http://imagej.273.s1.nabble.com/Fwd-Phansalkar-local-thresholding-tp5007401p5007406.html
Yes -as stated, I already have that info. The question was: is there more?
> On Apr 23, 2014, at 9:30, Gabriel Landini <
[hidden email]> wrote:
>
>> On Wednesday 23 Apr 2014 08:33:53 you wrote:
>> Can someone please point me at any published descriptions of the method,
>> testing, or use of the “Phansalkar” method of local thresholding? I see
>> one reference in the ImageJ docs; I’m looking for more.
>
> From the Auto Local Threshold info:
>
http://www.mecourse.com/landinig/software/autothreshold/autothreshold.html>
> Phansalkar
> This is a modification of Sauvola's thresholding method to deal with low
> contrast images.
>
> 1. Phansalskar N. et al. Adaptive local thresholding for detection of nuclei
> in diversity stained cytology images. International Conference on
> Communications and Signal Processing (ICCSP), 2011, 218-220.
>
> In this method, the threshold t is computed as:
>
> t = mean * (1 + p * exp(-q * mean) + k * ((stdev / r) - 1))
>
> where mean and stdev are the local mean and standard deviation respectively.
> Phansalkar recommends k = 0.25, r = 0.5, p = 2 and q = 10. In this plugin, k
> and r are the parameters 1 and 2 respectively, but the values of p and q are
> fixed.
> Parameter 1: is the k value. The default value is 0.25. Any other number than
> 0 will change its value.
> Parameter 2: is the r value. The default value is 0.5. This value is different
> from Sauvola's because it uses the normalised intensity of the image. Any
> other number than 0 will change its value
> Implemented from Phansalkar's paper description, although this version uses a
> circular rather than rectangular local window.
>
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