Depth image enhancement algorithm for preserving boundary

Zigu Zhou, Jie Cao, Qun Hao*, Zedong Gao, Yuqing Xiao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The drawback of current depth image enhancement algorithms is poor performance of edge preserving. To solve this drawback, the gradient mask guided joint filtering(GMGJF) algorithm is proposed. The Sobel gradient transform is used to obtain the boundary direction information, and the hole region of the depth images was utilized to generate the hole mask.Furthermore, taking the boundary direction and the cavity mask as the guidance, the color image was jointed to perform iterative Gaussian filtering and hole filling on the depth image. Experimental results show that the peak signal to noise ratio(PSNR) and the structural similarity index measure(SSIM) of GMGJF algorithm are improved by at least 3.50% and 1.07% respectively, compared with the iterative median filter(IMF), guided filter (GF) and joint bilateral filter(JBF) algorithms, it has both the strongest ability of denoising and hole filling, and can remain the boundary features best, which is good for feature extraction and target recognition of depth image.

Original languageEnglish
Pages (from-to)200-206
Number of pages7
JournalJournal of Applied Optics
Volume39
Issue number2
DOIs
Publication statusPublished - Mar 2018

Keywords

  • Depth image
  • Gradient mask guided joint filter
  • Hole mask
  • Image enhancement
  • PSNR

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