Fast Color-guided Depth Denoising for RGB-D Images by Graph Filtering

Qiwei Huang, Ruikang Li, Zidong Jiang, Wei Feng, Sijie Lin, Hui Feng, Bo Hu
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引用次数: 3

Abstract

Depth images captured by off-the-shelf RGB-D cameras suffer from much stronger noise than color images. In this paper, we propose a method to denoise the depth images in RGB-D images by color-guided graph filtering. Our iterative method contains two components: color-guided similarity graph construction, and graph filtering on the depth signal. Implemented in graph vertex domain, filtering is accelerated as computation only occurs among neighboring vertices. Experimental results show that our method outperforms state-of-art depth image denoising methods significantly both on quality and efficiency.
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基于图形滤波的RGB-D图像快速颜色引导深度去噪
由现成的RGB-D相机拍摄的深度图像比彩色图像遭受更强的噪声。本文提出了一种基于颜色引导图滤波的RGB-D图像深度图像去噪方法。我们的迭代方法包含两个部分:颜色引导的相似图构建和深度信号的图滤波。在图顶点域实现,滤波速度加快,因为计算只发生在相邻顶点之间。实验结果表明,该方法在质量和效率上都明显优于现有的深度图像去噪方法。
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