Subjective Evaluation of Light Field Image Compression Methods based on View Synthesis

Light field (LF) images provide rich visual information enabling amazing applications, from post-capture image processing to immersive applications. However, this rich information requires significant storage and bandwidth capabilities thus urgently raises the question of their compression. Many studies have investigated the compression of LF images using both spatial and angular redundancies existing in the LF images. Recently, interesting LF compression approaches based on view synthesis technique have been proposed. In these approaches, only sparse samples of LF views are encoded and transmitted, while the other views are synthesized at decoder side. Different techniques have been proposed to synthesize the dropped views. In this paper, we describe subjective quality evaluation of two recent compression methods based on view synthesis and comparing them to two pseudo-video sequence based coding approaches. Results show that view synthesis based approaches provide higher visual quality than the naive LF coding approaches. In addition, the database as well as subjective scores are publicly available to help designing new objective metrics or can be used as a benchmark for future development of LF coding methods.