For what it's worth, I like the plan.
Improving current code, making it shareable between multiple parts of the
codebase by pushing back to JAI-Ext....

It will be nice to have in the SLDService.

Regards,
Simone Giannecchini
==
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Visit http://goo.gl/it488V for more information.
==
Ing. Simone Giannecchini
@simogeo
Founder/Director

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On Wed, Nov 14, 2018 at 5:01 PM Andrea Aime <andrea.a...@geo-solutions.it>
wrote:

> Hi,
> I'm looking into extending the GeoServer SLDService API to work against
> raster data too.
> The current code in that module works off the vector classification
> functions for equal intervals, natural breaks and quantiles.
>
> When looking at extending it for rasters, I stumbled into
> the ClassBreaksOpImage and its subclasses, which
> does more or less what I need... with a hitch though: the rasters that I'm
> playing with can be large and have floats/doubles
>
> Looking at the implementation for quantilies and natural breaks I've
> noticed that all input values get collected
> either in a List<Double> or a Map<Double, Integer>, where the doubles are
> the values and the integer is a pixel count.
> Mind, this is the same as vector code is doing, but getting to a million
> of those in raster space only requires a 1000x1000
> image... and millions of double values (or map entries) take up a lot of
> space. I could look into using non boxed
> variants, but the issue is not really that one, it's just that keeping
> track of all values requires too much space.
>
> So I'd like to add an approximate calculator instead that collects
> histograms, and the works off the result applying the
> same logic as today. Ideally, these would be new entries in
> the ClassificationMethod enumeration, say
> QUANTILE_HISTOGRAM and NATURAL_BREAKS_HISTOGRAM, and ClassBreaksOpImage
> would have an
> extra optional parameter to decide the bucket count (with some reasonable
> defaults, e.g. 256 for byte data,
> 1000 for any other type).
> Working off histograms has a clear benefit, the size of the working memory
> is fixed at the start, and it's possible
> to use primitives in the data structure, of course it also means the
> resulting classification won't be exact, but
> should be close enough.
> The downside is that the min/max values need to be known in advance to
> build the buckets, so for the histogram
> based methods the "extrema" parameter in the ClassBreaksOpImage will be
> mandatory (exception thrown if not provided).
>
> How does that sound?
>
> Cheers
> Andrea
>
> PS: most operations are in jai-ext, mind if the ClassBreaksOpImage gets
> moved there, in its own module?
>
> --
>
> Regards, Andrea Aime == GeoServer Professional Services from the experts!
> Visit http://goo.gl/it488V for more information. == Ing. Andrea Aime
> @geowolf Technical Lead GeoSolutions S.A.S. Via di Montramito 3/A 55054
> Massarosa (LU) phone: +39 0584 962313 fax: +39 0584 1660272 mob: +39 339
> 8844549 http://www.geo-solutions.it http://twitter.com/geosolutions_it
> ------------------------------------------------------- *Con riferimento
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