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Pleiades Satellite Remote Sensing Image Fusion Algorithm Based on Shearlet Transform

机译:Pleiades卫星遥感图像融合算法基于Shearlet变换

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摘要

According to the characteristics of multi-spectral and panchromatic remote sensing images, this paper proposes a new image fusion algorithm based on nonsubsampled shearlet transform. Firstly, low frequency sub-band and high frequency directional sub-band is obtained by IHS color space conversion, and nonsubsampled shearlet transform apply to original multi-spectral images. Then, the adaptive weighted fusion rules is used to construct the low frequency sub-band coefficients, and regional consistency check and region-based local variance fusion rule are used to construct the high frequency sub-band coefficients. Lastly, the inverse of nonsubsampled shearlet transform and the inverse IHS transform are applied to the sub-band coefficients and then obtained the fused image. The comparison of simulation results with traditional fusion methods indicates that the proposed method have better fusion performance both in spectral characteristics and spatial resolution.
机译:根据多光谱和全谱遥感图像的特性,本文提出了一种基于非凹凸剪切变换的新型图像融合算法。 首先,通过IHS颜色空间转换获得低频子带和高频方向子带,并且非管制的Shearlet变换适用于原始多光谱图像。 然后,使用自适应加权融合规则来构造低频子带系数,并且使用区域一致性检查和基于区域的局部方差融合规则来构造高频子带系数。 最后,非管制采样的Shearlet变换的倒数和逆IHS变换被施加到子带系数,然后获得融合图像。 仿真结果与传统融合方法的比较表明,该方法在光谱特性和空间分辨率中具有更好的融合性能。

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