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《Remote Sensing for Land & Resources》 2012-03
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An Improved Wavelet Transformation Image Fusion Method and Evaluation of Its Fusion Result

DONG Zhang-yu1,2,ZHAO Ping3,4,LIU Dian-wei1,WANG Zong-ming1, TANG Xu-guang1,2,LIU jing-yi5(1.Northeast Institute of Geography and Agricultural Ecology,Changchun 130012,China;2.Graduate University of Chinese Academy of Science,Beijing 100049,China;3.College of Territorial Resources and Tourism,Anhui Normal University, Wuhu 241003,China;4.College of Resources and Environmental Engineering,Hefei University of Technology, Hefei 230009,China;5.College of Information Engineering,China University of Geosciences,Wuhan 430074,China)  
On the basis of a summary and analysis of wavelet transformation remote sensing image fusion method,in combination with the advantages of local variance and partial differential weighted criterion,and in the light of the deficiencies of wavelet transform method in enhancing space texture information,this paper has proposed an improved wavelet transformation remote sensing image fusion algorithm.With IKONOS multi-spectral and panchromatic as fusion experiments data,the new algorithm fusion effect was comprehensively evaluated from the subjective,the objective and the object-oriented classification accuracy.The results show that the improved algorithm combined with advantages of the wavelet transform and local algorithm is quite satisfactory.It greatly remedies the defects of traditional wavelet fusion method in remote sensing image texture information loss and serves as a kind of efficient remote sensing image fusion method.With the utilization of the new image fusion method,the remote sensing image variance is raised from the original 98.28 to 164.32,the information entropy increases from 5.30 to 7.85,the average gradient rises from 1.972 to 8.807,and the image classification accuracy increases by 10.24%.
【Fund】: 国家重点基础研究发展计划项目课题(编号:2009CB421103);; 中国科学院战略性先导科技专项子课题(编号:XDA05050101);; 国家水体污染控制与治理科技重大专项课题(编号:2012ZX07207-004)共同资助
【CateGory Index】: TP391.41
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