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首页> 外文期刊>Remote Sensing >Multispectral Pansharpening with Radiative Transfer-Based Detail-Injection Modeling for Preserving Changes in Vegetation Cover
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Multispectral Pansharpening with Radiative Transfer-Based Detail-Injection Modeling for Preserving Changes in Vegetation Cover

机译:基于辐射转移的细节注入模型进行多光谱全锐化,以保护植被的变化

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Whenever vegetated areas are monitored over time, phenological changes in land cover should be decoupled from changes in acquisition conditions, like atmospheric components, Sun and satellite heights and imaging instrument. This especially holds when the multispectral (MS) bands are sharpened for spatial resolution enhancement by means of a panchromatic (Pan) image of higher resolution, a process referred to as pansharpening. In this paper, we provide evidence that pansharpening of visibleear-infrared (VNIR) bands takes advantage of a correction of the path radiance term introduced by the atmosphere, during the fusion process. This holds whenever the fusion mechanism emulates the radiative transfer model ruling the acquisition of the Earth’s surface from space, that is for methods exploiting a multiplicative, or contrast-based, injection model of spatial details extracted from the panchromatic (Pan) image into the interpolated multispectral (MS) bands. The path radiance should be estimated and subtracted from each band before the product by Pan is accomplished. Both empirical and model-based estimation techniques of MS path radiances are compared within the framework of optimized algorithms. Simulations carried out on two GeoEye-1 observations of the same agricultural landscape on different dates highlight that the de-hazing of MS before fusion is beneficial to an accurate detection of seasonal changes in the scene, as measured by the normalized differential vegetation index (NDVI).
机译:每当对植被区域进行监测时,应将土地覆盖物的物候变化与获取条件的变化(例如大气成分,太阳和卫星高度以及成像仪器)脱钩。当借助更高分辨率的全色(Pan)图像对多光谱(MS)波段进行锐化以提高空间分辨率时,这一点尤为重要。在本文中,我们提供的证据表明,在融合过程中,可见/近红外(VNIR)波段的全景锐化利用了大气引入的路径辐射率项的校正。只要融合机制模拟了从空间获取地球表面的辐射传递模型,即对于利用从全色(Pan)图像提取到插值中的空间细节的乘性或基于对比度的注入模型的方法,这种方法都成立多光谱(MS)波段。在通过Pan乘积完成之前,应估计路径辐射度并从每个波段中减去。在优化算法的框架内,比较了基于经验和基于模型的MS路径辐射率估计技术。对同一农业景观在不同日期的两次GeoEye-1观测进行的模拟表明,融合之前对MS的除雾作用有助于标准化场景差分变化指数(NDVI)的测量,以准确检测场景中的季节变化。 )。

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