Camera Gamut (was Re: basiccolor INPUT)
On Nov 6, 2011, at : Iliah Borg <ib@pochtar.com> wrote:
I think we have a little language problem here. To quote, "there is no such thing as a camera, or scanner, gamut" http://www.cis.rit.edu/research/mcsl2/outreach/faq.php?catnum=3#255
Thanks for the link, Iliah.
"there is no such thing as a camera, or scanner, gamut"
There are several interesting discussions of this postulate in the literature. Unfortunately, the articles are expensive unless you have access to a research library, so I've taken the liberty of summarizing two of them for those without such access. Berns (1) takes the above position and argues that the term ‘‘color gamut’’ historically has been associated with color output such as optimal color stimuli and additive and subtractive imaging systems. He notes that from both historical and current contexts, ‘‘color gamut’’ is associated with producing color, not measuring color; that is, color gamuts are defined by output devices, not input devices. If a camera is considered a measurement device - not unlike a colorimeter or spectrophotometer - it cannot have a "color gamut" as it is able to respond to all colors presented to it (i.e., there is no such thing as an "out of gamut" color for the device). Berns takes issue with the use of the expression "color gamut" in scientific comparisons of digital cameras, and argues that "if a measurement device has a color gamut, ... [then] a miscalibrated spectrophotometer (calibrating to black instead of white) or camera with lens cap attached have small color gamuts." Rather than use the term "color gamut," he proposes the use of the expression, "color gamut rendering." "That is, under a set of stated conditions a target of colors has been rendered to a set of colorimetric coordinates owing to various parameters. The stated conditions might include an ensemble of spectral reflectance factors obtained using a spectrophotometer with stated measurement geometry (the target), the camera-taking light source, the camera’s optical properties and methodology of obtaining colorimetric coordinates if known, and the standard illuminant and observer for the colorimetric data. Differences in input device characteristics would result in the target’s color gamut being rendered differently." Brill (2) urges the explicit adoption of a definition for the camera color gamut. In his view, a viable definition seems to be the set of CIE XYZ triplets such that, for any such XYZ, there exists a spectral power distribution in a predefined set whose camera values map through a predefined algorithm to that XYZ. Brill notes that the term "color gamut" is problematic when applied to a scanner or digital camera. However, he acknowledges that it has been used in this context in various venues, including referred articles and conferences. In such discussions, "the definition is always assumed and never stated." Brill believes it is time to "make explicit what is implicitly understood, or metaphorically, to spray-paint the invisible definition." Brill discusses alternative definitions: he finds it "hard to grasp what could be a camera color gamut, because any light (visible or not) maps to some point in the camera color space—even if it is to the origin of the space. One could define a sensor (camera) gamut as the set of spectral radiances to which the sensor responds, but that would equate ‘‘spectrum’’ to ‘‘color’’ and the gamut could not be characterized in a space of reduced dimensionality such as a color space. Alternatively, a camera gamut could be ‘‘the largest set of scene colors that produce unique outputs,’’ but this definition also has difficulties." Brill notes that the term ‘‘camera color gamut’’ is a misnomer, because what is being discussed is not a property of just a camera. Rather, it is a property of a set of spectral power distributions (A), a camera (B), and an algorithm that maps camera values to CIE XYZs (C). Brill ultimately proposes the following definition: "Camera color analysis gamut: Attribute of a set of spectral power distributions (SPDs) (A), a camera (B), and an algorithm (C) that maps camera values to CIE XYZ triplets, that attribute being the set of CIE XYZ triplets for each of which there is an SPD in (A) that, when acquired by camera (B), produces camera values that, when processed by algorithm (C), produces that XYZ triplet. The gamut can be represented in a color space derived from XYZ triplets (such as CIELAB), or in a reduced space such as chromaticity (x,y). (The alternative term camera color gamut is also used). " Brill closes with the following statement: A definition of camera gamut is new, and needed. The definition I propose here is now being discussed by representatives of several standards bodies. The quality of the algorithm, or of the camera, or of the set of SPDs, are valid subjects of research papers, but one must start with a definition such as the one here so people know what is being discussed. Both of these short papers are excellent and make points worth understanding and remembering. --Rich Wagner === (1) Let's call it “color-gamut rendering” COLOR RESEARCH & APPLICATION Volume 32, Issue 4, August 2007, Pages: 334–335, Roy S. Berns (2) Camera color gamut: Spray-painting the invisible definition; COLOR RESEARCH & APPLICATION; Volume 32; Issue 3; June 2007; Pages: 236–237; Michael H. Brill
Hello Mr. Warner: Thank you for all this information. 2011/11/7 Richard Wagner <Rich@wildnaturephotos.com>:
Brill closes with the following statement: A definition of camera gamut is new, and needed. The definition I propose here is now being discussed by representatives of several standards bodies. The quality of the algorithm, or of the camera, or of the set of SPDs, are valid subjects of research papers, but one must start with a definition such as the one here so people know what is being discussed.
