Reduced Reference Quality Assessment of Light Field Images

Abstract

Immersive media, such as free view point video and 360° video, are expected to be dominant as broadcasting services. The light field (LF) imaging is being considered as a next generation imaging technology offering the possibility to provide new services, including six degree-of-freedom video. The drawback of this technology is in the size of the generated content thus requiring novel compression systems and the design of ad-hoc methodologies for evaluating the perceived quality. In this paper, the relation between depth map quality and overall quality of LF image is studied. Next, a reduced reference quality assessment metric for LF images is presented. To predict the quality of distorted LF images, the measure of distortion in the depth map is exploited. To test and validate the proposed framework, a subjective experiment has been performed, and a LF image quality dataset has been created. The dataset is also used for evaluating the performance of state-of-the-art quality metrics, when applied to LF images. The achieved results evidence that the estimated quality score by the proposed framework has a significant correlation with subjective quality rating. Consequently, reference data can be delivered to the clients thus allowing the local estimation of the perceived quality of service.