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2 0.173 33.4 2.05 2.78 7.73 0.224 1.14 0.256 15.3 1.93 0.516 0.565<br />

3 0.145 47.5 3.02 3.36 11.3 0.123 1.65 0.216 21.4 2.93 0.402 0.777<br />

4 0.127 62.0 4.02 3.80 14.4 0.071 2.16 0.191 27.4 3.86 0.313 0.99<br />

5 0.115 75.6 4.96 4.18 17.5 0.043 2.65 0.172 33.8 4.98 0.247 1.21<br />

N = number of applications.<br />

m1 = 1/ MTF50 2<br />

Blur more: m2 = (m1-3.6)/14.52<br />

Blur: m3 = (m1-3.6)/6.067<br />

Edge with Blur More applied twice<br />

Unmagnified 4X Magnified<br />

These results confirm an inverse square relationship between MTF50 and the number of Blur More and Blur applications. Two<br />

Blur more operations equals five Blur operations. m2 and m3 are approximately equal to the number of applications.<br />

Each application of Blur More cuts the response<br />

at 0.25 cycles per pixel (half the Nyquist<br />

frequency) by half. This suggests an equation<br />

(though probably not the one used to calculate<br />

BxU): BxU = -log2(MH) = -3.322 * log10(MH),<br />

where MH is the MTF at 0.25 cycles per pixels<br />

(half-Nyquist).<br />

The calculation of variance σ 2 is somewhat tricky. The equation is derived from probability theory, but it can behave strangely.<br />

σ 2 can have negative values because the line spread function LSF(t), which is the derivative of the averaged pulse, can have<br />

negative values (undershoots) that never occur for probability density functions.<br />

First, the mean location of LSF(t) needs to be calculated. This can be done using LSF or LSF 2 . The latter seems to work better.<br />

E(t) = Σ ti LSF 2 (ti) / Σ LSF 2 (ti)<br />

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