Depth Up-Sampling via Pixel-Classifying and Joint Bilateral Filtering

• Yannan Ren,
• Ju Liu,
• Hui Yuan,
• Yifan Xiao,

Vol. 12, No. 7, July 30, 2018
10.3837/tiis.2018.07.013, Download Paper (Free):

• Depth upsampling
• pixel classifying
• joint bilateral up-sampling
• edge map
• texture
• smooth

Abstract

In this paper, a depth image up-sampling method is put forward by using pixel classifying and jointed bilateral filtering. By analyzing the edge maps originated from the high-resolution color image and low-resolution depth map respectively, pixels in up-sampled depth maps can be classified into four categories: edge points, edge-neighbor points, texture points and smooth points. First, joint bilateral up-sampling (JBU) method is used to generate an initial up-sampling depth image. Then, for each pixel category, different refinement methods are employed to modify the initial up-sampling depth image. Experimental results show that the proposed algorithm can reduce the blurring artifact with lower bad pixel rate (BPR).

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