Video Rate Control Using an Adaptive Quantization Based on a Combined Activity Measure

A new rate control algorithm for videos is presented. The method comes from the MPEG-2 Test Model 5(TM5) rate control, while a buffer constraint and a new measure for the macroblock (MB) activity based on spatio-temporal sensitivity are introduced. Experimental results show that the proposed method...

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Bibliographic Details
Published inKnowledge-Based Intelligent Information and Engineering Systems pp. 1297 - 1302
Main Authors Lee, Si-Woong, Hong, Sung-Hoon, Choi, Jae Gark, Ko, Yun-Ho, Yun, Byoung-Ju
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture Notes in Computer Science
Subjects
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Exact sciences and technology
Human Visual System
Motion Vector
Quantization Step
Spatial Activity
Video Code
Control constraint
Signal quantization
Quality control
Video signal
Buffer system
Adaptive control
Artificial intelligence
Modeling
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Summary:A new rate control algorithm for videos is presented. The method comes from the MPEG-2 Test Model 5(TM5) rate control, while a buffer constraint and a new measure for the macroblock (MB) activity based on spatio-temporal sensitivity are introduced. Experimental results show that the proposed method outperforms the TM5 rate control in picture quality.
ISBN:3540288945
9783540288947
ISSN:0302-9743
1611-3349
DOI:10.1007/11552413_185