An efficient rate–distortion optimization method for dependent view in MV-HEVC based on inter-view dependency

Li, Tiansong; Yu, Li; Wang, Hongkui; Kuang, Zhuo

doi:10.1016/j.image.2021.116166

Cited by 1 publication

(1 citation statement)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To reduce coding complexity, Jiang et al [13] put forward inter-frame prediction method that reveals the relationship between mode selection and coding distortion threshold by a perceptual distortion threshold model. Li et al [19] proposed an RD optimization for the dependent viewpoint based on inter-viewpoint dependencies, and greatly improved its performance in MVC. In these general methods, the bitrate may increase sharply with the number of viewpoints, which is because the original video needs to be encoded in each viewpoint rather than the side information.…”

Section: Multi-view Video Codingmentioning

confidence: 99%

Multi-View Video Coding with GAN Latent Learning

Lan¹,

Luo²,

Yan³

et al. 2022

Preprint

View full text Add to dashboard Cite

The introduction of multiple viewpoints inevitably increases the bitrates to store and transmit video scenes. To reduce the compressed bitrates, researchers have developed to skip intermediate viewpoints during compression and delivery, and finally reconstruct them with Side Information (SI). Generally, the depth maps can be utilized to construct SI; however, it shows inferior performance with inaccurate reconstruction or high bitrates. In this paper, we propose a multi-view video coding based on SI of Generative Adversarial Network (GAN). At the encoder, we construct a spatio-temporal Epipolar Plane Image (EPI) and further utilize convolutional network to extract the latent code of GAN as SI; while at the decoder side, we combine the SI and adjacent viewpoints to reconstruct intermediate views by the generator of GAN. In particular, we set a joint encoder constraint of reconstruction cost and SI entropy, in order to achieve an optimal tradeoff between reconstruction quality and bitrate overhead. Experiments show a significantly improved Rate-Distortion (RD) performance compared with the state-of-the-art methods.

show abstract

Section: Multi-view Video Codingmentioning

confidence: 99%