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Application and Optimisation of the Spatial Phase Shifting ...

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3.2 <strong>Phase</strong>-shifting ESPI 59<br />

ϕ<br />

ϕ<br />

O,<br />

i<br />

O,<br />

f<br />

I3i<br />

( x, y) − I1i<br />

( x, y)<br />

( x, y) mod 2π<br />

= arctan<br />

I ( x, y) − I ( x, y)<br />

0i<br />

2i<br />

I3 f ( x, y) − I1f<br />

( x, y)<br />

( x, y) mod 2π<br />

= arctan<br />

I ( x, y) − I ( x, y)<br />

0 f 2 f<br />

, (3.22)<br />

<strong>and</strong> <strong>the</strong>n determine <strong>the</strong> phase change<br />

( O, f<br />

O,<br />

i )<br />

∆ϕ ( x, y) mod 2 π = ϕ ( x, y) mod 2π − ϕ ( x, y)<br />

mod 2π mod 2π<br />

. (3.23)<br />

Admittedly, this requires more information than <strong>the</strong> phase-<strong>of</strong>-difference approach – 8 images with (3.16),<br />

<strong>and</strong> 6 with (3.17) –, but eliminates all <strong>the</strong> problems brought about by <strong>the</strong> ambiguity <strong>of</strong> intensity<br />

differences. Also, <strong>the</strong> pixels are truly regarded as independent entities, which accounts appropriately for<br />

<strong>the</strong> speckle nature <strong>of</strong> <strong>the</strong> wavefront to determine. In this case, <strong>the</strong> phase calculation reproduces <strong>the</strong><br />

expected fringe pr<strong>of</strong>ile ra<strong>the</strong>r well, as <strong>the</strong> white curves in Fig. 3.3 demonstrate. The displayed sawtooth<br />

edges are somewhat blurred by <strong>the</strong> averaging over <strong>the</strong> residual speckle noise; but <strong>the</strong> corresponding<br />

measured phase map, shown in Fig. 3.7, is <strong>of</strong> excellent quality when we compare it with <strong>the</strong> o<strong>the</strong>r<br />

unfiltered results obtained so far. In that case, σ ∆ϕ = 18.2° without any low-pass filtering. Also, <strong>the</strong> pdf <strong>of</strong><br />

measured phases is now uniform, which shows that computational biases are negligible for this method.<br />

Fig. 3.7: Result <strong>of</strong> calculating ∆ϕ with <strong>the</strong> difference-<strong>of</strong>-phases method.<br />

This confrontation clearly indicates that it is necessary to genuinely measure <strong>the</strong> speckle phases twice to<br />

get <strong>the</strong> best sawtooth image. While an approximate recovery <strong>of</strong> information from reduced data sets is<br />

possible, <strong>the</strong> performance <strong>of</strong> this approach remains restricted. Therefore, <strong>the</strong> performance data given in<br />

chapters 5 <strong>and</strong> 6 are based on sawtooth images from <strong>the</strong> difference-<strong>of</strong>-phases method without exception.<br />

A practical merit <strong>of</strong> keeping ready <strong>the</strong> speckle phase distributions for every recorded object state is that<br />

one need not compare all data to <strong>the</strong> initial state anymore. In o<strong>the</strong>r words, it becomes possible to track<br />

phase differences incrementally even if <strong>the</strong> first <strong>and</strong> last state show decorrelated speckle patterns [Flo93].<br />

We will come back to this issue in Chapter 6.7.

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