Darren Ramsook

Title: Video Coding Artefact Suppression Using Perceptual Criteria

Supervision Team: Anil Kokaram, TCD / Noel O’Connor, DCU

Description: Video traffic accounts for about 70% of all internet traffic now, and predictions are on track for 80% by 2022. Data compression is the only reason that video has not broken the system. However lossy video compression causes artefacts e.g. blocking and contouring which have to be removed by the video player receiving the compressed data. All of the techniques for removing these artefacts currently do not exploit visual quality criteria relevant for humans. This causes a problem for video consumed on different devices. By exploiting the visibility of artefacts on different devices, this project develops new techniques for artefact reduction that are sensitive to the human visual system, hence enabling appropriate video quality/bitrate compromises to be made with different devices.