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#11
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difficulty drum scanning negatives
Jytzel wrote:
I sent some negatives and slides to drum scan to have the operator claim that negatives show more grain in the final scan than slides. Actually not that unusual an observation. Somewhat depends upon which films are being compared, since a few transparency films do scan with a very grainy appearance. I used 6x6 Fuji NPS 160, a film has low granularity rating. The other film I used was E100G slide film. Kodak E100G should scan substantially better than the Fuji NPS. Be aware that the print granularity, and transparency film grain index are not directly comparable numbers. Kodak has a technical document PDF about this if you want to explore more on that issue. I find it hard to believe the operator's claim. It seems that he is doing something wrong. What could it be and how to get the best scan out of my negatives? By the way, they use Crosfield drum scanners. thanks J I have not tried the Crosfield for drum scans, though I have noticed some films need a few tricks to get the best results. Other than the skill and experience of the operator being in question, you might have a scan of the negative done as a positive, and reverse it in your editing software. While I am not sure exactly why that works better, you might want to give it a try. Be aware that not all film and scanner combinations react the same, so having it drum scanned on another type of machine might be a better option. Ciao! Gordon Moat Alliance Graphique Studio http://www.allgstudio.com |
#12
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difficulty drum scanning negatives
In article , Jytzel
writes Now I need some definitions of some terms: "spot size", "sampling density", and "grain aliasing". Spot size: the size of the scanning spot which each sample in the scan is averaged over. Usually this is of the order of a few microns in diameter at the film plane, and anything from 3 to 10um are commonplace. If the spot is a uniform circle, then the photomultiplier in the scanner produces a signal which is proportional to the average illumination over the area of the spot. More commonly, the spot has a gaussian profile or something similar, so the average is weighted accordingly. Sampling density: the density that the samples are taken, which is what you would usually refer to as the pixels per inch on the image. Many novices assume that the spot size and the sample pitch (ie. the inverse of the sample density) should be the same for optimum image resolution, but fairly simple diagrams demonstrate that this is not the case. A spot can resolve image detail which is finer than the diameter of the spot, or the side of the spot if it is square or rectangular (as in the elements of a CCD scanner). However a sampled system cannot unambiguously resolve detail which has a spatial frequency greater than half the sampling density. Anything which the spot can resolve but the sampling system cannot is aliased, and appears at a greater scale (if the frequency extends over many samples, this can be a much greater scale) than in the original. Quite often, a scan is obtained at which all of the image detail is fully resolved by both the spot and the sampling system, however the latter is inadequate to resolve the grain from which the image is composed, but the spot can resolve it. As a result the grain is aliased. This is especially true of well defined grain with sharp structures - the edges of the grains produce the spurious high spatial frequencies which are aliased. However, since the grain is random and smaller than the spot size, each aliased grain only extends over a single pixel in the image - but this can be many times larger than the actual grain on the original. Consequently the scanned image can appear much more grainy than a chemically produced equivalent. For some examples of this, see http://www.photoscientia.co.uk/Grain.htm Part of the skill of the drum scan operator is adjusting the spot or aperture size to optimally discriminate between the grain and the image detail for particular film types, however some film types are difficult, if not impossible to achieve satisfactory discrimination. And how can I tell if it's real amplified grain or "grain-alaising"? Well, that's not so easy because once something, including grain, has aliased there is no way to tell from the resultant image whether it is an aliased artefact or not. In some cases, additional knowledge of the scene may help - you know, for example, that the bricks on a wall do not have that large pattern across them, or the colour fringing on that roof isn't there in real life, but in general without anything to compare it to, you just cannot say. Unfortunately grain in scanned images is just like that - the only way to tell for sure if it is aliased is to compare it to the original, unsampled, slide or negative - which usually means comparing it to a conventional chemically and optically produced print of the same size. Is there any solution to this problem or should I give up using negatives altogether? There are several post scan filters around which purport to remove grain from the image after it has been scanned. Examples are Neat Image and Kodak's GEM. However, all ("all" being a relative term here!) that these packages can do is analyse the image for fine random structure and then remove as much of that as the user is prepared to tolerate. That is fine if the grain is finer than the finest details in the image - the two can be separated without loss of image detail. However, grain and aliased grain cannot be finer than single pixel size thus, if your image contains detail on the same scale (which it probably does, because that is why you paid to have it scanned at such a fine resolution in the first place) then you inevitably sacrifice image sharpness in the process of removing or reducing the grain. How much you are prepared to sacrifice is a compromise. -- Kennedy Yes, Socrates himself is particularly missed; A lovely little thinker, but a bugger when he's ****ed. Python Philosophers (replace 'nospam' with 'kennedym' when replying) |
