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Middlesex University

Low complexity in-loop perceptual video coding

Abstract

dc:description.abstract

The tradition of broadcast video is today complemented with user generated content, as portable devices support video coding. Similarly, computing is becoming ubiquitous, where Internet of Things (IoT) incorporate heterogeneous networks to communicate with personal and/or infrastructure devices. Irrespective, the emphasises is on bandwidth and processor efficiencies, meaning increasing the signalling options in video encoding. Consequently, assessment for pixel differences applies uniform cost to be processor efficient, in contrast the Human Visual System (HVS) has non-uniform sensitivity based upon lighting, edges and textures. Existing perceptual assessments, are natively incompatible and processor demanding, making perceptual video coding (PVC) unsuitable for these environments. This research allows existing perceptual assessment at the native level using low complexity techniques, before producing new pixel-base image quality assessments (IQAs). To manage these IQAs a framework was developed and implemented in the high efficiency video coding (HEVC) encoder. This resulted in bit-redistribution, where greater bits and smaller partitioning were allocated to perceptually significant regions. Using a HEVC optimised processor the timing increase was < +4% and < +6% for video streaming and recording applications respectively, 1/3 of an existing low complexity PVC solution. Future work should be directed towards perceptual quantisation which offers the potential for perceptual coding gain.

Degree

thesis:*
Level dc:type.qualificationlevel
PhD thesis
Grantor dc:publisher.institution
Middlesex University
Year dc:date.issued
2016

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Joshi, Y.

Identifiers

dc:identifier.*
Identifier
oai:repository.mdx.ac.uk:86wyy
OAI identifier oai:identifier
oai:repository.mdx.ac.uk:86wyy

Chain of custody

source
Harvested from
Middlesex University
Base URL
repository.mdx.ac.uk/oai2
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Joshi, Y.. Low complexity in-loop perceptual video coding. PhD thesis thesis, Middlesex University, 2016.