Optical Spatial Frequency Filtering of Image Sensors ?

The point sampler suggested by the Shannon-Nyquist is a perfect point sampler (i.e. integration area/time approachin zero). For this to allow perfect recreation of general baseband signals you want to do perfect bandlimiting prior to the sampler (anti-aliasing prefilter) using a non-realizable sin(x)/x filter.

Assume that the active sensel + micro lense has a 100% "fill-rate". Then each sensel is integrating light spatially in a rectangular continous function. A boxcar integrator is a lowpass filter, although not a particularly good one. Then add the (common) lowpass pre-filter. Then add the lense PSF. Then add camera/subject movement. All of those "smear" the signal spatially, reducing high-(spatial-)frequency variation.

In my view the quote seems reasonable, except the claims about what is the "true" lowpass filter: it is what it is, every aspect that contribute to a reduction in high-frequency energy is in practice a lowpass filter. For indication of what would have happened if the fill-rate was extremely low (each sensel approaching a point-sampler), check out the results obtained with Canon 5Dmk2 for video when reading every n-th line to form a 1080p video frame.

Conclusion:

It is very hard to do a sub-pixel accurate characterization of a complete camera. But gut-feeling and practice suggests that it is quite far from an ideal Shannon-Nyquist spatial sampler.

-h