diff --git a/Documentation/Cookbook/rst/Recipes.rst b/Documentation/Cookbook/rst/Recipes.rst
index 9176933737d34b1598b1b27d5c15362e31193aaf..3fa97fbe6f6dab3835a060d32976e3db44c59074 100644
--- a/Documentation/Cookbook/rst/Recipes.rst
+++ b/Documentation/Cookbook/rst/Recipes.rst
@@ -10,8 +10,6 @@ future needs.
.. toctree::
:maxdepth: 6
-
- recipes/pleiades.rst
recipes/optpreproc.rst
recipes/sarprocessing.rst
recipes/residual_registration.rst
diff --git a/Documentation/Cookbook/rst/recipes/optpreproc.rst b/Documentation/Cookbook/rst/recipes/optpreproc.rst
index af48ae8d5183d0bb62060c95cf1b7d1b10e1357d..70fc1a0d4b9593f05c93aa92ec8fc47284468bd0 100644
--- a/Documentation/Cookbook/rst/recipes/optpreproc.rst
+++ b/Documentation/Cookbook/rst/recipes/optpreproc.rst
@@ -63,9 +63,6 @@ sensors are :
- Formosat
-Optical calibration with **OTB Applications**
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
The *OpticalCalibration* application allows to perform optical
calibration. The mandatory parameters are the input and output images.
All other parameters are optional. By default the level of calibration
@@ -84,40 +81,6 @@ A basic TOC calibration task can be performed with the following command:
otbcli_OpticalCalibration -in input_image -out output_image -level toc
-Optical calibration with **Monteverdi**
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-These transformations can also be done in **Monteverdi** .
-
-The 6S model needs atmospheric parameters to be able to compute
-radiative terms to estimate the atmospheric contributions on the input
-signal. Default parameters are available in the module. For atmospheric
-parameters, it is possible to indicate AERONET file. The AERONET
-(AErosol RObotic NETwork) program is a federation of ground-based remote
-sensing aerosol networks established by NASA and PHOTONS (Univ. of Lille
-1, CNES, and CNRS-INSU) and is greatly expanded by collaborators from
-national agencies, institutes, universities, individual scientists, and
-partners. The program provides accessible public domain database of
-aerosol optical, mircrophysical and radiative properties.
-
-The module produces four outputs:
-
-- Luminance image.
-
-- TOA reflectance image.
-
-- TOC reflectance image.
-
-- Difference TOA-TOC image, which allows to get the estimation of
- atmospheric contribution.
-
-.. figure:: ../Art/MonteverdiImages/monteverdi_optical_calibration.png
-
- Figure 1 : Optical calibration module.
-
-.. figure:: ../Art/MonteverdiImages/monteverdi_optical_calibration_outputs.png
-
- Figure 2 : Optical calibration module’s outputs.
Pan-sharpening
--------------
@@ -165,9 +128,6 @@ Using either **OTB Applications** or modules from **Monteverdi** , it is
possible to perform both steps in a row, or step-by-step fusion, as
described in the above sections.
-Pan-sharpening with **OTB Applications**
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
The *BundleToPerfectSensor* application allows to perform both steps in
a row. Seamless sensor modelling is used to perform zooming and
registration of the multi-spectral image on the panchromatic image. In
@@ -226,38 +186,10 @@ Increasing the available amount of RAM may also result in better
computation time, seems it optimises the use of the system resources.
Default value is 256 Mb.
-Pan-sharpening with **Monteverdi**
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-**Monteverdi** allows to perform step-by-step fusion. The followings
-screenshots highlight operations needed to perform Pan-Sharpening.
-
-- Open panchromatic and multispectral images in monteverdi using the
- *Open Dataset* module or using the ``-il`` option of the
- **Monteverdi** executable.
-
-- The *Superimpose* module is used to zoomed and registered the
- multispectral on the panchromatic image. As a result, we get a
- multispectral dataset with the same geographic extension and the same
- resolution as the panchromatic image, cf  [fig:qbmulsuper].
-
-.. figure:: ../Art/MonteverdiImages/monteverdi_QB_PAN_ROI.png
-
-
-
-.. figure:: ../Art/MonteverdiImages/monteverdi_QB_MUL_Superimpose.png
-
- Figure 4 : Panchromatic, Zoomed, and registered multispectral image.
-
-
-- Now the *Simple RCS pan-sharpening* module can be used using the
- panchromatic and the multispectral images as inputs. It produces a
- multispectral image with the same resolution and geographic extension
- (cf `Figure 5`).
