Pavan Gajjala

Graduation Semester and Year

2013

Language

English

Document Type

Thesis

Degree Name

Master of Science in Electrical Engineering

Department

Electrical Engineering

First Advisor

Kamisetty R Rao

Abstract

High Efficiency Video Coding (HEVC) [3] is the next generation video compression standard being jointly developed by the Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T WP3/16 and ISO/IEC JTC 1/SC 29/WG 11. The loss less coding is prominent in real-time applications like automotive vision, video conferencing and in web collaboration for remote desktop sharing. HEVC with the lossless mode can help in these applications effectively by providing content with certain level of compression when compared to other lossless compression techniques. This thesis focuses on improving the compression efficiency for the lossless coding mode of HEVC by using a novel approach of sample based angular intra prediction replacing the traditional intra prediction approach currently used in HEVC.The sample based angular intra prediction approach uses the same prediction mode signaling method and the same interpolation method as the HEVC block based angular intra prediction but instead uses adjacent neighbors as the reference samples for better intra prediction accuracy and performs prediction pixel by pixel. Compared to the HEVC-anchor mode (HM 9.2) the proposed SAP based lossless mode in this thesis achieves significant bit rate savings from 5.93% - 12.76% for AI configuration and 2.56% - 7.87% for LB-Main configuration. It also increases compression ratio by 10.7% for AI and 5.3% for LB-Main configurations respectively. The encoding and decoding times are also reduced using the SAP based HEVC lossless mode.For implementation purpose HM 9.2 [4] version of the HEVC reference software is used and the current HEVC draft is followed to comply with the semantics of the software. The proposed method is compared with existing lossless compression techniques such as JPEG-2000 [8], JPEG-LS [7], 7-Zip [9] and Win RAR [10].

Disciplines

Electrical and Computer Engineering | Engineering

Comments

Degree granted by The University of Texas at Arlington

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