NIQSV: A no reference image quality assessment metric for 3D synthesized views

Abstract

The popularity of 3D applications, such as Free View-point TV (FTV) and Multi-view Video plus Depth (MVD), induces a heavy requirement of synthesized views. However, the quality assessment of synthesized views is very challenging because the corresponding original views (reference views) are usually not available at both encoder and decoder sides. In this paper, we propose a new no-reference quality assessment model to evaluate the quality of 3D synthesized views, called NIQSV (No-reference Image Quality assessment of Synthesized Views). This metric is based on the hypothesis that a good quality image is composed of flat areas (objects) separated by sharp edges, and the quality estimation involves only a set of simple morphological operators. NIQSV integrates the distortions of all the components, and then uses an edge image to weight the final distortions since the distortions of synthesized views mainly happen around object edges. The experimental results show that the proposed metric outperforms traditional 2D metrics and ranks among the best of dedicated 3D synthesized and full reference metrics.