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Multispectral and panchromatic images fusion based on NSCT and GS transform

机译:基于NSCT和GS变换的多光谱和全色图像融合

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The spatial and spectral resolution of remote sensing images are mutually restricted due to the limitation of sensor technology. Multispectral (MS) image has high spectral resolution, but low spatial resolution. While, panchromatic (PAN) image can provide high spatial resolution. Fusion of MS and PAN images is to get MS image with high resolution, which is a hot research in the field of remote sensing image processing. In this paper, a fusion algorithm of MS and PAN images is presented based on non-subsampled contourlet transform (NSCT) and Gram-Schmidt (GS) transform. Firstly, the low-resolution PAN image is synthesized by weighing each band of MS image whose weight coefficients are obtained by least squares estimation. MS image is decomposed by GS transform with the first GS component of the synthetic low-resolution PAN image. Secondly, one-level and three-level NSCT decomposition is performed on the synthetic low-resolution PAN image and PAN image, respectively. Low-frequency coefficients of low-resolution PAN image are as ones of the generated PAN image. High-frequency coefficients of first level decomposition of low-resolution PAN image and PAN image are fused according to region energy. The other level high-frequency coefficients of PAN image are as ones of the generated PAN image. Thirdly, the generated PAN image is reconstructed by the inverse NSCT with these coefficients. Lastly, inverse GS transform is performed to gain improved MS image by replacing the first GS component with the generated PAN image. The experiments conducted on Quickbird satellite images show that the proposed method is superior to the other typical methods, which improves the spatial resolution and has smaller spectral distortion.
机译:由于传感器技术的限制,遥感图像的空间和光谱分辨率相互制约。多光谱(MS)图像具有高光谱分辨率,但空间分辨率低。同时,全色(PAN)图像可以提供高空间分辨率。 MS和PAN​​图像的融合是为了获得高分辨率的MS图像,这是遥感图像处理领域的一项热门研究。本文提出了一种基于非下采样轮廓波变换(NSCT)和格拉姆-施密特(GS)变换的MS和PAN​​图像融合算法。首先,通过对MS图像的每个频带进行加权来合成低分辨率PAN图像,MS图像的权重系数是通过最小二乘估计获得的。通过合成低分辨率PAN图像的第一个GS分量的GS变换将MS图像分解。其次,分别对合成的低分辨率PAN图像和PAN图像执行一级和三级NSCT分解。低分辨率PAN图像的低频系数与所生成的PAN图像的低频系数相同。根据区域能量将低分辨率PAN图像和PAN图像的第一级分解的高频系数融合。 PAN图像的其他级别的高频系数与所生成的PAN图像相同。第三,利用这些系数通过逆NSCT重建所生成的PAN图像。最后,通过用生成的PAN图像替换第一个GS分量,执行GS逆变换以获得改进的MS图像。在Quickbird卫星图像上进行的实验表明,该方法优于其他典型方法,不仅提高了空间分辨率,而且光谱失真较小。

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