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NEW HYBRID PAN-SHARPENING METHOD BASED ON TYPE-1 FUZZY-DWT STRATEGY

机译:基于1型模糊DWT策略的新型混合泛锐化方法

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摘要

The purpose of image fusion is to combine two images from the same view in order to produce an image with more information and higher quality. In this paper, a panchromatic image with high spatial resolution and a low-resolution multi-spectral image having rich spectral information are fused together to produce a high-resolution multi-spectral image that heritage the characteristics of both initial images. For this purpose, a hybrid pan-sharpening method, called ‘Improved Fuzzy-DWT’ have been proposed based on the modification of the parameters existed in the latest version of Fuzzy-Wavelet algorithm, and then it was compared with some other algorithms such as PCA, Gram-Schmidt, Wavelet, and two of its hybrid derivatives called PCA-Wavelet and IHS-wavelet. The comparison was conducted using DIV, SSIM, SID, CC, DS, and QNR spectral and spatial quality assessment metrics. The obtained results demonstrate that the proposed hybrid algorithm has relatively better performance in comparison with the other mentioned pan-sharpening techniques in terms of both spectral and spatial qualities, regarding it was superior in terms of SID, DIV, SSIM, DS. From the computational cost standpoint, the proposed method has the most running time compared with the other methods.
机译:图像融合的目的是将来自相同视图的两个图像组合以产生具有更多信息和更高质量的图像。本文中,具有高空间分辨率的全色图像和具有丰富的光谱信息的低分辨率多光谱图像被融合在一起以产生遗传遗传初始图像的特性的高分辨率多光谱图像。为此目的,已经基于在最新版本的模糊小波算法中存在的参数的修改,提出了一种混合泛锐化方法,然后与一些其他算法进行比较,如图所示PCA,Gram-Schmidt,小波和两个杂种衍生物称为PCA-小波和IHS-小波。使用Div,SSIM,SID,CC,DS和QNR谱和空间质量评估度量进行比较。所获得的结果表明,与频谱和空间质量方面的其他提到的泛锐化技术相比,所提出的混合算法具有相对更好的性能,关于其在SID,DIV,SSIM,DS方面是优越的。从计算成本的角度来看,与其他方法相比,所提出的方法具有最多运行的时间。

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