[Leica] On camera gamuts and the M8

[firkin at ncable.net.au (Alastair Firkin)]

Thanks for taking the time to post this stuff: now I need to take the  
time to read and digest it. I need a tutorial on ICC colour  
management and colour spaces before getting too much more into this  
digital world, or I will be so far in it will be too far to return:  
thanks again

On 16/11/2006, at 5:39, MARK DAVISON wrote:

> I have been reading through the technical information at  
> www.color.org (the home page of the International Color Consorium,  
> which sets the standards for profiles used in color management),  
> describing the contents of camera profiles, and I have been  
> inspecting some camera profiles with the ICC Profile Inspector  
> available at http://www.color.org/profileview2.html.
>
> My conclusion is that you cannot tell anything about how a camera  
> responds to the spectrum of light from looking at a "camera gamut"  
> which is derived from a camera profile. For a graphical example of  
> such a "camera gamut" look at:
>
> http://www.luminous-landscape.com/reviews/cameras/leica-m8.shtml
>
> (See Figure 1 on that page.)  This diagram shows a "camera gamut"  
> for the Leica M8 which extends outside of the gamut of CIE LAB space.
>
> Here's the problem with camera gamuts.  A profile for the camera  
> describes a function which maps camera device R,G, B values (the  
> ones you would encounter in a linear RAW file) to CIE Lab values.  
> The profile can define this mapping in (roughly) two ways.  The  
> first way is by giving the entries of a 3 x 3 matrix which you  
> would multiply times the column vector of (R, G, B) values to get  
> CIE X, Y, Z values, (which then can easily converted to CIE Lab).  
> The second method is by giving a color lookup table where you can  
> simply take a device R, G, B triple and look up the closest L, a, b  
> output.
> (This is a slight oversimplification:  the standard allows the  
> profile to specify separate non-linear functions to be applied  
> before and after the matrix transform or the color look up table  
> transform.)
>
> Now here is the conceptual difficulty:  it is straightforward to  
> write a piece of software which examines a profile and determines  
> the range of output values in CIE Lab space which will be attained  
> as the input varies over all possible combinations of device R, G  
> and B.  But the problem is that not all combinations of R, G and B  
> will ever come out of the camera.  The camera does have a perfectly  
> well defined device gamut which is a subset of R, G, B space. (The  
> intuitive reason for this is that the camera response is limited by  
> its responses to monochromatic light--you can't get more saturated  
> than monochromatic. You could determine the camera gamut via the  
> following experiment:  take a tunable source of monochromatic  
> light.  For a set of evenly spaced frequencies over a range which  
> includes the visible spectrum but extends into UV and IR, take a  
> monochromatic beam and shine it into the camera.  Record the R, G,  
> B values attained at that frequency.  Plot the percentage of R and  
> the percentage of G relative to the total.  If you look at the  
> resulting plot you will see a curve in a two dimensional space--the  
> spectrum locus.  The camera device gamut is the set of all points  
> in the convex set bounded by this curve.  Alternatively if you have  
> the camera spectral sensitivity curves for the three channels you  
> can calculate the spectrum curve mathematically.)
>
> What we want to know is the image of the device gamut under the  
> transformation defined by the profile, not the image of all of R,  
> G, B space. Unfortunately the camera profile does not contain any  
> information about the device gamut, so instead we show the range of  
> all of R, G, B space. Not surpisingly this larger range often  
> includes points outside the CIE Lab gamut. Unfortunately this is a  
> purely mathematical artifact and tells us nothing at all about the  
> camera or its spectral sensitivity curves.
>
> An example will make this clear.  Suppose some clever camera  
> company was able to construct a camera whose spectral sensitivity  
> functions exactly matched the color matching functions specified by  
> CIE.  (This camera would be able to exactly predict the colors seen  
> by human observers with ordinary color vision. Note that the camera  
> would have no sensitivity outside of the visible range of  
> wavelengths.)   For this camera the R, G, B responses to the  
> spectrum of light coming from an object would exactly match the CIE  
> X, Y, Z values.  The mappings recorded in the profile would be a 3  
> x 3 identity matrix (1's down the diagonal and 0's otherwise), and  
> a color look up table approximation to the standard mapping from X,  
> Y, Z to L, a b. If we ran gamut display software on the resulting  
