Reconstruction of photospheric velocity fields from highly corrupted data

TL;DR

This paper introduces a new image inpainting method to reconstruct highly corrupted photospheric velocity fields, enabling more accurate analysis of solar plasma turbulence despite data noise.

Contribution

A novel image inpainting technique specifically designed for restoring corrupted velocity data in solar photospheric observations.

Findings

Method effectively restores velocity fields in simulated data.

Restoration maintains all vector components of the original field.

Robust performance demonstrated on observational data.

Abstract

The analysis of the photospheric velocity field is essential for understanding plasma turbulence in the solar surface, which may be responsible for driving processes such as magnetic reconnection, flares, wave propagation, particle acceleration, and coronal heating. Currently, the only available methods to estimate velocities at the solar photosphere transverse to an observer's line of sight infer flows from differences in image structure in successive observations. Due to data noise, algorithms such as local correlation tracking (LCT) may lead to a vector field with wide gaps where no velocity vectors are provided. In this letter, a novel method for image inpainting of highly corrupted data is proposed and applied to the restoration of horizontal velocity fields in the solar photosphere. The restored velocity field preserves all the vector field components present in the original field. The method shows robustness when applied to both simulated and observational data.