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

Abstract

Context. Images of spatially resolved astrophysical objects contain a wealth of morphological and dynamical information, and effective extraction of this information is of paramount importance for understanding the physics and evolution of these objects. Algorithms and methods employed presently for this purpose (such as, for instance, Gaussian model fitting) often use simplified approaches for describing the structure of resolved objects. Aims. Automated (unsupervised) methods for structure decomposition and tracking of structural patterns are needed for this purpose, in order to be able to deal with the complexity of structure and large amount of data involved. Methods. A new Wavelet-based Image Segmentation and Evaluation (WISE) method is developed for multiscale decomposition, segmentation, and tracking of structural patterns in astronomical images. Results. The method is 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 exceptionally well the previous results of model fitting evaluation of the structure and kinematics in these jets. Extending the WISE structure analysis to the finer scales provides the first robust measurements of two-dimensional velocity fields in these jets and indicates that the velocity fields are likely to reflect the evolution of Kelvin-Hemlholtz instability developing the flow.