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CATEGORIES:Signal Processing and Communications Lab Seminars
SUMMARY:Dual-Tree Complex Wavelets - their key properties
and a range of image-processing applications - Pro
f Nick Kingsbury\, Signal Processing and Communica
tions Group\, Department of Engineering\, Universi
ty of Cambridge
DTSTART;TZID=Europe/London:20121024T140000
DTEND;TZID=Europe/London:20121024T150000
UID:TALK41255AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/41255
DESCRIPTION:We will describe the Dual-Tree Complex Wavelet Tra
nsform (DT CWT)\, a form of discrete wavelet trans
form which generates complex coefficients by using
two trees of wavelet filters in parallel to obtai
n their real and imaginary parts. This introduces
limited redundancy (2^m : 1 for m-dimensional sign
als) and the Hilbert-pair property is designed int
o the two wavelet bases such that the transform pr
ovides approximate shift invariance and directiona
lly selective filters (properties lacking in the t
raditional wavelet transform)\, while preserving t
he usual properties of perfect reconstruction and
computational efficiency with good well-balanced f
requency responses. Energy is preserved in the Q-s
hift wavelet filters\, resulting in tight-frame pr
operties too. In the decade since the dual tree wa
s first proposed\, it has been applied to images a
nd 3D datasets and has been shown to outperform tr
aditional wavelets in a range of applications\, wh
ich will be summarized. These will include image
registration\, fusion\, sparsisty-based deconvolut
ion\, and object feature detectors and descriptors
.\n\n
LOCATION:LR4\, Engineering\, Department of
CONTACT:Rachel Fogg
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