[Qgis-developer] min/max for rasters

[aperi2007]

AFAIK

The strategy of 2-98 is usually useful when there a "noised image", 
because we assume that the noise is a white noise and it
is randomized an isolated spikes.

THis is absolutely a right theory and really useful,
ma what kind of imagge are usually used in a gis system.

If we think at the ortophoto image the noise could be really happened 
because they came from a photo-sensor.

But is we think to a artificial image, like the 2-colors balck-white 
images named "carta tecnica" thata are trasposition of vectorial data.
Them are no noised images and has a really thin lines. Also the 
artifical thematic chars with colors and point and symbols and lines 
(outline and so on) are noise-less images.
Don't forget to think also to geological charts. Are all noise-less images.

So what kind of image are more used in a GIS system ?

This is not simple question.
The response is , "it is dependent by the kind of work you should do.".

But also another question is:
Usually the ortophoto are not simple to have . They are produced and 
have a license.
The thematic images are more easy to produce and are often without a 
license or has a free license.

More often the ortophoto images are available from a WMS system, and 
this is a solution that deny the use of the 2-98 strategy.

Andrea.

On 14/12/2013 07:17, Paolo Cavallini wrote:
> Il 13/12/2013 20:18, Radim Blazek ha scritto:
>
>>> Can you describe some examples where 2-98% is a problem (data type,
>>> number of bands, map content, features/phenomena represented by those
>>> 2+2%,...) so that we can think about it better?
> Example #1 (less problematic): dtm and their legend are always shown
> wrong; newbies do not understand why
> Example #2 (more serious): rasterizing sparse vectors (e.g. rivers)
> results in a black rectangle, as the number of pixels with valid data is
> <2%.
>
> In fact, I think we should help users more, e.g. by applying non linear
> colour scaling (log, exp)  in case of very skewed raster values
> distribution: if data are more or less normally distributed, no cut is
> applied, and linear scaling is used; if they are badly skewdw or with
> outliers, apply a non linear colour scaling. With some thinking, this
> should solve most if not all user cases, without asking a normal user to
> understand much about raster stats.
>
> However, in my case the general setting "use min/max" does not seem to
> be working.
> Thanks for your thoughts.
>