Scanning black and white film

jlbruyelle

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All this reasoning is pointless unless you quantify the "quite a bit", which can be large or negligible. Please don't make blanket statements. Your last statement, in particular, does not mean that the useful quantification limit is not higher than 8 bits.

In fact, if the pixels are small enough (then under certain conditions) a one bit ADC is sufficient to recover all of the information in the image.

This is a very hypothetical case that never happens in real life, unless you are scanning with a microscope (and even then...). What we call "grain" is not composed of the individual silver particles but of agglomerated particles, so they are not black/white but grey-level, and the noise level of this grain can be very low.

All this is pretty well known among the signal processing community. I am not a member of that community

I am Not that I am particularly proud of it, but I can at least say that my profesional skills and experience allow me to know how sensors and ADC's work.


Sorry, but there is no reason whatsoever why it would only happen in the highs that the film noise is lower than the quantification step. You are making hypotheses on the granularity that are not necessarily true.


That last sentence is correct. It is the reason why you only need to know the maximum OD (= Optical Density) of your scanner, since the latter is what takes into account the total noise generated by the sensor plus the electronics, no matter the technology.

A bit of theory may help clarify this point. Let's say that the maximum OD of your scanner is 3.0. This means that it is able to reproduce a contrast range of 1000:1, which we can translate as the noise background being 1/1000 of the maximum value. It is thus easy to understand that two quantification steps separated by 1/500 would be more separated than the noise, hence a loss of useful information. 1/1000 is what you want, and 10 bits will bring you this. This is why the maximum OD and the quantification bits are closely related. Note that 16 bits is too many since the step difference is lost in noise, but there is no such thing as a 10 bits files, and there is no real inconvenience to recording more bits than necessary - in fact, the least significant bits are usually stuffed with zeros since the ADC doesn't send them.

Please remember that the question here is whether or not 8 bits quantification is sufficient to retain all the information from the scanned film. No hypothesis has been made on the film granularity - and we all know that it can be very low, depending on the film. So reasoning on the effects of film granularity in this conversation is questionable. At most, we can say that the overall noise can be higher than the scanner due to film grain, and 8 bits can be enough on very grainy films.


Same thing as above: all these considerations boil down to the highest OD that your scanner (or whatever sensor you use) is able to handle, which you can read in the scanner's spec sheet or measure yourself with a grey scale. No need to count the photons at the sensor, it doesn't tell the whole story anyway. Incidentally I very much doubt that a H11870-01 was ever used in a drum scanner, it is intended for different applications - unless you have a reference to provide?

Now please let's come back to the topic at hand, which is whether you get a better image with 16 bits instead of 8. The answer to this question is yes, as long as the maximum density of your scanner and document is higher than 256:1, i.e. OD = 2.4.

For example the Epson V600, an entry-level flatbed scanner, claims 3.4 (2500:1) so it would call for 16 bits. OTOH Ilford Multigrade RC paper barely exceeds 2.0 (100:1) so 8 bits are probably enough, even if scanned on a V600 since these documents will never reach a density that would require more than 8 bits.

As a matter of reference, the dynamic range of the human eye is about 1000:1, so the 16 bits / 8 bits difference is noticeable at least to a viewer who pays attention. Of course there are always exceptions if the original image has a max OD inferior to 2.4, is only composed of uniform areas, or is so noisy that the RMS noise would exceed the 8-bit quantification step (possible with pushed Tri-X, but not with Kodachrome for instance). However this is the general rule, and unless you are tweaking your workflow for a specific case you are always better off following the general rule.

Incidentally, at work we have a 300 k€ machine based on a PMT which turns out to be less sensitive than its more recent counterparts with photodiode detectors. I can assure you that not all photodiodes are noisy, far from it: it's all a matter of grade, not of technology!

ADDENDUM: I forgot to mention it, but what I wrote about film grain is valid only if you consider grain as noise. It is also common practice to consider it as part of the contents, i.e. useful signal, in which case you will want to keep it as intact as possible. In this case, you will only consider the scanner noise to determine the number of bits that you need - which amounts to always using 16 bits, unless your scanner is really lousy.
 
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jlbruyelle

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Let's say that adding bits is very useful up to a given point, and then the quantification steps are separated by less than the noise level, and adding more bits will not help. In practice for imaging, this point is usually higher than 8 bits, but lower than 16 bits - but then you cannot make a 11-bit file, so 16 bits is good.

In a linear system, the noise is constant no matter the signal level, so the density does not make a difference. This said, some sensors are nonlinear so such effects may indeed appear, but if you notice them this is mostly a sign that you are dangerously close to parts of the curve that are not really usable any more, or possibly as an artistic effect.

Anyway, I would love to see some experimental results.

