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SUMMARY:Advances in astronomical image processing - Solving the problems o
f image coaddition and image subtraction
DTSTART;VALUE=DATE-TIME:20170614T080000Z
DTEND;VALUE=DATE-TIME:20170614T083000Z
DTSTAMP;VALUE=DATE-TIME:20200920T022833Z
UID:indico-contribution-15478@indico.in2p3.fr
DESCRIPTION:Speakers: Barak Zackay (Weizmann Institute of Science)\nWhile
co-addition and subtraction of astronomical images stand at the heart of o
bservational astronomy\, the existing solutions for them lack rigorous arg
umentation\, are not achieving maximal sensitivity and are often slow. Mor
eover\, there is no widespread agreement on how they should be done\, and
often different methods are used for different scientific applications.\n\
nI am going to present rigorous solutions to these problems\, deriving the
m from the most basic statistical principles. These solutions are proved o
ptimal\, under well defined and practically acceptable assumptions\, and i
n many cases improve substantially the sensitivity\, robustness and speed
of both coaddition and subtraction.\n\nFor coaddition\, I will present a c
oadd image that is:\n\na) sufficient for any further statistical decision
or measurement on the underlying constant sky\, making the entire data set
redundant.\n\nb) improves both survey speed (by 5-20%) and effective spat
ial resolution of past and future astronomical surveys.\n\nc) improves sub
stantially imaging through turbulence applications.\n\nd) much faster than
many of the currently used coaddition solutions.\n\nFor subtraction\, I w
ill present a subtraction image that is:\n\na) optimal for transient detec
tion under the assumption of spatially uniform noise.\n\nb) sufficient for
any further statistical decision on the differences between the images\,
including the identification of cosmic rays and other image artifacts.\n\n
c) Free of subtraction artifacts\, potentially allowing (for the first tim
e) robust automatic transient detection in real time\, opening new avenues
for scientific exploration.\n\nd) more sensitive than previous transient
detection methods\n\ne) orders of magnitude faster than past subtraction m
ethods.\n\nhttps://indico.in2p3.fr/event/13811/contributions/15478/
LOCATION:IN2P3 computing center Amphitheatre
URL:https://indico.in2p3.fr/event/13811/contributions/15478/
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