This it was my last thought of yesterday: the necessity of consensus in the glossary. And a clear definition that definitively exists and contributes with an alternative document for his debate.
Both of these short papers are excellent and make points worth understanding and remembering.
Are accessible these documents? Salud Jose Bueno
Very useful summaries, Rich, thank you for laying it all out. Given we have a camera, film or digital, we know that reproduction depends not just on the film properties or sensor properties, but on many other factors, like flare in the camera box, lens properties, ambient temperature, location of the battery, etc. From a practical standpoint, measuring sensor response in different wavelengths under different conditions and in different sensor areas we can come up with very different results. Of course we need somehow to define the observable effect of different reactions to light spectrum and to see how we can compare different sensitive materials in that regard. We also may want to see a measure that allows to predict how accurate can icc profiles be for a given sensitive material. But if we want just to solve everyday problem of colour reproduction we may need quite a different tool. -- Iliah Borg ib@pochtar.com
I can't resist commenting that the extensive quoting of Dr. Brill is the most coverage Datacolor has received on this list in a long while. As a friend and colleague of Mike I respect his comments, but I don't believe his proposal is the one end users are looking for. Actually, describing the needs and views of the end user to Mike is one of my main roles with him. My suggestion would be that the gamut of a color capture device be considered "the contiguous zone, outside of which the device cannot continue to distinguish color differences in a meaningful way", specifically further increases in saturation. If a capture device can continue to effectively distinguish color without changing settings on the device, then it's "gamut limit" has not yet been reached. This simple concept can then be appended with most everything else that as been said here, but the end user is unlikely to take away much from these further complications. Color scientists, on the other hand, will. C. David Tobie Global Product Technology Manager Imaging Color Solutions Datacolor inc. cdtobie@datacolor.com www.datacolor.com On Nov 7, 2011, at 5:03 PM, Richard Wagner <Rich@WildNaturePhotos.com> wrote:
On Nov 6, 2011, at : Iliah Borg <ib@pochtar.com> wrote:
I think we have a little language problem here. To quote, "there is no such thing as a camera, or scanner, gamut" http://www.cis.rit.edu/research/mcsl2/outreach/faq.php?catnum=3#255
Thanks for the link, Iliah.
"there is no such thing as a camera, or scanner, gamut"
There are several interesting discussions of this postulate in the literature. Unfortunately, the articles are expensive unless you have access to a research library, so I've taken the liberty of summarizing two of them for those without such access.
Berns (1) takes the above position and argues that the term ‘‘color gamut’’ historically has been associated with color output such as optimal color stimuli and additive and subtractive imaging systems. He notes that from both historical and current contexts, ‘‘color gamut’’ is associated with producing color, not measuring color; that is, color gamuts are defined by output devices, not input devices. If a camera is considered a measurement device - not unlike a colorimeter or spectrophotometer - it cannot have a "color gamut" as it is able to respond to all colors presented to it (i.e., there is no such thing as an "out of gamut" color for the device).
Berns takes issue with the use of the expression "color gamut" in scientific comparisons of digital cameras, and argues that "if a measurement device has a color gamut, ... [then] a miscalibrated spectrophotometer (calibrating to black instead of white) or camera with lens cap attached have small color gamuts." Rather than use the term "color gamut," he proposes the use of the expression, "color gamut rendering."
