  In this work we explore possibilities for coding and decoding tailor-made for
mean squared error evaluation of error in contexts such as image transmission.
To do so, we introduce a loss function that expresses the overall performance
of a coding and decoding scheme for discrete channels and that exchanges the
usual goal of minimizing the error probability to that of minimizing the
expected loss. In this environment we explore the possibilities of using
ordered decoders to create a message-wise unequal error protection (UEP), where
the most valuable information is protected by placing in its proximity
information words that differ by a small valued error. We give explicit
examples, using scale-of-gray images, including small-scale performance
analysis and visual simulations for the BSMC.
