Increasing the Fine Structure Visibility of the Hinode SOT Ca II H Filtergrams

TL;DR

This paper introduces an improved pattern recognition operator, Madmax, implemented in MATLAB, to enhance the visibility of fine structures like chromospheric jets in solar images, effectively reducing noise.

Contribution

The paper presents a new MATLAB implementation of the Madmax operator, optimized for detecting fine solar features amidst noise in Hinode SOT Ca II H filtergrams.

Findings

Effective enhancement of fine solar structures achieved

Demonstrated robustness against noise in real images

Provides adjustable parameters for optimal visibility

Abstract

We present the improved so-called Madmax (OMC) operator selecting maxima of convexities computed in multiple directions around each pixel rewritten in MatLab and shown to be very efficient for pattern recognition. The aim of the algorithm is to trace the bright hair-like features (for ex. chromospheric thin jets or spicules) of solar ultimate observations polluted by a noise of different origins. This popular spatial operator uses the second derivative in the optimally selected direction for which its absolute value has a maximum value. Accordingly, it uses the positivity of the resulting intensity signal affected by a superposed noise. The results are illustrated using a test artificially generated image and real SOT (Hinode) images are also used, to make your own choice of the sensitive parameters to use in improving the visibility of images.