[OSGeo-Announce] Orfeo ToolBox 6.4 is out!

[Jorge Sanz]

Dear all,

We are pleased to announce that Orfeo ToolBox 6.4.0 is out !

As usual, ready-to-use binary packages
<https://www.orfeo-toolbox.org/download/> are available for Windows, Linux
and Mac OS X:

You can also checkout the source directly with git:

git clone https://git@git.orfeo-toolbox.org/git/otb.git OTB -b release-6.4

We welcome your feedback and requests, and encourage you to join the OTB
community and mailing list
<https://groups.google.com/forum/?hl=fr#%21forum/otb-users/join>. If you
think you face a bug, please report it. <https://bugs.orfeo-toolbox.org>

There is  a lot of new things
<https://wiki.orfeo-toolbox.org/index.php/Requests_for_Changes#OTB-6.4.0>
in this first version for 2018. In addition, a total of 22 reported bugs
have been fixed. You can check the Release Notes
<https://git.orfeo-toolbox.org/otb.git/blob/refs/heads/release-6.4:/RELEASE_NOTES.txt>
for
details.
Satellite image is art!

OTB  6.4 features new filters and application to perform Adaptative
Histogram Equalization
<https://en.wikipedia.org/wiki/Adaptive_histogram_equalization>. It allows
to convert raw satellite images to colorful 8-bit visual product in a very
efficient and flexible way! Here’s a quick demo on a Sentinel-2 image:
[image: Original Sentinel-2 image][image: Equalizing in luminance (contrast
limitation set to 20)]


Check this blog post
<http://www.orfeo-toolbox.org/contrast-enhancement-for-fun-and-profit/> for
more information.
Support of Python 3

OTB is now fully compatible with both Python 2 and Python 3. Python3
wrappings can now be enabled during configuration with the OTB_WRAP_PYTHON3
CMake option. Standalone binary packages now provide both Python wrappings,
for Python versions 2.7 and 3.5. Note that older 3.x versions are not
guaranteed to work with those packages.
New packaged remote modules

Remote module temporal-gapfilling  for image time series
<http://tully.ups-tlse.fr/jordi/temporalgapfilling> has been added to the
list of packaged remote modules.  It provides filters and application to
replace invalid pixels (as designated by a mask) in a time series by
interpolating valid dates of the series. This application is used in the
iota2 processing chain which generates annual Land Cover Map on France
<https://www.theia-land.fr/en/products/land-cover-map> using Sentinel-2
images and is now directly available in OTB binary packages.
Welcome to Laurențiu Nicola

We have a new official OTB committer! Welcome to Laurentiu Nicola from
Cracovia, Romania. Laurentiu is a highly skilled C++ developer who has
already provided his expertise on several occasions to improve OTB code,
especially regarding performances and profiling.  His first contribution as
an official committer  improves the performances of time monitoring probes
in OTB, see RFC 120
<https://wiki.orfeo-toolbox.org/index.php/Request_for_changes-120:_Replacing_itk::TimeProbe>
.

So *Welcome Laurentiu*, and thanks again for joining!

We encourage anybody interested to get more involved in OTB to join
discussions and become part of the team.
Migration to Gitlab

Now that 6.4 is released we are ready to move OTB infrastructure to GitLab,
a web-based Git repository manager with wiki and issue tracker, as decided
during our last PSC meeting. GitLab will allow us to have a single entry
point for features, contributions, bugs and task planning. Contributions
will be made easier, as anyone who wishes to contribute will be able to
quickly set-up an account (GitLab even provides sign-in with GitHub), fork
the project and send a merge request. The same goes for bug reporting or
wiki editing, with a single account.

We hope that those easier mechanisms will in turn yield even more
contributions from the Orfeo ToolBox community.

Stay tuned with the OTB mailing list
<https://groups.google.com/forum/?hl=fr#%21forum/otb-users/join> and this
blog for more news related to this migration
<https://wiki.orfeo-toolbox.org/index.php/Moving_to_Gitlab>.

Thanks to everyone who helped during the release process!


OTB Dev Team
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