PhD Theses.The increase in demand for video rendering in 4K and beyond displays, as well
as immersive video formats, requires the use of e cient compression techniques. In
this thesis novel methods for enhancing the e ciency of current and next generation
video codecs are investigated. Several aspects that in
uence the way conventional video
coding methods work are considered. The methods proposed in this thesis utilise Neural
Networks (NNs) trained for regression tasks in order to predict data. In particular,
Convolutional Neural Networks (CNNs) are used to predict Rate-Distortion (RD) data
for intra-coded frames. Moreover, a novel intra-prediction methods are proposed with
the aim of providing new ways to exploit redundancies overlooked by traditional intraprediction
tools. Additionally, it is shown how such methods can be simpli ed in order
to derive less resource-demanding tools
