  Image compression has been a frequent topic of presentations at ADASS.
Compression is often viewed as just a technique to fit more data into a smaller
space. Rather, the packing of data - its "density" - affects every facet of
local data handling, long distance data transport, and the end-to-end
throughput of workflows. In short, compression is one aspect of proper data
structuring. For example, with FITS tile compression the efficient
representation of data is combined with an expressive logistical paradigm for
its manipulation.
  A deeper question remains. Not just how best to represent the data, but which
data to represent. CCDs are linear devices. What does this mean? One thing it
does not mean is that the analog-to-digital conversion of pixels must be stored
using linear data numbers (DN). An alternative strategy of using non- linear
representations is presented, with one motivation being to magnify the
efficiency of numerical compression algorithms such as Rice.
