Photographic Dynamic Range (PDR) is a More Useful Measure than the DxOMark Landscape Score

Started Apr 17, 2015 | Discussions thread
Detail Man
Detail Man Forum Pro • Posts: 17,073
Re: Photographic Dynamic Range (PDR) is a More Useful Measure than the DxOMark Landscape Score
2

bclaff wrote:

Horshack wrote:

Detail Man wrote:

bclaff wrote:

... The PDR criteria operates in the PTC region well above SNR=1 (at least until we get 384Mp sensors!).

In this region the subtle interplay of read noise, other noise, small amounts of photon noise, slope due to Full Well Capacity (FWC), etc. is captured.

It seems that (especially thses days, with higher performance image-sensors), Readout/Dark noise component are effectively "numerically swamped" by Photon Shot Noise. Rather "subtle", indeed.

But there's a distinct qualitative difference of read noise vs shot noise. John Sheehy once posted a simulation of an ISO 1,000,000 image with zero read noise and it looked more natural than a much lower ISO image with read noise.

In Detail Man's comment I think "swamped" is too strong a term.

My use of "swamped" refers to the existence of a relatively low numerical output sensitivity-factor existing as a function of Read/Dark noise components.

In this area of the PTC we are still very much in the read noise dominated region.

At (linear) SNR = 20 ?

If an image or an area of an image is entirely read noise then it has no detail and is essentially black.

How so where it comes to periodic noise components ? Random components are "invisible" ?

To have a photograph you must have photons and therefore photon noise.

To generate RAW image-files (with whatever internal system "warts" exist) is "painting with light" (or, more specifically, "painting with some amount of luminance"), aesthetics aside ...

Characterizing the photographic use of a sensor in a region of the PTC that is devoid of photon noise is, as I have stated more subtly above, brain-dead.

The phrase "brain dead" seems a bit dissmissive (of phenomena that can potentially "matter").

Here's a hypothetical.
Two sensors that are the same in every way except that one has a higher FWC.
(You can even imagine them both with zero read noise, DSNU, etc.)
Photographically these sensors are not identical.
You will get more useful dynamic range out of the one with the higher FWC.

The (minimum low-level analyzed) Photon Shot Noise components (relative to Read/Dark noise components) will scale in magnitude with the square-root of increases in "Full Well Capacity".

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Prior to DxO Labs releasing test results for the Olympus E-M5, I did some comparisons analyzing very deep shadow regions of reliable (sensor-level Exposure matched, nearly identical scene) RAW test shots from Panasonic DMC-GH2 and E-M5 at their base ISO settings. The GH2 clips blacks, the E-M5 does not. Differences in the shapes of the noise distributions could be seen at <= SNR=12 dB - but appear to have had minor numerical impact on the interpolated DxOMark SNR data from which the DxOMark DR spec is derived.

The Sensorgen.info (DxOMark data derived) base-ISO Read Noises listed are comparable:

http://www.sensorgen.info/PanasonicLumix-DMC-GH2.html

http://www.sensorgen.info/OlympusOM-D-E-M5.html

Estimates were made visually. In all groups of 2 images below, the order is GH2 followed by E-M5. Differences seen (as a function of SNRs 12 dB and 18 dB) were not large. As it turnd out, the E-M5 DR surpasses the GH2's DR almost entirely as a result of it's (nearly doubled) FWC compared to GH2.

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SNR ~ 12 dB (where Read/Dark Noise appears to dominate over Photon Shot Noise). The Standard Deviation of the E-M5 is approximately 0.5 EV higher than that of the GH2:

The location of the Mean Value is shown as a vertical gray line in the histograms below:

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(3 pixel-width) arithmetically averaged view; corresponding histograms allowing easier assessment:

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SNR ~ 18 dB (where Photon Shot Noise appears to dominate over Read/Dark Noise). The Standard Deviation of the E-M5 is only then approximately 0.5 EV lower than the GH2:

The location of the Mean Value is shown as a vertical gray line in the histograms below:

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(3 pixel-width) arithmetically averaged view; corresponding histograms allowing easier assessment:

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It seems that with differing FWCs in such a case as above (the E-M5 image-sensor FWC is around twice that of the GH2 image-sensor) - and where the (Sensorgen derived from DxOMark data) per-photosite Read Noise is very close to being numerically identical (and the pixel-pitches of the individual image-sensors are similar in value) - the "efficacy" of simply having a higher FWC is (remains) less influential - at low (enough) illumination levels.

People attempting to "push" a dim image in processing "fly by their minds' eyes". If shadows deep enough to matter within those persons' in-process viewing exist, Read/Dark noise will matter ?

DM

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