ianR
Veteran Member
There have been lots of comments about Fuji Super CCD and that it’s just interpolation at 6mp, it’s not really 6mp and what interpolation means. Here’s my crack at it.
Imagine you’ve lined up a load of snooker balls into a square. We’ll give them numbers the same as on the snooker table:
Red=1, Yellow=2, Green=3, Brown=4, Blue =5, Pink=6, Black=7
Here’s our first square with a ball missing.
Blue is 5.
5,5,5,5,5
5,5, ? ,5,5
5,5,5,5,5
What colour is it do you think? Blue you say. Good, what you’ve just done is interpolation. You’ve calculated the missing colour from what you see in the colours around it.
Now have a look at this. This time we’ve just got a square of 4 colours around the one missing in the centre. I can tell you that the snooker balls reflect the colour of the missing ball and it changes their colour slightly. So if they are blue and the missing ball is brown, then they’ll be a slightly brownie blue.
4.75, 4.75
?
4.75, 4.75
The four balls are slightly less than 5 which is on the brown side of 5, (brown is 4, blue is 5) so they are in fact brownie blue.
Now you’ll see you’ve got 2 possible answers for what the ball in the centre is.
Your two answers are that the snooker ball in the middle is either a brownie blue the same as the rest of them, or that the ball in the middle is brown .
So, you can represent the two answers thus:
Answer 1 where all the balls are brownie blue
4.75, 4.75
4.75
4. 75, 4.75
Answer 2 where the snooker ball in the middle is actually brown and the others are brownie blue because of the reflections.
4.75, 4.75
4
4.75, 4.75
Now answer 1 is what interpolation does in Photoshop and elsewhere. It looks mathematically at the balls around the missing one and gives you the average of what it sees. We know this is wrong in this case because we know a snooker ball can actually only be blue or brown and nothing in between.
However what I believe the Fuji interpolation does is more like Answer 2. It looks at the snooker balls- or really the photosites- the way we do. It says, if there’s a bit of brown coming from that direction, and another bit of brown coming from that direction, then what’s in between must be brown.
Now you can see that what we get from Fuji interpolation is actually adding detail rather than simply adding information, and that 6mp resolution is really a higher resolution than 3.3mp. And more importantly, it's accurate.
I hope that helps
Ian
Imagine you’ve lined up a load of snooker balls into a square. We’ll give them numbers the same as on the snooker table:
Red=1, Yellow=2, Green=3, Brown=4, Blue =5, Pink=6, Black=7
Here’s our first square with a ball missing.
Blue is 5.
5,5,5,5,5
5,5, ? ,5,5
5,5,5,5,5
What colour is it do you think? Blue you say. Good, what you’ve just done is interpolation. You’ve calculated the missing colour from what you see in the colours around it.
Now have a look at this. This time we’ve just got a square of 4 colours around the one missing in the centre. I can tell you that the snooker balls reflect the colour of the missing ball and it changes their colour slightly. So if they are blue and the missing ball is brown, then they’ll be a slightly brownie blue.
4.75, 4.75
?
4.75, 4.75
The four balls are slightly less than 5 which is on the brown side of 5, (brown is 4, blue is 5) so they are in fact brownie blue.
Now you’ll see you’ve got 2 possible answers for what the ball in the centre is.
Your two answers are that the snooker ball in the middle is either a brownie blue the same as the rest of them, or that the ball in the middle is brown .
So, you can represent the two answers thus:
Answer 1 where all the balls are brownie blue
4.75, 4.75
4.75
4. 75, 4.75
Answer 2 where the snooker ball in the middle is actually brown and the others are brownie blue because of the reflections.
4.75, 4.75
4
4.75, 4.75
Now answer 1 is what interpolation does in Photoshop and elsewhere. It looks mathematically at the balls around the missing one and gives you the average of what it sees. We know this is wrong in this case because we know a snooker ball can actually only be blue or brown and nothing in between.
However what I believe the Fuji interpolation does is more like Answer 2. It looks at the snooker balls- or really the photosites- the way we do. It says, if there’s a bit of brown coming from that direction, and another bit of brown coming from that direction, then what’s in between must be brown.
Now you can see that what we get from Fuji interpolation is actually adding detail rather than simply adding information, and that 6mp resolution is really a higher resolution than 3.3mp. And more importantly, it's accurate.
I hope that helps
Ian