A Novel Depth Image Enhancement Method Based on the Linear Surface Model

作者：Kang Seok Jae^*; Kang Mun Cheon; Kim Dae Hwan; Ko Sung Jea

来源：IEEE Transactions on Consumer Electronics, 2014, 60(4): 710-718.

DOI：10.1109/TCE.2014.7027347

• Depth image enhancement
• hole filling
• least squares method
• linear surface model
• piecewise linear approximation
• structured-light RGB-D camera

In three-dimensional (3D) video applications, structured-light RGB-D cameras are commonly used to capture depth images that convey the per-pixel depth information in a scene. However, these cameras often produce regions with missing pixels (MPs). These regions, referred to as holes, will not contain no any depth information for the captured depth image. In this paper, a novel depth image enhancement method that accurately estimates depth values of MPs is presented. In the proposed method, the neighboring region outside the hole is first segmented into superpixels using simple linear iterative clustering. Subsequently, the depth value trend of each superpixel is modeled as a linear surface. Finally, one of the linear surfaces is selected using a proposed metric, to estimate the depth value of a particular MP in the hole. Experimental results demonstrate that the proposed method provides superior performance, especially around the object boundary, compared with other state-of-the-art depth image enhancement methods(1).

• 出版日期2014-11