Wavelet for multidimensional signals analysis: Difference between revisions

Revision as of 19:00, 9 December 2015

Revision as of 19:02, 9 December 2015

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{{Orphan|date=November 2015}}

[[Wavelet]]s are often used to analyse piece-wise smooth signals.<ref>{{cite book|last1=Mallat|first1=Stéphane|title=A Wavelet Tour of Signal Processing|date=2008|publisher=Academic Press}}</ref> Wavelet coefficients can efficiently represent a signal which has led to data compression algorithms using wavelets. <ref>{{cite journal|last1=Devore|first1=Ronald|last2=Jawerth|first2=Bjorn|last3=Lucier|first3=Bradley|title=Data compression using wavelets: error, smoothness and quantization|journal=Data Compression Conference,IEEE|date=8-11 Apr 1991|page=186 - 195|doi=http://dx.doi.org/10.1109/DCC.1991.213386}}</ref>Wavelet analysis is extended for [[multidimensional signal processing]] as well. This article introduces a few methods for wavelet synthesis and analysis for multidimensional signals. There also occur challenges such as directivity in multidimensional case.

== Multidimensional separable Discrete Wavelet Transform (DWT) ==