#13
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difficulty drum scanning negatives
I had to adjust focus on my drum scanner, an Optronics Falcon, when scanning
negs to avoid high apearant grain. But once I made this slight focus adjustment the results were excellent http://www.jonlayephotography.com |
#14
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difficulty drum scanning negatives
Now I need some definitions of some terms: "spot size", "sampling
density", and "grain aliasing". And how can I tell if it's real amplified grain or "grain-alaising"? Is there any solution to this problem or should I give up using negatives altogether? Spot size is the spot diameter. This is somewhat of a misnomer, since the spots in commercial scanners are inevitably poorly formed. They are often approximated as gaussian figures of revolution, but only for convenience - they usually deviate from that in some important aspects. Ideally they should be airy discs, but that is unachievable in the price range for commercial labs or service bureaus. In most commercial scanners, 63% of the spot energy is within a 3-8 micron diameter circle at the smallest achievable spot size. When adjusted for larger spots, the spot shape usually becomes less well defined. Higher quality scanners with better spot shape control exist, but are generally unavailable to the public. Scanning microdensitometers are an example, though not necessarily optimum. Sampling density is the spots (or scan lines) per millimeter. The scanning density should be at least twice the resolution that you're trying to maintain from the film. Current high resolution commercially available color negative film can reach advertised resolutions of over 100 line pairs/mm (high contrast), but with an affordable camera/lens combination would rarely achieve over 70-80 or so on axis, less at the field edges. Black & white films can be twice that. Consumer grade color films from the 1950s achieved maybe half that at best. Aliasing (of any type, including of grain) was described by Nyquist in his papers on information sampling. It arises when information is sampled less frequently than the details that exist in the data, i.e. twice the highest frequency in the data. For example, if you sampled a 60 hertz sine wave at exactly 60 samples per second, each sample would occur at the same point on the curve, and you would conclude that you had a DC signal, not a 60 hertz AC signal. Without going into great depth here, sampling at anything below twice the highest frequency contained in the data will cause the data to later be reconstructed with the highest frequencies repoduced as erroneous lower frequencies, with the resulting distortions. It can be avoided by filtering out the high frequency data before sampling, an almost universal practice in all sampling systems except photography, where it is usually done crudely at best due to the difficulty and cost. Radio engineers call this effect hetrodyning. Physicists and other engineers call it intermodulation. Photographers call it aliasing. It is the source of the "jaggies" you see on straight edges in improperly digitized imagery as well as other problems. Grain aliasing is also a form of this, and is caused by using scan dot spacings too far apart for the grain sizes, without using a proper low pass filter in the image stream, e.g. a properly shaped scanning spot. A good commercial drum scanner operator (or the scanner often does it automatically) tries to matrch the spot size to the line spacing. Unfortunately, the more-or-less gaussian spot shape is not a very good low-pass filter. When sized to adequately reduce information that exceeds the Nyquist limit it also considerably reduces the in-band information that produces the fine detail that you would like to keep. The only practical solution to this is to oversample the image, i.e use a sample spacing and spot size that are much smaller than necessary, and then down-sample the result using an algorithm which approximates an optimum filter. While this sounds good, in practice it is hard to do with commercial grade equipment and fine grain films. Films with an average grain size of 4 microns will have a significant fraction of the grain at less than half that size. A scanning density of 1000 lines/mm or so (25,000 lines per inch) with a spot size on the order of 1 micron would be required, and the resulting file size would be huge, nearly 5 gigabytes for a 35 mm negative scanned with 16 bit depth. This would have to be stored uncompressed (or with lossless compression) untill after the downsampling was done. Also, the computer doing the downsampling would have to cope with a file size that large - pretty much beyond the ability of current 32 bit chips in common workstation use. And the whole operation would be slooooow. The upshot is, practically speaking, accept the grain as a fact of life, whatever the source. You might want to try several service bureaus, as the quality of the equipment and competence of the operators does vary. Don |
#15
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difficulty drum scanning negatives
Thanks for the tutorial.
