On Oct 9, 2013, at 10:52 AM, Matthew Hunt <m...@pobox.com> wrote:
>> 
>>> It seems to me that if you had a rear illuminated sensor, with no space
>>> between the pixels, and it had no bayer filter, then aliasing/moire would
>>> not happen, because the light value would be averaged over the whole sample.
>>> 
>>> It's the discontinuous aspect of what is effectively three overlayed photos
>>> that is causing the aliasing.
>> 
>> Aliasing occurs regardless of how close together the cells are because the 
>> cells are discrete. This kind of aliasing is a function of discrete 
>> mathematics.
> 
> I think you're dismissing Larry's point too easily. When we first
> learn about aliasing, it's usually in the context of the Nyquist
> sampling theorem, which (in the time domain) assumes instantaneous
> sampling. In a pixel array, "instantaneous sampling" would correspond
> infinitely small (point-sized) pixels (separated by a certain pitch).
> 
> Enlarging the sensitive area of the pixels (relative to their pitch)
> does provide some anti-aliasing effect. ... 

Some amount of antialiasing effect is not the same as eliminating aliasing, 
making it "not happen". 

Aliasing will continue to exist regardless of how close together the bins are 
because they are handled as discrete elements in an 2D array. Larry's statement 
about what causes aliasing is incorrect. 

Aliasing occurs at the discrete discriminant: simplistically, does this object 
belong in bin a or bin b? Aliasing in discrete image collection apparatus 
occurs when the sampling frequency combined with the nature of the phenomenon 
creates a multi-valued solution to that question, the object is replicated into 
several bins (usually at different levels of intensity).

Lots of things can help to attenuate aliasing, some to the point at which it is 
no longer visible or significant, but that doesn't mean aliasing does not 
happen. It's one of the issues when using discrete mathematics to represent 
continuous, Real-valued phenomena.

G
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