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CHARISM A I 7
Photo-induced luminescence images produced in the presence of ambient stray radiation
will contain information on both the luminescence properties of the object and the stray
radiation reflected from its surface. In order to decouple these contributions, a measurement
of the reflective properties of the surface under investigation must be made by inserting a
reflectance standard in the photo-induced luminescence image, Figure 1-22(a).’? These
reflectance standards (e.g. the 99% Spectralon diffuse reflectance standard, as described in
Chapter 2) are non-luminescent and thus appear dark in the absence of stray radiation but
allow the evaluation of any ambient (and parasitic) stray radiation as RGB (or XYZ) values,
Figure 1-22(b).
These average values are multiplied pixel by pixel and channel by channel by a corrected
reflected image in the same spectral region as the luminescence image, in this case a
visible-reflected image Figure 1-22(c), which has been transformed into a reflectance map of
the object by rescaling the image from 0 to 1 (dividing each pixel in the reflected image by
the average grey level value on the 99% reflectance standard). The result is an image which
mathematically reconstructs the ambient stray radiation, Figure 1-22(d). This can then be
subtracted pixel by pixel from the photo-induced luminescence image to produce the
corrected image, Figure 1-22(e).
The above method can also be applied to visible-induced infrared and visible-induced visible
images (although the post-processing of this image type is outside the scope of this work)
and will be integrated into a workflow for the development of the post-processing software
addressing the correction of luminescence images (see Chapter 3). The optimisation of
experimental procedures to minimise the presence of parasitic and ambient stray radiation
as well as the data acquisition requirements for post-processing are discussed in Chapter 2.
Version No. 1.0 27 Date : 14/10/2013