ABSTRACT
The optical absorption of thin-film thermal infrared detectors was calculated as a function of wavelength, pixel size, and area fill factor by use of the finite-difference time-domain (FDTD) method. The results indicate that smaller pixels absorb a significantly higher percentage of incident energy than larger pixels with the same fill factor. A polynomial approximation to the FDTD results was derived for use in system models.
ABSTRACT
Image sampling effects have been variously quantified as aliased signal, spatial signal, and spatial noise. However, a relationship between these characteristics and human object recognition has not been established in a coherent, mathematical form. We present a heuristic study that characterizes the performance degradation that is due to the spurious response of a sampled imaging system as an effective increase in system blur. A character recognition experiment was performed in which 20 observers responded to 3500 character pairs of blur and sample spacing. A baseline was created where the probability of character recognition was determined as a function of blur without sampling. The sampled characters were then compared with this baseline so that the effect of sampling on character recognition could be determined. Finally, an increase in blur was established as a function of spurious response, which describes the overall effect of sampling on observer character recognition.
