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Application and Optimisation of the Spatial Phase Shifting ...

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2.2 First-order speckle statistics 21<br />

positive correlation <strong>of</strong> I <strong>and</strong> I x <strong>and</strong> <strong>the</strong> anticorrelation <strong>of</strong> I <strong>and</strong> ϕ x , an anticorrelation <strong>of</strong> I x <strong>and</strong> ϕ x results<br />

that is impressively illustrated by <strong>the</strong> figure: <strong>the</strong> worm-like structures <strong>of</strong> high Fϕ x F circumscribe <strong>the</strong> bright<br />

speckles (being regions <strong>of</strong> high FI x F) almost exactly. The white boxes assist in finding examples. The<br />

pinched maxima <strong>of</strong> Fϕ x F indicate phase singularities (see Fig. 2.17).<br />

Fig. 2.9: Maps <strong>of</strong> I x (left) <strong>and</strong> ϕ x (right). White boxes allow comparison <strong>of</strong> details.<br />

2.2.4 Gradients in two dimensions<br />

The previous treatment, although particularly relevant for our subject <strong>of</strong> spatial phase measurement, does<br />

not provide a complete insight into <strong>the</strong> structure <strong>of</strong> speckle intensity <strong>and</strong> phase. Therefore we consider<br />

also <strong>the</strong> two-dimensional gradients,<br />

⎛ I ⎞<br />

∇ I = I<br />

2<br />

+ I<br />

2<br />

y<br />

x y with θI<br />

= arctan⎜<br />

⎟<br />

⎝ Ix<br />

⎠<br />

. (2.27)<br />

⎛ ϕy<br />

⎞<br />

∇ ϕ = ϕ<br />

2<br />

x + ϕ<br />

2<br />

y with θϕ<br />

= arctan⎜<br />

⎟<br />

⎝ ϕ ⎠<br />

The pdf's in terms <strong>of</strong> F∇IF, F∇ϕF are easily obtained from functions involving I x , I y , ϕ x , ϕ y by integrating<br />

2 2<br />

x y<br />

over θ I <strong>and</strong>/or θ ϕ on <strong>the</strong> circles given by I + I <strong>and</strong>/or ϕ + ϕ , which gives factors <strong>of</strong> 2πF∇IF<br />

<strong>and</strong> 2πF∇ϕF, respectively. This changes (2.8) to<br />

from which we can derive<br />

x<br />

2 2<br />

x y<br />

I I<br />

I I<br />

p( I , ∇I<br />

, ∇ ) = exp ⎛ ⎞<br />

⎜−<br />

⎟ ∇ ∇ ϕ ⎛<br />

exp − ∇ 2<br />

1<br />

⎞ ⎛<br />

exp⎜<br />

I ⎝ I ⎠ C<br />

⎜<br />

⎝ IC ⎟ − ∇ ϕ<br />

ϕ<br />

4 ⎠ ⎜<br />

0 2 8 0 ⎝<br />

2C0<br />

2<br />

⎞<br />

⎟ , (2.28)<br />

⎟<br />

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