壤风蚀强度动态遥感监测研究[J]. 遥感技术与应用, 2018, 33(5): 965-974.
[6] 胡云锋,商令杰,张千力,王召海. 基于GEE平台的1990年以来北京市土地变化格局及驱动机制分析[J]. 遥感技术与应用, 2018, 33(4): 573-583.
[7] 李晨伟,张瑞丝,张竹桐,曾敏 . 基于多源遥感数据的构造解译与分析—以西藏察隅吉太曲流域为例[J]. 遥感技术与应用, 2018, 33(4): 657-665.
[8] 李生生,王广军,梁四海,彭红明,董高峰,罗银飞. 基于Landsat-8 OLI数据的青海湖水体边界自动提取[J]. 遥感技术与应用, 2018, 33(4): 666-675.
[9] 廖凯涛,齐述华,王成,王点. 结合GLAS和TM卫星数据的江西省森林高度和生物量制图[J]. 遥感技术与应用, 2018, 33(4): 713-720.
[10] 张震,刘时银,魏俊锋,蒋宗立. 1974~2012年珠穆朗玛峰地区冰川物质平衡遥感监测研究[J]. 遥感技术与应用, 2018, 33(4): 731-740.
[11] 王琳,徐涵秋,李胜. 重钢重工业区迁移对区域生态的影响研究[J]. 遥感技术与应用, 2018, 33(3): 387-397.
[12] 任浙豪,周坚华. 增大特征空间复杂度的方法——以城镇下垫面遥感分类为[J]. 遥感技术与应用, 2018, 33(3): 408-417.
[13] 王宝刚,晋锐,赵泽斌,亢健. 被动微波遥感在地表冻融监测中的应用研究进展[J]. 遥感技术与应用, 2018, 33(2): 193-201.
[14] 秦振涛,杨茹,张靖,杨武年. 基于聚类结构自适应稀疏表示的高光谱遥感图像修复研究[J]. 遥感技术与应用, 2018, 33(2): 212-215.
[15] 郭宇柏,卓莉,陶海燕,曹晶晶,王芳. 基于空谱初始化的非负矩阵光谱混合像元盲分解[J]. 遥感技术与应用, 2018, 33(2): 216-226.