DocumentCode :
3264101
Title :
Efficient conditional entropy estimation for distributed video coding
Author :
Louw, Daniel J. ; Kaneko, Hironori
Author_Institution :
Dept. of Comput. Sci., Tokyo Inst. of Technol., Tokyo, Japan
fYear :
2013
fDate :
8-11 Dec. 2013
Firstpage :
61
Lastpage :
64
Abstract :
Distributed video coding (DVC) is a compression method that aims to produce low complexity encoding. One of the main practical problems facing DVC is that the encoder must know the required rate. Theoretically, the rate is lower bounded by the conditional entropy of the source given the side information. In practice, there are losses that must also be taken into account in estimating the rate. However, an accurate rate estimate starts with an accurate estimate of the conditional entropy. In this paper we propose a computationally efficient method for accurately estimating the conditional entropy.
Keywords :
entropy codes; estimation theory; video coding; DVC; conditional entropy estimation; distributed video coding; low complexity encoding; rate estimation; Complexity theory; Decoding; Entropy; Equations; Estimation; Mathematical model; Video coding; Conditional Entropy Estimation; Distibuted Video Coding; Rate Estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Picture Coding Symposium (PCS), 2013
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4799-0292-7
Type :
conf
DOI :
10.1109/PCS.2013.6737683
Filename :
6737683
Link To Document :
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