On Wed, Aug 12, 2015 at 7:58 PM, Rémi Cresson <[email protected]> wrote:

> Hello Rashad,
>
> Thank you for testing it.
> I made the changes you suggest, except I put sources in include folder
> (instead of src).
>

yes that is correct. it was my bad mentioning src if you dont have .cxx in
library


> I had to read the dashboard output, because it compiled fine on my system
> without any error...
>

I have the new build without errors. But however tests are failing. But
that can be fixed easily. Have a look at -
http://dash.orfeo-toolbox.org/testDetails.php?test=32229576&build=195008

For doxygen, it is required to mention the ingroup in the header as doxygen
comments.


Dasboard submission:
http://dash.orfeo-toolbox.org/testDetails.php?test=32229575&build=195008



you have test images which is now in test folder. But usually OTB keeps all
baseline and example data in OTB-Data repository.
 So if you could run the test on some images already existing in OTB-Data,
I think that would be nice. Also I am not sure about adding new baseline
for remote modules which are not official yet.

OTB-Data -https://git.orfeo-toolbox.org/otb-data.git

>
> Waiting for your feedback !
>
> Rémi
>
>
> 2015-08-12 17:15 GMT+02:00 Rashad M <[email protected]>:
>
>> Hi,
>>
>> On Mon, Aug 10, 2015 at 6:56 PM, remicres <[email protected]> wrote:
>>
>>> Hi,
>>>
>>> I've just commited a remote module on GitHub wich deals with image
>>> mosaics generation (https://github.com/remicres/otb-mosaic.git).
>>> Provided are mosaicing filters and one application.
>>> All filters support streaming. The application performs the mosaic
>>> generation of multiple images, whith some color/radiometric harmonization
>>> features, and feathering features (Details are provided above*)
>>>
>>> I hope that you will try and enjoy it. Keep me updated about issues !
>>> Feel free to ask questions, if any.
>>>
>>
>> I tried to setup nightly build for your remote module but didnt work.
>>
>> here is the dasboard output:
>> http://dash.orfeo-toolbox.org/buildSummary.php?buildid=194873
>>
>> From first look,
>>
>> you have all code in app folder include .h and .hxx.
>>
>> but otb remote module needs:
>>
>> all library code in src/*.h *.txx (  .txx is because all other modules
>> use it that way. you need to confirm with someone else in the list)
>>
>> all application code in app/
>>
>> Also please add a file like the below in your git repo.
>>
>> https://github.com/jmichel-otb/GKSVM/blob/master/GKSVM.remote.cmake
>>
>>
>>>
>>> Cheers,
>>>
>>> Rémi
>>>
>>>
>>>
>>>
>>>
>>> * The application:
>>>
>>>    - From a given input images list, a mosaic is produced. The pipeline
>>>    supports streaming, so there is no restriction on images number or size.
>>>    - It implements a color harmonization method explained on our paper:
>>>    Cresson R., Saint-Geours N., "Natural Color Satellite Image Mosaicking
>>>    Using Quadratic Programming in Decorrelated Color Space"IEEE Journal of
>>>    Selected Topics in Applied Earth Observations and Remote Sensing 
>>> (Volume:PP
>>>    ,  Issue: 99) July 2015
>>>    
>>> <http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7154397&filter%3DAND%28p_IS_Number%3A4609444%29>.
>>>    In brief, it performs the global colorimetric harmonization of 
>>> overlapping
>>>    images in natural colors (i.e. input images must have 3 bands, RGB). You
>>>    can set the application parameter "-harmo.method" to "rgb" to use this
>>>    feature. However, the global radiometric harmonization can also be
>>>    performed on each band individually by setting the application parameter
>>>    "-harmo.method" to "band" (it can be useful if the color space is not 
>>> truly
>>>    RGB like raw Spot6/7, or if you want to perform a kind of radiometric
>>>    equalized mosaic). Various statistical cost functions can be used (e.g.
>>>    rmse) to find a correction model (which is linear with zero-y intercept:
>>>    input images are scaled). We have developed a richer harmonization 
>>> solver,
