Astronomical image processing based on fractional calculus: the AstroFracTool

TL;DR

The paper introduces AstroFracTool, a new image processing method based on fractional calculus that enhances astronomical images by improving edge detection and revealing faint structures for scientific analysis.

Contribution

It presents a novel fractional calculus-based tool for astronomical image enhancement, enabling better detection of faint objects and surface details.

Findings

Enhanced image quality and edge detection in astronomical images.

Improved detection of faint objects and galaxy structures.

Better surface detail visualization for planetary studies.

Abstract

The implementation of fractional differential calculations can give new possibilities for image processing tools, in particular for those that are devoted to astronomical images analysis. As discussed in arxiv:0910.2381, the fractional differentiation is able to enhance the quality of images, with interesting effects in edge detection and image restoration. Here, we propose the AstroFracTool, developed to provide a simple yet powerful enhancement tool-set for astronomical images. This tool works evaluating the fractional gradient of an image map. It can help produce an output image useful for further research and scientific purposes, such as the detection of faint objects and galaxy structures, or, in the case of planetary studies, the enhancement of surface details.