- Python (Python 3 recommended, not tested on Python 2)
- Matplotlib
- Numba
- Numpy
- OpenCV
- Scipy
- Scikit-image
pip install astropenap
- 8-bit, 16-bit, 32-bit image conversion
- Background subtraction (gradient removal included)
- Chromatic adaptation (build-in D50 to/from D65 with XYZ scaling/Bradford/Von Kries method, custom white-point or method allowed)
- Color matrix conversion (similar to that of
imagemagick) - Color space conversion (built-in sRGB to linear RGB D65, more in development)
- Deconvolution (NOT recommended due to lack of deringing algorithm)
- Gamma correction
- High dynamic range 2D deconvolution
- Histogram
- Local histogram equilization
- Logging
- Masks: star mask, global threshold mask, etc.
- RNC stretch (credit to Roger N. Clark for the functions)
- Simple star detection
- Star (PSF) fitting with 2D Gaussian (more PSF models in development)
- Star size reduction
- Starlet transformation
Example in OpenAP/tests
test_main.py outlines workflow associated with images with extended nebulosity.
test_dso.py outlines workflow associated with images with little to none nebulosity.
Thanks @jinleic for inspiration and packaging.