Sorry, I don't have time for this. Besides I must confess I just don't have the motivation: it's been demonstrated time and again, and I'm sure you will find it in any good signal acquisition course / book / tutorial.
 

removed account4

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This is why I said that these are not really what we are talking about in this thread, unless I missed something in the ces1um's question.
no worries, i was agreeing with juan's statement which was above mine.
(i've been scanning stuff since the mid 90s -- old habits die hard)
 

jim10219

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16 bit grayscale will get you more dynamic range. 24 bit color is actually the same as 8 bit grayscale. Since there are three components to a color scan (RGB), you get 8x3=24.

I always scan B&W film in grayscale. You can get a higher quality scan at a lower file size. Then, if I want to tint it later, (which I often will just to keep it from looking so dull) I'll do that in the computer.
 

Michael Firstlight

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I scan in 16-bit B&W most of the time for the above mentioned reasons, but on lower end scanners I sometimes found thin negatives where the tones would go totally black or only scan a partial image - so for those I switch to color 24-bit and get the whole image and full tonal range. That was with a lower end Epson flatbed. Now that I have a Nikon Super Coolscan 9000 again in service, it is an entirely different experience

Mike
 

jlbruyelle

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I've just noticed that in my multiple replies I had forgotten to reply to you, sorry about that. The answer here is that there is much more to photometry than just the number of shades. The main thing is that, whereas the image file spreads its grey tones on a linear scale, the eye works on a logarithmic scale. In other words, the eye is able to distinguish shades very finely in the shadows of the image, much less so in the highlights. This is a general rule in perception, either visual or auditory. Incidentally, this is why you read in serious books that the eye can perceive contrasts in excess of 1000:1, and only 80 to 400 shades of grey. Both assertions seem to contradict each other and yet both are correct, owing to the logarithmic response of your visual system.

In contrast, the digital image needs to keep a linear scale, i.e. a constant separation between neighbouring tones no matter the value. Logarithmic ADCs have existed, but performing calculations on a logarithmic scale is a royal PITA, so no one does it this way. Now comes the big point: if you want both worlds to integrate smoothly, i.e. if you want that your eyes cannot see the linear quantification steps in the areas where it is at its best (that is in the shadows), you need to digitize with a constant step that will be fine enough in the shadows, and therefore uselessly fine in the highlights.

When you do the math, you find that you need at least 10 bits to achieve the 1000:1 contrast that your eyes are able to perceive. It's a waste of shades in the highlights, but 8 bits is low-grade nowadays, as it yields visible flat-tint effects on slow luminance gradients, e.g. blue skies. All the good quality video systems are 10-bit at least.

As already mentioned, there is absolutely no benefit to scanning a B&W image in colour, you only get 3 times the same image since Red = Green = Blue in this case.
 
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Ces1um

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That certainly helps! I will continue to scan in greyscale from now on unless I'm specifically trying to reproduce a sepia effect that my monobath tends to produce after the solutions have been used a few times. Thanks for the help!
 

Bob Carnie

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That certainly helps! I will continue to scan in greyscale from now on unless I'm specifically trying to reproduce a sepia effect that my monobath tends to produce after the solutions have been used a few times. Thanks for the help!
Stay in 16 bit Greyscale Gamma 2.2 no sharpening. , you can convert to RGB in PS and make the sepia look,
 
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alanrockwood

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All this reasoning is pointless unless you quantify the "quite a bit", which can be large or negligible.

I am preparing for a long trip right now and have only limited time for discussing this right now. However, with regard to my background, here are a few of my patents and scientific papers that deal with signal processing or equivalent topics.

“Resolution improvement in an ion cyclotron resonance mass spectrometer” US Patent 4990775 (filed 1988).

“Multi-anode time to digital converter ” US Patent 5777326 (filed 1996).

"Isotopic beat patterns in Fourier transform ion cyclotron resonance mass spectrometry...", International Journal of Mass Spectrometry and Ion Processes (1994). Although my name occurs in the middle of the author list (misspelled), I was the instigator of the paper and contributed all of the material discussing the convolution theorem.

“Relationship of Fourier transforms to isotope distribution calculations”, Rapid Communications in Mass Spectrometry (1995).

“Rapid Calculation of Isotope Distributions”, Analytical Chemistry (1995).

“Ultrahigh-speed calculation of isotope distributions”, Analytical Chemistry (1996).

“Ultrahigh Resolution Isotope Distribution Calculations”, Rapid Communications in Mass Spectrometry (1996).

“Mass Spectral Peak Distortion Due to Fourier Transform Signal Processing”, Journal of The American Society for Mass Spectrometry (2014).

“On the Fine Isotopic Distribution and Limits to Resolution in Mass Spectrometry”, Journal of The American Society for Mass Spectrometry (2015).

“Sequence Alignment by Cross-Correlation”, J Biolmol Tech (2005).