"That is, under a set of stated conditions a target of colors has been rendered to a set of colorimetric coordinates owing to various parameters. The stated conditions might include an ensemble of spectral reflectance factors obtained using a spectrophotometer with stated measurement geometry (the target), the camera-taking light source, the camera’s optical properties and methodology of obtaining colorimetric coordinates if known, and the standard illuminant and observer for the colorimetric data. Differences in input device characteristics would result in the target’s color gamut being rendered differently."
Brill (2) urges the explicit adoption of a definition for the camera color gamut. In his view, a viable definition seems to be the set of CIE XYZ triplets such that, for any such XYZ, there exists a spectral power distribution in a predefined set whose camera values map through a predefined algorithm to that XYZ.
Brill notes that the term "color gamut" is problematic when applied to a scanner or digital camera. However, he acknowledges that it has been used in this context in various venues, including referred articles and conferences. In such discussions, "the definition is always assumed and never stated." Brill believes it is time to "make explicit what is implicitly understood, or metaphorically, to spray-paint the invisible definition."
Brill discusses alternative definitions: he finds it "hard to grasp what could be a camera color gamut, because any light (visible or not) maps to some point in the camera color space—even if it is to the origin of the space. One could define a sensor (camera) gamut as the set of spectral radiances to which the sensor responds, but that would equate ‘‘spectrum’’ to ‘‘color’’ and the gamut could not be characterized in a space of reduced dimensionality such as a color space. Alternatively, a camera gamut could be ‘‘the largest set of scene colors that produce unique outputs,’’ but this definition also has difficulties." Brill notes that the term ‘‘camera color gamut’’ is a misnomer, because what is being discussed is not a property of just a camera. Rather, it is a property of a set of spectral power distributions (A), a camera (B), and an algorithm that maps camera values to CIE XYZs (C).
Brill ultimately proposes the following definition:
"Camera color analysis gamut: Attribute of a set of spectral power distributions (SPDs) (A), a camera (B), and an algorithm (C) that maps camera values to CIE XYZ triplets, that attribute being the set of CIE XYZ triplets for each of which there is an SPD in (A) that, when acquired by camera (B), produces camera values that, when processed by algorithm (C), produces that XYZ triplet. The gamut can be represented in a color space derived from XYZ triplets (such as CIELAB), or in a reduced space such as chromaticity (x,y). (The alternative term camera color gamut is also used). "
Brill closes with the following statement: A definition of camera gamut is new, and needed. The definition I propose here is now being discussed by representatives of several standards bodies. The quality of the algorithm, or of the camera, or of the set of SPDs, are valid subjects of research papers, but one must start with a definition such as the one here so people know what is being discussed.
Both of these short papers are excellent and make points worth understanding and remembering.
--Rich Wagner
===
(1) Let's call it “color-gamut rendering” COLOR RESEARCH & APPLICATION Volume 32, Issue 4, August 2007, Pages: 334–335, Roy S. Berns
(2) Camera color gamut: Spray-painting the invisible definition; COLOR RESEARCH & APPLICATION; Volume 32; Issue 3; June 2007; Pages: 236–237; Michael H. Brill
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To all, By definition, if the camera has overlapping filter sets, all wavelengths will be captured and unless there is a horrible problem in post processing, energy from very small shifts in wavelength will be quite measureable. That's how we measure the spectral sensitivity of a sensor. The earlier paper that was cited, written, by Jack Holms showed the effective difference between the outline of the locus produced by CIE 1931 observer and an arbitrary camera. That locus is often mistakenly stated to represent a gamut. It does not. It is true, particularly with emissive narrow band radiation, that a camera may not be able to capture the entire wavelength range at one setting of exposure, but it certainly will be able to distinguish the difference between two wavelengths very close together. After all, the human eye does the same thing with three overlapping sensitivities. The issue, as Brill correctly stated, isn't gamut, it is how colors are arbitrarily mapped by the continuous sensitivities of the camera. The real question comes down to a decision to get the most accurate color or the most pleasing color, which has nothing to due with gamut. In general, gamut clipping occurs in all cameras using a predetermined color space, because the clipping is defined by the selected color space, typically sRGB or Adobe RGB. The camera certainly captures data outside of these spaces (assuming that the sensitivities are reasonable). In raw processing, the color space is often assumed to be RIMM (or ProPhoto RGB)which is defined with imaginary color primaries and it far exceeds the gamut of real world colors, but it does not enclose the CIE locus. I'm not sure that using hyperbole such as "the contiguous zone, outside of which the device cannot continue to distinguish color differences in a meaningful way", really adds to a serious technical discussion of the issue and continuing to define one word, used in an incorrect context, with a vague description adds nothing to the end user's understanding of the issues. End user's are quite capable of understanding complex issues, if those issues are explained properly. The trick is in the teaching, not the hype. Regards, Tom Lianza On 11/7/11 7:25 PM, "Charles D Tobie" <cdtobie@mac.com> wrote:
I can't resist commenting that the extensive quoting of Dr. Brill is the most coverage Datacolor has received on this list in a long while. As a friend and colleague of Mike I respect his comments, but I don't believe his proposal is the one end users are looking for. Actually, describing the needs and views of the end user to Mike is one of my main roles with him.
