missing kernel or block size in equalize_adapthist

[Kai Wiechen]

Hi Steve,

yes, I would like to have finer control of block/kernel size to obtain 
similar results if I apply this to small test patches or the larger 
complete image. Is there any reason to limit ntiles_x/y to 16?

Regards,

Kai

Am Mittwoch, 27. Mai 2015 03:17:01 UTC+2 schrieb Steven Silvester:
>
> Hi Kai,
>
> Is the issue that you want finer grain control of the block size?  If so, 
> that would require a substantial rewrite.
>
> Please feel free to open an issue on Github if that is the case.
>
>
> Regards,
>
> Steve
>
>
> On May 26, 2015, at 1:58 AM, Kai Wiechen <kwie... at gmail.com <javascript:>> 
> wrote:
>
> Hi Steve,
>
> but these parameters are limited to the range 1..16. The small test 
> patches are 150x150 pixels, the complete images have 1920x1448 pixels. I 
> have applied equalize_adapthist here with default parameters (n_tiles=8).
>
> Best regards,
>
> Kai
>
> On Tuesday, May 26, 2015 at 12:54:34 AM UTC+2, Steven Silvester wrote:
>>
>> Hi Kai,
>>
>> Do the `n_tiles*` arguments not meet your needs?  By defining the number 
>> of tiles in X and Y, you are equivalently setting a block size.
>>
>>
>> http://scikit-image.org/docs/stable/api/skimage.exposure.html#equalize-adapthist
>>
>>
>> Regards,
>>
>> Steve
>>
>> On Monday, May 25, 2015 at 1:49:53 PM UTC-5, Kai Wiechen wrote:
>>>
>>>
>>> <https://lh3.googleusercontent.com/-0jVbtyT6ArM/VWNtiWHECgI/AAAAAAAABOg/AKpRcr4fKHU/s1600/nuclei_equalize_adapthist.jpg>
>>> Hello,
>>>
>>> I am using equalize_adapthist after color deconvolution and some 
>>> morphological operations to enhance local contrast of nuclei in 
>>> histological images. There are different results when applying 
>>> equalize_adapthist when using small patches and larger size whole images 
>>> (left small patch, right large size whole image). The CLAHE implementation 
>>> in ImageJ has a 'block size' parameter and the implementation in Pixinsight 
>>> has a 'Kernel size' parameter to get results depending on the local 
>>> context. Is it possible to 'simulate' this behaviour with scikit-image?
>>>
>>> Best regards,
>>>
>>> Kai
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
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