Low complexity in-loop perceptual video coding

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

[img]
Preview
PDF - Final accepted version (with author's formatting)
Download (45MB) | Preview

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.

Item Type: Thesis (PhD)
Research Areas: A. > School of Science and Technology
B. > Theses
Item ID: 21278
Depositing User: Jennifer Basford
Date Deposited: 14 Feb 2017 12:39
Last Modified: 13 Sep 2018 03:06
URI: http://eprints.mdx.ac.uk/id/eprint/21278

Actions (login required)

Edit Item Edit Item

Full text downloads (NB count will be zero if no full text documents are attached to the record)

Downloads per month over the past year