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#21
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difficulty drum scanning negatives
Hi,
Recently, Kennedy McEwen posted: Neil Gould writes Recently, Kennedy McEwen posted: 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. In which case, I disagree with your usage of the term "identity". 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". The principle is not where the problem lies. It is in the implementation. From your own response to an earlier post: "With a drum scanner the spot size (and it's shape) is the anti-alias filter, and the only one that is needed. One of the most useful features of most drum scanners is that the spot size can be adjusted independently of the sampling density to obtain the optimum trade-off between resolution and aliasing..." ^^^^^^^^^^^^^^^^^^^^^^^^^ In another post, you reported: "then the photomultiplier in the scanner produces a signal which is proportional to the average illumination over the area of the spot." Sounds (and looks) like distortion to me, given that the "area of the spot" may have more than one illumination level, and the recorded value is averaged. ;-) If properly filtered prior to sampling then the sampled data is a *perfect* representation of the filtered subject. In short, there may be *less* information in the properly sampled and reconstructed subject than in the original, but there can never be more. Which only further reinforces my disagreement with your usage of "identitiy". I've not heard the term used in such a way that it includes a "less than" clause. ;-) 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. I didn't suggest that jaggies are aliasing artifacts. They are clearly output representation artifacts, as are "lumpies" or other kinds of distortions dependent on the representation of the pixels identified in the numeric data resulting from sampling. My claim is that the numeric data contains various distortions of the subject, and while some may be assignable to the input filtering (including those you mentioned), but others are assignable to the practical limitations of math operations, and that these errors are inextricable. Each sample represents a measure of the subject at an infinitesimally small point in space (or an infinitesimally small point in time). As you present in another post, the issue relevent to the topic appears to be: "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. " IOW, the measure of the subject is not "infinitesimally small", and by your own admission, some aspects of the subject (e.g. minimum grain sizes) can be smaller than the sample size. 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. Not according to your own posts (as excerpted, above). I agree with those statements in your posts, even if you don't! ;-) 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. I see. And, just what kind of system are you using that avoids such artifacts as rounding errors, for example? 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. Our disagreement boils down to whether artifacts are introduced by real-world recording processes. The reason that I stressed how _audio_ is recorded -- as opposed to the burning of the end result onto a CD master -- is that the first stages of the recording process is somewhat more analogous to scanning than "recording a CD". MANY artifacts are introduced because of the lack of, as you have put it, an adequate input filter. There is not a microphone made that will capture actual acoustic events due to many factors, not the least of which is that those events are typically not two dimensional in nature, but the processes of the capturing devices (microphones) are. The rest of the recording process is one of manipulation and error correction to create an acceptable representation of the original acoustic events. I've not run into anyone "in the biz" that would claim that these two are "in identity", or that it would be possible to reconstruct the original acoustic events from the sampled data (recording). Finally, the process of reducing the recorded data to the 44.1/16 standard introduces MORE errors by virtue of whether dithering is used, and if so, which dithering algorithms one chooses. By the time a CD is ready for purchase, it's much more akin to a painting than a scanned photograph, which is why I think it was a poor choice as an example for this topic. 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. And, is in fact, one of the issues at the root of my perspective. ;-) 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. The crux of the matter is that I'm only interested in what happens in real world implementations, as film in hand represents just that. I don't have a problem with the theory, and not only understand it, but agree that *in theory* the math behind sampling can lack distortion. However, I don't live in theory, and have little real-world use for theoretical "solutions" that can't be (or at least, aren't) realized. ;-) To that end, I think I'll just rely on the results I've been able to obtain. I, as I presume the OP, am interested in understanding the limitations of the process. Your own posts have provided excellent bases for the understanding of such limitations. What puzzles me is that you don't see the "trade offs" that you spoke of as distortions of the original subject. What, exactly, are you "trading off" that doesn't result in a reduction of the available data in the subject? 