Colorcheck:
color accuracy and tonal response

Imatest™ Colorcheck analyzes images of the X-Rite (formerly GretagMacbethTM ) ColorChecker® for color accuracy, tonal response, gamma, and noise. It is particularly useful for measuring the effectiveness of White Balance algorithms and settings under a variety of lighting conditions. The ColorChecker is available from ColorHQ, Adorama, and other suppliers.

You can select the Colorchecker reference values (using standard values or the contents of a data file) and one of six color spaces: sRGB, Adobe RGB (1998), Wide Gamut RGB, ProPhoto RGB, Apple RGB, or ColorMatch. Danny Pascale/Babelcolor’s page on the Colorchecker contains nearly everything you want to know about the chart.

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To run Colorcheck, photograph the ColorChecker, taking care to avoid glare. For best results, the chart image should be 500-1500 pixels wide, though smaller images produce satisfactory results. For testing white balance, you can photograph a ColorChecker in a scene. The ColorChecker image can be very small if a noise analysis is not required. Load the image file, crop it (if needed), then make any needed changes to the input dialog box (for color space, which defaults to sRGB, etc.).

The first figure: gray scale analysis

shows the tonal response and noise of
the gray patches at the bottom of the Colorchecker and and selected EXIF data..

The upper left plot shows the pixel levels of the
six patches. Gamma (the exponent of the equation that relates scene luminance to pixel level) is defined by the
first order fit (the dotted blue line).
   The upper right plot is the transfer curve
(with similar scaling to film transfer curves): the density (log(Pixel
level/255)) as a function of Log exposure ( (-) target density). Stepchart produces a more detailed transfer curve. It also shows the exposure error. The best results are obtained if it is kept under 0.25 f-stops. Note that the x-axis scale (log exposure) is reversed from the plots on the left.

Figure 2.

The lower left plot shows the R, G, B, and Y (luminance) noise, normalized to the difference
between the white and black patches (a density difference of 1.45). Several additional options are available for displaying noise or SNR (Signal-to-Noise Ratio).
  The lower right region displays EXIF data, if
available.

The
second figure: noise detail (Imatest Master only)

shows the density response, noise in f-stops (a relative measurement
that corresponds to the workings of the eye), noise for the third
Colorchecker row, which contains primary colors, and the noise spectrum of the selected patch.

The upper left plot  is the density
response
of the
colorchecker (gray squares). It includes the first and second order
fits
(dashed blue and green lines). The horizontal axis is Log Exposure (minus the target
density), printed on
the
back of the ColorChecker. Stepchart provides a more detailed
density response curve. It also shows exposure error in f-stops.
  The upper right plot shows the noise in the
third colorchecker row, which contains the most strongly colored
patches: Blue, Green, Red, Yellow, Magenta, and Cyan. In certain
cameras noise may vary with the color. Problems may be apparent that
aren’t visible in the gray patches. Several options are available for displaying noise or SNR (Signal-to-Noise Ratio).

The lower left plot shows the R, G, B, and Y
(luminance) RMS noise or SNR as a function of Log Exposure
each patch. Any of several displays may be selected. The above figure has RMS noise is expressed in f-stops, a relative measure that
corresponds closely to the workings of the human eye. This measurement
is described in detail in the Stepchart tour. It is largest in the dark areas because the pixel
spacing between f-stops is smallest.
  The lower right plot shows the noise
spectrum for the R, G, B, and Y channels for the selected patch. An unually rapid dropoff may indicate a large amount of noise reduction software,
which can mask fine detail.

 

 

The third figure: color error

 

shows the color error (the difference between the measured and ideal (reference) values)
in the a*b* plane of the CIELAB color space, which is relatively perceptually
uniform (not perfect, but far more uniform than the common xy Chromaticity
diagram). The small squares are the ideal values; the large circles are
the measured (camera) values. The chroma (related to the perception of saturation) of an individual color is
proportional to its distance from the origin (a* = b* = 0).

The mean camera
chroma (the average of all camera chroma values) relative to the
mean ideal chroma is displayed on the upper right. You can select one of three color error metrics: ΔE*ab (CIE 1976; the familiar Euclidian distance), ΔE*94 (CIE 1994), and ΔE*CMC. ΔE*94 and ΔE*CMC are more complex but more accurate. Mean and RMS (root mean square; σ) or maximum color errors (measured with and without a correction for camera chroma boost or cut) can be displayed. RMS error gives more weight to large errors. Calculation details are given in the Colorcheck Appendix.

 

Images can be analyzed in sRGB, Adobe RGB (1998), Wide Gamut RGB, ProPhoto RGB, Apple RGB, and ColorMatch RGB color spaces. The light gray curve is the boundary of the sRGB color space.

When you interpret the results, keep the following in mind.

Camera manufacturers do not necessarily aim for accurate color reproduction, which often appears flat and dull. They recognize that there is a difference between accurate and pleasing color: most people prefer deep blue skies, saturated green foliage, and warm, slightly saturated skin tones. Ever mindful of the bottom line, they aim to please.
Hence they often boost chroma (i.e., saturation), especially in blues, greens, and skin tones.

Colorcheck can be used to check white balance algorithms and camera performance under different lighting conditions. John Beale’s excellent article on Lighting and Color uses this Colorcheck figure to examine the effects of different lighting on color accuracy.

The fourth figure: color analysis

is an image of the ColorChecker with the correct colors superposed in the center of each patch. The colors in the central squares are corrected for the difference in luminance between the exposed and the ideal values. The colors in the small rectangles to the right of central squares are uncorrected.

The gray patches with exaggerated White Balance error are shown on the bottom. White balance error is displayed in HSV Saturation units, degrees Kelvin, and Mireds (1000/degrees K; a useful unit for filtration).
  You can learn more about Colorcheck from 
Using Colorcheck

 

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