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SUMMARY:Bayesian Fusion of Hyperspectral and Multispectral images - Qi Wei
 \, University of Toulouse
DTSTART:20150130T140000Z
DTEND:20150130T150000Z
UID:TALK57700@talks.cam.ac.uk
CONTACT:Fredrik Lindsten
DESCRIPTION:Hyperspectral (HS) imaging\, which consists of acquiring a\nsa
 me scene in several hundreds of contiguous spectral bands\, has opened a n
 ew range of relevant applications\, such as target detection\, classificat
 ion and spectral unmixing.\nWhile HS sensors provide abundant spectral inf
 ormation\,\ntheir spatial resolution is generally more limited. To obtain\
 nimages with good spectral and spatial resolutions\, the remote \nsensing 
 community has been devoting increasing research efforts to the problem of 
 fusing HS with multispectral (MS) or\npanchromatic (PAN) images\, which ow
 ns much higher spatial resolution. Since the fusion problem is usually ill
 -posed\, the Bayesian methodology offers a convenient way to regularize th
 e problem by defining appropriate prior distribution for the scene of inte
 rest. In this talk\, different state-of-the-art Bayesian fusion techniques
  for \nremotely sensed multi-band images will be presented.
LOCATION:LR5\, Cambridge University Engineering Department
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