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! I "had it" long before your first posts on the subject. However, I see every stage of the real-world process as introducing errors, and thus distortions of the subject. 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! As, to my knowledge, there is no system available that implements perfect input filtering and flawlessly applies sampling algorithms, all that is left is to expand my knowledge by being presented with such a system. ;-) 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. I'm not terribly concerned about sampling (e.g. the math) without input filters (e.g. the implementation). I'm only concerned about systems. So there's no "about face" involved, we're just interested in different things, it seems. ;-) Regards, -- Neil Gould -------------------------------------- Terra Tu AV - www.terratu.com Technical Graphics & Media |
#22
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difficulty drum scanning negatives
In article .net, Neil
Gould writes Hi, From your own response to an earlier post: "With a drum scanner the spot size (and it's shape) is the anti-alias filter, and the only one that is needed. One of the most useful features of most drum scanners is that the spot size can be adjusted independently of the sampling density to obtain the optimum trade-off between resolution and aliasing..." ^^^^^^^^^^^^^^^^^^^^^^^^^ In another post, you reported: "then the photomultiplier in the scanner produces a signal which is proportional to the average illumination over the area of the spot." Sounds (and looks) like distortion to me, given that the "area of the spot" may have more than one illumination level, and the recorded value is averaged. ;-) Ok - I give up! I thought I was discussing the subject with someone who understood a little of what they were talking about and merely required some additional explanatory information. That comment indicates that you simply do not have a clue what you are talking about at all, since you are clearly incapable of understanding either the action of a spatial filter or the difference between the action of the filter and the action of sampling. Please learn the basics of the topic before wasting people's time with such drivel. If properly filtered prior to sampling then the sampled data is a *perfect* representation of the filtered subject. In short, there may be *less* information in the properly sampled and reconstructed subject than in the original, but there can never be more. Which only further reinforces my disagreement with your usage of "identitiy". I've not heard the term used in such a way that it includes a "less than" clause. ;-) Try *reading*! The identity is with the filtered subject which, having been filtered is less than the subject! More obfuscation and/or deliberate misrepresentation! 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. I didn't suggest that jaggies are aliasing artifacts. No? I didn't suggest you did, however you did defend the suggestion made by a third party that they were. Try reading your opening input into this thread again and stop the obfuscation. My claim is that the numeric data contains various distortions of the subject, and while some may be assignable to the input filtering (including those you mentioned), but others are assignable to the practical limitations of math operations, and that these errors are inextricable. And this is precisely where you depart company from the very principles of the Sampling Theorem, which is hardly surprising given your previous statements indicating your total confusion of the topic! Let me explain it one more time, finally. There are two filters, an input (antialiasing) filter and an output (reconstruction) filter between which is placed a sampling system. The performance of the system is totally independent of whether the sampling system is actually present or not providing that the filters are matched to the dimensions of the sampling system. In short, it is impossible to determine whether the information has been sampled or not simply by examining the output of the reconstruction filter, because the sampling process itself does not introduce any distortion or limitation of the signal at all. Since you clearly do not understand this fundamental concept on which the entire science of information technology is based, I suggest you acquaint yourself in detail with its scientific proof, presented clearly in Claude Shannon's 1948 paper "A Mathematical Theory of Communication" and desist from arguing the case against something which is a proven mathematical fact, as relevant to audio communication as it is to scanning images. Each sample represents a measure of the subject at an infinitesimally small point in space (or an infinitesimally small point in time). As you present in another post, the issue relevent to the topic appears to be: "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. " IOW, the measure of the subject is not "infinitesimally small", and by your own admission, some aspects of the subject (e.g. minimum grain sizes) can be smaller than the sample size. Indeed - and they would only reach the sampling system if the input filter, in this case the optic MTF and the spot size and shape, permit them to. With an adequate input filter, the grain is not sampled and grain aliasing does not occur. Snipped the rest of this tripe, you really haven't a clue what you are talking about. Before posting anything else, read up on the topic - specifically the texts I have suggested. They may not be the most comprehensive, but they are the most readable explanations of the topic for even a layman to understand. -- 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) |