My suggestion would be that the gamut of a color capture device be considered "the contiguous zone, outside of which the device cannot continue to distinguish color differences in a meaningful way", specifically further increases in saturation. If a capture device can continue to effectively distinguish color without changing settings on the device, then it's "gamut limit" has not yet been reached. This simple concept can then be appended with most everything else that as been said here, but the end user is unlikely to take away much from these further complications. Color scientists, on the other hand, will.
C. David Tobie Global Product Technology Manager Imaging Color Solutions Datacolor inc. cdtobie@datacolor.com www.datacolor.com
On Nov 7, 2011, at 5:03 PM, Richard Wagner <Rich@WildNaturePhotos.com> wrote:
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My suggestion would be that the gamut of a color capture device be considered "the contiguous zone, outside of which the device cannot continue to distinguish color differences in a meaningful way",
This brings a question of metameric failures.
specifically further increases in saturation.
Pixel saturation? I have a feeling that we are trying here to avoid discussion of spectral responses. Camera characterisation through the map of spectral responses over the area of the sensor, with different lenses, at different ISO speed values is what IMHO what end users need. -- Iliah Borg ib@pochtar.com
On Nov 7, 2011, at 3:31 PM, José Ángel Bueno García wrote:
Are accessible these documents?
As much as I would like to post the short articles in their entirety, copyright law prevents me from doing so - I can't afford the wrath of Wiley. It is unfortunate that Wiley does not reduce the cost of these articles for those not associated with institutions. There is definitely a need for "open-access" type publishing of academic research (http://en.wikipedia.org/wiki/Open_access), as even many institutions are choking over subscription costs. For the sake of completeness, there are two follow-up letters to the two articles that might be of interest. (3) Camera color analysis gamut Color Research & Application (February 2008), 33 (1), pg. 81-82 Robert W. G. Hunt; Michael R. Pointer http://resolver.scholarsportal.info/resolve/03612317/v33i0001/81_ccag Michael Brill has opened a valuable discussion about camera gamuts and Roy Berns has questioned the use of the word “gamut” in that proposal. We would like to stress the importance of associating a gamut with an imaging output device and would thus question the use of the concept proposed for assessing the capabilities of an input device. © 2007 Wiley Periodicals, Inc. Col Res Appl, 33, 81–82, 2008 (4) Try camera gamut again: Not for size, but for camera and profile evaluation Color Research & Application (February 2008), 33 (1), pg. 82-83 Michael Brill http://resolver.scholarsportal.info/resolve/03612317/v33i0001/82_tcganfbfcap... Hunt and Pointer call into question the utility of the camera color gamut (at least by my definition). Such doubt may be partly due to the connection of gamut with a size metric. Quite apart from gamut size, the sets that define my gamut definition are essential to the evaluation of digital cameras in conjunction with their profiles. The output‐device gamut; emphasized by Hunt and Pointer is also important, but appears at another stage of color management. © 2007 Wiley Periodicals, Inc. Col Res Appl, 33, 82–83, 2008 --Rich Wagner
Richard, Your post made me look into an old email I sent to Mr. Berns in 2007 following the article you refer too. Since these are my words and there is no confidential or personal content, here is the letter: ------------- "Dear Mr. Berns, I read with curiosity your comment titled “Let’s Call It Color-Gamut Rendering,”ref-1 which caught my attention because it conveyed various concepts in my mind. While I agree with the overall content of your comment, uneasiness remained with the expression. I found it was because of the word “rendering,” which triggers my neurons corresponding to “output”, especially when positioned as the last word. I understand that a camera output is rendered, but, in this case, it could be argued that the rendering is effectively done before the gamut is generated. It then became clear that the end result of the measuring instrument is a “Color-Rendering Gamut,” i.e. the gamut of the rendered color. This