Processing All-Sky Images At Scale On The Amazon Cloud: A HiPS Example
CoRR(2024)
摘要
We report here on a project that has developed a practical approach to
processing all-sky image collections on cloud platforms, using as an exemplar
application the creation of three-color Hierarchical Progressive Survey (HiPS)
maps of the 2MASS data set with the Montage Image Mosaic Engine on Amazon Web
Services. We will emphasize issues that must be considered by scientists
wishing to use cloud platforms to perform such parallel processing, so
providing a guide for scientists wishing to exploit cloud platforms for similar
large-scale processing. A HiPS map is based on the HEALPix sky-tiling scheme.
Progressive zooming of a HiPS map reveals an image sampled at ever smaller or
larger spatial scales that are defined by the HEALPix standard. Briefly, the
approach used by Montage involves creating a base mosaic at the lowest required
HEALPix level, usually chosen to match as closely as possible the spatial
sampling of the input images, then cutting out the HiPS cells in PNG format
from this mosaic. The process is repeated at successive HEALPix levels to
create a nested collection of FITS files, from which PNG files are created that
are shown in HiPS viewers. Stretching FITS files to produce PNGs is based on an
image histogram. For composite regions (up and including the whole sky), the
histograms for each tile can be combined to create a composite histogram for
the region. Using this single histogram for each of the individual FITS files
means all the PNGs are on the same brightness scale and displaying them side by
side in a HiPS viewer produces a continuous uniform map across the entire sky.
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