#23
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difficulty drum scanning negatives
Recently, Kennedy McEwen posted:
In article .net, Neil Gould writes From your own response to an earlier post: "With a drum scanner the spot size (and it's shape) is the anti-alias filter, and the only one that is needed. One of the most useful features of most drum scanners is that the spot size can be adjusted independently of the sampling density to obtain the optimum trade-off between resolution and aliasing..." ^^^^^^^^^^^^^^^^^^^^^^^^^ In another post, you reported: "then the photomultiplier in the scanner produces a signal which is proportional to the average illumination over the area of the spot." Sounds (and looks) like distortion to me, given that the "area of the spot" may have more than one illumination level, and the recorded value is averaged. ;-) Ok - I give up! I thought I was discussing the subject with someone who understood a little of what they were talking about and merely required some additional explanatory information. That comment indicates that you simply do not have a clue what you are talking about at all, since you are clearly incapable of understanding either the action of a spatial filter or the difference between the action of the filter and the action of sampling. What *should* be clear to you is that I have repeatedly stated that I am referring to real-world implementations, and not simply sampling theory. I have repeatedly asked you to suggest a system (to make it clearer that is HARDWARE I'm talking about) capable of performing near the levels of accuracy that sampling theories implied. Your response is to point once again at -- usually the same -- theoretical sources, and you've NOT ONCE indicated the existance of such hardware. If you think that such exists, that is where we part in our perspectives. Please learn the basics of the topic before wasting people's time with such drivel. In short, this has nothing to do with my capability to understand sampling theory, and everything to do with what one can actually purchase and/or use. I tried to emphasize my point by excerpting your own posts, indicating the limitations typical of such systems. So, if it's drivel, I'm afraid it didn't originate with me, sir. If properly filtered prior to sampling then the sampled data is a *perfect* representation of the filtered subject. In short, there may be *less* information in the properly sampled and reconstructed subject than in the original, but there can never be more. Which only further reinforces my disagreement with your usage of "identitiy". I've not heard the term used in such a way that it includes a "less than" clause. ;-) Try *reading*! The identity is with the filtered subject which, having been filtered is less than the subject! Your statement, that the sampled data is a perfect representation of the filtered subject is essentially stating that the sampling alogrithm has not altered the post-filter data. On a theoretical level, we are in agreement about this point; the input filter has presumably restricted the information to fall within the capabilities of the sampling algorithm to represent it accurately. More to the point, the only way that I dispute this is in real-world implementations, e.g. math coprocessor variances such as the rounding errors I wrote of. Surely, you don't insist that such impacts are non-existant in real-world systems? More obfuscation and/or deliberate misrepresentation! On whose part? Here is the exchange in question: " Recently, Kennedy McEwen posted: 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. " It is clear in this exchange that you have relocated "the subject" from being the pre-filter object I inquired about to a post-filtered representation of that object. I am not now, nor have I ever been referring to "the subject" as a post-filtered representation of the object. The distortion I spoke of is the difference between the subject and the post-filter representation, and in other parts of the exchange, included the possibile accumulation of errors due to hardware computational limitations. I've never claimed differently. So, where is the "obfuscation and/or deliberate misrepresentation", beyond your claim that it exists in this material? 