simple word inversion better conveys, at least in my neurons, the underlying process. It is also structured in the same way as other acronyms, such a CRI (Color-Rendering Index), CMF (Color-Matching Function), which are structured as Noun-Verb-Noun. Furthermore, this makes for a catchy acronym, CRG, with a similarity to CRI (but likely more useful), and a word sequence that reads like a quantity, while “Color-Gamut Rendering” reads like a method. As a test, I simply swapped the two expressions in your text, and saw no obvious disagreement, except that the revised expression seemed to better fit the concept. I also made a quick Web search and found no direct hit with my revised wording, although these three words are often used close together in the same sentence; my suggestion should thus not contradict another usage. I concur with your suggestion to formalize the descriptive words for the range of colors measured by an instrument, and with your choice of words, but I would say “Let’s Call It Color-Rendering Gamut”. (...) 1- COLOR research and application, Volume 32, Number 4, August 2007, p. 334" ------------- In essence the same concept but looked with a different eye. Danny ----- Original Message ----- From: "Richard Wagner" <Rich@WildNaturePhotos.com> To: "ColorSync Forum" <colorsync-users@lists.apple.com> Sent: Monday, November 07, 2011 5:03 PM Subject: Camera Gamut (was Re: basiccolor INPUT)
On Nov 6, 2011, at : Iliah Borg <ib@pochtar.com> wrote:
I think we have a little language problem here. To quote, "there is no such thing as a camera, or scanner, gamut" http://www.cis.rit.edu/research/mcsl2/outreach/faq.php?catnum=3#255
Thanks for the link, Iliah.
"there is no such thing as a camera, or scanner, gamut"
There are several interesting discussions of this postulate in the literature. Unfortunately, the articles are expensive unless you have access to a research library, so I've taken the liberty of summarizing two of them for those without such access.
Berns (1) takes the above position and argues that the term ‘‘color gamut’’ historically has been associated with color output such as optimal color stimuli and additive and subtractive imaging systems. He notes that from both historical and current contexts, ‘‘color gamut’’ is associated with producing color, not measuring color; that is, color gamuts are defined by output devices, not input devices. If a camera is considered a measurement device - not unlike a colorimeter or spectrophotometer - it cannot have a "color gamut" as it is able to respond to all colors presented to it (i.e., there is no such thing as an "out of gamut" color for the device).
Berns takes issue with the use of the expression "color gamut" in scientific comparisons of digital cameras, and argues that "if a measurement device has a color gamut, ... [then] a miscalibrated spectrophotometer (calibrating to black instead of white) or camera with lens cap attached have small color gamuts." Rather than use the term "color gamut," he proposes the use of the expression, "color gamut rendering."
"That is, under a set of stated conditions a target of colors has been rendered to a set of colorimetric coordinates owing to various parameters. The stated conditions might include an ensemble of spectral reflectance factors obtained using a spectrophotometer with stated measurement geometry (the target), the camera-taking light source, the camera’s optical properties and methodology of obtaining colorimetric coordinates if known, and the standard illuminant and observer for the colorimetric data. Differences in input device characteristics would result in the target’s color gamut being rendered differently."
Brill (2) urges the explicit adoption of a definition for the camera color gamut. In his view, a viable definition seems to be the set of CIE XYZ triplets such that, for any such XYZ, there exists a spectral power distribution in a predefined set whose camera values map through a predefined algorithm to that XYZ.
Brill notes that the term "color gamut" is problematic when applied to a scanner or digital camera. However, he acknowledges that it has been used in this context in various venues, including referred articles and conferences. In such discussions, "the definition is always assumed and never stated." Brill believes it is time to "make explicit what is implicitly understood, or metaphorically, to spray-paint the invisible definition."
