<div dir="ltr">From the fpzip website, the lossless (fpzip) algorithm achieves compression ratios of 1.5 - 4x depending on the data. It is also designed for streaming with little to no latency when decompressing. The lossy (zfp) algorithm achieves compression ratios of ~100x. The C/C++ library is freely available.<div><br></div><div> -- Paul </div></div><br><div class="gmail_quote gmail_quote_container"><div dir="ltr" class="gmail_attr">On Mon, Oct 27, 2025 at 12:35 PM Dubois-Felsmann, Gregory P. <<a href="mailto:gpdf@ipac.caltech.edu">gpdf@ipac.caltech.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">Paul, <br>
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The "tile" in tile compression arises, in part, from the idea that for quantized compression there are advantages to aligning the quantization with local conditions across an image. It also facilitates accessing only part of a large image if all that's needed is a cutout.<br>
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I'm not familiar with fpzip; can you comment on whether there are overhead issues that would push one toward compressing images as a whole or whether the "tile" approach matches up with how fpzip performs?<br>
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I've found references that say that LLNL's "zfp" is designed for streaming processing, which would likely mean it would be well-matched to tiling as well. I wasn't able to find as clear a statement on their "fpzip", but that might be because I'm having (temporary, I assume) trouble accessing the original paper.<br>
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Thanks,<br>
Gregory<br>
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________________________________________<br>
From: fitsbits <<a href="mailto:fitsbits-bounces@listmgr.nrao.edu" target="_blank">fitsbits-bounces@listmgr.nrao.edu</a>> on behalf of Seaman, Robert Lewis - (rseaman) via fitsbits <<a href="mailto:fitsbits@listmgr.nrao.edu" target="_blank">fitsbits@listmgr.nrao.edu</a>><br>
Sent: Monday, October 27, 2025 08:37<br>
To: <a href="mailto:fitsbits@listmgr.nrao.edu" target="_blank">fitsbits@listmgr.nrao.edu</a><br>
Subject: Re: [fitsbits] Adding fpzip floating point compression {External}<br>
<br>
Hi Paul,<br>
<br>
You do mean adding it as an option to FITS tile compression, right? This may include bintable compression, as well as image arrays.<br>
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There have been a number of suggestions lately related to enabling additional algorithms for tile compression. It was always designed to support this. Any such that are adopted into FITS should (at least) be enabled for FPACK. It would be good if such algorithms could be evaluated similarly to as described in papers I and II linked at: <a href="https://heasarc.gsfc.nasa.gov/docs/software/fitsio/fpack/" rel="noreferrer" target="_blank">https://heasarc.gsfc.nasa.gov/docs/software/fitsio/fpack/</a><br>
<br>
(The website is still accessible, if not being maintained, during the gov’t shutdown.)<br>
<br>
Speed as well as compression ratio are important in efficient data representations. Decompression may be faster or slower than compression, etc.<br>
<br>
Rob Seaman<br>
Lunar and Planetary Laboratory<br>
University of Arizona<br>
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—<br>
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On 10/27/25, 8:27 AM, "fitsbits" wrote:<br>
<br>
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External Email<br>
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I'm not quite understanding how this would be implemented. Is this a new BITPIX ? Or does it only apply to a new extension. like how BINTABLE was done?<br>
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I get worried if we encode (compression) algorithms in order to decode FITS files.<br>
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- peter<br>
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On 10/27/25 11:13, Barrett, Paul via fitsbits wrote:<br>
I would like to suggest that FITS add the fpzip<<a href="https://computing.llnl.gov/projects/fpzip" rel="noreferrer" target="_blank">https://computing.llnl.gov/projects/fpzip</a>> floating point compression algorithm to the FITS standard. fpzip is primarily designed for lossless compression but also has a provision for lossy compression.<br>
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I will be adding it to FITSFiles.jl, a pure Julia implementation of the FITS standard.<br>
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-- Paul<br>
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<br>
--<br>
Paul Barrett, PhD<br>
Department of Physics<br>
The George Washington University<br>
Washington, DC 20052<br>
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</blockquote></div>