  Light field (LF) technology is considered as a promising way for providing a
high-quality virtual reality (VR) content. However, such an imaging technology
produces a large amount of data requiring efficient LF image compression
solutions. In this paper, we propose a LF image coding method based on a view
synthesis and view quality enhancement techniques. Instead of transmitting all
the LF views, only a sparse set of reference views are encoded and transmitted,
while the remaining views are synthesized at the decoder side. The transmitted
views are encoded using the versatile video coding (VVC) standard and are used
as reference views to synthesize the dropped views. The selection of
non-reference dropped views is performed using a rate-distortion optimization
based on the VVC temporal scalability. The dropped views are reconstructed
using the LF dual discriminator GAN (LF-D2GAN) model. In addition, to ensure
that the quality of the views is consistent, at the decoder, a quality
enhancement procedure is performed on the reconstructed views allowing smooth
navigation across views. Experimental results show that the proposed method
provides high coding performance and overcomes the state-of-the-art LF image
compression methods by -36.22% in terms of BD-BR and 1.35 dB in BD-PSNR. The
web page of this work is available at
https://naderbakir79.github.io/LFD2GAN.html.

Image and Video Processing