missing kernel or block size in equalize_adapthist

[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 <kwiechen1 at gmail.com> 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 <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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