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RGB-NIR Demosaicing Using Deep Residual U-Net

机译:使用深残留U-Net的RGB-NIR去马赛克

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Multi-spectral image acquisition brings numerous potential benefits in computer vision and image processing applications. Single-sensor acquisition helps to overcome problems with misalignments occurring in multiple-sensor acquisition. However, the single-sensor approach poses the problem of interpolation of missing values. In this paper we propose an adapted version of a residual U-Net, with application in demosaicing. The experiments show that the proposed method achieves state-of-the-art results, and has good generalization capabilities to different color filter array patterns.
机译:多光谱图像采集在计算机视觉和图像处理应用中带来了许多潜在的好处。单传感器采集有助于克服多传感器采集中出现的未对准问题。然而,单传感器方法提出了缺失值的插值的问题。在本文中,我们提出了残差U-Net的改进版本,并将其应用于去马赛克。实验表明,该方法达到了最新的结果,并且对不同的彩色滤光片阵列模式具有良好的泛化能力。

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