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

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.

arXiv comment5 pages, 4 figures

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• Graph Laplacian Regularization for Image Denoising: Analysis in the Continuous Domain
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