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Application and Optimisation of the Spatial Phase Shifting ...

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52 Electronic or Digital Speckle Pattern Interferometry<br />

greatly extended <strong>the</strong> possibilities <strong>of</strong> ESPI <strong>and</strong> enhanced <strong>the</strong> attainable accuracy <strong>of</strong> phase measurements by<br />

a factor <strong>of</strong> about 10. Whereas quantitative evaluation <strong>of</strong> correlation fringes requires sophisticated<br />

automation algorithms (see Chapter 4.1) or laborious interactive procedures, <strong>the</strong> phase shifting method<br />

automatically yields complete phase maps, so that today <strong>the</strong> correlation fringe methods have mostly been<br />

superseded by phase-shifting ESPI.<br />

To introduce temporal phase sampling, or stepping, we establish <strong>the</strong> expression<br />

In ( x, y, tn ) = Ib ( x, y) + M<br />

I<br />

( x, y) ⋅ cos( ϕO ( x, y, tn ) + α<br />

n<br />

( x, y, tn<br />

))<br />

(3.12)<br />

with<br />

n: number <strong>of</strong> phase sample<br />

I n : measured intensity in <strong>the</strong> n th frame<br />

I b : bias intensity; corresponds to O+R<br />

M I : intensity modulation; corresponds to 2LOR<br />

ϕ O : speckle phase<br />

α n : additional (known) shift <strong>of</strong> ϕ R ; generally, α n =nα <strong>and</strong> n ∈ {0,..,N-1}.<br />

For now, we restrict ourselves to static phase shifts, since a distinction between temporal <strong>and</strong> spatial<br />

phase ramping must be made that will be described in 3.3 <strong>and</strong> 3.4.4, respectively. Also, ϕ R has been set to<br />

zero as above. All quantities depend on x <strong>and</strong> y due to <strong>the</strong> underlying speckle field. The phase shift<br />

α n (x,y,t n ) may be, but in practice seldom is, spatially uniform; various numbers N <strong>of</strong> phase samples can be<br />

used. Assuming O(x,y) <strong>and</strong> R(x,y) to remain temporally quasi-stable, we still have to account for possible<br />

temporal fluctuations <strong>of</strong> ϕ O <strong>and</strong> ϕ R . For convenience we put <strong>the</strong>m all into ϕ O .<br />

The set <strong>of</strong> equations given by (3.12) can easily be linearised; <strong>the</strong> principle is outlined in Appendix C. It<br />

contains three unknowns, namely I b , M I , <strong>and</strong> ϕ O , <strong>and</strong> hence we need at least three linearly independent<br />

measurements <strong>of</strong> <strong>the</strong> I n (N3), with pairwise different α n , to solve unambiguously for ϕ O . This can be<br />

done by generating an expression that gives tan(ϕ O )=sin(ϕ O )/cos(ϕ O ); i.e. one needs a numerator<br />

proportional to <strong>the</strong> sine <strong>and</strong> a denominator proportional to <strong>the</strong> cosine <strong>of</strong> ϕ O . To achieve this, <strong>the</strong> I n are put<br />

toge<strong>the</strong>r as<br />

ϕ<br />

O<br />

N −1<br />

∑a I<br />

modπ<br />

= arctan<br />

n=<br />

0<br />

N −1<br />

∑b I<br />

n=<br />

0<br />

n n<br />

n n<br />

with<br />

∑<br />

n<br />

a<br />

n<br />

∑<br />

= b = 0, (3.13)<br />

n<br />

n<br />

which is valid for any phase-sampling scheme. In all <strong>of</strong> such formulae, <strong>the</strong> coefficients in numerator <strong>and</strong><br />

denominator add up to zero, which cancels <strong>the</strong> contribution from I b . The simplest expression to evaluate<br />

<strong>the</strong> recorded data relies on equally spaced α n that are uniformly distributed in <strong>the</strong> interval [0,2π); it is well

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