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Sub-pixel mapping of remote sensing images based on sub-pixel/pixel spatial attraction models with anisotropic spatial dependence model

机译:基于具有各向异性空间依赖模型的子像素/像素空间吸引模型的遥感图像的子像素映射

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Sub-pixel mapping (SPM) based on the Sub-pixel /Pixel Spatial Attraction Models (SPSAM) is a technique that improve the spatial resolution of remote sensing images. SPSAM-based SPM is based on the spatial dependence theory with isotropic assumption. In SPSAM, the weight calculation of spatial dependence is only relevant with the distance between the sub-pixel and its neighboring pixel. Obviously, the direction of spatial dependence is neglected. In this paper, a revised SPSAM-based SPM with anisotropic spatial dependence model (SPSAMA) is proposed. Sobel operator is utilized to determine the gradient magnitude and direction of coarse proportion image at every pixel. Then the gradient magnitude and direction will be used to reckon the weights of adjacent pixels proportions in the neighborhood. Experimental results demonstrated that the SPSAMA can produce land cover maps with greater accuracy than traditional SPSAM.
机译:基于子像素/像素空间吸引模型(SPSAM)的子像素映射(SPM)是提高遥感图像的空间分辨率的技术。基于SPSAM的SPM基于具有各向同性假设的空间依赖性理论。在SPSAM中,空间依赖的权重计算仅与子像素和其相邻像素之间的距离相关。显然,空间依赖的方向被忽略了。本文提出了一种具有各向异性空间依赖模型(SPSAMA)的修正的基于SPSAM的SPM。 Sobel操作员用于确定每个像素处的粗糙比例图像的梯度幅度和方向。然后,梯度幅度和方向将用于估计附近相邻像素比例的重量。实验结果表明,Spsama可以生产比传统SPSAM更高的准确性陆地覆盖图。

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