Multidimensional signal processing: Difference between revisions

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'''Multidimensional Signal Processing'''

In [[signal processing]], '''multidimensional signal processing''' covers all signal processing done using [[multidimensional sampling]]. While multidimensional signal processing is a subset of signal processing, it is unique in the sense that it deals specifically with data that can only be adequately detailed using more than one dimension. Specifically, useful data is sampled in more than one dimension, such that multiple sensors are used to construct the data set. Examples of this are [[image processing]] and multi-sensor radar detection. Both of these examples use multiple sensors to sample signals in adjacent space and form images based on the manipulation of these multiple signals.

Multidimensional signals are part of [[multidimensional systems]], and as such are generally more complex than classical, single dimension signal processing. Processing in multi-dimension (m-D) requires more complex algorithms to handle calculations such as the [[Fast Fourier Transform]] due to more degrees of freedom<ref name="dudmer83">D. Dudgeon and R. Mersereau, Multidimensional Digital Signal Processing, Prentice-Hall, First Edition, pp. 2, 1983.</ref>. In some cases, m-D signals and systems can be simplified into single dimension signal processing methods, utilizing assumptions such as symmetry.