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Multiresolution-based image fusion with additive wavelet decomposition

机译:基于多分辨率的图像融合与加性小波分解

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摘要

The standard data fusion methods may not be satisfactory to merge a high-resolution panchromatic image and a low-resolution multispectral image because they can distort the spectral characteristics of the multispectral data. The authors developed a technique, based on multiresolution wavelet decomposition, for the merging and data fusion of such images. The method presented consists of adding the wavelet coefficients of the high-resolution image to the multispectral (low-resolution) data. They have studied several possibilities concluding that the method which produces the best results consists in adding the high order coefficients of the wavelet transform of the panchromatic image to the intensity component (defined as L=(R+G+B)/3) of the multispectral image. The method is, thus, an improvement on standard intensity-hue-saturation (IHS or LHS) mergers. They used the ¿a trous¿ algorithm which allows the use of a dyadic wavelet to merge nondyadic data in a simple and efficient scheme. They used the method to merge SPOT and LANDSATTM images. The technique presented is clearly better than the IHS and LHS mergers in preserving both spectral and spatial information.
机译:标准数据融合方法可能无法令人满意地合并高分辨率全色图像和低分辨率多光谱图像,因为它们会扭曲多光谱数据的光谱特性。作者开发了一种基于多分辨率小波分解的技术,用于此类图像的合并和数据融合。提出的方法包括将高分辨率图像的小波系数与多光谱(低分辨率)数据相加。他们研究了几种可能性,得出的结论是,产生最佳结果的方法包括将全色图像的小波变换的高阶系数添加到图像的强度分量(定义为L =(R + G + B)/ 3)上。多光谱图像。因此,该方法是对标准强度-色相-饱和度(IHS或LHS)合并的一种改进。他们使用了“ trous”算法,该算法允许使用二进小波以简单有效的方案合并非二进数据。他们使用该方法合并SPOT和LANDSATTM图像。在保留频谱和空间信息方面,提出的技术显然比IHS和LHS合并要好。

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