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Multispectral inverse problems in satellite image processing

机译:卫星图像处理中的多光谱逆问题

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Abstract: Satellite imaging is nowadays one of the main sources of geophysical and environmental information. It is, therefore, extremely important to be able to solve the corresponding inverse problem,: reconstruct the actual geophysics- or environmental-related image from the observed noisy data. Traditional image reconstruction techniques have been developed for the case when we have a single observed image. This case corresponds to a single satellite photo. Existing satellites take photos in several wavelengths. To press this multiple-spectral information, we can use known reasonable multi-image modifications of the existing single-image reconstructing techniques. These modifications, basically, handle each image separately, and try to merge the resulting information. Currently, a new generation of image satellites is being launched, that will enable us to collect visual images for about 500 different wavelengths. This two order of magnitude increase in data amount should lead to a similar increase in the processing time, but surprisingly, it does not. An analysis and explanation of this paradoxical simplicity is given in the paper. !16
机译:摘要:如今,卫星成像是地球物理和环境信息的主要来源之一。因此,能够解决相应的反问题极为重要:从观察到的噪声数据中重建与地球物理或环境相关的实际图像。当我们只有一个观察到的图像时,已经开发了传统的图像重建技术。这种情况对应于一张卫星照片。现有的卫星可以拍摄几种波长的照片。要按此多光谱信息,我们可以使用现有单图像重构技术的已知合理多图像修改。这些修改基本上是分别处理每个图像,然后尝试合并结果信息。当前,新一代图像卫星正在发射,这将使我们能够收集约500种不同波长的视觉图像。数据量的这两个数量级的增加应该导致处理时间的类似增加,但是令人惊讶的是,事实并非如此。本文对这种矛盾的简单性进行了分析和解释。 !16

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