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Paper: Optimal DN Encoding for CCD Detectors
Volume: 411, Astronomical Data Analysis Software and Systems XVIII
Page: 101
Authors: Seaman, R.L.; White, R.L.; Pence, W.D.
Abstract: 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 nonlinear representations is presented, with one motivation being to magnify the efficiency of numerical compression algorithms such as Rice.
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