Tag Archives: Bayer CFA

adobe camera raw, Color

A Question of Balance

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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.

Figure 1. DON’T touch them color dials (including Tint)! courtesy of Capture One

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.

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Color, color science, correlated color temperature

White Point, CCT and Tint

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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 XYZ color space, obtained by multiplying wavelength-by-wavelength its SPD (the blue curve below) by the Color Matching Functions of a Standard Observer (\hat{x},\hat{y},\hat{z})

Figure 1.  Spectral Power Distribution of Standard Daylight Illuminant D5300 with a Correlated Color Temperature of  5300 deg. K; and CIE (2012) 2-deg XYZ “physiologically relevant” Color Matching Functions from cvrl.org.

Adding (integrating) the three resulting curves up we get three values that represent the illuminant’s coordinates in the XYZ color space.  The White Point is then obtained by dividing these coordinates by the Y value to normalize it to 1.

The White Point is then seen to be independent of the intensity of the arriving light, as Y represents Luminance from the scene.   For instance a Standard Daylight Illuminant with a Correlated Color Temperature of 5300k has a White Point of[1]

XYZn = [0.9593 1.0000 0.8833] Continue reading White Point, CCT and Tint →

Color, DNG, xyz

Linear Color Transforms

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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 r, g, b for short.

Since the resulting intensities are linearly independent they can form the basis of a 3D coordinate system, with each rgb 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.

Figure 1. The linear sRGB Cube, courtesy of Matlab toolbox Optprop.

The job of the color transform is to project demosaiced raw data rgb to a standard output RGB color space designed for viewing.   Such spaces have names like sRGB, Adobe RGB or Rec. 2020 .  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 →

Color, Exposure, Photometry, Radiometry, Sensors

Connecting Photographic Raw Data to Tristimulus Color Science

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Absolute Raw Data

In the previous article we determined that the three r_{_L}g_{_L}b_{_L} 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 L(\lambda) at the lens – can be estimated as follows:

(1)   \begin{equation*} r_{_L}g_{_L}b_{_L} =\frac{\pi p^2 t}{4N^2} \int\limits_{380}^{780}L(\lambda) \odot SSF_{rgb}(\lambda) d\lambda \end{equation*}

with subscript _L indicating absolute-referred units and SSF_{rgb} the three system Spectral Sensitivity Functions.   In this series of articles \odot 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 →