Overview of Linear Methods

If at the outset the data are very noisy and if the noise predominates in the Fourier frequency range needed to effect a restoration, constraints provide the only hope for improvement. The reason is that many of the noise values in the data would restore to physically unrealizable values by linear deconvolution. The constrained methods are inherently more robust because they must find a solution that is consistent with both data and physical reality. 

Andrews, H. C. (1975). In Top. Appl. Phys. Picture Processing and Digital Filtering, Vol. 6 (T. S. Huang, ed.), pp. 21-68. Springer-Verlag, New York. 

Andrews, H. C., and Hunt, B. R. (1977). Digital Image Restoration. Prentice-Hall, Englewood Cliffs, New Jersey. 

Backus, G., and Gilbert, F. (1970). Philos. Trans. R. Soc. London, A266, 123-192. 

and Halsey, G. W. (1981). Deconvolution of Absorption Spectra. Academic Press, New York. 

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