chengxinlun/openap

Astrophotography Post Processing with OpenCV

Astrophotography Post Processing with OpenCV

Dependencies

• Python (Python 3 recommended, not tested on Python 2)
• Matplotlib
• Numba
• Numpy
• OpenCV
• Scipy
• Scikit-image

Install

pip install astropenap

Current Functionalities

• 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

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.

Credit

Thanks @jinleic for inspiration and packaging.