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Method for Large-Area Satellite Image Quality Enhancement With Local Aerial Images Based on Non-Target Multi-Point Calibration

机译:基于非目标多点标定的局部航空影像大面积卫星影像质量增强方法

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This paper designed a non-target multi-point calibration method for the quality enhancement of large-area satellite images by using local aerial images. Satellite images are more sensitive to atmospheric effects compared with aerial images. Atmospheric effects on aerial images are even negligible in fine weather. Given that aerial remote sensing has high spatial resolution and geometric fidelity, more spatial details can be recorded in aerial images. However, the scan bandwidth of aerial images is limited compared with that of satellite images. Thus, taking high-quality aerial images of a neighborhood as reference can provide prior knowledge for point spread function (PSF) estimation and for the quality enhancement of large-area satellite images. The least square method and interpolation are used for the PSF estimation of spatial variation, and then total variation minimization is used for recovery. The results show that the designed method can effectively enhance the quality of large-area satellite images.
机译:本文设计了一种非目标多点标定方法,以利用局部航拍图像增强大面积卫星图像的质量。与航空图像相比,卫星图像对大气影响更为敏感。在晴朗的天气下,对航空影像的大气影响甚至可以忽略不计。鉴于航空遥感具有较高的空间分辨率和几何保真度,因此可以在航空图像中记录更多的空间细节。但是,与卫星图像相比,航空图像的扫描带宽是有限的。因此,以邻域的高质量航空图像作为参考可以为点扩展函数(PSF)估计和大面积卫星图像的质量增强提供先验知识。最小二乘法和插值用于空间变化的PSF估计,然后将总变化最小化用于恢复。结果表明,所设计的方法可以有效地提高大面积卫星图像的质量。

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