Deblurring Gaussian Blur

Cover Deblurring Gaussian Blur
Deblurring Gaussian Blur
Robert a Hummel
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Z . . "^^ ^, 2"-2"' y"-2™ = H^(y) - m! (n-2m) ! m=0 • The theorem above could have been proved using the convolution theorem and by computing the Fourier transform of K^{x) . We will nonetheless compute V.^ in order to show that the multiplier for Kj^ approaches, pointwise, the inverse of the multiplier for the operator T (see (2. 2)).
Observation 2 : Kj^(u) ) ■*■ e"^ '^ pointwise as N -»• » .
N/2 . . K 2 Proof : K„(co) = E J-lii—. Rf e"^ H2, ^(x)] (u), where F stands for the k=0 -^ k!2'^ ' Fou
...rier tansform operator. Now, F[e-A2i, (x)J(a3) = f[ (-1)2^^ i^ (e"^ )] M = (io))2k/;r. E^^/'' .
Thus %' (-^^" . (-1)^ . 2^ /7 e-'/^ k=0 ♦^ 1^1 2^ e - ^, since otherwise the Fourier transforni of that function would be e'^ ', which is impossible.
2 _ 2 Kj^(x) does converge in L (e '^ dx), but that does not imply polntwlse convergence to any function. We accordingly have stable deblurring when using the kernels Kj^(x), where stability is measured in terms of 9-2 deviation from a polynomial of degree N, and the L (e ^ dx) norm is used as the metric.


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