Image Fusion for High-Resolution Optical Satellites Based on Panchromatic Spectral Decomposition

Image Fusion for High-Resolution Optical Satellites Based on Panchromatic Spectral Decomposition
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基于全色光谱分解的高分辨率光学卫星图像融合

DOI:
10.3390/s19112619
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发表时间:
2019-06
期刊:
影响因子:
3.9
通讯作者:
Xiaoxiao Feng
Xiaoxiao Feng
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Luxiao He;Mi Wang;Ying Zhu;Xueli Chang;Xiaoxiao Feng

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比值变换方法是高分辨率光学卫星图像融合的常用方法。利用比值变换的前提是全色波段与对应的多光谱波段之间存在零偏线性关系。然而,在现实中,有偏置项和残差项具有较大的值,这取决于传感器,响应光谱范围和土地覆盖类型。针对这一问题,提出了一种基于全色光谱分解(PSD)的全色与多光谱图像融合方法。利用低分辨率全色图像和多光谱图像求解比例系数、偏差系数和残差矩阵。这些系数被代入高分辨率全色波段,并将其分解为高分辨率多光谱波段。实验表明,该方法能使融合图像获得较高的色彩保真度和清晰度,对不同传感器和特征具有较强的鲁棒性,可应用于高分辨率光学卫星的全色和多光谱融合。
Ratio transformation methods are widely used for image fusion of high-resolution optical satellites. The premise for the use the ratio transformation is that there is a zero-bias linear relationship between the panchromatic band and the corresponding multi-spectral bands. However, there are bias terms and residual terms with large values in reality, depending on the sensors, the response spectral ranges, and the land-cover types. To address this problem, this paper proposes a panchromatic and multi-spectral image fusion method based on the panchromatic spectral decomposition (PSD). The low-resolution panchromatic and multi-spectral images are used to solve the proportionality coefficients, the bias coefficients, and the residual matrixes. These coefficients are substituted into the high-resolution panchromatic band and decompose it into the high-resolution multi-spectral bands. The experiments show that this method can make the fused image acquire high color fidelity and sharpness, it is robust to different sensors and features, and it can be applied to the panchromatic and multi-spectral fusion of high-resolution optical satellites.
使用分类 MS 和全色图像的回归进行全色锐化以减少颜色失真
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