One question: Is there a difference between the "Nyquist sampling limit", the "Shannon limit", and what I learned in school (a long time ago) as the "Whittaker-Shannon sampling theorem"? It sounds like they are different names for the same bandwidth/2 concept. -- Ron Andrews http://members.hostedscripts.com/antispam.html "Kennedy McEwen" wrote in message ... In article , Don writes Aliasing (of any type, including of grain) was described by Nyquist in his papers on information sampling. Aliasing was never mentioned by Nyquist in any of his papers - not ever! Nor did he ever publish any papers on information sampling - the technology for sampling simply did not exist in his time, or at least in the time when he was undertaking his most groundbreaking work. However, in Nyquist's 1924 internal Bell Labs circulation "Certain Factors Affecting Telegraph Speed" later published in his 1928 paper entitled "Certain Topics in Telegraph Transmission Theory" he laid out the underlying equations which would govern information sampling and defined the mathematical limit of "N/2 sinusoidal components necessary to determine a wave" unambiguously. It was his interest in sending analogue signals across telegraph lines essentially designed for Morse, which was inherently digital in nature, that led Nyquist to this conclusion. The bandwidth of the line determined the maximum Morse rate and Nyquist showed mathematically what the maximum frequency of the signal that could be transmitted on that same line. However, the signal and the line bandwidth were both analogue and continuous concepts, no sampling was involved whatsoever. What happened "beyond the Nyquist limit" was never questioned because the equations defined the bandwidth of the line from the maximum frequency of the Morse signal they supported. Essentially Nyquist defined the maximum digital signal which could be carried by an analogue line, not vice versa. It was a decade later, in 1938, that Alec Reeves invented the concept of sampling, analogue to digital conversion and patented pulse code modulation which, for obvious reasons, remained a classified technology shared only by the British and Americans, for several years. The "Nyquist sampling limit" was essentially introduced by Claude Shannon in his 1948 paper "A Mathematical Theory of Communication" which laid the foundation of IT as we know it today and who recognised the significance of Nyquist's (and Ralph Hartley's) early work to the new technology. Indeed, many publications refer to this as the "Shannon limit", whilst the Shannon-Hartley limit defines the maximum amount of information which can be carried over a sampled multilevel communication channel - effectively the amount of information that your n-bit ADC scanner can pull off of the film when sampling at x ppi. ;-) Incidentally, Nyquist was actually born with a family name of Johnsson and his father changed the name to Nyquist because other local families had the same name and this led to confusion with the post office. Years later, a colleague discovered a limiting noise power source in telegraph lines which appeared to be proportional to the resistance of the line and to temperature. Harry Nyquist set about the problem and, in 1928, he and his colleague published papers under the almost same titles, "Thermal Agitation of Electric Charge in Conductors" and "Thermal Agitation of Electricity in Conductors" respectively. His colleague's paper addressed the experimental evidence for this noise, whilst Nyquist's paper addressed the theoretical derivation of the noise from physics first principles. The predictions of Nyquist's theory were consistent with his colleague's measurements. Today we often refer to that as "Johnson Noise" - after Nyquist's colleague, J B Johnson, who just happened to have the same name he was born with! Radio engineers call this effect hetrodyning. Not the same thing at all - heterodyning does not require any sampling and, indeed, was a commonplace rf technique before sampling was ever conceived. Physicists and other engineers call it intermodulation. Again, not the same - that *is* more like a heterodyne. Photographers call it aliasing. As do engineers and physicists when they are actually referring to this effect. I know... I R 1 ! Aliasing is much more akin to the traditional Moire effect, which is a true sampling process - sampling the pattern of one layer of muslin through the apertures in a top layer. It is the source of the "jaggies" you see on straight edges in improperly digitized imagery as well as other problems. No it isn't! Jaggies occur because of inadequately filtered reconstruction systems. Not because of inadequate sampling! A jagged edge occurs because the reconstruction of each sample introduces higher spatial frequencies than the sampled image contains, for example by the use of sharp square pixels to represent each sample in the image. This can occur whether the data has been sampled correctly or not. It is a *related* effect, but quite distinct. Aliasing *only* occurs on the input to the sampling system - jaggies occur at the output. -- Kennedy Yes, Socrates himself is particularly missed; A lovely little thinker, but a bugger when he's ****ed. Python Philosophers (replace 'nospam' with 'kennedym' when replying) |
#16
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difficulty drum scanning negatives
Recently, Kennedy McEwen posted:
In article , Don wrote: writes Aliasing (of any type, including of grain) was described by Nyquist in his papers on information sampling. Radio engineers call this effect hetrodyning. Not the same thing at all - heterodyning does not require any sampling and, indeed, was a commonplace rf technique before sampling was ever conceived. Could it be that Don was referring to interference patterns resulting from the overlaying of multiple frequencies? The analogy to scanning would be the overlaying of the scanner's frequency on the target's frequency, and in such a case, interference patterns certainly result. Photographers call it aliasing. As do engineers and physicists when they are actually referring to this effect. I know... I R 1 ! Aliasing is much more akin to the traditional Moire effect, which is a true sampling process - sampling the pattern of one layer of muslin through the apertures in a top layer. I have some problems with this analogy, because it requires too many qualifiers to be accurate. If the two layers are from the same piece of muslin, *and* the muslin is of high quality such that the aperture grid formed by the weave is a consistent size, then this is more akin to the phase shifted heterodyning of two signals of the same frequency. I don't see it as a good example of scanning issues, because the likelihood