  Many information systems employ lossy compression as a crucial intermediate
stage among other processing components. While the important distortion is
defined by the system's input and output signals, the compression usually
ignores the system structure, therefore, leading to an overall sub-optimal
rate-distortion performance. In this paper we propose a compression methodology
for an operational rate-distortion optimization considering a known system
layout, modeled using linear operators and noise. Using the alternating
direction method of multipliers (ADMM) technique, we show that the design of
the new globally-optimized compression reduces to a standard compression of a
"system adjusted" signal. Essentially, the proposed framework leverages
standard compression techniques to address practical settings of the noisy
source coding problem. We further explain the main ideas of our method by
theoretically studying the case of a cyclo-stationary Gaussian signal. We
present experimental results for coding of one-dimensional signals and for
video compression using the HEVC standard, showing significant gains by the
adjustment to an acquisition-rendering system.
