Name: Ritesh Patel
Affiliation: ARIES Nainital
Conference ID : ASI2022_523
Title : A Simple Radial Gradient Filter for batch-processing of Coronagraph images
Authors : Ritesh Patel Satabdwa Majumdar Vaibhav Pant Dipankar Banerjee
Abstract Type: Poster
Abstract Category : Sun and the Solar System
Abstract : The images 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 different heights in the solar corona within the full field of view. To process the bulk of coronagraph images with the steep radial intensity gradients, we have developed an algorithm, Simple Radial Gradient Filter (SiRGraF). It is based on subtracting a minimum background created using long-duration images and then dividing the resultant by a uniform intensity gradient image to enhance the K corona. In this presentation, we demonstrate the utility of this algorithm to bring out the short time scale transient structures of the corona. We have successfully tested the algorithm on images of Large Angle Spectroscopic COronagraph (LASCO) C2 on-board Solar and Heliospheric Observatory (SOHO), and COR-2A on-board Solar TErrestrial RElations Observatory (STEREO) with good signal to noise ratio (SNR) along with low SNR images of STEREO/COR-1A and KCor. We also compared the performance of SiRGraF with an existing widely used algorithm, Normalising 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 NRGF providing better identification of coronal dynamic structures throughout the field of view. We discuss the advantages and limitations of the algorithm. The application of SiRGraF on COR-1 images could be extended for an automated coronal mass ejection (CME) detection algorithm in the future which will help in our study of the CMEs' characteristics in the inner corona.