>>>    wich can deal with general linear correction models (i.e. scale, and 
>>> shift
>>>    scale of images) but the maths tools brought by VNL were not sufficient,
>>>    and we had to make use of external libraries to make it work (OOQP,
>>>    QuadProg++). That is why we brought only simple zero-y intercept (i.e.
>>>    scale) correction model in this current module. In future release, I 
>>> think
>>>    we should propose OOQP based (or QuadProg++ based) solver because it is 
>>> far
>>>    more robust than VNL routines (Sometimes VNL's routines throw unexpected
>>>    errors, obviously coming from numerical instabilities). Waiting what will
>>>    be the OTB framework for third parties...
>>>    - As the harmonization method rely of local image statistics, those
>>>    must be exempt from perturbations (e.g. clouds, ice, brutal landcover
>>>    change between two images, ...). That's why it is possible to input some
>>>    vector data to mask valid areas (need one vector data for one input 
>>> image,
>>>    in the same order as appearing in input).
>>>    - It is possible to input some vector data for cutline (need one
>>>    vector data for one input image, in the same order as appearing in 
>>> input).
>>>    - Another cool feature is the feathering/blending of input images,
>>>    which allows to produce seamless mosaics. The current limitation is that 
>>> we
>>>    use a distance map image for each input, computed by
>>>    itk::DanielssonDistanceMapImageFilter wich is not a streamable filter.
>>>    That's why the current process first generates all distance map images in
>>>    temporary .tif files, from resampled input images (the decimation factor
>>>    can be set using the "-alphamasks.spacing"). Then, the filters use these
>>>    previously computed distance map images to perform the 
>>> feathering/blending
>>>    of the input images. At the moment, 2 feathering methods are implemented
>>>    (slim: blends the last image over earlier ones in areas of overlap, on a
>>>    given transition distance / large: blends all images on largests possible
>>>    overlapping areas)
>>>
>>> We tested the application successfully on big images collections:
>>> RapidEye, France coverage from 2011 (~130 images), Spot6/7, France coverage
>>> from 2014 (~190 images), both with a reasonable processing time. Processing
>>> time is o(n) for both mosaic generation and statistics computation
>>> (n=number of input images pixels). Harmonization problem is solved in o(m)
>>> with m=number of input images (about some milliseconds for a hundred of
>>> input images).
>>>
>>> The filters:
>>>
>>>    - otbStreamingMosaicFilterBase: is the base class of all mosaicing
>>>    filters
>>>    - otbStreamingSimpleMosaicFilter: inherits
>>>    otbStreamingMosaicFilterBase, performs simple mosaics with a simple
>>>    compositing technique which copies the last image over earlier ones in
>>>    areas of overlap
>>>    - otbStreamingStatisticsMosaicFilter: inherits
>>>    otbStreamingMosaicFilterBase, computes statistics of the input images in
>>>    each overlapping areas (e.g. mean of image i in overlap j, for all i and 
>>> j)
>>>    - otbStreamingMosaicFilterWithBlendingBase: inherits
>>>    otbStreamingMosaicFilterBase, is the base class for all mosaicing filters
>>>    which use a distance map image (feathering filters...)
>>>    - otbStreamingFeatherMosaicFilter: inherits
>>>    otbStreamingMosaicFilterWithBlendingBase, generates a mosaic with blends
>>>    the last image over earlier ones in areas of overlap, on a given 
>>> transition
>>>    distance
>>>    - otbStreamingLargeFeatherMosaicFilter: inherits
>>>    otbStreamingMosaicFilterWithBlendingBase, blends all images on largests
>>>    possible overlapping areas
>>>    - otbStreamingMultibandFeatherMosaicFilter: inherits
>>>    otbStreamingFeatherMosaicFilter, experimental. Multiband blending of 
>>> input
>>>    image using the laplacian (see Burt & Adelson "A multiresolution spline
>>>    with application to image mosaics"). Could use GPU support for gaussian
