SOCIS 2017 Ideas Page

X-ray VIsibility Synthesis ImagiNg or Xray-VISION

Suggested Mentor(s): Shane Maloney,

Difficulty: Intermediate/Advanced

Astronomy knowledge needed: Fourier Transform knowledge nice to have but not essential

Programming skills: Python

Description

X-ray synthesis imaging is dependent upon deconvolution algorithms to counteract the sparse sampling in Fourier space. Synthesis imaging is often associated with large radio interferometric arrays but has also been used in X-rays. Specifically in the solar context in the past with Yohkoh/HXT, currently with RHESSI and in the future with Solar Orbiter/STIX. Numerous algorithms with different methodologies have been developed to solve this problem. The objective of this project is to create an afiliated package which will provide high-level access to generalised algorithms such as but not limited to:

• CLEAN
• Multiscale CLEAN
• MEM
• PIXON 1, 2.

This could be accomplished by creating pure python implementations (preferred), creating wrappers around existing implementations or a combination of both. This would facilitate the comparison of the existing methods as well as any new methods, it would also allow for ensemble reconstructions in the future.

Expected Outcomes

At the conclusion of this project the community will have access to well documented image reconstruction algorithms in python.

Someone undertaking this project will specifically complete the following:

1. Create suitable representation for generalised visibilities
2. Implement CLEAN with sufficient documentation and tests
3. Integrate the resulting images with the existing SunPy sunpy.map.Map object
4. Investigate implementation of the advanced method(s).

A successful proposal will demonstrate that the applicant has understood the project and present tasks and timeline for completion.

sunkit-image

Suggested Mentor(s): Jack Ireland, Stuart Mumford

Difficulty: Beginner

Astronomy knowledge needed: None

Programming skills: Python

In this project you would create the foundations of the 'sunkit-image' SunPy affiliated package, a package to contain image processing routines and functionality specific to the analysis of solar physics data.

Description

There have been various proposals for adding image processing and manipulation code to the SunPy library. SunPy has decided that this functionality will instead reside in an affiliated package, tentatively named 'sunkit-image'. This project will setup this package and implement the initial functionality.

There is various functionality that should be added to 'sunkit-image' some of it already developed, some of it not! This project should achieve some or all of the following goals (roughly in this order):

1. Port the Multi-Scale Gaussian Normalisation code from #1899.
2. Convert the differential rotation code in SunPy to use sunpy.coordinates.
3. Implement image warping for solar differential rotation. #1876.
4. Implement the OCCULT-2 algorithm for coronal loop tracing.
5. Implement running and base difference functionality and the persistence transform. See Figure 2 in this paper for some ideas.

optional extras:

6. Refactor and write a Python wrapper for FLCT code.
7. Implement image alignment using feature detection and tracking. Example

Expected Outcomes

• Have copied in and documented and tested the MGN code.
• Have opened a PR to SunPy to convert the sunpy.physics module to use sunpy.coordinates.
• Have implemented the Map warping code.
• Have got the SunPy PR for coordinates in sunpy.physics merged.
• Have implemented OCCULT-2.