Hi Léo,

In OTB there is an application to perform basic conversion : otbcli_Convert.

This applications allows to convert the dynamic of an image to an output pixels type (linear and log transform supported). It will compute min/max for each band and stretch this dynamic to the output range of your destination pixel type (i.e. 0-255 for uint8). By default, 2% of the histogram are cut on each side (can be tuned). You can also supply a mask to discard pixels during the histogram computation (can be useful for clouds).

Regards,
Guillaume

On 12/12/2016 04:10 AM, Léo HUERTA wrote:
Hi everybody,

I 'm currently working on Pleiades Datasets, and i would like to perform automatic contrast enhancement and color correction, and i would like to know if anybody know a workflow to do that...
I would like to reproduce a thing like "OVR" from Pleiades Data distributed by Airbus Defense & Space.

I experimented software like Image magick with this kind of code:
convert -monitor -modulate 100,130 -channel R -gamma 1 -channel G -gamma 0.95 -channel B -gamma 0.875 -channel RGB -sigmoidal-contrast 11x40% %OUT%BUNDLE_ORTHO_RGB.TIF -compress lzw %OUT%BUNDLE_ORTHO_RGB_CC.TIF
It's not bad but, i spend lot of time trying to find the correct parameters... And i don't know how to calculate them automatically.

A good software (but not open source) do a thing like that: Spectral discovery (by Geosage, an Australian company), this software perform L8 pre-processing (for data visualisation only): this soft read metada (MTL files, like DIMAP for pleiades), to estimate parameters for stretching, and scaling to produce a good looking L8 RGB tiff. I think it is possible to do that with the dimap but i don't know how...

I have read a good paper about color correction for sat imagery:
An Inquiry on Contrast Enhancement Methods for Satellite Images

They speak about to very good algo: MSR (Multi Scale Retinex) and LCC (Local Color Correction), but i don't know how to aplly them on my Pleiades dataset.


If anyone want to share about contrast enhancement and color correction, i am very happy to share my ressource.

Thank you for your time

Léo



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