Sunkit Image
This project developed several image processing algorithms and manipulation routines for sunkit-image, an affiliated Python package of the Sunpy Project. The rigorous analysis of solar images is of paramount importance to the Heliophysics community as this can reveal more information on solar features and events, which in turn can affect the Earth. This project brought selected solar image processing algorithms under the umbrella of a new library.
Algorithms Implemented
Algorithms Implemented
This algorithm reduces the radial gradient thus revealing the features in the sun's corona.
Input Image
Output Image
It reduces the dynamic range of the image by normalizing the pixel values at different scales (or standard deviation) using Gaussian kernels. It highlights the information embedded on the solar surface.
Input Image
Output Image
Output Image
Designed to trace the magnetic field loops over the surface of the sun.
Input Image
Output Image
It helps in calculating the 2D velocity flow field between two images taken at some time instant apart from each other. An existing C code was wrapped using Cython to make it available to the Python API.
Further details regarding the project can be found at the Sunkit-image GitHub repository. I would like to thank my mentors - Nabil Freji, Jack Ireland and Stuart Mumford for their valuable suggestions and guidance.