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Satellite image Super-Resolution using overlapping blocks via sparse representation

机译:通过稀疏表示使用重叠块的卫星图像超分辨率

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In image processing the Super-Resolution (SR) has played an important role by acquiring High-Resolution (HR) images from the corresponding Low-Resolution (LR) images. In this paper, a Super-Resolution technique for satellite images is proposed but it can be used on images of different nature. In the current proposal to achieve a HR image, it is necessary an intermediate step, which consists in performing an initial interpolation, then features are extracted from this initial image, here, it is necessary to reduce the information obtained by the features extraction via principal component analysis (PCA). Patches are extracted from the initial image and the reduction via PCA. For each patch, the sparse representation is obtained and then, it is used to recover the HR image. By using the quality objective criteria PSNR and SSIM, the proposed technique is evaluated and shows a superiority in comparison against other existing proposals.
机译:在图像处理中,超高分辨率(SR)通过从相应的低分辨率(LR)图像中获取高分辨率(HR)图像而发挥了重要作用。本文提出了一种用于卫星图像的超分辨率技术,但该技术可用于不同性质的图像。在当前的用于获得HR图像的建议中,需要一个中间步骤,该步骤包括执行初始插值,然后从该初始图像中提取特征,此处,有必要减少通过原理提取特征所获得的信息。成分分析(PCA)。从初始图像中提取补丁,并通过PCA进行缩小。对于每个补丁,都将获得稀疏表示,然后将其用于恢复HR图像。通过使用质量目标标准PSNR和SSIM,对提出的技术进行了评估,并显示出与其他现有提议相比的优越性。

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