Precise depth map upsampling and enhancement based on edge-preserving fusion filters

Ting An Chang, Jar Ferr Yang

Research output: Contribution to journalArticlepeer-review

Abstract

A texture image plus its associated depth map is the simplest representation of a three-dimensional image and video signals and can be further encoded for effective transmission. Since it contains fewer variations, a depth map can be coded with much lower resolution than a texture image. Furthermore, the resolution of depth capture devices is usually also lower. Thus, a low-resolution depth map with possible noise requires appropriate interpolation to restore it to full resolution and remove noise. In this study, the authors propose potency guided upsampling and adaptive gradient fusion filters to enhance the erroneous depth maps. The proposed depth map enhancement system can successfully suppress noise, fill missing values, sharpen foreground objects, and smooth background regions simultaneously. Their experimental results show that the proposed methods perform better in terms of both visual and subjective metrics than the classic methods and achieve results that are visually comparable with those of some time-consuming methods.

Original languageEnglish
Pages (from-to)651-658
Number of pages8
JournalIET Computer Vision
Volume12
Issue number5
DOIs
Publication statusPublished - 2018 Aug 1

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition

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