Stranica 35 [35]
OCR
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