.. figure:: ../Art/MonteverdiImages/monteverdi_QB_XS_pan-sharpened.png
- Figure 5 : Pan-sharpened image using the simple RCS module.
+Figure 5 : Pan-sharpened image using Orfeo ToolBox.
Please also note that since registration and zooming of the
multi-spectral image with the panchromatic image relies on sensor
diff --git a/Documentation/Cookbook/rst/recipes/pleiades.rst b/Documentation/Cookbook/rst/recipes/pleiades.rst
deleted file mode 100644
index 14b7e034f85736c821bb25ab933d89b5bf13ed81..0000000000000000000000000000000000000000
--- a/Documentation/Cookbook/rst/recipes/pleiades.rst
+++ /dev/null
@@ -1,283 +0,0 @@
-Using Pleiades images in OTB Applications and Monteverdi
-========================================================
-
-The typical `Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_
-product is a pansharpened image of 40 000 by 40 000 pixels large, with 4
-spectral bands, but one can even order larger mosaics, whose size can be
-even larger, with hundreds of thousands of pixels in each dimension.
-
-To allow easier storage and transfer of such products, the standard
-image file format is
-`Jpeg2000 <http://en.wikipedia.org/wiki/JPEG_2000>`_ , which allows to
-achieve high compression rates. The counterpart of these better storage
-and transfer performances is that the performance of pixels accesses
-within those images may be poorer than with an image format without
-compression, and even more important, the cost of accessing pixels is
-not uniform: it depends on where are the pixels you are trying to
-access, and how they are spatially arranged.
-
-To be more specific,
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ images are
-internally encoded into 2048 per 2048 pixels tiles (within the
-`Jpeg2000 <http://en.wikipedia.org/wiki/JPEG_2000>`_ file). These tiles
-represent the atomic decompression unit: if you need a single pixel from
-a given tile, you still have to decode the whole tile to get it. As a
-result, if you plan to access a large amount of pixels within the image,
-you should try to access them on a per tile basis, because anytime you
-ask for a given tile more than once, the performances of your processing
-chains drop.
-
-What does it mean? In Orfeo Toolbox , the streaming (on the flow)
-pipeline execution will try to stay synchronised with the input image
-tiling scheme to avoid decoding the same tile several time. But you may
-know that in the Orfeo Toolbox world, one can easily chain numerous
-processing, some them enlarging the requested region to process the
-output - like neighbourhood based operators for instance - or even
-completely change the image geometry - like ortho-rectification for
-instance. And this chaining freedom is also at the heart of
-Monteverdi . In short, it is very easy to build a processing
-pipeline in Orfeo Toolbox or chain of modules in Monteverdi that
-will get incredibly bad performances, even if the Orfeo Toolbox
-back-end does its best to stay in tune with tiles. And here, we do not
-even speak of sub-sampling the whole dataset at some point in the
-pipeline, which will lead to even more incredibly poor performances, and
-is however done anytime a viewer is called on a module output in
-Monteverdi .
-
-So, can Monteverdi or OTB Applications open and process
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ images?
-Fortunately yes. Monteverdi even takes advantage of
-`Jpeg2000 <http://en.wikipedia.org/wiki/JPEG_2000>`_ ability to
-generate coarser scale images for quick-look generation for
-visualisation purposes. But to ease the use of
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ images in
-Monteverdi , we chose to open them in a separate data type, and to
-lock the use of most of modules for this data type. It can only be used
-in the Viewer module and a dedicated module allowing to uncompress a
-user-defined part of a
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ image to disk. One
-can still force the data type during the opening of the image, but this
-is not advised: the advised way to use the other modules with
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ data is to first
-uncompress to disk your area of interest, and then open it again in
-Monteverdi (careful, you may need a lot of disk space to do this).
-As for the applications, they will work fine even on
-`Jpeg2000 <http://en.wikipedia.org/wiki/JPEG_2000>`_
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ data, but keep in
-mind that a performance sink might show depending on the processing you
-are try to achieve. Again, the advised way of working would be to
-uncompress your area of interest first and then work with the
-uncompressed file, as you used to with other data.
-
-A final word about metadata: OTB Applications and Monteverdi can
-read the Dimap V2 (note that we also read the less non-official Dimap
-V1.1 format) metadata file associated with the
-`Jpeg2000 <http://en.wikipedia.org/wiki/JPEG_2000>`_ file in the
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ product. It reads
-the RPC localisation model for geo-coding and the information needed to
-perform radiometric calibration. These metadata will be written in an
-associated geometry file (with a *.geom* extension) when uncompressing
-your area of interest to disk, so that both Monteverdi and OTB
-Applications will be able to retrieve them, even for images extracts.
