Quote:
Originally Posted by alocky
Not entirely true - the signal strength is indeed being increased by the effective integration time, but the noise power decreases as a result of the stack. Consider the image to be composed of signal + a random noise. The next sub is composed of the same signal, but a different realisation of the random noise. Adding the two random signals together gives a new random signal with less power than either of the two original noise components (because the 'noisy' pixels don't occur in the same place), but you get twice the signal. With a bit of simple maths it's easy to show that if the noise is truly random, the signal to noise is now 1.41 times better than either of the originals. Here's a link to one of the awful books I remember from my undergrad last century that describes a related application of the theory...
<http://books.google.com.au/books?id=oRP5fZYjhXMC&pg=PA185&lpg= PA185&dq=stacking+random+noise&sour ce=bl&ots=C9-fMrZslb&sig=VBTxJVg1HUhsRmiZEIwUO_y 7bf8&hl=en&sa=X&ei=MlWBUIeTI5G0iQfS rIC4BA&ved=0CEkQ6AEwBg>
cheers,
Andrew.
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Sorry Andrew, I'm not convinced. Ignoring inconvenient practical issues like read noise, whether I collect and integrate exactly the same stream of photons in a single exposure or across multiple exposures with the same total length I get exactly the same data in the end.