Abstract:
Images of the extended solar corona, as observed by different white-light coronagraphs,
include the K- and F-corona and suffer from a radial variation in intensity. These images
require separation of the two coronal components with some additional image-processing
to reduce the intensity gradient and analyse the structures and processes occurring at dif ferent heights in the solar corona within the full field of view. Over the past few decades,
coronagraphs have been producing enormous amounts of data, which will be continued with
the launch of new telescopes. To process these bulk coronagraph images with steep radial intensity gradients, we have developed the algorithm Simple Radial Gradient Filter (SiR GraF). This algorithm is based on subtracting a minimum background (F-corona) created
using long-duration images and then dividing the resultant by a uniform-intensity-gradient
image to enhance the K-corona. We demonstrate the utility of this algorithm to bring out
the short-time-scale transient structures of the corona. SiRGraF can be used to reveal and
analyse such structures. It is not suitable for quantitative estimations based on intensity. We
have successfully tested the algorithm on images of the Large Angle Spectroscopic COron agraph (LASCO)-C2 onboard the Solar and Heliospheric Observatory (SOHO) and COR 2A onboard the Solar TErrestrial RElations Observatory (STEREO) with good signal-to noise ratio (SNR) along with low-SNR images of STEREO/COR-1A and the KCoronagraph
(KCor). We also compared the performance of SiRGraF with the existing widely used algo rithm Normalizing Radial Gradient Filter (NRGF). We found that when hundreds of images
have to be processed, SiRGraF works faster than NRGF, providing similar brightness and
contrast in the images and separating the transient features. Moreover, SiRGraF works better
on low-SNR images of COR-1A than on NRGF, providing better identification of dynamic
coronal structures throughout the field of view. We discuss the advantages and limitations
of the algorithm. The application of SiRGraF to COR-1 images can be extended for an au tomated coronal mass ejection (CME) detection algorithm in the future, which will help in
our study of the characteristics of CMEs in the inner corona.
