Abstract
In principle, the extension to multidimensional \(\underline{z}\) of the concepts of regularization from Chapter 2 and the static and dynamic estimators of Chapters 3 and 4 is perfectly straightforward. The only inherent limitation in the developed estimators is that the unknowns \(\underline{x}\) and measurements \(\underline{m}\) are required to be column vectors. Attempting to substitute matrices (e.g., a measured image) for \(\underline{m}\) will yield meaningless results.
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© 2011 Springer New York
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Fieguth, P. (2011). Multidimensional Modelling. In: Statistical Image Processing and Multidimensional Modeling. Information Science and Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7294-1_5
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DOI: https://doi.org/10.1007/978-1-4419-7294-1_5
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