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Wavelet coefficients can be computed by passing the signal to be decomposed though a series of filters. In the case of 1-D, there are two filters at every level-one low pass for approximation and one high pass for the details. In the multidimensional case, the number of filters at each level depends on the number of tensor product vector spaces. For M-D, {{math|2<sup>M</sup>}} filters are necessary at every level. Each of these is called a subband. The subband with all low pass (LLL...) gives the approximation coefficients and all the rest give the detail coefficients at that level.
For example, for {{math|M{{=}}3}} and a signal of size {{math| N1 × N2 × N3}} , a separable DWT can be implemented as follows:
[[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]]
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