of both the scanner and subject frequency being the same is fairly low, especially for silver-based negatives. Further, if the two muslin pieces are from a different weave or of low quality such that the apertures vary in size, then it's not really a good example to use to represent either sampling or Moiré, though it can be an analogy to the heterodyning of two frequency modulated (FM) signals. However, looking through the (high quality) muslin at another subject may be a good example of both the visible Moiré problems *and* aliasing caused by sampling. All one has to do is imagine that each square of the muslin grid can only contain a single color. If the subject has a regular repeating pattern, Moiré will result if the frequencies of that pattern are not perfectly aligned with the frequency and orientation of the muslin grid, and aliasing will result from re-coloring portions of the aperture to conform to the single color limitation of sampling. It is the source of the "jaggies" you see on straight edges in improperly digitized imagery as well as other problems. No it isn't! Jaggies occur because of inadequately filtered reconstruction systems. Not because of inadequate sampling! A jagged edge occurs because the reconstruction of each sample introduces higher spatial frequencies than the sampled image contains, for example by the use of sharp square pixels to represent each sample in the image. While I understand your complaint, I think it is too literal to be useful in this context. Once a subject has been sampled, the "reconstruction" has already taken place, and a distortion will be the inevitable result of any further representation of those samples. This is true for either digital or analog sampling, btw. Aliasing *only* occurs on the input to the sampling system - jaggies occur at the output. Whether one has "jaggies" or "lumpies" on output will depend on how pixels are represented, e.g. as squares or some other shape. However, that really misses the relevance, doesn't it? That there is a distortion as a result of sampling, and said distortion *will* have aliasing which exemplifies the difficulty of drum scanning negatives, and that appears to be the point of Don's original assertion. Our elaborations haven't disputed this basic fact. Regards, -- Neil Gould -------------------------------------- Terra Tu AV - www.terratu.com Technical Graphics & Media |
#17
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difficulty drum scanning negatives
In article , Ron Andrews
writes Thanks for the tutorial. One question: Is there a difference between the "Nyquist sampling limit", the "Shannon limit", and what I learned in school (a long time ago) as the "Whittaker-Shannon sampling theorem"? It sounds like they are different names for the same bandwidth/2 concept. Not really, they are all descriptions of the same basic concept that Shannon identified in Nyquist's original work. -- Kennedy Yes, Socrates himself is particularly missed; A lovely little thinker, but a bugger when he's ****ed. Python Philosophers (replace 'nospam' with 'kennedym' when replying) |
#18
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difficulty drum scanning negatives
In article et, Neil
Gould writes Recently, Kennedy McEwen posted: In article , Don wrote: writes Aliasing (of any type, including of grain) was described by Nyquist in his papers on information sampling. Radio engineers call this effect hetrodyning. Not the same thing at all - heterodyning does not require any sampling and, indeed, was a commonplace rf technique before sampling was ever conceived. Could it be that Don was referring to interference patterns resulting from the overlaying of multiple frequencies? The analogy to scanning would be the overlaying of the scanner's frequency on the target's frequency, and in such a case, interference patterns certainly result. I am sure that this *is* what Don was referring to, however there is a significant difference between the continuous waves, as use in heterodyne systems, and sampling systems which use a series of delta functions. Aliasing is analogous to heterodyning, but not the same as it. Photographers call it aliasing. As do engineers and physicists when they are actually referring to this effect. I know... I R 1 ! Aliasing is much more akin to the traditional Moire effect, which is a true sampling process - sampling the pattern of one layer of muslin through the apertures in a top layer. I have some problems with this analogy, because it requires too many qualifiers to be accurate. If the two layers are from the same piece of muslin, *and* the muslin is of high quality such that the aperture grid formed by the weave is a consistent size, then this is more akin to the phase shifted heterodyning of two signals of the same frequency. Since they are at different distances from the viewer - and in the case where the layers are actually in contact that difference will be very small - they cannot produce the same spatial frequency on the retina, and hence aliasing does result which is not simply phase shifting. I don't see it as a good example of scanning issues, because the likelihood of both the scanner and subject frequency being the same is fairly low, especially for silver-based negatives. The aliased frequency is simply the difference between the sampling frequency and the input frequency - they do not have to be the same or even nearly the same. However differentiation of the aliased output from the input is obviously easier to perceive when the input becomes close to the sampling frequency. All that is necessary is that the input exceeds the Nyquist limit - and that is a much greater probability irrespective of the medium of the original. Further, if the two muslin pieces are from a different weave or of low quality such that the apertures vary in size, then it's not really a good example to use to represent either sampling or Moiré, though it can be an analogy to the heterodyning of two frequency modulated (FM) signals. I disagree. The critical difference between heterodyne and sampling is that a heterodyne multiplies two continuous level signals - the input and the reference - at all levels, and all levels contribute to the output. In sampling, the input is either sampled (multiplied by unity) or ignored (multiplied by zero) - there is no continuous level between the two and nothing between the two contributes to the output. In the analogy with muslin, the pattern on the lower layer is either passed by the apertures in the upper layer (multiplied by unity) or blocked by the weave (multiplied by zero), which is much more akin to sampling than the continuous level heterodyne process. However, looking through the (high quality) muslin at another