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Image-guided depth map upsampling using normalized cuts-based segmentation and smoothness priors

机译:使用基于归一化剪切的分割和平滑先验的图像引导深度图上采样

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In this paper, we propose an image segmentation-based algorithm to perform upsampling of noisy low-resolution depth maps using information from the high-resolution color image. The depth map is initially upscaled using standard image interpolation technique, and then refined by a process based on the combination of Normalized Cuts segmentation and various smoothness priors in order to obtain a high quality highresolution depth map. Our method outperforms other existing methods when applied on both synthetic and real-world datasets.
机译:在本文中,我们提出了一种基于图像分割的算法,利用高分辨率彩色图像中的信息对嘈杂的低分辨率深度图进行上采样。首先使用标准图像插值技术对深度图进行放大,然后通过基于归一化分割分割和各种平滑度先验相结合的过程进行精化,以获得高质量的高分辨率深度图。当将其应用于合成数据集和真实数据集时,我们的方法优于其他现有方法。

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