[gdal-dev] Fwd: [OpenJPEG] OpenJPEG v2.3.0 is out: more speed and memory improvement

[Even Rouault]

Hi,

I've just done changes in GDAL to be able to use the newly released openjpeg version: 
https://trac.osgeo.org/gdal/ticket/7074

For trunk,
- for linux builds, autoconf now uses pkg-config to be able to support more easily the /usr/
include/openjpeg-2.X path pattern
- for windows build, your option OPENJPEG_CFLAGS option now must point directly to the 
the include/openjpeg-2.X path

For branches/2.2, I've just extended the previous painful pattern to handle openjpeg 
versions.
(if you use GDAL 2.2.2 unmodified, you can just copy rename/symlink the include/
openjpeg-2.3 to include/openjpeg-2.2, and that will build fine as well)

Even

----------  Forwarded Message  ----------

Subject: [OpenJPEG] OpenJPEG v2.3.0 is out: more speed and memory improvement
Date: jeudi 5 octobre 2017, 02:42:41 CEST
From: Antonin - OpenJPEG <info at openjpeg.org>
To: openjpeg at googlegroups.com <openjpeg at googlegroups.com>

Good news everyone !

OpenJPEG 2.3.0 is released today:
https://github.com/uclouvain/openjpeg/releases/tag/v2.3.0

This new release finalizes the work made by Even Rouault and funded by several academic 
institutions and archival organizations to make OpenJPEG significantly faster and safer.

In addition to what has been done in v2.2.0 (multithreading at decoding, speed 
optimizations, memory consumption reduction, etc, see http://www.openjpeg.org/
2017/08/10/OpenJPEG-2.2.0-released for details), this release adds improvement to sub-tile 
decoding.

Now when you handle a huge single tile image and only wants to decode a small part of it, 
only the window of interest is actually processed: sounds quite natural but I can ensure it 
wasn't that easy to implement. This leads to drastic speed and memory improvements as 
they now only depend on the size of the window and not on the original image size. This 
release also adds the ability to decode only a subset of components.

Overall, if we compare performances of OpenJPEG before all Even's optimizations (v2.1.2) 
and the ones reached by the new v2.3.0 release, we observe a 55-60% speed improvement on 
a single thread whole image decoding (even more on big images like 10000x10000). Memory 
consumption is also drastically reduced on mega-image decoding: for example, for a full 
decoding of a single tile 8000x12000 image, it is reduced from 2 to 1.3 GB RAM. But more 
importantly, OpenJPEG is now a workable solution for workflows involving partial decoding.

Benchmarks are hard to compare as there are many variables that can influence the results: 
so if you are an OpenJPEG user, please download and try this new release within your 
workflow ... And share your feedback, that would be highly appreciated.

As indicated above and described in a previous post (https://groups.google.com/d/msg/
openjpeg/CltNQpbbwm4/jajpDKq0AAAJ), all this has been made possible thanks to a 
funding from academic institutions and archival organizations, namely:
- Wellcome Library
- Stanford University
- Nationale Bibliotheek van Nederland (KBNL)
- University of Michigan
- University of California, Los Angeles (UCLA)

… And logistic support from the International Image Interoperability Framework (IIIF), the 
Council on Library and Information Resources (CLIR), intoPIX, and of course the Image and 
Signal Processing Group (ISPGroup) from University of Louvain (UCL, Belgium) hosting the 
OpenJPEG project. Thanks to all of them !

Many thanks also to Even Rouault, the developper who actually implemented these 
improvements, and of course to all contributors having suggested fixes or enhancements.

Enjoy,

Antonin

More info:
News: https://github.com/uclouvain/openjpeg/blob/v2.2.0/NEWS.md
Changelog: https://github.com/uclouvain/openjpeg/blob/v2.2.0/CHANGELOG.md
Full Changelog: https://github.com/uclouvain/openjpeg/compare/v2.1.2...v2.2.0

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OpenJPEG is mainly supported by : 
* UCL Image and Signal Processing Group (http://sites.uclouvain.be/ispgroup) 
* IntoPIX (www.intopix.com)

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