subject may be a good example of both the visible Moiré problems *and* aliasing caused by sampling. All one has to do is imagine that each square of the muslin grid can only contain a single color. If the subject has a regular repeating pattern, Moiré will result if the frequencies of that pattern are not perfectly aligned with the frequency and orientation of the muslin grid, and aliasing will result from re-coloring portions of the aperture to conform to the single color limitation of sampling. You seem to be limiting your definition of aliasing to situations where the input frequency extends over many samples, which is certainly useful for visualising the effect but not necessary for its occurrence - as grain aliasing clearly demonstrates. Single grains usually extend over less than one complete sample pitch. It is the source of the "jaggies" you see on straight edges in improperly digitized imagery as well as other problems. No it isn't! Jaggies occur because of inadequately filtered reconstruction systems. Not because of inadequate sampling! A jagged edge occurs because the reconstruction of each sample introduces higher spatial frequencies than the sampled image contains, for example by the use of sharp square pixels to represent each sample in the image. While I understand your complaint, I think it is too literal to be useful in this context. Once a subject has been sampled, the "reconstruction" has already taken place, and a distortion will be the inevitable result of any further representation of those samples. This is true for either digital or analog sampling, btw. That is simply untrue although it is a very popular misconception - *NO* reconstruction has taken place at the point that sampling occurs. Reconstruction takes place much later in the process and can, indeed usually does, use completely different filters and processes from those associated with the sampling process, resulting in completely different system performance. An excellent example of this occurs in the development of the audio CD. The original specification defined two channels sampled at 44.1kHz with 16-bit precision and this is indeed how standard CDs are recorded. Early players, neglecting the first generation which used 14-bit DACs or a single 16-bit DAC multiplexed between both channels, reproduced this data stream directly into the analogue domain using a 16bit DAC per channel followed by a "brick wall" analogue filter. However, the SNR and distortion present in the final audio did not meet the theoretical predictions of the process. Initial attempts to resolve the inadequacy involved the use of higher resolution DACs to ensure that the reproduction system did not limit the result. Still, the noise and distortion present in the output fell well short of what should have been possible. Then the concept of a "digital noise shaping reproduction filter" was introduced, such that the data on the CD was digitally filtered and interpolated to much higher frequencies which were then converted to analogue and filtered much more crudely, the new sampling frequency being several orders of magnitude beyond the audio range. Suddenly, improvements in measurable audio quality were achieved, with the results much closer to theoretical predictions. This was subsequently followed by Matsu**** (Panasonic/Technics) introducing MASH (Multi-stAge noise SHaping), a high bit depth (21-26bits depending on the generation) digital filter with only a 3.5-bit Pulse Width Modulation DAC per channel and ultimately by the Philips "Bitstream" system where only a 1-bit Pulse Density Modulation DAC was required. In these latter systems, which are now virtually generic in all CD players, the full theoretical limits of the original specification were actually met. Oversampling, noise shaping, PWM and PDM output were never part of the original Red Book specification and the improvements apply (and can be measured) on CDs that were available in 1981 just as readily as they apply to the latest CDs issued today. The difference is in the reconstruction, not in the sampling process and the reconstruction is completely independent of the sampling process. I was hoping to point you to a longstanding article on the ChipCenter website but I just checked and it has been removed - perhaps as a consequence of my complaint about the serious errors it contained. I have an archived copy if you are interested in reading it though! Basically, this article, like your statement above, assumed that the "reconstruction" had already taken place when the signal was sampled and, after several pages of examples of perfectly valid oscilloscope traces demonstrating the distortion introduced by sampling whilst completely ignoring the reconstruction filter, concluded with a table of the ratio of sampling to maximum signal frequency required to achieve a certain signal to noise ratio in the data. Note "the data" - the requirement for an appropriate reconstruction filter applies however the sampled data is analysed just as much as to the final analogue signal, and this is not only the crux of noise shaping CD players, but of the error in the ChipCentre article. This significant but subtle error resulted in the conclusion, fed to untold millions of electronic engineers as fact, that 16-bit accuracy required sampling at least 569x greater than the highest frequency in the signal - some 235x greater than Nyquist and Shannon require - and 36x for 8-bit accuracy, with the conclusion that audio CDs cannot reproduce much more than 1kHz at a marginal SNR! I know many audiophiles who consider CDs to be poor, but none who consider them to be that bad, but it demonstrates the consequence of ignoring the reconstruction filter which is fundamental to the sampling process. Aliasing *only* occurs on the input to the sampling system - jaggies occur at the output. Whether one has "jaggies" or "lumpies" on output will depend on how pixels are represented, e.g. as squares or some other shape. However, that really misses the relevance, doesn't it? Not at all - it is critical. "Jaggies" in an image produced from sampled data indicate inadequate reconstruction filters. You seem to have a missplaced assumption that the sampled data itself is distorted - that can only occur if the input filter is inadequate, which is the crux of the issue of selecting an appropriate spot size and shape in the drum scanner. That there is a distortion as a result of sampling, and said distortion *will* have aliasing No, that is completely wrong. A sampled system requires two filters - an input filter, which is present in the signal stream prior to the sampling process, and an output filter which is present in the signal stream after the sampling has been undertaken. Aliasing