Electrical and Computer Engineering ETDs

Publication Date

Summer 7-10-2020


The dissertation proposes the use of a multi-objective optimization framework for designing and selecting among enhanced GOP configurations in video compression standards. The proposed methods achieve fine optimization over a set of general modes that include: (i) maximum video quality, (ii) minimum bitrate, (iii) maximum encoding rate (previously minimum encoding time mode) and (iv) can be shown to improve upon the YouTube/Netflix default encoder mode settings over a set of opposing constraints to guarantee satisfactory performance. The dissertation describes the implementation of a codec-agnostic approach using different video coding standards (x265, VP9, AV1) on a wide range of videos derived from different video datasets. The results demonstrate that the optimal encoding parameters obtained from the Pareto front space can provide significant bandwidth savings without sacrificing video quality. This is achieved by the use of effective regression models that allow for the selection of video encoding settings that are jointly optimal in the encoding time, bitrate, and video quality space. The dissertation applies the proposed methods to x265, VP9, AV1 and using new GOP configurations in x265, delivering over 40% of the optimal encodings in two standard reference videos. Then, the proposed encoding method is extended to use video content to determine constraints on video quality during real-time encoding. The content-based approach is demonstrated on identifying camera motions like panning, stationary and zooming in the video. Overall, the content-based approach gave bitrate savings of 35 % on the zooming & panning motion from Shields video, and 51.5 % on stationary & panning motion from Parkrun video. Additionally, the dissertation develops a segment-based encoding approach that delivers bitrate savings over YouTube's recommended bitrates. Using BD-PSNR and BD-VMAF, a comparison is made of x265, VP9, AV1 against the emerging VVC encoding standard. The new VVC-VTM encoder is found to outperform all rival video codecs. Based on subjective video quality assessment study, AV1 was found to provide higher quality than x265 and VP9.


Video codecs, Pareto front, Regression models, Video encoding, Video quality assessment

Document Type




Degree Name

Computer Engineering

Level of Degree


Department Name

Electrical and Computer Engineering

First Committee Member (Chair)

Marios Pattichis

Second Committee Member

Manuel Martinez-Ramon

Third Committee Member

Ramiro Jordan

Fourth Committee Member

Sylvia Celedon-Pattichis

Fifth Committee Member

Andreas Panayides