-
-.. _section1:
-
-
-Opening a `Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ image in Monteverdi
-----------------------------------------------------------------------------------------
-
-Opening a `Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ image in
-Monteverdi is not different from opening other kind of dataset: use
-the *Open Dataset* item from the *File* menu, and select the JP2 file
-corresponding to you image using the file browser.
-
-
-.. figure:: ../Art/MonteverdiImages/pleiades_open.png
-
- Figure 1 : Dialog window when opening a Pleiades image in Monteverdi
-
-.. figure:: ../Art/MonteverdiImages/pleiades_monteverdi.png
-
- Figure 2 : Pleiades images in the main Monteverdi window
-
-
-`Figure 1` shows the dialog box when opening a `Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_
-image in Monteverdi . One can see some changes with respect to
-the classical dialog box for images opening.
-The first novelty is a combo box allowing to choose the resolution of
-the `Jpeg2000 <http://en.wikipedia.org/wiki/JPEG_2000>`_ file one wants
-to decode. As said in the introduction of this section, Orfeo
-Toolbox can take advantage of
-`Jpeg2000 <http://en.wikipedia.org/wiki/JPEG_2000>`_ capability to
-access coarser resolution ver efficiently. If you select for instance
-the *Resolution: 1* item, you will end with an image half the size of
-the original image with pixels twice as big. For instance, on a
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ panchromatic or
-pansharpened product, the *Resolution: 0* image has a ground samping
-distance of 0.5 meters while the *Resolution: 1* image has a ground
-samping distance of one meter. For a multispectral product, the
-*Resolution: 0* image has a ground samping distance of 2 meters while
-the *Resolution: 1* image has a ground samping distance of 4 meters.
-
-The second novelty is a check-box called *Save quicklook for future
-re-use*. This option allows to speed-up the loading of a
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ image within
-Monteverdi . In fact, when loading a
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ image,
-Monteverdi generates a quicklook of this image to be used as a
-minimap in the *Viewer Module* as well as in the *Uncompress Jpeg2000
-image* module. This quicklook is the coarser level of resolution from
-the `Jpeg2000 <http://en.wikipedia.org/wiki/JPEG_2000>`_ file: it
-should decode easily, but can still take a while. This is why if the
-check-box is checked, Monteverdi will write this quicklook in
-uncompressed *Tiff* format next to the
-`Jpeg2000 <http://en.wikipedia.org/wiki/JPEG_2000>`_ file. For
-instance, if the file name is:
-
-::
-
- IMG_PHR1A_MS_201204011017343_SEN_IPU_20120529_1596-002_R1C1.JP2
-
-Monteverdi will write, if it can, the following files in the same
-directory:
-
-::
-
- IMG_PHR1A_MS_201204011017343_SEN_IPU_20120529_1596-002_R1C1.JP2_ql_by_otb.tif
- IMG_PHR1A_MS_201204011017343_SEN_IPU_20120529_1596-002_R1C1.JP2_ql_by_otb.geom
-
-Next time one will try to open this image in Monteverdi , the
-application will find these files and load directly the quicklook from
-them, instead of decoding it from the
-`Jpeg2000 <http://en.wikipedia.org/wiki/JPEG_2000>`_ file, resulting in
-an instant loading of the image in Monteverdi . Since the wheight of
-these extra files is ususally of a few megaoctets, it is recommended to
-keep this option checked unless one has a very good reason not to. Now
-that the `Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ image is
-loaded in Monteverdi , it appears in the main Monteverdi window,
-as shown in `Figure 2`.
-
-Viewing a `Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ image in Monteverdi
-----------------------------------------------------------------------------------------
-
-You can open the `Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_
-image in the viewer, either by using the contextual menu or by opening
-the *Viewer Module* through the menu bar.
-
-You can notice that the viewer opens quickly without showing the
-traditional progress bar. This is because Monteverdi already loaded
-the quick-look upon opening, and we do not need to re-compute it each
-time the image is opened in the *Viewer Module*.
-
-.. figure:: ../Art/MonteverdiImages/pleiades_viewer.png
-
- Figure 3 : A Pleiades image displayed in Monteverdi viewer. (c) CNES 2012
-
-`Figure 3` shows a `Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ image displayed in
-the *Viewer Module*. One can notice that the navigation experience is
-rather smooth. If you navigate using arrows keys, you will notice that
-latency can occur now and then: this is due to the viewport switching to
-a new `Jpeg2000 <http://en.wikipedia.org/wiki/JPEG_2000>`_ tile to
-decode. On can also observe that the latitude and longitude of the pixel
-under the mouse pointer is displayed, which means that the sensor
-modelling is handled (if you have an internet connection, you may even
-see the actual name of the place under mouse pointer). Last, as said in
-the foreword of this section,
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ image can be quite
-large, so it might be convenient to switch the viewer style from
-*Packed* to *Splitted*, in which case you will be able to maximize the
-*Scroll Window* for better localisation of the viewed area. To do so,
-one can go to the *Setup* tab of the *Viewer Control Window*.