is a consequence of an inadequate input filter. This will result in distortion of the sampled data, however if the filter is adequate then there is no reason for such distortion to be present. Ideal sampling itself does *not* introduce distortion - I suggest reading Claude Shannon's very readable original paper on the topic if you have difficulties grasping this. Clearly practical sampling will introduce some distortion since all samples are not in the exact place that they should be, however in almost all cases this is negligible. This is achieved through the use of crystal oscillators for the generation of the sampling frequency, or high accuracy lithography of the semiconductor industry for the generation of the spatial sampling frequency, as is the case with scanners. Jaggies, or output distortion, are a consequence of an inadequate output filter - just as the inadequate output filters caused poor SNR and excess THD (the direct audio equivalent of jaggies) in those early CD players. which exemplifies the difficulty of drum scanning negatives, and that appears to be the point of Don's original assertion. A properly filtered sampled system exhibits *NO* distortion. Nyquist's mathematics is not an approximation, it is *EXACT*, which is why Shannon, who was particularly pedantic in most respects, based his entire thesis on it, which has well stood the test of time. Our elaborations haven't disputed this basic fact. On the contrary, I hope you now see the difference! -- Kennedy Yes, Socrates himself is particularly missed; A lovely little thinker, but a bugger when he's ****ed. Python Philosophers (replace 'nospam' with 'kennedym' when replying) |
#19
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difficulty drum scanning negatives
Hi,
Recently, Kennedy McEwen posted: Neil Gould writes Recently, Kennedy McEwen posted: Jaggies occur because of inadequately filtered reconstruction systems. Not because of inadequate sampling! A jagged edge occurs because the reconstruction of each sample introduces higher spatial frequencies than the sampled image contains, for example by the use of sharp square pixels to represent each sample in the image. While I understand your complaint, I think it is too literal to be useful in this context. Once a subject has been sampled, the "reconstruction" has already taken place, and a distortion will be the inevitable result of any further representation of those samples. This is true for either digital or analog sampling, btw. That is simply untrue although it is a very popular misconception - *NO* reconstruction has taken place at the point that sampling occurs. Oh? Then, are you under the impression that the sample data and the subject are in identity? If so, I strongly disagree with this notion. If not, then the sampled data is a reconstruction of the subject, regardless of the format and whether the format is perceivable as a representation of the subject. IOW, it could be a serial list of numbers, but that is how the sample is representing _the subject_, and not just some unrelated event. It is therefore a construct representative of the subject, aka a reconstruction. However, more to the point, distortion is inextricably inherent in the sampled data, and thus relevant to the "difficulty drum scanning negatives". Reconstruction takes place much later in the process and can, indeed usually does, use completely different filters and processes from those associated with the sampling process, resulting in completely different system performance. You appear to be referring to an interpretation of the sampled data. That process will introduce another set of distortions, and disregards the fact that the data is already a distortion. An excellent example of this occurs in the development of the audio CD. The original specification defined two channels sampled at 44.1kHz with 16-bit precision and this is indeed how standard CDs are recorded. No, that's how CDs are duplicated or replicated. Typically, professional CDs are currently recorded at sample rates of up to 192 kHz, with 24 bit or greater precision, manipulated (e.g. "mixed" and "master mixed") at 56 bits or greater precision, and down-sampled to the final audio specification of 44.1 kHz / 16 bit using various dithering algorithms to mask the sample conversion errors. I think people would be horrified by the results if such an approach was used to scan negatives. We don't have to go there. I was hoping to point you to a longstanding article on the ChipCenter website but I just checked and it has been removed - perhaps as a consequence of my complaint about the serious errors it contained. I have an archived copy if you are interested in reading it though! Basically, this article, like your statement above, assumed that the "reconstruction" had already taken place when the signal was sampled I think that we are in disagreement only about use of the term "reconstruction". I (and I suspect Don) was using it in the context of the sampled data being a construct not in identity with the subject. In that context, it is representation of the subject with a unique structure, and by its association with the subject a "reconstruction" of it. I was *not* referring to, for example, images that are generated from the stored data (which, as we agree, introduces new and independent errors). However, I understand the distinction that you are making, and agree with it, for the most part. ;-) My main problem with this line of discourse is that it ignores the fact that the inescapable distortions inherent in the sampled data are at the heart of the topic at hand. I think we should be talking about those distortions and how to improve the representation within the scope of drum scanning, rather than pursuing some tangential issue of semantics. Aliasing *only* occurs on the input to the sampling system - jaggies occur at the output. Whether one has "jaggies" or "lumpies" on output will depend on how pixels are represented, e.g. as squares or some other shape. However, that really misses the relevance, doesn't it? Not at all - it is critical. "Jaggies" in an image produced from sampled data indicate inadequate reconstruction filters. You seem to have a missplaced assumption that the sampled data itself is distorted - that can only occur if the input filter is inadequate, which is the crux of the issue of selecting an appropriate spot size and shape in the drum scanner. As has already been pointed out, the smallest spot size available to "commonplace" drum scanners is still larger than the smallest grains in "commonplace" films. Other consequences of "real world" dot shapes were discussed, as well. How can those *not* result in distortions of the orignal subject? (the quotes are