missing kernel or block size in equalize_adapthist

[Kai Wiechen]

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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