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Satellite Image Fusion Based on Improved Fast Discrete Curvelet Transforms

机译:基于改进的快速离散Curvelet变换的卫星图像融合

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Image fusion is the process of merging two or more images into a more informative single image. Satellite image fusion uses high resolution panchromatic image and low resolution multispectral image. IHS, Brovery, PCA, Wavelet, Curvelet etc are the existing techniques available for image fusion. But simultaneous retention of spatial and spectral resolution is an important concern in remote sensing applications. In this paper we proposed an improved Satellite image fusion method based on Fast Discrete curvelet Transform (FDCT) via wrapping. The method uses an improved fusion rule, were the maximum FDCT coefficients from each cell of the Intensity component of the MS image and histogram matched PAN image are taken. The resulting image is then undergone a comparative analysis with the outcomes of existing methodologies. The comparative analysis proves that the proposed method retains more spatial and spectral details than other methods.
机译:图像融合是将两个或更多图像合并为信息量更大的单个图像的过程。卫星图像融合使用高分辨率全色图像和低分辨率多光谱图像。 IHS,Brovery,PCA,小波,Curvelet等是可用于图像融合的现有技术。但是,在遥感应用中,同时保留空间和光谱分辨率是一个重要的问题。在本文中,我们提出了一种基于快速离散曲波变换(FDCT)的改进的卫星图像融合方法。该方法使用了改进的融合规则,分别从MS图像和直方图匹配的PAN图像的强度分量的每个像元中获取最大FDCT系数。然后将所得图像与现有方法的结果进行比较分析。对比分析表明,与其他方法相比,该方法保留了更多的空间和光谱细节。

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