Quality assessment of 3D synthesized views with depth map distortion

Most existing 3D image quality metrics use 2D image quality assessment (IQA) models to predict the 3D subjective quality. But in a free viewpoint television (FTV) system, the depth map errors often produce object shifting or ghost artifacts on the synthesized pictures due to the use of Depth Image Based Rendering (DIBR) technique. These artifacts are very different from the ordinary 2D distortions such as blur, Gaussian noise, and compression errors. We thus propose a new 3D quality metric to evaluate the quality of stereo images that may contain artifacts introduced by the rendering process due to depth map errors. We first eliminate the consistent pixel shifts inside an object before the usual 2D metric is applied. The experimental results show that the proposed method enhances the correlation of the objective quality score to the 3D subjective scores.