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Line 27: [[Image:Wiki figures mod.001.png\|framed\|none\|The figure depicts 3-D separable DWT procedure by applying 1-D DWT for each dimension and splitting the data into chunks to obtain wavelets for different subbands]] Applying the 1-D DWT analysis filterbank in dimension {{math\|N1}}, it is now split into two chunks of size {{math\| {{frac\|N1\|2}} × N2 × N3}}. Applying 1-D DWT in {{math\|N2}} dimension, each of these chunks is split into two more chunks of {{math\|{{frac\|N1\|2}} × {{frac\|N2\|2}} × N3}}. This repeated in 3-D gives a total of 8 chunks of size {{math\| {{frac\|N1\|2}} × {{frac\|N2\|2}} × {{frac\|N3\|2}}}}. ~~The first chunk is passed via a low pass filter in each of these dimensions and the second one via high-pass.~~ <ref>{{cite journal\|last1=Cheng-Wu\|first1=Po\|last2=Gee-Chen\|first2=Liang\|title=An efficient architecture for two-dimensional discrete wavelet transform\|journal=IEEE Transactions on Circuits and Systems for Video technology\|date=7 August 2002\|volume=11\|issue=4\|pages=536-545\|doi=10.1109/76.915359\|url=http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=915359&tag=1}}</ref> [[Image:Filterbank mod try 2.001.png\|framed\|none\|The figure shows the 3-D analysis filterbank for 3-D separable DWT]]

Wavelet for multidimensional signals analysis: Difference between revisions