Brill discusses alternative definitions: he finds it "hard to grasp what could be a camera color gamut, because any light (visible or not) maps to some point in the camera color space—even if it is to the origin of the space. One could define a sensor (camera) gamut as the set of spectral radiances to which the sensor responds, but that would equate ‘‘spectrum’’ to ‘‘color’’ and the gamut could not be characterized in a space of reduced dimensionality such as a color space. Alternatively, a camera gamut could be ‘‘the largest set of scene colors that produce unique outputs,’’ but this definition also has difficulties." Brill notes that the term ‘‘camera color gamut’’ is a misnomer, because what is being discussed is not a property of just a camera. Rather, it is a property of a set of spectral power distributions (A), a camera (B), and an algorithm that maps camera values to CIE XYZs (C).
Brill ultimately proposes the following definition:
"Camera color analysis gamut: Attribute of a set of spectral power distributions (SPDs) (A), a camera (B), and an algorithm (C) that maps camera values to CIE XYZ triplets, that attribute being the set of CIE XYZ triplets for each of which there is an SPD in (A) that, when acquired by camera (B), produces camera values that, when processed by algorithm (C), produces that XYZ triplet. The gamut can be represented in a color space derived from XYZ triplets (such as CIELAB), or in a reduced space such as chromaticity (x,y). (The alternative term camera color gamut is also used). "
Brill closes with the following statement: A definition of camera gamut is new, and needed. The definition I propose here is now being discussed by representatives of several standards bodies. The quality of the algorithm, or of the camera, or of the set of SPDs, are valid subjects of research papers, but one must start with a definition such as the one here so people know what is being discussed.
Both of these short papers are excellent and make points worth understanding and remembering.
--Rich Wagner
===
(1) Let's call it “color-gamut rendering” COLOR RESEARCH & APPLICATION Volume 32, Issue 4, August 2007, Pages: 334–335, Roy S. Berns
(2) Camera color gamut: Spray-painting the invisible definition; COLOR RESEARCH & APPLICATION; Volume 32; Issue 3; June 2007; Pages: 236–237; Michael H. Brill
Danny, Thanks for posting your letter. Your suggestion makes good sense to me. --Rich On Nov 7, 2011, at 6:45 PM, dpascale wrote:
Richard,
Your post made me look into an old email I sent to Mr. Berns in 2007 following the article you refer to.
Since these are my words and there is no confidential or personal content, here is the letter:
------------- "Dear Mr. Berns,
I read with curiosity your comment titled “Let’s Call It Color-Gamut Rendering,”ref-1 which caught my attention because it conveyed various concepts in my mind. While I agree with the overall content of your comment, uneasiness remained with the expression. I found it was because of the word “rendering,” which triggers my neurons corresponding to “output”, especially when positioned as the last word. I understand that a camera output is rendered, but, in this case, it could be argued that the rendering is effectively done before the gamut is generated. It then became clear that the end result of the measuring instrument is a “Color-Rendering Gamut,” i.e. the gamut of the rendered color.
This simple word inversion better conveys, at least in my neurons, the underlying process. It is also structured in the same way as other acronyms, such a CRI (Color-Rendering Index), CMF (Color-Matching Function), which are structured as Noun-Verb-Noun. Furthermore, this makes for a catchy acronym, CRG, with a similarity to CRI (but likely more useful), and a word sequence that reads like a quantity, while “Color-Gamut Rendering” reads like a method. As a test, I simply swapped the two expressions in your text, and saw no obvious disagreement, except that the revised expression seemed to better fit the concept. I also made a quick Web search and found no direct hit with my revised wording, although these three words are often used close together in the same sentence; my suggestion should thus not contradict another usage.
I concur with your suggestion to formalize the descriptive words for the range of colors measured by an instrument, and with your choice of words, but I would say “Let’s Call It Color-Rendering Gamut”.
(...)
1- COLOR research and application, Volume 32, Number 4, August 2007, p. 334"
-------------
In essence the same concept but looked with a different eye.
participants (6)
-
Charles D Tobie
-
dpascale
-
Iliah Borg
-
José Ángel Bueno García
-
Richard Wagner
-
Tom Lianza