Wavelet-based decomposition and analysis of structural patterns in astronomical images

¹ Max-Planck-Institut für Radioastronomie, Auf dem Hugel 69, 53121 Bonn, Germany
e-mail: florent.mertens@gmail.com
² Institut für Experimentalphysik, Universität Hamburg, Luruper Chaussee 149, 22761 Hamburg, Germany

Received: 9 July 2014
Accepted: 28 November 2014

Abstract

Context. Images of spatially resolved astrophysical objects contain a wealth of morphological and dynamical information, and effectively extracting this information is of paramount importance for understanding the physics and evolution of these objects. The algorithms and methods currently employed for this purpose (such as Gaussian model fitting) often use simplified approaches to describe the structure of resolved objects.

Aims. Automated (unsupervised) methods for structure decomposition and tracking of structural patterns are needed for this purpose to be able to treat the complexity of structure and large amounts of data involved.

Methods. We developed a new wavelet-based image segmentation and evaluation (WISE) method for multiscale decomposition, segmentation, and tracking of structural patterns in astronomical images.

Results. The method was tested against simulated images of relativistic jets and applied to data from long-term monitoring of parsec-scale radio jets in 3C 273 and 3C 120. Working at its coarsest resolution, WISE reproduces the previous results of a model-fitting evaluation of the structure and kinematics in these jets exceptionally well. Extending the WISE structure analysis to fine scales provides the first robust measurements of two-dimensional velocity fields in these jets and indicates that the velocity fields probably reflect the evolution of Kelvin-Helmholtz instabilities that develop in the flow.