Table 1. Resolving-power, cycles per millimetre
High
Contrast
Low Contrast
Pan X
Tri X
Pan X
Tri X
Axis ...
49
26
29
14
Edge
47
23
27
11
Axis/Edge ..
1-04
1-14
107
1-27
Now it clearly would make little difference, in ranking
these two cases, whether we used high or low contrast
resolving power, Tri X or Panatomic X emulsion. This is
indeed obvious even from a glance at the graph. Yet the
transfer functions, at frequencies much lower than the
resolving powers, show a great difference in modulation
transfer, which must somehow be evidenced in the quality of
definition. How such differences can affect image quality is
discussed in the next section. In general the relative merit of
systems as judged by their resolving power will depend on
the shape of their transfer functions, the position of the
emulsion thresholds, and the target contrast. A low target
contrast is often valuable because it forces the comparison
into the low frequency region, where some systems have a
relatively poor transfer of modulation over a fairly wide
bandwidth, thus emphasising deficiencies which would not be
revealed by a high contrast test. In Figure 5 it is not the
difference of modulation transfer at any one frequency
which matters (we cannot interpret directly from resolving
power or spatial frequency to image quality at reciprocal
size) but the generally poor transfer over a substantial part
of the spectrum. In practice resolving-power usually ranks
systems in their correct order, because transfer functions
often have rather similar shapes, but its fundamental limita
tions must always be borne in mind.
We have implicitly assumed the use of sine-wave thresholds
in this account, but resolving-power is commonly measured
on bar targets ; can these be fitted into the model? A bar
target, like any other sharp-edged pattern, has a complex
spectrum, and the image contrast as a function of frequency
changes in different ways for different transfer functions.
It is possible to calculate “ response functions ” for bar
targets, assuming conditions such as a perfect lens or specific
amounts of aberration, but there is no generally applicable
relationship between the sine-wave and bar target responses.
In general the bar response is greater than the sine-wave
response at a given frequency, but the difference depends on
the state of correction of the lens and on the frequency.
Also, it is not evident which kind of threshold should be
used, since for a rigorously correct approach the threshold
would have to be determined with the same transfer function
as the one for which the resolution is being predicted, which
is absurd. Resolving-power prediction is in fact an emprical
technique and will not bear rigorous examination. Never
theless, it is still a useful tool if its limitations are recognized,
and enables the designer to estimate performance within say
plus or minus 10 per cent, which is helpful in choosing
between alternative systems.
Definition and the Transfer Function
One of the apparent advantages of the transfer function
is that it reveals the system performance over its whole
frequency range, but so far we have only tied it down to
image quality at one frequency, the resolving-power. How
can we make better use of the total information provided by
the function? Resolving-power as such has little or no
significance for aerial photography ; it persists because of
the inertia of established custom and because it is simple and
convenient in use. Spatial frequencies as such have no
significance at all ; the Fourier technique is valuable and
sometimes indispensable for research and system design, but
in the end our eyes operate on images, not on their Fourier
transforms. What really interests us in aerial photography
is definition as a function of detail size. The general desire
for information in such terms is expressed by the common
mistake of taking the value of the transfer function at some
frequency as an index of the quality of an image whose size
is the reciprocal of the frequency. A “ frequency ” is of
course a repetitive sinusoidal pattern without beginning or
end. A large object is not a low frequency any more than
a small object is a high frequency ; on the contrary, a small
object is a wide bandwidth if transformed into frequency
terms. If we wish to make deductions directly from transfer
functions we must keep consistently to frequencies, and not
confuse them with sizes.
In our simplified one-dimensional space, a small object is
a narrow bar, which can stand for the shapes of aerial
photography, in a preliminary consideration. We could
assume that some ground detail size was the smallest of
interest and use the corresponding bar width in image scale
as a critical dimension at which to study image quality. Our
interest in the quality of the bar image might be reduced to
two cases ; when it is just worse than a perfect image, and
when it is so degraded that its presence can only just be
detected. Before we can operate on the bar with transfer
functions we must transform it into its frequency spectrum,
which is easily done from knowledge of its width and the
sin x/x relationship. Figure 2 shows part of the theoretical
spectrum for lines 1 millimetre and 1/10 millimetre wide,
illustrating the general principle that narrow lines have a
wide bandwidth and vice versa. Remembering that the
spectrum theoretically extends to infinity it will now be
apparent that there is no such thing as a theoretically perfect
reproduction of any bar, however wide, for its spectrum will
always extend beyond the finite cut-off point of any optical
system. Transfer functions, for the normal photographic
case of incoherent light, fall progressively towards the higher
frequencies, so that the outer lobes of the spectrum must
always suffer some attenuation, and in practice the cut-off or
the drop to a very low value may occur well below the first-
zero frequency. Figure 6 shows the spectra for bar-widths
FREQUENCY CYCLES PER M.M.
Figure 6. Spectra for Various Line Widths with
Transfer Function for f/5.6 Lens and Plus X Aerecon
Emulsion
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