Output-Constrained Lossy Source Coding With Application to Rate-Distortion-Perception Theory
This work addresses theoretical limits in source coding for applications like rate-distortion-perception theory, but it is incremental as it builds on existing frameworks with specific assumptions.
The paper analyzed the distortion-rate function for output-constrained lossy source coding with limited common randomness, deriving an explicit expression for Gaussian distributions and partially characterizing the information-theoretic limit for rate-distortion-perception coding with specific perception measures.
The distortion-rate function of output-constrained lossy source coding with limited common randomness is analyzed for the special case of squared error distortion measure. An explicit expression is obtained when both source and reconstruction distributions are Gaussian. This further leads to a partial characterization of the information-theoretic limit of quadratic Gaussian rate-distortion-perception coding with the perception measure given by Kullback-Leibler divergence or squared quadratic Wasserstein distance.