Complexity analysis of adaptive binary arithmetic coding software implementations

Authors:
Evgeny Belyaev;Anton Veselov;Andrey Turlikov;Liu Kai
Affiliations:
Tampere University of Technology, Tampere, Finland;Saint-Petersburg State University of Aerospace Instrumentation, Bolshaya, St. Petersburg, Russia;Saint-Petersburg State University of Aerospace Instrumentation, Bolshaya, St. Petersburg, Russia;School of Computer Science and Technology, Xidian University, Xi'an, China
Venue:
NEW2AN'11/ruSMART'11 Proceedings of the 11th international conference and 4th international conference on Smart spaces and next generation wired/wireless networking
Year:
2011

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Abstract

This paper is dedicated to the complexity comparison of adaptive binary arithmetic coding integer software implementations. Firstly, for binary memoryless sources with known probability distribution, we prove that encoding time for arithmetic encoder is a linear function of a number of input binary symbols and source entropy. Secondly, we show that the byte-oriented renormalization allows to decrease encoding time up to 40% in comparison with bit-oriented renormalization. Finally, we study influence of probability estimation algorithm for encoding time and show that probability estimation algorithm using "Virtual Sliding Window" has less computation complexity than state machine based probability estimation algorithm from H.264/AVC standard.