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. I didn't suggest that jaggies are aliasing artifacts. No? I didn't suggest you did, however you did defend the suggestion made by a third party that they were. Try reading your opening input into this thread again and stop the obfuscation. Perhaps you should re-read that opening input again, and stop trying to misrepresent what I stated. Here it is, for your convenience: Don wrote: " It is the source of the "jaggies" you see on straight edges in improperly digitized imagery as well as other problems." Your reply: " 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." My reply: "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." My opening statement, "...I understand your complaint..." is that I am agreeing with you, but questioning the value of the distinction you are making. Put plainly, you are referring strictly to the algorithm applied to post-filtered data. To clarify my response, it is that by the time the subject (not post-filtered representation of the subject) is sampled, it is already distorted (by the input filter), and will only be further distorted by the time of output in a real-world system. And, directly to the issue of jaggies: You stated: " Aliasing only occurs on the input to the sampling system - jaggies occur at the output." My reply was: "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." Clearly, I am agreeing with YOU that jaggies are output artifacts. My response elaborates on some possible artifacts that _output devices_ may introduce. There is NOTHING in my statement that merits your claim that "...however you did defend the suggestion made by a third party that..." (jaggies are aliasing artifacts). The remaining content merely questions whether the points you are making addresses the OP's question at hand. At best, my entry recognized the idea that a real-world system, e.g. scanner as a piece of hardware, not simply the sampling-stage mathematic operation on post-filtered data, can present the end user with a file that contains aliasing, and possibly to that end, Don was responding to the OP. I was not then, and am not now arguing about any aspect of sampling theory independent of a real-world implementation through existant hardware. Make no mistake that my choice is not because I don't understand, or have not read the material. Your insults aside, the fact is that we're talking apples and oranges. The problem is, you fail to acknowledge this. If you wish to criticise the accuracy or relevance of my comments, you'll do so not by pointing at various sources of sampling theory, but by pointing at the hardware that performs to the degree of accuracy that such theories imply. To distill the point of my input to a single sentence: If such hardware existed, the "trade offs" you spoke of would, in all likelihood, be unnecessary. Regards, -- Neil Gould -------------------------------------- Terra Tu AV - www.terratu.com Technical Graphics & Media |
#24
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difficulty drum scanning negatives
In article .net, Neil
Gould writes Recently, Kennedy McEwen posted: In article .net, Neil Gould writes From your own response to an earlier post: "With a drum scanner the spot size (and it's shape) is the anti-alias filter, and the only one that is needed. One of the most useful features of most drum scanners is that the spot size can be adjusted independently of the sampling density to obtain the optimum trade-off between resolution and aliasing..." ^^^^^^^^^^^^^^^^^^^^^^^^^ In another post, you reported: "then the photomultiplier in the scanner produces a signal which is proportional to the average illumination over the area of the spot." Sounds (and looks) like distortion to me, given that the "area of the spot" may have more than one illumination level, and the recorded value is averaged. ;-) Ok - I give up! I thought I was discussing the subject with someone who understood a little of what they were talking about and merely required some additional explanatory information. That comment indicates that you simply do not have a clue what you are talking about at all, since you are clearly incapable of understanding either the action of a spatial filter or the difference between the action of the filter and the action of sampling. What *should* be clear to you is that I have repeatedly stated that I am referring to real-world implementations, and not simply sampling theory. Really - the issues raised in this and other posts do not relate to specific hardware implementations, but to generic steps in the process. In particular your insistence that sampling itself, not the filters, introduces distortions which you have never specified. I have already mentioned the practical limitations of positional accuracy in real sampling systems which are insignificant in modern systems, but you have yet to divulge what these imaginary distortions you think exist in real practical hardware at the sampling stage. I have repeatedly asked you to suggest a system (to make it clearer that is HARDWARE I'm talking about) capable of performing near the levels of accuracy that sampling theories implied. Your response is to point once again at -- usually the same -- theoretical sources, and you've NOT ONCE indicated the existance of such hardware. I did, but you were clearly too lost in your own flawed mental model of the process to notice that I had. I suggest you back up a few posts and find it. -- 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) |
#25
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difficulty drum scanning negatives
Recently, Kennedy McEwen posted:
