RZM <[email protected]> wrote:
> 
> Thanks Jordi,
>
> using the ram option did, indeed, help to eliminate the stripes (but i still 
> get a blank image. well an image with a single value).
> we can not use BandMath because we want to convert 100+ images and do not 
> know their min and max values a priori.
>

You can use the ComputeImageStatistics application to generate an xml
(horror!) file with mean and std. You can then parse this with some
python to generate the BandMath expression.

However, if you know that you have NDVI values, you may consider
applying the same rescaling to all images.

Jordi

> On Wed, Dec 16, 2015 at 2:32 PM, Jordi Inglada <[email protected]> 
> wrote:
>
>
>  Raul ZM <[email protected]> wrote:
>  >
>  > Hi there,
>  >
>  > we are trying to transform a float32 tiff image into a uint8 (so from 
> decimals to the interval 0 to 255).
>  > For this we have tested Convert:
>  > olbcli_Convert -in file1.tiff -out file2.tif uint8 -type linear (btw, what 
> would be type "none"?)
>  >
>  > and Rescale:
>  > otbcli_Rescale -in file1.tiff -out file2.tif uint8 -outmin 0 -outmax 255 
> (also tried without the last three parameters as these are the default values)
>  >
>  > in both cases we get blank images or an stripped image that has nothing to 
> do with the original file.
>  > Any idea/suggestion of what might be going on?
>  >
>
>  Hi,
>
>  Images with stripes can appear due to streaming (or multi-threading, I
>  am not sure) because the min/max values for the input image are not
>  computed globally. I guess that you can avoid that by using the -ram
>  option for streaming.
>
>  But if you know the range of your input image, the easiest is to use the
>  BandMath application to do the operation and choose the output pixel
>  value:
>
>  otbcli_BandMath -il float.tif -out rescaled.tif uint8 -exp 
> "(im1b1-min)/(max-min)*255"
>
>  If you have several bands, you will have to adapt the expression.
>
>  Jordi
>
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