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SUMMARY:Dual-Tree Complex Wavelets - their key properties and a range of i
 mage-processing applications - Prof Nick Kingsbury\, Signal Processing and
  Communications Group\, Department of Engineering\, University of Cambridg
 e
DTSTART:20121024T130000Z
DTEND:20121024T140000Z
UID:TALK41255@talks.cam.ac.uk
CONTACT:Rachel Fogg
DESCRIPTION:We will describe the Dual-Tree Complex Wavelet Transform (DT C
 WT)\, a form of discrete wavelet transform which generates complex coeffic
 ients by using two trees of wavelet filters in parallel to obtain their re
 al and imaginary parts. This introduces limited redundancy (2^m : 1 for m-
 dimensional signals) and the Hilbert-pair property is designed into the tw
 o wavelet bases such that the transform provides approximate shift invaria
 nce and directionally selective filters (properties lacking in the traditi
 onal wavelet transform)\, while preserving the usual properties of perfect
  reconstruction and computational efficiency with good well-balanced frequ
 ency responses. Energy is preserved in the Q-shift wavelet filters\, resul
 ting in tight-frame properties too. In the decade since the dual tree was 
 first proposed\, it has been applied to images and 3D datasets and has bee
 n shown to outperform traditional wavelets in a range of applications\, wh
 ich will be summarized.  These will include image registration\, fusion\, 
 sparsisty-based deconvolution\, and object feature detectors and descripto
 rs.\n\n
LOCATION:LR4\, Engineering\, Department of
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