Enhancement of range data using a structure-aware filter

• We achieve color-guided normal smoothing from a noisy depth map, which can successfully obtain a reliable normal field.
• We develop a structure-preserving range data enhancement algorithm based on normal information through a 3D bilateral filter.
• The proposed method can inherently circumvent common artifacts such as texture copy and edge blurring by avoiding using color information in depth adjustment.

Range data acquired by affordable IR depth sensors are significantly noisy and lack shape detail, making it difficult to obtain high-quality scans using depth cameras. Most methods to enhance noisy data do not preserve the original structure of the measured scene during data refinement, particularly at sharp edges and object boundaries. We present a novel approach to enhance the range data in a structure-aware manner based on the normal information in a scene. We first computed reliable normals by smoothing out noise and sharpening the edges of individual points using color-guided normal smoothing. Based on the normal information, the noisy range data were refined by a 3D bilateral filtering technique while preserving ridges, valleys, and depth discontinuities. In a comparison, our method outperformed previous techniques in terms of noise suppression and faithful structure reconstruction.

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