A new depth image quality metric using a pair of color and depth images

Thanh Ha Le, Seung Won Jung, Chee Sun Won

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Typical depth quality metrics require the ground truth depth image or stereoscopic color image pair, which are not always available in many practical applications. In this paper, we propose a new depth image quality metric which demands only a single pair of color and depth images. Our observations reveal that the depth distortion is strongly related to the local image characteristics, which in turn leads us to formulate a new distortion assessment method for the edge and non-edge pixels in the depth image. The local depth distortion is adaptively weighted using the Gabor filtered color image and added up to the global depth image quality metric. The experimental results show that the proposed metric closely approximates the depth quality metrics that use the ground truth depth or stereo color image pair.

Original languageEnglish
Pages (from-to)11285-11303
Number of pages19
JournalMultimedia Tools and Applications
Volume76
Issue number9
DOIs
StatePublished - 1 May 2017

Keywords

  • Depth image
  • Image quality assessment
  • Quality metric
  • Reduced reference

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