  Under the limited storage, computing and network bandwidth resources, the
video compression coding technology plays an important role for visual
communication. To efficiently compress raw video data, a colorization-based
video compression coding method is proposed in this paper. In the proposed
encoder, only the video luminance components are encoded and transmitted. To
restore the video chrominance information, a generative adversarial network
(GAN) model is adopted in the proposed decoder. In order to make the GAN work
efficiently for video colorization, the generator of the proposed GAN model
adopts an optimized MultiResUNet, an attention module, and a mixed loss
function. Experimental results show that when compared with the H.265/HEVC
video compression coding standard using all-intra coding structure, the
proposed video compression coding method achieves an average of 72.05% BDBR
reduction, and an average of 4.758 dB BDPSNR increase. Moreover, to our
knowledge, this is the first work which compresses videos by using GAN-based
colorization, and it provides a new way for addressing the video compression
coding problems.