to suggest that one may not consider a US$100k device to be "commonplace", yet it will have these limitations). That there is a distortion as a result of sampling, and said distortion *will* have aliasing No, that is completely wrong. A sampled system requires two filters - an input filter, which is present in the signal stream prior to the sampling process, and an output filter which is present in the signal stream after the sampling has been undertaken. Aliasing is a consequence of an inadequate input filter. This will result in distortion of the sampled data, however if the filter is adequate then there is no reason for such distortion to be present. Do you really see your comment as a rebuttal to my statement? "Aliasing is a consequence of an inadequate input filter" is simply another way to d escribe that one form of distortion (there are others) inherent in samples from drum scanners, given that the "input filter" of "commonplace" drum scanners *will* be inadequate to flawlessly sample "commonplace films". ;-) which exemplifies the difficulty of drum scanning negatives, and that appears to be the point of Don's original assertion. A properly filtered sampled system exhibits *NO* distortion. Perhaps you can point the OP to such a system, so that he can get his film scanned flawlessly, putting this matter to rest? ;-) Best regards, -- Neil Gould -------------------------------------- Terra Tu AV - www.terratu.com Technical Graphics & Media |
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difficulty drum scanning negatives
In article . net, Neil
Gould writes Hi, Recently, Kennedy McEwen posted: Neil Gould writes Recently, Kennedy McEwen posted: Jaggies occur because of inadequately filtered reconstruction systems. Not because of inadequate sampling! A jagged edge occurs because the reconstruction of each sample introduces higher spatial frequencies than the sampled image contains, for example by the use of sharp square pixels to represent each sample in the image. While I understand your complaint, I think it is too literal to be useful in this context. Once a subject has been sampled, the "reconstruction" has already taken place, and a distortion will be the inevitable result of any further representation of those samples. This is true for either digital or analog sampling, btw. That is simply untrue although it is a very popular misconception - *NO* reconstruction has taken place at the point that sampling occurs. Oh? Then, are you under the impression that the sample data and the subject are in identity? No, however the sampled data is in identity with the subject *after* it has been correctly filtered at the input stage. This principle is the entire foundation of the sampling process. No information can get past the correct input filter which cannot be accurately and unambiguously captured by the sampling system. "Accurately and unambiguously" = "No distortion". If not, then the sampled data is a reconstruction of the subject, regardless of the format and whether the format is perceivable as a representation of the subject. If properly filtered prior to sampling then the sampled data is a *perfect* representation of the filtered subject. The filtering may remove information from the subject, but it cannot add information. As such, when properly reconstructed, the sampled data will *exactly* match the subject after input filtering. In short, there may be *less* information in the properly sampled and reconstructed subject than in the original, but there can never be more. However imperfect reconstruction will result in artefacts and distortion which are not present in the original subject - false additional information, and jaggies fall into this category, they are not aliasing artefacts. IOW, it could be a serial list of numbers, but that is how the sample is representing _the subject_, and not just some unrelated event. It is therefore a construct representative of the subject, aka a reconstruction. The list of numbers is the minimum data stream that the subject can be represented in. As such, it represents the subject in a coded form however, inherent in that coding is the notion that it requires decoding to accurately reconstruct the subject. Each sample represents a measure of the subject at an infinitesimally small point in space (or an infinitesimally small point in time). The samples themselves are not a reconstruction of the subject, they are merely a representation of it, just as ASCII is not a reconstruction of your text, merely a representation of it - it requires a decoding process (ASCII to text) to turn that representation into a reconstruction. However, more to the point, distortion is inextricably inherent in the sampled data, and thus relevant to the "difficulty drum scanning negatives". Sorry Neil, but that is completely wrong. The entire principle of sampling is based on the fact that it does *not* introduce distortion because *all* of the information present in appropriately filtered input signal is captured by the sampling system. This really is not something you should be arguing about because there are numerous mathematical proofs around which explain the concept far more efficiently than can ever be achieved in a text only medium. Reconstruction takes place much later in the process and can, indeed usually does, use completely different filters and processes from those associated with the sampling process, resulting in completely different system performance. You appear to be referring to an interpretation of the sampled data. That process will introduce another set of distortions, and disregards the fact that the data is already a distortion. That, most certainly, is *NOT* a fact! Whilst I am referring to an interpretation of the sampled data, the correct interpretation does *not* introduce distortion. You appear to be hung up on the false notion that every step introduces distortion - it does not. An excellent example of this occurs in the development of the audio CD. The original specification defined two channels sampled at 44.1kHz with 16-bit precision and this is indeed how standard CDs are recorded. No, that's how CDs are duplicated or replicated. No, that is the Red Book specification - I suggest you look it up - how yo get to that sampled data is irrelevant to the discussion on the reconstruction filter. Typically, professional CDs are currently recorded at sample rates of up to 192 kHz, with 24 bit or greater precision, manipulated (e.g. "mixed" and "master mixed") at 56 bits or greater precision, and down-sampled to the final audio specification of 44.1 kHz / 16 bit using various dithering algorithms to mask the sample conversion errors. The *original* recording systems used for the creation of CDs