-
-Handling mega-tiles in Monteverdi
---------------------------------------
-
-If the `Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ product is
-very large, it might happen that the image is actually splitted into
-several `Jpeg2000 <http://en.wikipedia.org/wiki/JPEG_2000>`_ files,
-also called mega-tiles. Since the area of interest might span two or
-more mega-tiles, it is convenient to stitch together these tiles so as
-to get the entire scene into one Monteverdi dataset. To do so, one
-must first open all mega-tiles in Monteverdi , as described in :ref:`section1`.
-Once all mega-tiles are opened as shown in `Figure 1`
-
-Once this is done, one can use the *Mosaic Images module* from the
-*File* menu. Simply append all mega-tiles into the module and run it:
-the module will look for the :math:`RiCj` pattern to determine the
-mega-tiles layout, and will also check for consistency, e.g. missing
-tiles or mega-tiles size mismatch. Upon success, it generates a new
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ image dataset,
-which corresponding to the entire scene, as shown in `Figure 4`. One can
-then use this dataset as a regular
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ dataset.
-
-.. figure:: ../Art/MonteverdiImages/pleiades_mtiles_open.png
-
-Figure 4: Pleiades mega-tiles and output mosaic in Monteverdi
-
-Partial uncompressing of `Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ images in Monteverdi
---------------------------------------------------------------------------------------------------------
-
-The next very important thing one can do with Monteverdi is to
-select an area of interest in the
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ image so as to
-uncompress it to disk. To do so, open the
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ dataset into the
-*Uncompress Jpeg2000 image module* from the *File* menu.
-
-.. figure:: ../Art/MonteverdiImages/pleiades_uncom.png
-
-Figure 5: A Pleiades image in Monteverdi Uncompress Jpeg2000 image module. (c) CNES 2012
-
-`Figure 5` shows what this module looks like. On the left, one can find
-informations about the images dimensions, resolution level, and number of
-`Jpeg2000 <http://en.wikipedia.org/wiki/JPEG_2000>`_ tiles in image,
-dimension of tiles, and size of tiles in mega-octets. The center part of
-the module is the most important one: it displays a quick-look of the
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ image. On this
-quick-look, one can select the area to be decoded by drawing a rectangle
-with the mouse. The red rectangle shown by the module corresponds to
-this user-defined area. On the left, in red, one can find the start
-index and size of corresponding region.
-
-The module also displays a green rectangle, which shows the minimum set
-of tiles to be decoded to decode the red area: this is the region that
-will actually be decoded to disk. On the left, in green, one can find
-information about this region: how many tiles it contains, and what will
-be the size of the corresponding decoded output file.
-
-Once one chose her area of interest, one can click on the *Save* button,
-and select an output file. The module will write a geometry file (with
-the *.geom* extension) with all useful metadata in it, so that when
-reading back the file in Monteverdi or in OTB Applications ,
-geometry and radiometry based functionalities can still be used.
-
-
-Other processing of `Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ images with Monteverdi
------------------------------------------------------------------------------------------------------
-
-For all the reasons exposed in the foreword of this section, we do not
-allow to use directly
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ images in the
-remaining of Monteverdi modules: the advised way of doing so is to
-first uncompress the area of interest to disk.
-
-Processing of `Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ images with OTB Applications
------------------------------------------------------------------------------------------------------
-
-The OTB Applications are able to work directly with
-`Pleiades <http://smsc.cnes.fr/PLEIADES/index.htm>`_ images. However,
-keep in mind that performances may be limited due to the reasons exposed
-in the foreword of this section. If you experiment poor performances
-with some application, try to uncompress the area of interest from your
-image with Monteverdi first. One can also use the *ExtractROI*
-application for this purpose.
-
-One thing that is interesting to know is that one can access the coarser
-resolution of the `Jpeg2000 <http://en.wikipedia.org/wiki/JPEG_2000>`_
-file by appending :math:`:i` to the filename, where :math:`i` is the
-resolution level starting at 0. For instance, one can use the following:
-
-::
-
- otbcli_ExtractROI -in IMG_PHR1A_PMS_201201151100183_SEN_IPU_20120222_0901-001_R2C1.JP2:5 -out test.tif uint16