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Multidimensional signal processing
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<p>In <a href="/facts/Signal_processing/Npaja6zb">signal processing</a>, multidimensional signal processing covers all signal processing done using multidimensional signals and systems. 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. In m-D digital signal processing, useful data is sampled in more than one dimension. Examples of this are <a href="/facts/Image_processing/zenalNCf">image processing</a> and multi-sensor radar detection. Both of these examples use multiple sensors to sample signals and form images based on the manipulation of these multiple signals. Processing in multi-dimension (m-D) requires more complex algorithms, compared to the 1-D case, to handle calculations such as the <a href="/facts/Fast_Fourier_transform/caT7UUCh">fast Fourier transform</a> due to more degrees of freedom. In some cases, m-D signals and systems can be simplified into single dimension signal processing methods, if the considered systems are separable. </p><p>Typically, multidimensional signal processing is directly associated with <a href="/facts/Digital_signal_processing/PEG7azr8">digital signal processing</a> because its complexity warrants the use of computer modelling and computation. A multidimensional signal is similar to a single dimensional signal as far as manipulations that can be performed, such as <a href="/facts/Sampling_(signal_processing)/xxck7aLN">sampling</a>, <a href="/facts/Fourier_analysis/sUA8JP6q">Fourier analysis</a>, and <a href="/facts/Filter_(signal_processing)/vydJCNle">filtering</a>. The actual computations of these manipulations grow with the number of dimensions. </p>