A New Geostatistical Solution to Remote Sensing Image Downscaling
A New Geostatistical Solution to Remote Sensing Image Downscaling
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DOI：
10.1109/tgrs.2015.2457672
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发表时间：
2016
影响因子：
8.2
通讯作者：
Qunming Wang;W. Shi;P. Atkinson;E. Pardo‐Igúzquiza
中科院分区：
文献类型：
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作者：
Qunming Wang;W. Shi;P. Atkinson;E. Pardo‐Igúzquiza
全色波段在遥感图像中的可用性催生了所谓的图像融合技术，将图像的空间分辨率提高到全色波段。但是，诸如MODIS和Landsat传感器的这种空间锐化图像的空间分辨率可能不足以提供所需的详细的土地覆盖/土地利用信息。本文提出了一种基于区域到点回归克里格（ATPRK）的地统计学解决方案，以提高遥感图像的空间分辨率，超过任何输入图像，包括PAN波段。该方法分为两阶段，包括协变量降尺度和基于atpr的图像融合。该方法将PAN波段作为协变量，利用其纹理信息。它明确地考虑了传感器的支撑大小、空间相关性和点扩展函数，并具有与原始粗数据完全一致的特点。此外，新的降尺度方法可以通过合并其他辅助信息来扩展。采用陆地卫星和MODIS图像对所提出的方法进行了检验。结果表明，与四种基准方法相比，该方法能产生更精确的锐化图像。
The availability of the panchromatic (PAN) band in remote sensing images gives birth to so-called image fusion techniques for increasing the spatial resolution of images to that of the PAN band. The spatial resolution of such spatially sharpened images, such as for the MODIS and Landsat sensors, however, may not be sufficient to provide the required detailed land-cover/land-use information. This paper proposes an area-to-point regression kriging (ATPRK)-based geostatistical solution to increase the spatial resolution of remote sensing images beyond that of any input images, including the PAN band. The new approach is a two-stage approach, including covariate downscaling and ATPRK-based image fusion. The new approach treats the PAN band as the covariate and takes advantages of its textural information. It explicitly accounts for the size of support, spatial correlation, and the point spread function of the sensor and has the characteristic of perfect coherence with the original coarse data. Moreover, the new downscaling approach can be extended readily by incorporating other ancillary information. The proposed approach was examined using both Landsat and MODIS images. The results show that it can produce more accurate sharpened images than four benchmark approaches.