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#1
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I did an analysis of the D300 vs the 40D image quality using raw data taken under controlled conditions.
The end result is that the raw data are quite comparable, with the 40D doing better by some measures, and the D300 faring better by other criteria. Here's the URL: http://theory.uchicago.edu/~ejm/pix/...300_40D_tests/ |
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#2
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Even though you're probably not going to get as much response here as on DPReview, I just wanted to let you know that your info (and mentioning it here on OPF) is highly appreciated. Your write-up is well done and provides an informative overview. Of course there are also other factors besides noise and quantum efficiency that define image quality, e.g. MTF response, but it is important to know how our basic building blocks (photons) are converted into (hopefully) clean data. Bart |
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#3
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Just a question, relating to 'gain' determination. As a side note, I'm not sure "quantum efficiency" is a better descriptor than "gain". To me QE is more about the percentage of photons from the incoming photon flux that do get converted to charge. I also agree that "gain" is not an entirely appropriate description, but it has a tradition (in electronic amplification). You determine 'gain' from a single exposure point (which saves time). Do you think you might get an even more accurate/robust number by determining the slope of a linear regression between several exposure levels close to saturation? As an example, from my 1Ds2: ![]() Note: the saturation/clipping exposures have been omitted from the regression calculation/chart, due to non-linear response. Bart |
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#4
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As for semantics, I think QE is more appropriate, or at least 'relative QE'; if you divide the per pixel measurement by the pixel area, you get an unnormalized measure of the photons being captured per unit area (Table 8 of my little essay); so this is a solid number whose ratio between different sensors is their ratio of absolute QE's. And on another note, I was unhappy with the quality of the test I used for judging relative sensitivity, so I redid it and the revised results are in an update of the webpage. Bottom line -- both cameras expose similarly, the D300 is NOT more sensitive. Last edited by Emil Martinec; November 28th, 2007 at 08:09 PM. |
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#5
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There is another benefit to a linear regression though, it takes away the dependency on (the accuracy of) the read noise determination. But since the read noise will probably be determined anyway, it just shows that there are more routes leading to the same destination. Personally I like the visual feedback that a trendline offers, but then as a photographer I have a visual orientation. Bart |
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#6
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A couple more data points to add. I looked at the ISO extension. The low ISO extension appears to be ISO 125 in actual fact (based on the raw level compared to ISO 200, shot under the same conditions). Saturation at the low ISO is the same raw level as at ISO 200. The high ISO extension isn't obviously implemented in software -- there are no gaps in the raw histogram as there is in Canons. |
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#7
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Also, Nikon tends to rescale data after capture. You will often see a periodic pattern superimposed on the full histogram - this means that the numbers have been altered, and if there were an integer push, it could be somewhat hidden by this. Gaps in every other histogram value tells you that the push is integer, but the lack of gaps does not prove that there is no such push. |
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