simply applied a band limiting analogue filter and sampled the resulting audio directly at 16-bit accuracy for writing to the CD. I am well aware that there have been improvements in the recording technology over the years however that merely improves the input filter prior to creating the 16-bit data samples which are written on the CD. A CD published in 1980 has the conventional PCM audio signal encoded in exactly the same way as a CD published in 2004. However the point, which you chose to snip from the text, is that improvements to the *reconstruction* filter through the introduction of oversampling, noise shaping, MASH and Bitstream systems is equally relevant to the publications of 1980 as it is to those of 2004 - yet the data still has the same limitations - 2-channel 16-bit 44.1kHz representations of the audio stream. I think people would be horrified by the results if such an approach was used to scan negatives. We don't have to go there. Many people do go there, without even thinking about it. Scan at 16bpc at 4000ppi, process to optimise the image, downsample to 3000ppi or 2000ppi, reduce to 8bpc and archive - much the same process and overhead between capture and archive as 192kHz 24bpc audio is to the 44.1kHz 16bpc CD publication. Of course, this approach assumes that the entire image can be adequately represented in 3000 or 2000ppi, which may not be the case, just as many audiophiles clamour for HD-CD media to met their higher representation requirements. I was hoping to point you to a longstanding article on the ChipCenter website but I just checked and it has been removed - perhaps as a consequence of my complaint about the serious errors it contained. I have an archived copy if you are interested in reading it though! Basically, this article, like your statement above, assumed that the "reconstruction" had already taken place when the signal was sampled I think that we are in disagreement only about use of the term "reconstruction". From your subsequent statements that would not appear to be the case! My main problem with this line of discourse is that it ignores the fact that the inescapable distortions inherent in the sampled data are at the heart of the topic at hand. When there is nothing there it is reasonable to ignore it. There is no distortion in sampling a correctly filtered signal - that, it would appear, is the crux of the disagreement between us. Since the mathematics behind this is well beyond a text only medium, I suggest you browse a few textbooks on the subject. There are many that I could suggest but, whilst its main topic is a mathematical technique which is highly significant to this subject, Ron Bracewell's classic text "The Fourier Transform and its Applications" covers the matter in very precise detail. Specifically I refer you to Chapters 5, dealing with the Impulse function, as a forerunner to Chapter 10, which details the mathematics of the entire sampling process. Once again though, I suggest you read some of Claude Shannon's very original and readably texts on the topic, specifically Shannon's Sampling Theorem which states that: "When the input signal is band limited to meet the Nyquist Sampling Criterion that signal can be reconstructed with full accuracy from the sampled data." Your assertion that the sampled data is inherently distorted and that this inevitably passes into the reproduction is in complete disagreement with Claude Shannon's 1949 proof. I suggest that you will need much more backup than a simple statement of disagreement before many people will take much notice of such an unfounded allegation. I think we should be talking about those distortions and how to improve the representation within the scope of drum scanning, rather than pursuing some tangential issue of semantics. We are - however your claim that sampling introduces its own distortions irrespective of the rest of the system prevents that discussion from moving forward to any degree. As has already been pointed out, the smallest spot size available to "commonplace" drum scanners is still larger than the smallest grains in "commonplace" films. Other consequences of "real world" dot shapes were discussed, as well. How can those *not* result in distortions of the orignal subject? (the quotes are to suggest that one may not consider a US$100k device to be "commonplace", yet it will have these limitations). Good God, I think he's finally got it, Watson! The spot is part of the input filter of the sampling system, just as the MTF of the imaging optics are! Indeed these components (optics, spot etc.) can be used without sampling in the signal path at all, as in conventional analogue TV, and will result in exactly the same distortions that you are referring to. If this is not proof that sampling itself does not introduce an inherent distortion then I do not know what is! Just in case you haven't noticed, you have in the above statement made a complete "about-face" from your previous statements - you are now ascribing the distortions, correctly, to the input filter not the sampling process itself, which introduces *no* distortion, or the reconstructon filter which can introduce distortion (eg. jaggies) if improperly designed. That there is a distortion as a result of sampling, and said distortion *will* have aliasing No, that is completely wrong. A sampled system requires two filters - an input filter, which is present in the signal stream prior to the sampling process, and an output filter which is present in the signal stream after the sampling has been undertaken. Aliasing is a consequence of an inadequate input filter. This will result in distortion of the sampled data, however if the filter is adequate then there is no reason for such distortion to be present. Do you really see your comment as a rebuttal to my statement? Absolutely - there is a vast distinction between the filters in the total system and the sampling process itself. In a correctly filtered system the sampling process can be added and removed without introducing distortion of any kind or level whatsoever. Perhaps you can point the OP to such a system, so that he can get his film scanned flawlessly, putting this matter to rest? ;-) The point is that he has already done this - most drum scanner manufacturers produce equipment capable of the task, unfortunately many operators are not up to driving them close to perfection - often because they erroneously believe that such perfection is unobtainable in sampled data, so why bother at all. -- Kennedy Yes, Socrates himself is particularly missed; A lovely little thinker, but a bugger when he's ****ed. Python Philosophers (replace 'nospam' with 'kennedym' when replying) |
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