Multiresolution and Hierarchical Analysis of Astronomical Spectroscopic Cubes using 3D Discrete Wavelet Transform
This addresses the need for automated pattern recognition in astronomy to handle complex interstellar structures, but it is incremental as it builds on existing 2D methods.
The paper tackled the problem of identifying and connecting source components in 3D astronomical spectroscopic cubes by extending wavelet-based multiresolution analysis from 2D to 3D and combining it with Dendrograms for hierarchical representation, demonstrating feasibility through testing on ALMA data.
The intrinsically hierarchical and blended structure of interstellar molecular clouds, plus the always increasing resolution of astronomical instruments, demand advanced and automated pattern recognition techniques for identifying and connecting source components in spectroscopic cubes. We extend the work done in multiresolution analysis using Wavelets for astronomical 2D images to 3D spectroscopic cubes, combining the results with the Dendrograms approach to offer a hierarchical representation of connections between sources at different scale levels. We test our approach in real data from the ALMA observatory, exploring different Wavelet families and assessing the main parameter for source identification (i.e., RMS) at each level. Our approach shows that is feasible to perform multiresolution analysis for the spatial and frequency domains simultaneously rather than analyzing each spectral channel independently.