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《Geomatics and Information Science of Wuhan University》 2012-11
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An Improved SVR Image Fusion Algorithm Base on Low-pass Filter and Histogram Matching

GAO Yonggang1,2 XU Hanqiu1,2(1 College of Environment and Resources,Fuzhou University,2 Xueyuan Road,Fuzhou 350108,China)(2 Institute of Remote Sensing Information Engineering,Fuzhou University,2 Xueyuan Road,Fuzhou 350108,China)  
To avoid the spectral distortion of SVR(synthetic variable ratio) algorithm,we propose an improved algorithm by using a low-pass filter and histogram matching performance,which is hence named SVR based on low-pass filter and histogram matching(SVRFM) algorithm.Two subsets from the IKONOS image of Fuzhou,representing different land cover types were used as test data.The spectral fidelity and the ability of gaining high frequency information were assessed by using visual and statistical analysis.The fused images were compared with those fused using the SVR,wavelet transform,pansharp,ehlers and Gram-Schmidt algorithms,respectively.The results show that the spectral fidelity of the SVRFM algorithm is generally better than the five algorithms compared.
【Fund】: 福建省自然科学基金资助项目(2011J01269);; 海岛(礁)测绘技术国家测绘地理信息局重点实验室基金资助项目(2010B09);; 福州大学科技发展基金资助项目(2009-XY-9)
【CateGory Index】: P237
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