Benchmarking Objective Quality Assessment Methods for Light Field Coding Applications

Abstract

This paper presents a comprehensive performance evaluation of objective quality assessment methods for evaluating the visual quality of compressed light field content. Leveraging a carefully curated dataset and a subjective experiment, we examine the performance of 21 widely-used image and video quality metrics covering both full-reference and no-reference techniques. The performance of metrics is assessed using correlation measures and validated through statistical significance testing. Our findings identify the most reliable metrics for light field quality assessment and highlight persistent challenges in capturing subtle perceptual degradations. The study contributes empirical evidence and methodological guidance to support ongoing standardization efforts within the JPEG Pleno framework.