A novel quality metric for evaluation of depth dependent coding artifacts in 3D images

The two-dimensional quality metric Peak-Sional-To-Noise-Ratio (PSNR) is often used to evaluate the quality of coding schemes for different types of light field based 3D-images, e.g. integral imaging or multi-view. The metric results in a single accumulated quality value for the whole 3D-image. Evaluating single views - seen from specific viewing angles gives a quality matrix that present the 3D-image quality as a function of viewing angle. However, these two approaches do not capture all aspects of the induced distortion in a coded 3D-image. We have previously shown coding schemes of similar kind for which coding artifacts are distributed differently with respect to the 3D-image's depth. In this paper we propose a novel metric that captures the depth distribution of coding-induced distortion. Each element in the resulting quality vector corresponds to the quality at a specific depth. First we introduce the proposed full-reference metric and the operations on which it is based. Second, the experimental setup is presented. Finally, the metric is evaluated on a set of differently coded 3D-images and the results are compared, both with previously proposed quality metrics and with visual inspection