TY - GEN

T1 - Source coding with distortion profile constraints

AU - Moulin, Pierre

N1 - Publisher Copyright:
© 2017 IEEE.

PY - 2017/8/9

Y1 - 2017/8/9

N2 - In rate-distortion theory, three main types of distortion constraints have been popular: average, pointwise, and excess probability (aka-fidelity). A new setup is proposed here, which is suitable for fixed-length codes and constrains the distribution (profile) of distortions. This is accomplished by imposing multiple constraints on excess-distortion probabilities as well as an optional constraint on average distortion. We show that coding redundancy for compressing discrete memoryless sources is upper-bounded by R2/√n + log n/2n + O(log log n/n) + R4 + o(1) where n is the block length, R2 the second-order coding rate, and R4 a constant. For the special case of coding with a single-fidelity constraint, R2 = √V Q-1() where V is the source rate-dispersion function, and Q is the tail probability of a normal random variable. The upper bound is proved using a random coding scheme and deriving exact asymptotics for the probability of distortion balls with input type dependent radius.

AB - In rate-distortion theory, three main types of distortion constraints have been popular: average, pointwise, and excess probability (aka-fidelity). A new setup is proposed here, which is suitable for fixed-length codes and constrains the distribution (profile) of distortions. This is accomplished by imposing multiple constraints on excess-distortion probabilities as well as an optional constraint on average distortion. We show that coding redundancy for compressing discrete memoryless sources is upper-bounded by R2/√n + log n/2n + O(log log n/n) + R4 + o(1) where n is the block length, R2 the second-order coding rate, and R4 a constant. For the special case of coding with a single-fidelity constraint, R2 = √V Q-1() where V is the source rate-dispersion function, and Q is the tail probability of a normal random variable. The upper bound is proved using a random coding scheme and deriving exact asymptotics for the probability of distortion balls with input type dependent radius.

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U2 - 10.1109/ISIT.2017.8007123

DO - 10.1109/ISIT.2017.8007123

M3 - Conference contribution

AN - SCOPUS:85034039745

T3 - IEEE International Symposium on Information Theory - Proceedings

SP - 3215

EP - 3219

BT - 2017 IEEE International Symposium on Information Theory, ISIT 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 IEEE International Symposium on Information Theory, ISIT 2017

Y2 - 25 June 2017 through 30 June 2017

ER -