Suppose now we have two functions with equal input variation Ii and 
frequency \) hut different time functions. When presenting both signals 
to the eye the higher frequencies present in 2b will be filtered out more 
than the repetition frequency 03* So that to for the sawtooth wave form 
fig, 2b is less than to for the sine fig, 2a. With the right choise of 
T 3 the sine will be detected as flickering while the sawtooth gives the 
impression of no flickering. 
CONCLUSION 
Based on the approximate assumption that the eye-brain mechanism 
acts as a low-frequency pass filter for intensity variation: a sine 
wave will have the highest critical frequency for flicker detection 
compared to other waveforms with equal variation. 
A certain spectral signature class can now be extracted by resequencing 
the order of presentation in time of the different band transparancies 
in such a way as to make the intensity of a test field to appear varying 
a sinoidal way, see fig. 3 « 
resequence 
fig. 3 Resequencing of the time series towards a sine—like form 
When resequencing alone is not sufficient to approximate a sine wave, 
different weight may be given to different bands by means of a callibrated 
grey-wedge (fig. 4 ). Wi are the respectively weights given to the bands.