The separation of high resolution remote sensing images based on dictionary learning

H. Wang
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Abstract

Separating the high resolution remote sensing images is a difficult problem in the relative research field of image processing and remote sensing. A novel model of separating the high resolution remote sensing images is proposed based on sparse representation, different dictionary which has an efficient indication of different content of remote sensing image is obtained based on dictionary learning algorithm according to the characteristics of the high spatial resolution remote sensing images, separating by SSF algorithm. After experimental, it is showed that the algorithm can separate features of remote sensing images better, and it is more robust.
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基于字典学习的高分辨率遥感图像分离
高分辨率遥感图像的分离是图像处理和遥感相关研究领域的一个难题。提出了一种基于稀疏表示的高分辨率遥感图像分离新模型,根据高空间分辨率遥感图像的特点,基于字典学习算法获得能有效表示遥感图像不同内容的不同字典,采用SSF算法进行分离。实验表明,该算法能较好地分离遥感图像的特征,具有较强的鲁棒性。
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