(...)
@SpcCb: can you share some more details about how you did the math?
(I tried to understand the AMaZE algorithm, but only figured out how to call it; if you can shed some light, I'm interested)
I will try to be simple, I mean I hope I will be..
We can refer to what
we discussed in the dual_iso thread about SVE images to explain the DR in this case:
We can see how is the gain with dual_iso in a perfect world (calculations done @10E-15 & results round @10E-3);
With a single frame:
DR
sf = 20log
10[(i
max / i
min)] = 20log
10[16384]
DR
sf = 84.288 dB
With a SVE image with ISO 100/800 like in dual_iso:
DR
SVE = 20log
10[(i
max / i
min) (e
max / e
min)]
ISO 100/800, so e
1 = 64e
0DR
SVE = 20log
10[16384×64]
DR
SVE = 120.412 dB
-> Wooh, on the paper it is monstrous!
However I suppose you prefer a more physical approach to compare with samples, then from DR
SVE we get:
DR
di = log
2[(( WL - offset ) / (σ
Smaxx̄ σ
Smin) ) (s
max / s
min)]
Note: we should use the same WL and offset in both frames; because of course _for example_ with a different offset it will generate noise (!).
In my case I used a 5D2;
With a single frame, in the best case and with thermal considerations (short exposure time, up to CMOS @40°C):
DR
sf = log
2(( 15760 - 1024 ) / 6.47 )
DR
sf = 11.153 stops
With dual_iso 100/800:
DR
di = log
2[(( 15760 - 1024 ) / √{( 8² + 6.47² ) / 2 }) 64 ]
DR
di = 16.984 stops
Then, now we have basic maths to do projection of our SVE, but be careful it does not take consideration of the PSF + MTF, so the wavelength of the source, etc.
To do that we have to introduce light diffraction model in the equation.
I will not demonstrate the maths here, it's a bit complex and I think not relevant to make projections with samples we use: It requires calibrated sources, lens modelisation, etc.
BTW, in my study with a off-continuum mono-spectral source (λ = 0.656μm,
Hα source) I recorded an average difference of 3.9% and a sigma difference of 5.0% (both ±10E-1) between single frame image and dual_iso image by using AMaZE both for CR2->DNG & DNG demosaicing.
This mainly because I use 1 of 4px in the Bayer Matrix in this case and there's an intrication between the dual_iso SVE and the Bayer Matrix.
Beside, a similar effect should be observed in regular photography.
About AMaZE, what is very interesting is this algorithm do multiple analyses to proceed to the reconstruction.
There's a (spatial) vector analyse of structures (macro-blocks &
special sophisticate diagonal), color/chromic analyse and _in the lasts versions_ a CA analyse, and there's a Nyquist texture (pattern) analyse to make better area interpolations.
IMHO, it is very smart from Emil Martinec _and certainly not foreign to the fact what Emil works in Astrophysics_ because this is well know in our domain what without taking consideration of the light nature it is hard to be close to the reality (even we never match her).
With this algorithm there's a significant SNR improvement face to other reconstruction algorithms; I ever measured +25% on hard cases face to VNG HAD HFFE etc. So compared to the simple mathematical projection where just an average is considered, we should see a gain, even if it's not +2 stops or -50% of sigma.
When we see SNR gain, we see DR gain. So, voilà.
Don't hesitate to point me what you don't find clear, I will see how to make it more simple or from a different point of view.