This represents a small part of my involvement in the principles of signal processing or equivalent, most of which has not been published. Many (not all) of the patents and peer reviewed publications above deal with Fourier transform methods applied to either Fourier transform mass spectrometry or to the calculation of isotopic distributions, but these topics are all based on signal processing theory. One paper deals with signal processing techniques applied to DNA alignment, which again is based on signal processing theory.

With regard to using a low resolution analog-to-digital converter to acquire a high resolution signal this web page contains a nice tutorial on some of the concepts: http://www.dspguide.com/ch3/7.htm. This discusses using a one bit ADC.

Also, regarding the relationship of noise to dynamic range, there is actually a well-known technique where noise is artificially added to a signal in order to increase the dynamic range of the signal (https://www.e2v.com/shared/content/resources/File/documents/broadband-data-converters/doc0869B.pdf). Although the application is different, the principle is the same as what I have been discussing, namely if there is noise in the signal (regardless of whether the noise is inherent in the signal, such as film grain, or noise arising from physical processes, such as thermal noise in electronic circuitry, or artificial noise deliberately added), then provided that the noise is comparable in magnitude to the ADC step size, one can get away with using a lower resolution ADC and still maintain the effective dynamic range of the signal.

In the realm of photography, a well known application of the principle of using a single-bit representation of a higher dynamic range image is the use of half tone printing https://en.wikipedia.org/wiki/Halftone. Here each small region of the image is represented by a zero or a one (white or black) but at a normal viewing distance the image looks like a continuous tone print.
 

alanrockwood

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I have calculated numerical simulations of a one dimensional signal. There are four cases. The images show a portion of the signal (a linear ramp going from 0.1 to 100 with a step size of 0.1, a dynamic range of 1000). The first would be the result of an ADC with a step size of 0.1 signal units. The result is a smooth ramp. The second is the result of and ADC with a step size of 1 signal unit. The result is a staircase. In a two dimensional image this would be show up as banding. The third and fourth graphs are the result of adding a random signal (Gaussian distribution) with a standard deviation of 1 unit. The third graph is the result of an ADC with a step size of 0.1 unit. The result is a smooth ramp with a little bit of noise superimposed. The fourth graph is the result of and ADC with a step size of 1 unit. The result is a smooth ramp with a little bit of noise superimposed. The difference between graphs three and four is negligible. In an the case of an image neither would show banding. They would both show a smooth ramp, albeit with a little noise superimposed. The amount of noise between the two would not be visibly distinguishable. Going from a low resolution ADC to a high resolution ADC would add no useful additional information.

I can add the following point. As noted above, the noise had a standard deviation of 1 step size unit for the low resolution ADC. One can even go to somewhat lower noise than 1 step size unit of the low res ADC and get a nearly equivalent result. However, when the noise is a small fraction of one step size unit of the low res ADC then the simulation of the low res ADC result will start looking like a stair step and in a real image it would the begin to show banding.

 

faberryman

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Gee, I just scan my negatives. Seems to work fine. I believe sometimes we tend to over think and under do.
 
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ced

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My is that really needed, do we have to cough up our CV each time we make a statement on any subject?
Anyway enjoy the long trip!
 

faberryman

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My is that really needed, do we have to cough up our CV each time we make a statement on any subject?
Anyway enjoy the long trip!
You're right. I've edited my post. Thanks.
 

alanrockwood

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My is that really needed, do we have to cough up our CV each time we make a statement on any subject?
Anyway enjoy the long trip!

Good point. I wouldn't have posted part of my CV except that I was challenged on the point of whether I was knowledgeble on the topic.

Thanks for the wishes for enjoying the long trip.
 

ced

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Phew that has turned the heat down a bit (some are always wanting to roll up their sleeves for nothing).
faberryman you've sure got me confused now.
 

MattKing

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I've often thought that there should be a role for lasers when it comes to scanning black and white film.
(ducks and covers)
 

ced

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I think the scanning hey days are long gone, you do have a point(excuse the pun) but the beam needs to cope with scatter too and there is no budgets about that could make it pay I guess. Lasers were good for output.
Yes, ducks and dons helmet.
 

faberryman

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faberryman you've sure got me confused now.
I thought you were referring to what I said I would be doing over the next couple of weeks as my "CV". I now see you were referring to Alan's post. I needed to keep my post on point though, so I shortened it up.
 

jlbruyelle

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Good point. I wouldn't have posted part of my CV except that I was challenged on the point of whether I was knowledgeble on the topic.

Thanks for the wishes for enjoying the long trip.

First off, have a good trip.

Sorry if my posts hurt your feelings, but then no one here questioned your knowledge of signal processing, except yourself when you said "this is pretty well known among the signal processing community. I am not a member of that community", so you have no reason to get upset by a challenge that never existed. Signal processing theory is hardly the point here anyway. OTOH I did (and still do) question the relevance of your considerations to the topic, which is quite different.