Neil Gould writes I have repeatedly asked you to suggest a system (to make it clearer that is HARDWARE I'm talking about) capable of performing near the levels of accuracy that sampling theories implied. Your response is to point once again at -- usually the same -- theoretical sources, and you've NOT ONCE indicated the existance of such hardware. I did, but you were clearly too lost in your own flawed mental model of the process to notice that I had. I suggest you back up a few posts and find it. While I did respond to the various analogies that others presented, I don't recall presenting a mental model of the process. However, perhaps you did answer the question, and it's possible that the post you are referencing above is not available on my news server. The closest response that I can locate is from our exchange on 4/5: You wrote: "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." Is your intent is to suggest that the only source of grain aliasing in the resultant file is operator error? If so, the difficulty that I have is in reconciling such a notion against your own excellent description on 4/1: There, you wrote in part: "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." It appears to imply that, regardless of operator skill, there will be cases in which some artifacts are unavoidable. This explanation is one that I understood to be the case, and directly experienced, at least decades before this thread began. Perhaps you'll indulge me by clarifying this, as it is the primary source of any "confusion" that I may have? Regards, -- Neil Gould -------------------------------------- Terra Tu AV - www.terratu.com Technical Graphics & Media |
#26
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difficulty drum scanning negatives
In article .net, Neil
Gould writes While I did respond to the various analogies that others presented, I don't recall presenting a mental model of the process. Your repeated statements that sampling itself introduces distortion is evidence of a flawed mental model of the process, one which is at direct odds with the underlying principles of sampling in general. You wrote: "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." Is your intent is to suggest that the only source of grain aliasing in the resultant file is operator error? Not at all, many systems are designed in such a way that grain aliasing cannot be avoided. For example, until recently, this was impossible to avoid in almost all desktop scanners, and still is in many. Some drum scanners apparently suffer from a similar problem, specifically that the aperture shape and size and/or the sampling density cannot be increased to a sufficient degree to prevent aliasing. If so, the difficulty that I have is in reconciling such a notion against your own excellent description on 4/1: There, you wrote in part: "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." It appears to imply that, regardless of operator skill, there will be cases in which some artifacts are unavoidable. This explanation is one that I understood to be the case, and directly experienced, at least decades before this thread began. Perhaps you'll indulge me by clarifying this, as it is the primary source of any "confusion" that I may have? As mentioned above, there are cases where this cannot be avoided, irrespective of the operator skill, simply due to hardware design limitations. Also, as previously mentioned there are some films, almost exclusively monochrome, high contrast, ultrathin emulsions, which are capable of resolving image detail right up to the spatial frequencies at which grain structure exists. Had you looked up some of the references I cited you would have found that this type of case is specifically addressed, where the image is effectively randomly sampled by the film grain which is in turn regularly sampled by the scanner system. If neither loss of image content nor grain aliasing are acceptable then these films require sampling and input filtering beyond the resolution of the film itself. The aperture, together with normal optical diffraction limits, still performs an input filter to the sampling process, reducing the contrast of the grain to a minimum above the Nyquist of the sampling density, however the sampling density can easily reach 12,000ppi or more (true, not interpolated). Few scanners are capable of this, however, given that the film MTF has fallen significantly before grain contrast becomes significant, it is still perfectly feasible to identify an optimum, if less than perfect, differentiation point in lesser scanners. Such issues are rarely a problem with the much thicker and multilayer colour emulsions where resolution generally falls off well before grain contrast becomes significant. Just as importantly the grain itself is indistinct, having been bleached from the emulsion to leave soft edged dye clouds, resulting in a slow rise in granular noise as a function of spatial frequency. Thus the ability to differentiate between resolved image content and grain is much enhanced and the failure to do so with adequate equipment is invariably due to operator skill (or interest or both) limitations. -- 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) |
#27
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difficulty drum scanning negatives
Recently, Kennedy McEwen posted:
