The inversion of a Convolution equation, i.e., the solution for of an equation of the form

given and , where is the Noise and denotes the Convolution. Deconvolution is ill-posed and will usually not have a unique solution even in the absence of Noise.

Linear deconvolution Algorithms include Inverse Filtering and Wiener Filtering. Nonlinear Algorithms include the CLEAN Algorithm, Maximum Entropy Method, and LUCY.

**References**

Cornwell, T. and Braun, R. ``Deconvolution.'' Ch. 8 in
*Synthesis Imaging in Radio Astronomy: Third NRAO Summer School, 1988*
(Ed. R. A. Perley, F. R. Schwab, and A. H. Bridle). San Francisco, CA: Astronomical Society of the Pacific, pp. 167-183, 1989.

Press, W. H.; Flannery, B. P.; Teukolsky, S. A.; and Vetterling, W. T. ``Convolution and Deconvolution Using the FFT.'' §13.1 in
*Numerical Recipes in FORTRAN: The Art of Scientific Computing, 2nd ed.* Cambridge, England:
Cambridge University Press, pp. 531-537, 1992.

© 1996-9

1999-05-24