Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6906080 | Astronomy and Computing | 2016 | 14 Pages |
Abstract
Soon to be operational HÂ I survey instruments such as APERTIF and ASKAP will produce large datasets. These surveys will provide information about the HÂ I in and around hundreds of galaxies with a typical signal-to-noise ratio of â¼10 in the inner regions and â¼1 in the outer regions. In addition, such surveys will make it possible to probe faint HÂ I structures, typically located in the vicinity of galaxies, such as extra-planar-gas, tails and filaments. These structures are crucial for understanding galaxy evolution, particularly when they are studied in relation to the local environment. Our aim is to find optimized kernels for the discovery of faint and morphologically complex HÂ I structures. Therefore, using HÂ I data from a variety of galaxies, we explore state-of-the-art filtering algorithms. We show that the intensity-driven gradient filter, due to its adaptive characteristics, is the optimal choice. In fact, this filter requires only minimal tuning of the input parameters to enhance the signal-to-noise ratio of faint components. In addition, it does not degrade the resolution of the high signal-to-noise component of a source. The filtering process must be fast and be embedded in an interactive visualization tool in order to support fast inspection of a large number of sources. To achieve such interactive exploration, we implemented a multi-core CPU (OpenMP) and a GPU (OpenGL) version of this filter in a 3D visualization environment (SlicerAstro).
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
D. Punzo, J.M. van der Hulst, J.B.T.M. Roerdink,