  Over the past years, the ever-growing trend on data storage demand, more
specifically for "cold" data (i.e. rarely accessed), has motivated research for
alternative systems of data storage. Because of its biochemical
characteristics, synthetic DNA molecules are considered as potential candidates
for a new storage paradigm. Because of this trend, several coding solutions
have been proposed over the past years for the storage of digital information
into DNA. Despite being a promising solution, DNA storage faces two major
obstacles: the large cost of synthesis and the noise introduced during
sequencing. Additionally, this noise increases when biochemically defined
coding constraints are not respected: avoiding homopolymers and patterns, as
well as balancing the GC content. This paper describes a novel entropy coder
which can be embedded to any block-based image-coding schema and aims to
robustify the decoded results. Our proposed solution introduces variability in
the generated quaternary streams, reduces the amount of homopolymers and
repeated patterns to reduce the probability of errors occurring. In this paper,
we integrate the proposed entropy coder into four existing JPEG-inspired DNA
coders. We then evaluate the quality -- in terms of biochemical constraints --
of the encoded data for all the different methods.
