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Remote modules allow anyone to extend the functionalities of OTB without being part of the core project repository. Remote modules can have different licenses than the main OTB repository.
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Remote modules allow anyone to extend the functionalities of OTB without being part of the core project repository. Those modules can have different licenses than the main OTB repository.
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To start hacking on your own remote module, you can start by forking the [remote module template](https://gitlab.orfeo-toolbox.org/remote_modules/remote-module-template).
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## Official remote modules
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"Official" remote modules are just regular remote modules that we consider particularly useful for users. Some of those are shipped in the [binary packages](https://www.orfeo-toolbox.org/Download/) so you don't need to build them yourself.
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### DiapOTB
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https://gitlab.orfeo-toolbox.org/remote_modules/diapotb <br>
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*License*: Apache License 2.0
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The differential SAR interferometry (DInSAR) technique relies on the processing of two SAR images of the same portion of the Earth’s surface taken at different time. The aim is to analyze potential events (earthquake, destruction, …) by highlighting differences between SAR images. DInSAR involves a set of tools such as creation of deformation grids , coregistration or building of interferograms.
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The Orfeo Toolbox remote module DiapOTB contains all necessary steps and allows to launch a complete DInSAR chain. This module has been used with Sentinel-1 data with satisfactory results.
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This module is a port from DIAPASON tool, integrated in the [ESA GeoHazards TEP](http://terradue.github.io/doc-tep-geohazards/tutorials/diapason-sm.html).
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### otb-mosaic - Image mosaiking
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https://github.com/remicres/otb-mosaic <br>
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*Author*: Rémi Cresson <br>
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*License*: CeCILL-B
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This module provides one application dedicated to images mosaicking with several compositing methods available.
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**This module is now part of OTB since version 7.0.0**
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### otb-bv - Estimation of bio-physical variables with OTB
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http://tully.ups-tlse.fr/jordi/otb-bv/tree/master <br>
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*Author*: Jordi Inglada <br>
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*License*:
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The otb-bv project allows for estimation of biophysical variables (LAI, fAPAR, fCover) from optical imagery using machine learning nonlinear regressions for the inversion of PROSPECT+SAIL.
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### otbFFSforGMM - Large-scale feature selection with Gaussian mixture models
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https://github.com/Laadr/otbFFSforGMM <br>
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*Author*: Adrien Lagrange <br>
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*License*: Apache
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This module implements a method to perform a fast forward feature selection using a Gaussian Mixture Model for the classification of high dimensional remote sensing images. The algorithm is describes in the following paper https://hal.archives-ouvertes.fr/hal-01382500.
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### GRM - Generic region merging segmentation
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http://tully.ups-tlse.fr/lassallep/grm/tree/master <br>
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*Author*: Pierre Lassalle <br>
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*License*:
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This module provides the GRM OTB application to perform multi-scale region-merging segmentation on satellite images. Three local homogeneity criteria are available: the Baatz & Schäpe criterion, the Full Lambda Schedule criterion and the simple Euclidean Distance criterion. This module was contributed by Pierre Lassalle who also provides a [tutorial](http://pierre33.github.io/tutorials/grm_tuto.html) to learn how to use the library.
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### SertitObject - Object oriented image analysis
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https://github.com/sertit/SertitObject <br>
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*Author*: SERTIT - University of Strasbourg <br>
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*License*: CeCILL-B
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This module provides two OTB applications dedicated to object-oriented image analysis.
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### Phenotb
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http://tully.ups-tlse.fr/jordi/phenotb.git <br>
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*Author*: Jordi Inglada <br>
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*License*: GNU Affero General Public License v3.0
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This module implements several algorithms allowing to extract phenological information from time profiles. These time profiles should represent vegetation status as for instance NDVI, LAI, etc.
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### Temporal gap-filling
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http://tully.ups-tlse.fr/jordi/temporalgapfilling.git <br>
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*Author*: Jordi Inglada <br>
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*License*: GNU Affero General Public License v3.0
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This module provides classes and one application to perform for temporal gap-filling in image time series (linear and spline interpolators are provided).
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## Community remote modules
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### Feature selection
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https://github.com/boussaffawalid/FeatureSelection <br>
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*Author*: Walid Boussafa and Nesrine Chehata <br>
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*License*:
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This module contains a FeatureSelection application based on the [FST3Lib](http://fst.utia.cz/).
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### GKSVM - Generic kernel SVM
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https://github.com/jmichel-otb/GKSVM <br>
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*Author*: Julien Michel <br>
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*License*:
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GKSVM contains a modified version of libsvm to support generic kernels, as well as a set of Orfeo ToolBox classes to use them. This code once belonged to Orfeo ToolBox source code, but has been removed to enforce the new third party policy (no modified third party in source code). Code has been turned into a legacy remote module.
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### otbtf - OTBTensorflow
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https://gitlab.irstea.fr/remi.cresson/otbtf <br>
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*Author*: Rémi Cresson <br>
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*License*: Apache License 2.0
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This remote module of the [Orfeo ToolBox](https://www.orfeo-toolbox.org) provides a generic, multi purpose deep learning framework, targeting remote sensing images processing. It contains a set of new process objects that internally invoke [Tensorflow](https://www.tensorflow.org/), and a bunch of user-oriented applications to perform deep learning with real-world remote sensing images. Applications can be used to build OTB pipelines from Python or C++ APIs. |
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For more information, see the [CookBook](https://www.orfeo-toolbox.org/CookBook-develop/RemoteModules.html) |
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