>>>    filtering. One need to fix some issues related to side effects (around no
>>>    data pixels of images).
>>>    - otbSummingFilter: utility filter which sums input images.
>>>    - otbQuadraticallyConstrainedSimpleSolver: is the solver used for
>>>    images color/radiometric harmonization. Works only with zero-y intercept
>>>    correction models (as explained before).
>>>
>>> We try to make sense of this multilevel inheritance, but it might be
>>> perfectible !
>>> A possible optimization might be to process every threadedRegion by
>>> subdividing it in multiple smaller regions, in order to loop only on
>>> relevant images: an actual drawback is where the threadedRegion is large,
>>> a lot of input images have to be checked even if they are out of the
>>> region. Another one might be to pre-compute areas where interpolators can
>>> work, instead of checking every processed pixel if the current point is
>>> inside the buffer.
>>> On excellent upgrade would be to strengthen the architecture, and
>>> implements those optimizations in a general way (currently, we have to do
>>> it for each filter... that is why I think this could be better built)
>>>
>>> --
>>> --
>>> Check the OTB FAQ at
>>> http://www.orfeo-toolbox.org/FAQ.html
>>>
>>> You received this message because you are subscribed to the Google
>>> Groups "otb-users" group.
>>> To post to this group, send email to [email protected]
>>> To unsubscribe from this group, send email to
>>> [email protected]
>>> For more options, visit this group at
>>> http://groups.google.com/group/otb-users?hl=en
>>> ---
>>> You received this message because you are subscribed to the Google
>>> Groups "otb-users" group.
>>> To unsubscribe from this group and stop receiving emails from it, send
>>> an email to [email protected].
>>> For more options, visit https://groups.google.com/d/optout.
>>>
>>
>>
>>
>> --
>> Regards,
>>    Rashad
>>
>> --
>> --
>> Check the OTB FAQ at
>> http://www.orfeo-toolbox.org/FAQ.html
>>
>> You received this message because you are subscribed to the Google
>> Groups "otb-users" group.
>> To post to this group, send email to [email protected]
>> To unsubscribe from this group, send email to
>> [email protected]
>> For more options, visit this group at
>> http://groups.google.com/group/otb-users?hl=en
>> ---
>> You received this message because you are subscribed to a topic in the
>> Google Groups "otb-users" group.
>> To unsubscribe from this topic, visit
>> https://groups.google.com/d/topic/otb-users/tXsf0YvarIo/unsubscribe.
>> To unsubscribe from this group and all its topics, send an email to
>> [email protected].
>> For more options, visit https://groups.google.com/d/optout.
>>
>
> --
> --
> Check the OTB FAQ at
> http://www.orfeo-toolbox.org/FAQ.html
>
> You received this message because you are subscribed to the Google
> Groups "otb-users" group.
> To post to this group, send email to [email protected]
> To unsubscribe from this group, send email to
> [email protected]
> For more options, visit this group at
> http://groups.google.com/group/otb-users?hl=en
> ---
> You received this message because you are subscribed to the Google Groups
> "otb-users" group.
> To unsubscribe from this group and stop receiving emails from it, send an
> email to [email protected].
> For more options, visit https://groups.google.com/d/optout.
>



-- 
Regards,
   Rashad

-- 
-- 
Check the OTB FAQ at
http://www.orfeo-toolbox.org/FAQ.html

You received this message because you are subscribed to the Google
Groups "otb-users" group.
To post to this group, send email to [email protected]
To unsubscribe from this group, send email to
[email protected]
For more options, visit this group at
http://groups.google.com/group/otb-users?hl=en
--- 
You received this message because you are subscribed to the Google Groups 
"otb-users" group.
To unsubscribe from this group and stop receiving emails from it, send an email 
to [email protected].
For more options, visit https://groups.google.com/d/optout.

Reply via email to