Hierarchical image representation is multiscale decomposition of images which is proven very useful in automated faint astronomical source detection from optical images. Hierarchical image representation is typically done using tree data structure (i.e. max-tree), whose computational cost of construction highly depends on the resolution and the dynamic range of image. Efficient and fast tree construction is crucial here because the amount of optical imaging data is increasing exponentially, and the upcoming new giant telescopes such as European Extremely Large Telescope (E-ELT) will produce even more images. Here we investigate some of the recent developments in tree construction algorithms and optimization techniques that have significantly increased its computation speed.
|Publication status||Published - 7-Oct-2019|
|Event|| the Astronomical Data Analysis and Software Systems conference (ADASS) 2019 - MartiniPlaza, Leonard Springerlaan 2, Groningen, Netherlands|
Duration: 6-Oct-2019 → 10-Oct-2019
|Conference||the Astronomical Data Analysis and Software Systems conference (ADASS) 2019|
|Abbreviated title||ADASS 2019|
|Period||06/10/2019 → 10/10/2019|