Characterizing plasma with emission tomography-Feasibility study on synthetic and experimental data

Area of Science:

• Plasma physics
• Tomography
• Image reconstruction

Background:

• Tomographic reconstruction is an ill-posed problem due to limited projection data, viewing angles, and noise.
• Plasma diagnostics often require accurate spatial distribution of parameters.

Purpose of the Study:

• To assess the feasibility of different tomographic algorithms for plasma reconstruction.
• To identify suitable algorithms for symmetric, asymmetric, and complex plasma systems.
• To evaluate noise reduction techniques for improved image quality.

Main Methods:

• Investigated single-angle Abel inversion, two-angle approach, and multiple-angle 2D plasma tomography.
• Tested algorithms on simulated symmetric/asymmetric functions and experimental microwave argon plasma data.
• Applied smoothing techniques and total variation minimization for noise reduction.
• Assessed image quality using peak signal-to-noise ratio and universal image quality measures.

Main Results:

• Abel inversion is suitable only for radially symmetric systems.
• The two-angle approach can reconstruct systems with slight asymmetry.
• Full 2D tomography is necessary for systems lacking symmetry.
• Filtered back projection and simultaneous algebraic reconstruction technique yielded best reconstruction results.
• Total variation minimization proved most effective for denoising.

Conclusions:

• Algorithm choice depends critically on plasma symmetry.
• 2D tomography is essential for accurately characterizing asymmetric plasmas.
• Effective noise reduction is crucial for reliable plasma image reconstruction.