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Image Deconvolution

Deconvolution is performed by dividing the Fourier transform of the blurred image by that of the psf image (complex division because the transforms have real and imaginary components). The amount of improvement in resolution is limited by the amount of random noise in the images. Various methods are used to limit the influence of the noise. The following interactive Java tutorial shows Wiener deconvolution and the consequence of too small a noise limit, and also compares the result of deconvolution (which improves detail resolution) to unsharp masking (which simply increases the contrast of already resolved detail).

Interactive Java Tutorial
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The tutorial initializes with a blurry image of a spiral galaxy appearing in the Specimen Image window. The buttons display the Original (blurred) image, the result of applying an Unsharp Mask to increase contrast (but not resolution), the measured Point Spread Function, the Deconvolved result, or the Noisy deconvolved result that is obtained when too small a Wiener constant is used.

Contributing Authors

John C. Russ - Materials Science and Engineering Dept., North Carolina State University, Raleigh, North Carolina, 27695.

Matthew Parry-Hill, and Michael W. Davidson - National High Magnetic Field Laboratory, 1800 East Paul Dirac Dr., The Florida State University, Tallahassee, Florida, 32310.


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