[SciPy-User] Large Memory usage while doing median filter

[Juan Nunez-Iglesias]

If you can cast your image as a uint8 image, try the median filter in scikit-image's filters.rank module. It's very fast and has a minimal memory footprint. But it doesn't work on floats or high ints. 



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On Mon, May 11, 2015 at 3:25 PM, Jerome Kieffer <Jerome.Kieffer at esrf.fr>
wrote:

> On Mon, 11 May 2015 00:56:29 +0530
> Joe P Ninan <indiajoe at gmail.com> wrote:
>> Hi,
>> I was trying median_filter in scipy.ndimage.filters
>> on a 1024x1024 array.
>> 
>> What I noticed is that the memory requirement grows really fast when we
>> increase the size of the median filter.
>> On a machine with 6gb RAM I could do only (150,150) size filter.
>> Anything above gives Memory Error.
>> 
>> On a bigger server I could see it takes about 16gb RAM while using a filter
>> size (200, 200)
>> 
>> I can understand, computation time increasing with size of filter, but why
>> is the memory size exploding with respect to size of the median filter?
>> Is this expected behaviour?
> I guess this is because scipy creates a 1024x1024x(40000) array to do the sort along the last axis.
> maybe no the best from the memorry point of view.
> Cheers,
> -- 
> Jérôme Kieffer
> Data analysis unit - ESRF
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