In this article we confirm quantitatively that getting the White Point, hence the White Balance, right is essential to obtaining natural tones out of our captures. How quickly do colors degrade if the estimated Correlated Color Temperature is off?
Tag Archives: white point
A Question of Balance
In this article I bring together qualitatively the main concepts discussed in the series and argue that in many (most) cases a photographer’s job in order to obtain natural looking tones in their work during raw conversion is to get the illuminant and relative white balance right – and to step away from any slider found in menus with the word ‘color’ in them.
If you are an outdoor photographer trying to get balanced greens under an overcast sky – or a portrait photographer after good skin tones – dialing in the appropriate scene, illuminant and white balance puts the camera/converter manufacturer’s color science to work and gets you most of the way there safely. Of course the judicious photographer always knew to do that – hopefully now with a better appreciation as for why.
White Point, CCT and Tint
As we have seen in the previous post, knowing the characteristics of light at the scene is critical to be able to determine the color transform that will allow captured raw data to be naturally displayed from an output color space like ubiquitous sRGB.
White Point
The light source Spectral Power Distribution (SPD) corresponds to a unique White Point, namely a set of coordinates in the 
color space, obtained by multiplying wavelength-by-wavelength its SPD (the blue curve below) by the response of the retina of a typical viewer, otherwise known as the CIE Color Matching Functions of a Standard Observer (
in the plot)
Adding (integrating) the three resulting curves we get three values that represent the illuminant’s coordinates in the color space. The White Point is obtained by dividing these coordinates by the 
value to normalize it to 1.
For example a Standard Daylight Illuminant with a Correlated Color Temperature of 5300 kelvins has a White Point of[1]
= [0.9593 1.0000 0.8833]
assuming CIE (2012) 2-deg XYZ “physiologically relevant” Color Matching Functions from cvrl.org. Continue reading White Point, CCT and Tint
Linear Color Transforms
Building on a preceeding article of this series, once demosaiced raw data from a Bayer Color Filter Array sensor represents the captured image as a set of triplets, corresponding to the estimated light intensity at a given pixel under each of the three spectral filters part of the CFA. The filters are band-pass and named for the representative peak wavelength that they let through, typically red, green, blue or 
, 
, 
for short.
Since the resulting intensities are linearly independent they can form the basis of a 3D coordinate system, with each 
triplet representing a point within it. The system is bounded in the raw data by the extent of the Analog to Digital Converter, with all three channels spanning the same range, from Black Level with no light to clipping with maximum recordable light. Therefore it can be thought to represent a space in the form of a cube – or better, a parallelepiped – with the origin at [0,0,0] and the opposite vertex at the clipping value in Data Numbers, expressed as [1,1,1] if we normalize all data by it.
The job of the color transform is to project demosaiced raw data to a standard output 
color space designed for viewing. Such spaces have names like 
, 
or 
. The output space can also be shown in 3D as a parallelepiped with the origin at [0,0,0] with no light and the opposite vertex at [1,1,1] with maximum displayable light. Continue reading Linear Color Transforms
Connecting Photographic Raw Data to Tristimulus Color Science
Absolute Raw Data
In the previous article we determined that the three 
values recorded in the raw data in the center of the image plane in units of Data Numbers per pixel – by a digital camera and lens as a function of absolute spectral radiance 
at the lens – can be estimated as follows:
(1) 
with subscript 
indicating absolute-referred units and 
the three system Spectral Sensitivity Functions. In this series of articles 
is wavelength by wavelength multiplication (what happens to the spectrum of light as it progresses through the imaging system) and the integral just means the area under each of the three resulting curves (integration is what the pixels do during exposure). Together they represent an inner or dot product. All variables in front of the integral were previously described and can be considered constant for a given photographic setup. Continue reading Connecting Photographic Raw Data to Tristimulus Color Science
Phase One IQ3 100MP Trichromatic vs Standard Back Linear Color, Part III
Over the last two posts we’ve been exploring some of the differences introduced by tweaks to the Color Filter Array of the Phase One IQ3 100MP Trichromatic Digital Back versus its original incarnation, the Standard Back. Refer to those for the background. In this article we will delve into some of these differences quantitatively[1].
Let’s start with the compromise color matrices we derived from David Chew’s captures of a ColorChecher 24 in the shade of a sunny November morning in Ohio[2]. These are the matrices necessary to convert white balanced raw data to the perceptual CIE XYZ color space, where it is said there should be one-to-one correspondence with colors as perceived by humans, and therefore where most measurements are performed. They are optimized for each back in the current conditions but they are not perfect, the reason for the word ‘compromise’ in their name:
Continue reading Phase One IQ3 100MP Trichromatic vs Standard Back Linear Color, Part III