A computationally efficient denoising and hole-filling method for depth image enhancement

Soulan Liu; Chen Chen; Nasser Kehtarnavaz

doi:10.1117/12.2230495

29 April 2016 A computationally efficient denoising and hole-filling method for depth image enhancement

Soulan Liu, Chen Chen, Nasser Kehtarnavaz

Proceedings Volume 9897, Real-Time Image and Video Processing 2016; 98970V (2016) https://doi.org/10.1117/12.2230495
Event: SPIE Photonics Europe, 2016, Brussels, Belgium

Abstract

Depth maps captured by Kinect depth cameras are being widely used for 3D action recognition. However, such images often appear noisy and contain missing pixels or black holes. This paper presents a computationally efficient method for both denoising and hole-filling in depth images. The denoising is achieved by utilizing a combination of Gaussian kernel filtering and anisotropic filtering. The hole-filling is achieved by utilizing a combination of morphological filtering and zero block filtering. Experimental results using the publicly available datasets are provided indicating the superiority of the developed method in terms of both depth error and computational efficiency compared to three existing methods.

Citation Download Citation

Soulan Liu, Chen Chen, and Nasser Kehtarnavaz "A computationally efficient denoising and hole-filling method for depth image enhancement", Proc. SPIE 9897, Real-Time Image and Video Processing 2016, 98970V (29 April 2016); https://doi.org/10.1117/12.2230495

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