In article .net, Neil Gould writes While I did respond to the various analogies that others presented, I don't recall presenting a mental model of the process. Your repeated statements that sampling itself introduces distortion is evidence of a flawed mental model of the process, one which is at direct odds with the underlying principles of sampling in general. I'm afraid that you are mistaken about my comments sampling errors. Rather than put full quotes here, I'll follow your lead and invite you to read them again. I've never questioned the integrity of the theoretical functions involved in sampling, and wrote so more than once. However, I did state that any real-world implementation of sampling algorithms by hardware will introduce at least rounding errors due to hardware limitations. I would not call that a "mental model of the process", in that it explicitly describes hardware functioning. All of my other comments regarding distortions (errors, if you prefer) involved the state of the information about the subject post-input filter, the issue being GIGO at the sampling stage. Again, this is simply a description of hardware functioning, and not a mental model of the process. If you disagree with any of this, please let me know how and why. You wrote: "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." Is your intent is to suggest that the only source of grain aliasing in the resultant file is operator error? Not at all, many systems are designed in such a way that grain aliasing cannot be avoided. For example, until recently, this was impossible to avoid in almost all desktop scanners, and still is in many. Some drum scanners apparently suffer from a similar problem, specifically that the aperture shape and size and/or the sampling density cannot be increased to a sufficient degree to prevent aliasing. Now, we're getting somewhere. My repeated request was for a reference to a commonly available machine which has sufficiently high performance capabilities to reliably avoid grain aliasing with all commonly available films (obviously, for all subjects and without sacrificing detail or introducing other artifacts). I am unaware of the existance of such a scanner, and would appreciate make and model, or a pointer to the site. If you've already done so, it isn't on my news service. But, I suspect that we actually agree about this, as you have responded with: As mentioned above, there are cases where this cannot be avoided, irrespective of the operator skill, simply due to hardware design limitations. Also, as previously mentioned there are some films, almost exclusively monochrome, high contrast, ultrathin emulsions, which are capable of resolving image detail right up to the spatial frequencies at which grain structure exists. Which is the crux of the problem, is it not? And, it's not news to me. ;-) Regards, -- Neil Gould -------------------------------------- Terra Tu AV - www.terratu.com Technical Graphics & Media |
#28
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difficulty drum scanning negatives
In article .net, Neil
Gould writes I'm afraid that you are mistaken about my comments sampling errors. Rather than put full quotes here, I'll follow your lead and invite you to read them again. I've never questioned the integrity of the theoretical functions involved in sampling, and wrote so more than once. You wrote: "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" In your next post you the wrote: "However, more to the point, distortion is inextricably inherent in the sampled data" And then wrote: "My claim is that the numeric data contains various distortions of the subject, and while some may be assignable to the input filtering (including those you mentioned), but others are assignable to the practical limitations of math operations, and that these errors are inextricable." All of these statements, especially the last one, refer quite specifically to the sampling process, not to the limitations of the input filter which you specifically address separately in the latter statement. Now, we're getting somewhere. My repeated request was for a reference to a commonly available machine which has sufficiently high performance capabilities to reliably avoid grain aliasing with all commonly available films (obviously, for all subjects and without sacrificing detail or introducing other artifacts). I am unaware of the existance of such a scanner, and would appreciate make and model, or a pointer to the site. If you've already done so, it isn't on my news service. Pick any of the currently available film/flatbed scanners and you will have in your hands a scanner which does not alias grain. Look at the Minolta 5400 for a higher resolution scanner which, which the grain dissolver activated, does not alias grain. Although not technically a drum scanner, the Imacon 848 provides most of the related features and will cope with most photographic film without grain aliasing or resolution loss. Finally, its expensive but the Aztek Premier will do 16000ppi optical sampling with independent aperture control to get everything off the highest resolution monochrome film without introducing grain aliasing at all. But, I suspect that we actually agree about this, as you have responded with: As mentioned above, there are cases where this cannot be avoided, irrespective of the operator skill, simply due to hardware design limitations. Also, as previously mentioned there are some films, almost exclusively monochrome, high contrast, ultrathin emulsions, which are capable of resolving image detail right up to the spatial frequencies at which grain structure exists. Which is the crux of the problem, is it not? Not really. Most, if not all of the people on this forum, are interested in scanning images from colour film where such high resolution requirements just don't exist. -- 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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difficulty drum scanning negatives
