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Light field technology represents a viable path for providing a high-qualityVR content. However, such an imaging system generates a high amount of dataleading to an urgent need for LF image compression solution. In this paper, wepropose an efficient LF image coding scheme based on view synthesis. Instead oftransmitting all the LF views, only some of them are coded and transmitted,while the remaining views are dropped. The transmitted views are coded usingVersatile Video Coding (VVC) and used as reference views to synthesize themissing views at decoder side. The dropped views are generated using theefficient dual discriminator GAN model. The selection of reference/droppedviews is performed using a rate distortion optimization based on the VVCtemporal scalability. Experimental results show that the proposed methodprovides high coding performance and overcomes the state-of-the-art LF imagecompression solutions.

Light Field Image Coding Using Dual Discriminator Generative Adversarial Network and VVC Temporal Scalability