> profile, it would show that the camera gamut occupied all of CIE X,  
> Y, Z space, spilling out well beyond the CIE gamut limits.  Would  
> we then conclude that our ideal camera has extended IR response?   
> That it can see unreal colors?
>
> There is a further complication:  the mappings defined by camera  
> profiles do not have to represent the result of physical profiling  
> of the camera.  They can be "renderings", i.e. mappings chosen to  
> create a pleasant appearance in the resulting image.  Thus the  
> profile can be a matter of taste rather than scientific calibration.
>
> A sidebar for those unfamiliar with CIE X, Y, Z coordinates.  One  
> way to think of these coordinates is that they are the raw device  
> coordinates of an abstract camera whose spectral sensitivites have  
> been chosen so that if two input spectra yield the same X, Y, Z  
> coordinates, then human observers with normal color vision will  
> identify the two spectra as having the same color. Think of it as a  
> color camera that can always identify matching colors.  (My wife  
> wishes I had one when I pick socks.)
>
>
>
> The whole point of color management (roughly) is to define every  
> device you use in terms of these
> CIE X, Y, Z coordinates.  (I say roughly because there are  further  
> complications to account for the human ability to perceive neutral  
> gray as a constant color under different illumination, even though  
> the X, Y, Z coordinates of a totally gray object will slide around  
> in X, Y, Z space as the illumination changes.  This is the dread  
> white balance phenomenon.)
>
> For an output device like a printer the characterization problem is  
> easy:  you run through all possible input values (R, G, B triples  
> for typical home inkjet printers), print a little patch for each  
> triple, and then use a colorimeter to measure the CIE X, Y, Z  
> values (under a specified illumination.)  The range of all possible  
> X, Y, Z values that you can obtain is literally the gamut of colors  
> that the printer can achieve.  The printer gamut will always lie  
> inside the CIE X, Y, Z gamut, because these gamut values are the  
> result of direct physical measurement.  A printer can never create  
> a color you can't see.
>
> For a camera the problem is harder.  The mapping from raw camera R,  
> G, B values to X, Y, Z values has to be chosen by a human for a  
> particular purpose.  Do you want the mapping to produce pleasing  
> images for an unrestricted set of photographic situtations?  Do you  
> want the mapping to produce the most accurate possible X, Y, Z  
> values for a limited range of input spectra under a fixed lighting  
> type?  Even an accurate camera profile gamut (where you only look  
> at the range of X, Y, Z values when the input R, G, B values are  
> restricted to the camera's device gamut) may tell you more about  
> the profile maker than the camera.
>
> Cameras don't create colors. Human profile makers create colors.  
> There can be no camera color gamut without a profile.  (Of course  
> if you set the camera to create .jpg files, the camera dutifully  
> creates R, G, B values in a well-defined color space which has a  
> clearly specified way of mapping from color space R, G, B to X, Y,  
> Z.  Here the camera firmware is choosing and applying a mapping  
> from device R, G, B to color space R, G, B. So in that sense,  
> cameras can create colors, but it is the human camera firmware  
> writer who is deciding on the colors.)
>
> References:
>
> For more than you want to know about human color vision and  
> colorimetry see
>
> The Science of Color, Steven K. Shevell editor, Optical Society of  
> America
>
> This book is unique for relating psychophysical experiments (color  
> matching) to the anatomy of the eye.  For example:  did you know  
> that there are no short wavelength cones in the very center of the  
> retina? If you thought de-mosaicing an R, G, B image from a Bayer  
> array is tough, wait till you see the pictures of the distribution  
> of S, M and L cones in the human retina--it just looks like random  
> sprinkles.  The book also defines CIE X,Y, Z space exactly in terms  
> of physical measurements. The introductory chapter on the history  
> of color science is also extremely illuminating. It took a long  
> time for scientists to realize that the color of an object is not  
> an independent attribute of that object, but rather a human  
> sensation derived from light being reflected from or emitted from  
> the object.
>
> For an introduction  to color management and profiles see:
> http://www.color.org/slidepres.html
>
> Proviso:  I am not a color-scientist myself, but I have a Ph.D. in  
> Mathematics and have worked as a software engineer for many years,  
> so I can read and understand the technical descriptions of color  
> science.
>
>
> Mark Davison
>
>
>
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