Paul Schmidt wrote:
What are the best films for scanning say one or two brands/types in each of these categories: B&W (what's best old tech, new tech, chromogenic) I'm partial to the Fuji line. I've settled mostly on Neopan 400 and Neopan 1600. Some Acros 100. (Don't ask me why it's not Neopan 100. I have no idea. Acros 100: http://canid.com/sioux_falls/falls_park1.html Neopan 400: http://canid.com/johanna/butterfly1.html Neopan 1600: http://canid.com/johanna/balancing_act.html -- Eric http://canid.com/ |
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difficulty drum scanning negatives
Recently, Kennedy McEwen posted:
In article .net, Neil Gould writes I'm afraid that you are mistaken about my comments sampling errors. Rather than put full quotes here, I'll follow your lead and invite you to read them again. I've never questioned the integrity of the theoretical functions involved in sampling, and wrote so more than once. You wrote: "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" "Jaggies or lumpies" clearly refers to the result post output-filter, as identified in the first part of the first sentence by the words "on output". The latter reference of distortion has to do with GIGO, and I didn't go into detail at that point. I did make it plainly clear in subsequent posts that I am referring to real-world implementations in hardware. In your next post you the wrote: "However, more to the point, distortion is inextricably inherent in the sampled data" It should be obvious that this refers to the state of the information post input-filter, as that comprises the content of "the sampled data". GIGO, once again. And then wrote: "My claim is that the numeric data contains various distortions of the subject, and while some may be assignable to the input filtering (including those you mentioned), but others are assignable to the practical limitations of math operations, and that these errors are inextricable." All of these statements, especially the last one, refer quite specifically to the sampling process, not to the limitations of the input filter which you specifically address separately in the latter statement. Not really. That "the numeric data contains various distortions of the subject" directly addresses the end result of all stages up to the point where that data can be examined -- e.g. post sampling, and post storage. It in no way isolates the sampling stage, as exemplified by "...some may be assignable to the input filtering...", while the last portion refers to the *implementation*, e.g. "practial limitations of math operations", or put another way, real-world execution of those functions. Unless you have access to some device the rest of the world has yet to see, this is an accurate statement. Now, we're getting somewhere. My repeated request was for a reference to a commonly available machine which has sufficiently high performance capabilities to reliably avoid grain aliasing with all commonly available films (obviously, for all subjects and without sacrificing detail or introducing other artifacts). I am unaware of the existance of such a scanner, and would appreciate make and model, or a pointer to the site. If you've already done so, it isn't on my news service. Pick any of the currently available film/flatbed scanners and you will have in your hands a scanner which does not alias grain. However, in the process, they compromise the image in other ways, and as such do not meet the criteria that I've spelled out, above in "...for all subjects and without sacrificing detail or introducing other artifacts". Look at the Minolta 5400 for a higher resolution scanner which, which the grain dissolver activated, does not alias grain. Ditto. Although not technically a drum scanner, the Imacon 848 provides most of the related features and will cope with most photographic film without grain aliasing or resolution loss. "Most photographic film" is not "all commonly available film", which is another of the criteria from above. Finally, its expensive but the Aztek Premier will do 16000ppi optical sampling with independent aperture control to get everything off the highest resolution monochrome film without introducing grain aliasing at all. I'll look into this model. Thank you for the reference, even if I remain skeptical that 16000 ppi is sufficiently high frequency to "get everything off the highest resolution monochrome film" without any artifacts, at least it's not flatbed territory or CCD-based. Which is the crux of the problem, is it not? Not really. Most, if not all of the people on this forum, are interested in scanning images from colour film where such high resolution requirements just don't exist. Definitely not "all of the people on this forum", based on the number of inquiries related to scanning monochrome negatives. You shouldn't have to search very deeply to find a significant number of such requests. Furthermore, there are color films that are also challenging to scan, such as the Kodachromes. I've gotten much better results from optical enlargements of those slides. I haven't used NPS 160, as is the case of the OP, but allow for the possibility that this might be another such film. Do you know for certain that it isn't? Regards, -- Neil Gould -------------------------------------- Terra Tu AV - www.terratu.com Technical Graphics & Media |
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