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首页> 外文期刊>International journal of image and data fusion >Resolution-enhanced remote sensing via multi spectral and spatial data fusion
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Resolution-enhanced remote sensing via multi spectral and spatial data fusion

机译：通过多光谱和空间数据融合提高分辨率的遥感

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摘要

Super-resolution and image enhancement are frequently sought for in remote sensing. Many approaches were used over the years to obtain this yearned enhancement. In this article, the authors present a novel super-resolution approach based on iterative data fusion algorithms. The proposed algorithm can be implemented using either a plurality of images with varied resolution generated from different regions of the field of view, or a plurality of spectral images of the same region. The suggested approach is gradual, allowing the build-up of one single high-resolution (HR) image. The iterative procedure used in this article is based on iterative ping-pong computation between the spatial domain and its spectral distribution, similar to the approach used by Gerchberg and Saxton, and later by Gerchberg and Papoulis; however, the new approach makes use of dynamic parameters. The dynamic-iterative approach enables the retrieval of HR data from data which mostly contain low-resolution (LR) images. In both the approaches mentioned (the spatial as well as the spectral one), one may mix HR and LR information by the insertion of properly defined constraints, and achieve an enhanced image in terms of resolution, clarity, correlation with true data and contrast.
机译：在遥感中经常需要超分辨率和图像增强。这些年来，使用了许多方法来获得本年度的增强功能。在本文中，作者提出了一种基于迭代数据融合算法的新颖超分辨率方法。可以使用从视场的不同区域产生的分辨率不同的多个图像或同一区域的多个光谱图像来实现所提出的算法。建议的方法是循序渐进的，可以建立一个单独的高分辨率（HR）图像。本文使用的迭代过程基于空间域及其频谱分布之间的迭代乒乓计算，类似于Gerchberg和Saxton以及后来的Gerchberg和Papoulis所采用的方法。但是，新方法利用了动态参数。动态迭代方法使得能够从主要包含低分辨率（LR）图像的数据中检索HR数据。在上述两种方法（空间方法和光谱方法）中，可以通过插入适当定义的约束条件来混合HR和LR信息，并在分辨率，清晰度，与真实数据的相关性和对比度方面获得增强的图像。

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