Purpose: Image stitching and core segmentation software for large scale digital holography (Quantitative Phase Imaging). You must cite this work by providing a reference to this page.
Authors: Kevin Han, Zelun Luo
Mentor: Mikhail Kandel
Requirement:
-
Visual Studio 2013 (Visual Studio 2012 will not work)
-
- Extension package: NumPy, SciPy, PIL
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OpenCV 3.0 alpha (OpenCV 2.x will not work)
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fftw (provided)
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libtiff (provided)
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Eigen (provided)
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tminres (provided)
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CMake for GCC (YMMV)
Usage: For stitching and core segmentation, run
python wrapper.py [-s <config file for stitch>] [-c <config file for seg>]
Output of stitching is in a format suitable for uploading to CATMAID or [Zoomify] (http://www.zoomify.com).
Additionally, TIFF files are provided for inspection in ImageJ.
The config file is JSON, consisting of a single object with these keys:
###Config file parameters for wrapper.py: ####Stitching:
| Parameter | Description |
|---|---|
| inDir | directory with poslist file; file name must end in "poslist" |
| outDir | output directory |
| projName | project name for |
| zoomLvls | number of zoom levels |
| Optional parameter | Description | Default |
|---|---|---|
| pixelRatio | Conversion from stage coordinates to pixels | 1 pixel/micron (off) |
| maxPeakX | Max pixel offset of phase correlation peak from stage value for horizontally offset images. | dx / w * 0.2 sqrt(w*h), where dx is x overlap. |
| maxPeakY | Max pixel offset of phase correlation peak from stage value for vertically offset images. | dy / h * 0.2 sqrt(w*h), where dy is y overlap. |
| maxPeakXY | Max pixel offset of phase correlation peak from stage value for diagonally offset images. | (dx*dy) / (w*h) * 0.2 sqrt(w*h) |
| cacheSz | # images to cache when reading. | 50 |
| poslist | Path of poslist relative to inDir. | Any file ending in "poslist" (can only be one) |
| skipAlign | true to skip aligment, and raster the "poslist" as-is |
false |
| weightPwr | During least squares optimization, the error for each offset is weighted by peak sum ^ weightPwr. So, 0 = no weighting. |
1 |
| peakRadius | Amount on each side of the peak to sum up. 0 = 1 pixel total (just the peak); 1 = 9 pixels total, etc. | 1 |
| fixNaN | true to replace NaN values in image with zeros. |
true |
| bgSub | percentage of input images used to generate the background. (0 if not doing background subtraction) | 0 |
| outWidth | Rasterized tile width | 1024 |
| outHeight | Rasterized tile height | 1024 |
| writeJPG | Write JPGs? | true |
| writeTIF | Write floating point TIF files? | false |
| colormapMin | Color for pure black (0,0,0) | -0.3 |
| colormapMax | Color for pure white (1,1,1) | 0.8 |
| rasterFormat | Naming convention for files, choose from CATMAID or ZOOMIFY |
CATMAID |
The defaults for peak offset linearly extrapolate between 0% image overlap (0 peak offset; trust stage completely), and 100% overlap (peak offset is 0.2 * "image dimension"). (Maybe this will work?)
####Segmentation:
| Parameter | Description |
|---|---|
| inDir | directory with project.yaml; output directory of stitching. |
| outDir | output directory of segmented cores. |
| coreW | number of cores in each row. |
| coreH | number of cores in each column. |
| Optional parameter | Description | Default |
|---|---|---|
| winW | width of segmenting window in cropped.jpg. |
55 |
| winH | height of segmenting window in cropped.jpg. |
55 |
| crop | 1 = generate the output; 0 = only view the segmentation result in downsampled image. | 0 |