Adzic, Velibor

We are presenting work that is aimed at employing characteristics of human visual
system in optimizing video coding compression. Preliminary experiments that include temporal
and motion masking show results with significant savings in bitrate compared to state of the art
coding algorithms.

The main goal of video coding algorithms is to achieve high compression efficiency while
maintaining quality of the compressed signal at the highest level. Human visual system is
the ultimate receiver of compressed signal and final judge of its quality. This dissertation
presents work towards optimal video compression algorithm that is based on the
characteristics of our visual system. Modeling phenomena such as backward temporal
masking and motion masking we developed algorithms that are implemented in the state-of-
the-art video encoders. Result of using our algorithms is visually lossless compression
with improved efficiency, as verified by standard subjective quality and psychophysical
tests. Savings in bitrate compared to the High Efficiency Video Coding / H.265 reference
implementation are up to 45%.