ORCID Identifier(s)

0000-0001-8230-1365

Graduation Semester and Year

2015

Language

English

Document Type

Thesis

Degree Name

Master of Science in Electrical Engineering

Department

Electrical Engineering

First Advisor

Kamisetty R Rao

Abstract

In this thesis an intra prediction algorithm is proposed that terminates complete full search prediction for the CU and is replaced by CU early termination algorithm which determines the complexity of the CU block and then decision is made to further split or non-split the CU. When the CU texture is complex the CU is split into smaller sub units to find the best size and when the CU texture is flat, the CU is not divided further into sub – units. Down sampling is done first after which complexity is calculated by which a threshold value is set. This threshold value dictates early termination of CU block. This is followed by a TU mode decision to find the optimal prediction mode from the 35 prediction modes. Proposed method will use tree split/tree merge algorithm. Experimental results based on several video test sequences suggest a decrease of about 12%-24% in encoding time is achieved with implementation of the proposed CU early termination algorithm and fast intra mode decision algorithm for intra predication with negligible degradation in peak signal to noise ratio (PSNR). Metrics such as BD-bitrate (Bjøntegaard Delta bitrate), BD-PSNR (Bjøntegaard Delta Peak Signal to Noise Ratio), RD graph (Rate Distortion) and computational complexity are also used.

Keywords

Intra prediction, Early termination algorithm

Disciplines

Electrical and Computer Engineering | Engineering

Comments

Degree granted by The University of Texas at Arlington

25499-2.zip (1576 kB)

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.