As regards your last posts, dithering and decimation converters are well-known and very useful techniques indeed, but I have to point out a couple of things, and then I'll be through with it:

There is no such as a 1-bit ADC really, it is only through misuse of language that decimation ADC's are called 1-bit. They do output several bits and have a bit depth as you will easily see in the data sheets, so it doesn't make any difference to the business at hand. Likewise halftoning, D-class audio, and all pulse-width modulation techniques simply spread the bits in the time or space domain, instead of directly representing them as numbers, and they always use lowpass filtering (even if just your eyes/ears) to revert to the multiple-bit domain. Incidentally, several techniques have been used to properly scan halftone prints, but as I said no one directly scans the silver grains of the negative for obvious reasons, so I still fail to understand why you mentioned it here.

As regards dithering, your figures are an illustration of what I said re. the relation between quantification step and noise. Two remarks here: (1) Film grain can be considered as noise like in the good old days, or as part of the image which is the current trend. In the 2nd case, only take into consideration the noise of the scanner itself in calculating the required bit depth, or the grain will quite probably look awful on the scanned image. (2) In practice one can expect a gain of a bit or maybe two through dithering, not to make a 8-bit image look like a decent 16-bit image, that would be too good. So, although mathematically correct, theoretically interesting and widely used for other things, dithering is not an answer to the 16 bits vs. 8 bits debate - not even to the 12 bits vs. 8 bits debate (12 bits being roughly the useful bit depth of a good little scanner).

Conclusion: reducing to 8 bits will probably make you lose data no matter what you do to conceal the difference, OTOH scanning to 16 bits B&W files will be safe - and save space with respect to 3x8 bits colour too. And I think this will be the end of this thread as far as I am concerned: I have passed on all the useful information I have, and I am not at all interested in a war of egos
 
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alanrockwood

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Jlbruyelle,

Sorry. I misinterpreted one of your earlier comments as questioning whether I was knowledgeable about signal processing, but upon re-reading your post I see that I misinterpreted the post. In pointing out some of my relevant background in reply it was not for the purpose of a "war of egos" but rather to establish that I am knowledgeable on the topic of signal processing.

I may have more to say on this topic in the future, but please do not feel any obligation to respond (or not respond) to what I may post on the topic.
 

alanrockwood

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Caution: entering mathematics zone:

Regarding film grain, the RMS granularity is defined in terms of the RMS variation of the density calculated from a signal acquired from a patch of film 0.048mm in diameter. (This has the same area as a square patch of 0.043mm on a side.) The RMS granularity is further specified at a film density of 1 density unit. Refining the definition a bit more, if you multiply the RMS density variation (which happens to also be the standard deviation of the density) by 1000 you get the RMS granularity.

To take an example, a typical film has an RMS granularity of about 10, which means that the standard deviation in the density is 0.010 at a density of 1.

A 4000 pixel per inch scanner sensor element has an area equivalent to a square of 0.0064mm on a side. Actually, the true sensor area is equivalent to a smaller square because you can't use 100% of the nominal silicon area assigned to the sensor for the sensor itself, but let's not quibble about the fine points.

Anyway, the RMS density variation will become larger as the sampling spot size becomes smaller, basically as the square root of the spot area or linearly with the width of the spot. Skipping over some of the math, this means that in terms of signal strength (after converting everything from density to signal strength) the standard deviation in the signal for a typical scanner sensor will be 0.015. Note that full scale in this analysis is 1.00, or 100% of light transmitted through the film, which means that the standard deviation is 1.5% of the full scale. An 8 bit ADC has a step size of 0.39% of full scale. This means that the standard deviation of the signal due to film grain is about 3.8X greater than the ADC step size. This in turn means that an 8 bit ADC is more than sufficient to acquire all usable information in a region of film having a density of 1. In fact, it is more like 7.6X better than needed, not 3.8X better, because even a half bit dither prior to ADC is enough to virtually eliminate banding in smooth gradients.

In theory it is possible to repeat this analysis for different densities, but RMS density data is usually not readily available for densities other than 1. However, given the fact that an 8 bit ADC is far beyond being sufficient at D=1, it is reasonable to conclude that an 8 bit ADC will also be good enough for either the entire range or most of the entire range of pictorially useful densities in a negative without losing useful information or having the risk of banding in smooth gradients.

Slide film, especially Velvia, may need a separate analysis for more than one reason, but I think this thread is about scanning of negatives, so that would be another discussion.

Note: this post has been edited to correct a math error.
 
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alanrockwood

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As a point of clarification, when I said that the sensor of a 4000 pixel per inch scanner element is 0.0064mm on a side, what I mean is that the area of film projected on the scanner element is 0.0064mm on a side, not that the sensor itself is that size.
 

faberryman

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If you can scan at 16-bit do so; if you can't, scanning at 8-bit will be fine.