Greyscale reconstruction and merging CellProfiler code

[Tony Yu]

2011/7/10 Stéfan van der Walt <stefan at sun.ac.za>

> On Thu, Jul 7, 2011 at 6:30 PM, Tony Yu <tsyu80 at gmail.com> wrote:
> > I added a reference and tried to expand on the description, but the
> > description is still poor. Even in the papers I've read, the descriptions
> > are quite difficult for me to understand (the figures in those papers
> really
> > help). I've also added an example to the docstring, but it's quite ...
> > verbose.
>
> I guess the question then becomes whether such a specialised algorithm
> is of enough common interest to include it.  In the end, every piece
> of code requires maintenance, and our aim is to provide a fairly
> generic set of tools that can be used to construct image processing
> experiments.
>
> I don't know this algorithm specifically, so I can't say, but it is an
> aspect worth considering.
>
> > I'd like to add a longer example in the docs, but that will have to wait
> > until I have a bit more time. When I do add it, where should put it? I'd
> > like for it to be more like a tutorial than a function-specific example
> > (specifically, I'd like to compare reconstruction and top-hat for peak
> > detection).
>
> We are eagerly awaiting tutorial contributions for the docs, but no
> one's volunteered so far :)  I'd love to have more of these, as it
> shows common patterns (such as how to use io, displaying images,
> etc.).
>
> Regards
> Stéfan
>

Hi again,

I'm still interested in getting greyscale reconstruction into scikits.image.
To that end, I've updated my branch with a tutorial demonstrating peak
detection using reconstruction (
https://github.com/tonysyu/scikits.image/tree/reconstruction), with
comparisons to thresholding and white top hat. This example should
demonstrate reconstruction better than I was able to explain it earlier.

Let me know if you have trouble building the docs. There's still some
changes I want to make, but first I want to know whether this example is
enough to convince you that the reconstruction algorithm is worth including
;)

Best,
- Tony

A couple of random notes:

* This branch adds the ipython_directive (and ipython_console_hightlighting)
sphinx extension, because it allows you to show code examples with text
in-between (and still be able to access variables from previous blocks).
These extensions require the latest ipython (i.e. 0.11).

* morphology.greyscale_white_top_hat has issues with underflow because
there's a subtraction in the algorithm and it requires uint8 images (I
think). A similar issue came up in this thread:
http://groups.google.com/group/scikits-image/browse_thread/thread/c081f18d9e089e6e?pli=1.
But I guess, that applied specifically to functions using ndimage.convolve.

* the morphology names seem a bit clunky to work with. For example, white
top hat is called with "morphology.greyscale_white_top_hat". The greyscale
routines are already isolated to morphology.grey, so maybe
morphology/__init__.py can just call "import grey" (instead of "from grey
import *") and then the "greyscale_" prefix can be removed from the
functions?
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