# Image-Optimized Coronal Magnetic Field Models

## TL;DR

This paper introduces an image-based method to enhance global coronal magnetic field models using realistic white-light coronagraph data, addressing projection challenges and demonstrating significant improvements.

## Contribution

The study extends previous work by applying the image-based optimization technique to realistic coronagraph constraints, including line-of-sight projection effects.

## Key findings

- Substantial improvement in magnetic field models with coronagraph constraints.
- Effective handling of line-of-sight projection issues.
- Method proves robust even with features outside the image plane.

## Abstract

We have reported previously on a new method we are developing for using image-based information to improve global coronal magnetic field models. In that work we presented early tests of the method which proved its capability to improve global models based on flawed synoptic magnetograms, given excellent constraints on the field in the model volume. In this follow-up paper we present the results of similar tests given field constraints of a nature that could realistically be obtained from quality white-light coronagraph images of the lower corona. We pay particular attention to difficulties associated with the line-of-sight projection of features outside of the assumed coronagraph image plane, and the effect on the outcome of the optimization of errors in localization of constraints. We find that substantial improvement in the model field can be achieved with this type of constraints, even when magnetic features in the images are located outside of the image plane.