Quality Assessment of Synthesized 3D Video with Distorted Depth Map

Abstract

In the virtual-view 3D video coding system, both the RGB image data and the depth maps are compressed and translated to the receivers. After compression, the depth maps are distorted and may cause visible artifacts on the synthesized video. We study the visual effect of compressed depth maps on the synthesized video and develop a quality assessment model that predicts the subjective quality. We use HEVC Test Model (HTM) to compress the depth maps. The distorted depth value may lead to ghost artifacts around object edges and unnatural object motion on the synthesized video. In our proposed quality assessment (QA) model, we use SSIM to compute the basic score of stereo image pair; we extract the edge, motion, and depth features of stereo pairs and combine them to form a local weight to increase the sensitivity of the noticeable regions. We use the binocular perception model to calculate the score of stereo pairs. We conduct our own subjective tests. The results of our experiments show that our model has a better match to the subjective scores when it is compared with the other existing metrics.