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,


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.




On Monday, May 25, 2015 at 1:49:53 PM UTC-5, Kai Wiechen wrote:


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,