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Low complexity H.264 video encoder design using machine learning techniques

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Date Issued:
2008
Summary:
H.264/AVC encoder complexity is mainly due to variable size in Intra and Inter frames. This makes H.264/AVC very difficult to implement, especially for real time applications and mobile devices. The current technological challenge is to conserve the compression capacity and quality that H.264 offers but reduce the encoding time and, therefore, the processing complexity. This thesis applies machine learning technique for video encoding mode decisions and investigates ways to improve the process of generating more general low complexity H.264/AVC video encoders. The proposed H.264 encoding method decreases the complexity in the mode decision inside the Inter frames. Results show, at least, a 150% average reduction of complexity and, at most, 0.6 average increases in PSNR for different kinds of videos and formats.
Title: Low complexity H.264 video encoder design using machine learning techniques.
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Name(s): Carrillo, Paula.
Department of Computer and Electrical Engineering and Computer Science
College of Engineering and Computer Science
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Issued: 2008
Publisher: Florida Atlantic University
Physical Form: electronic
Extent: xiii, 59 p. : ill. (some col.).
Language(s): English
Summary: H.264/AVC encoder complexity is mainly due to variable size in Intra and Inter frames. This makes H.264/AVC very difficult to implement, especially for real time applications and mobile devices. The current technological challenge is to conserve the compression capacity and quality that H.264 offers but reduce the encoding time and, therefore, the processing complexity. This thesis applies machine learning technique for video encoding mode decisions and investigates ways to improve the process of generating more general low complexity H.264/AVC video encoders. The proposed H.264 encoding method decreases the complexity in the mode decision inside the Inter frames. Results show, at least, a 150% average reduction of complexity and, at most, 0.6 average increases in PSNR for different kinds of videos and formats.
Identifier: 316798878 (oclc), 166448 (digitool), FADT166448 (IID), fau:2831 (fedora)
Note(s): by Paula Carrillo.
Thesis (M.S.C.S.)--Florida Atlantic University, 2008.
Includes bibliography.
Electronic reproduction. Boca Raton, Fla., 2008. Mode of access: World Wide Web.
Subject(s): Code division multiple access
Digital media -- Technological innovations
Image transmission -- Technological innovations
Coding theory
Data structures (Computer science)
Persistent Link to This Record: http://purl.flvc.org/FAU/166448
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU