Created by Tomio on 2010-03-04 and last modified on 2020-06-18
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39. By Tomio on 2020-06-18

Minor changes in the main code.
This version contains several example scripts for image processing, relying on this package and the BatchAnalyzer for some I/O, e.g. simple reporting and data dumping to text files.

Circl-analysis is to detect circles in fluorescence images by finding the negative patches within.

Gauss-edge is to use an asymmetric, rotated Gaussian kernel to detect lines or edges in images, for improved orientation statistics. For those, who need it, the structure tensor method is also available in the ImageP package, so one can play around with these for edge detection, etc.

RadialProfileAnalysis is a simple tool to detect point distribution by distance from the center of mass. Naturally, after some background correction, potential dynamic range compression with a power law tranformation and thresholding. It was originally meant for statistics of neuron images with explants in the middle.

The current GaussKernel based filters use non-zero padding at the image edges decreasong the high intensity frames there. Naturally, this is a bit different artefact replacing a common one. The assumption is here that the intensity is not zero outside of the image, but the same as the last pixel. This works only for filters which can be run in 1D.

Display got some changes too to catch up with the development of matplotlib. It should handle now the figure objects a bit better. Allowing for overplotting information easier.

Further details are in the DevelopmentNotes.txt file.

38. By Tomio on 2019-06-11

Now it is properly done...

37. By Tomio on 2019-06-11

Minor change. The 'noclip' option in the BPass filter is deprecated, the 1D filter takes care of the problem automatically. I removed this switch from BPass.

36. By Tomio on 2019-05-21

Added the proper link to the circle fitting algorithm.

35. By Tomio on 2019-05-21

Added a Circle_fit function to fit segments of circles and identify their centers as well as radii. It is a code I adopted from the web, it is quite fast and robust.

34. By Tomio on 2019-05-20

Minor change: padding in 2D convolution generates kernel dependent artefacts we had better avoid. Thus, padding is solved for the ConvFilter1D, but such solution is not possible for ConvFilter in general.
What remains is the filters cut the returned image back to the size of the original.

33. By Tomio on 2019-05-20

Upped the version number to signify the changes in convolution.

32. By Tomio on 2019-05-20

There are some minor changes. I have rewritten the convolution filters such, that they return an image with the same size as the original. This is a major change in a couple of places!
The 1D convolution also pads the curves with their end values, minimizing the edge effect caused by zero padding. This results in much clearer images for Gauss filters, edge detector, etc.

31. By Tomio on 2019-04-05

Added new source files I missed in the previous push.

30. By Tomio on 2019-04-05

A couple of minor changes affecting the whole package. Such as a proper skeletonization algorithm, an edge detector integrating parts to use a second derivative Gaussian filter to highlight edges, a local maxima finder based on a Gaussian gradient filter, etc.
The distance transform works for 1D and 2D, and it is easily extensible to 3D if needed.

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