In this paper, we propose a source coding scheme that represents data from
unknown distributions through frequency and support information. Existing
encoding schemes often compress data by sacrificing computational efficiency or
by assuming the data follows a known distribution. We take advantage of the
structure that arises within the spatial representation and utilize it to
encode run-lengths within this representation using Golomb coding. Through
theoretical analysis, we show that our scheme yields an overall bit rate that
nears entropy without a computationally complex encoding algorithm and verify
these results through numerical experiments.Comment: This work has been submitted to the IEEE for possible publication.
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