Fernando Voltolini de Azambuja

Imaging and color measurement

CAM16 and Hellwig–Fairchild calculator

Compare what standard CAM16 and the 2022 Hellwig–Fairchild proposal predict for the same XYZ stimulus and viewing conditions. The calculation runs in your browser.

Inputs

Enter the stimulus, adopted white, and background on the same scale; adapting luminance remains absolute.

Stimulus XYZ
Adopted white XYZ

L_A remains an absolute luminance in cd/m² and is not changed by this scaling.

Results

Appearance correlates

Reference result for the example inputs.

CorrelateCAM162022 proposal
Lightness J59.130559.1305
Brightness Q232.56179.1392
Chroma C49.866434.4892
Colorfulness M51.835345.5003
Saturation s47.211157.494
Hue angle h45.6445.64

Shaded rows are redefined by the proposal. The columns use different scales, so their raw magnitudes are not a color difference and are not directly rankable.

Hue is shown only when the opponent response is large enough to distinguish a direction from floating-point cancellation.

Model implementation 1.2.1

What the models report

Both models describe appearance with lightness J, brightness Q, chroma C, colorfulness M, saturation s, and hue angle h. The proposal preserves J and h while changing the definitions and scales of the other four correlates.

The table reports appearance correlates rather than display RGB or a color-difference score. Comparing the columns shows how the formulations differ; it does not determine which one better predicts observers.

Why viewing conditions matter

The same XYZ can appear different as the adopted white, background, surround, or adapting luminance changes. Enter the conditions for the intended observation; they remain visible and editable beside the result.

Why compare the formulations

The 2022 proposal revisits linked brightness, chroma, colorfulness, and saturation relations in CAM16. Across the observer datasets reported in the paper, the proposal has higher coefficients of determination for brightness and chroma and a lower one for colorfulness. See the equation study for the equations and fit results.

View the implementation and numerical checks on GitHub.