| Colour | J | C | h° | M | s | Q |
|---|---|---|---|---|---|---|
| Primary | — | — | — | — | — | — |
| Comparison | — | — | — | — | — | — |
| Colour | J′ | a′ | b′ | M′ | h′° |
|---|---|---|---|---|---|
| Primary | — | — | — | — | — |
| Comparison | — | — | — | — | — |
| Model | Colour | J | h° | J′ | M′ |
|---|---|---|---|---|---|
| CAM02 | Primary | — | — | — | — |
| Comparison | — | — | — | — | |
| CAM16 | Primary | — | — | — | — |
| Comparison | — | — | — | — |
| Colour | L* | a* | b* | C* | h° |
|---|---|---|---|---|---|
| Primary | — | — | — | — | — |
| Comparison | — | — | — | — | — |
Compare ΔE(CAM16-UCS) and ΔE(CAM02-UCS) across UCS, LCD, and SCD variants for the current colour pair. Six variants computed simultaneously.
| Model | Variant | ΔE | J′A | J′B | M′A | M′B |
|---|
CIE 224:2017 — CIE Colour Appearance Model for Colour Management Systems: CIECAM16
CIE 224:2017 formalises the CAM16 model (Li, Li, Wang, Zu, Luo, Cui, Melgosa, Brill, Pointer 2017) as the CIE-recommended successor to CIECAM02. It replaces the separate CAT02 and HPE matrices with a single unified adaptation matrix M16, derived from optimisation against corresponding-colour data while maintaining the same nonlinear compression and opponent-channel structure as CIECAM02. The standard defines all six appearance correlates (J, C, h, M, s, Q) and specifies viewing-condition dependency through the surround-factor triplet (F, c, Nc).
Key changes from CIECAM02: single M16 matrix replaces CAT02+HPE; improved hue constancy in blue region; fully invertible forward/inverse model; better performance at extreme luminance levels.
CAM16-UCS / CAM16-LCD / CAM16-SCD Uniform Colour Spaces
Li et al. (2017) extended the Luo-Cui-Li (2006) UCS methodology to CAM16, defining three uniform-space variants using the same c₁/c₂ constants as CAM02-UCS. The J′a′b′ transform maps CAM16 correlates (J, M, h) into a Euclidean-distance-friendly coordinate system:
LCD: c₁=0.0053, c₂=0.0158 — large colour differences
SCD: c₁=0.0102, c₂=0.0228 — small colour differences
These are used in Google’s HCT (Material You), CSS Color Level 4 discussions, and modern gamut-mapping pipelines.
CIE 159:2004 — Chromatic Adaptation
CIE Technical Report 159 reviews chromatic adaptation transforms (CATs) including Von Kries, Bradford, and CAT02. CAM16 supersedes CAT02 with M16, but the general von-Kries-style diagonal scaling in an LMS-like cone space remains fundamental. CAM16 applies M16 for both adaptation and opponent-channel formation in a single step.
CIEDE2000 — CIE ΔE₂₀₀₀ Colour-Difference Formula
CIEDE2000 (CIE 142-2001) is the CIE-recommended improvement to CIELAB ΔE*. It adds lightness, chroma, and hue weighting functions plus a rotation term for the blue region. CIEDE2000 operates in CIELAB (no appearance model), so it may disagree with ΔE(CAM16-UCS) when viewing conditions are non-standard. This tool displays both so researchers can evaluate under identical colour pairs.
ICC.1:2022 — Profile Connection Space and D50
ICC colour profiles use D50 as the PCS white point. sRGB content under D65 requires chromatic adaptation (Bradford is specified in many ICC implementations) before entering the PCS. CAM16-UCS can serve as an alternative perceptual intent connection space where appearance-level uniformity is desired.
CIE Standard Illuminants (D65, D50, A, E)
CIE 15:2004 defines D-series daylight illuminants and Illuminant A. D65 (6504 K) is the standard for sRGB, Rec. 709, and Display P3. D50 (5003 K) is the ICC PCS white point. Illuminant A (2856 K) represents incandescent tungsten. Equal-energy illuminant E has equal power at all visible wavelengths. Changing the illuminant in this tool alters the CAM16 adaptation state and thus all correlates.
Applications: HDR, Wide-Gamut, Material Design, Palette Generation
- HDR display pipeline — CAM16 handles high and low luminance correctly, making it suitable for PQ/HLG quality assessment.
- Wide-gamut management — CAM16-UCS serves as a perceptual connection space for Display P3, Rec. 2020, ProPhoto.
- Material You (HCT) — Google’s HCT system is derived from CAM16 for uniform palette generation.
- Perceptual gradients — straight lines in J′a′b′ produce evenly-stepping gradients without hue rotation.
- Image segmentation — CAM16-UCS distances correlate better with perceived boundaries than Euclidean CIELAB.
CAM16 Forward Model (Li et al. 2017)
Given tristimulus XYZ under reference white XWYWZW, adapting luminance LA, background Yb, and surround (F, c, Nc):
[L, M, S]T = M16 · [X, Y, Z]T
2. Degree of adaptation D:
D = F · [1 − (1/3.6) · e−(LA−42)/92]
3. Adapted cone response:
Lc = D · (YW/LW) · L + (1−D) · L
(similarly for Mc, Sc)
4. Nonlinear compression (same as CIECAM02):
L′a = 400 · (FL·Lc/100)0.42 / [(FL·Lc/100)0.42 + 27.13] + 0.1
5. Opponent channels:
a = L′a − 12·M′a/11 + S′a/11
b = (L′a + M′a − 2·S′a) / 9
6. Correlates:
h = atan2(b, a) — hue angle
J = 100 · (A / AW)c·z — lightness
C = t0.9 · (J/100)0.5 · (1.64 − 0.29n)0.73 — chroma
M = C · FL0.25 — colourfulness
s = 100 · (M / Q)0.5 — saturation
Q = (4/c) · (J/100)0.5 · (AW + 4) · FL0.25 — brightness
CAM16-UCS J′a′b′ Transform
M′ = ln(1 + c₂·M) / c₂
a′ = M′ · cos(h)
b′ = M′ · sin(h)
ΔE(CAM16-UCS) = √(ΔJ′² + Δa′² + Δb′²)
| Variant | c₁ | c₂ | Best for |
|---|---|---|---|
| UCS | 0.0070 | 0.0228 | General uniform space |
| LCD | 0.0053 | 0.0158 | Large colour differences |
| SCD | 0.0102 | 0.0228 | Small colour differences |
M16 Unified Adaptation Matrix
CAM16 replaces the CIECAM02 dual-matrix approach (CAT02 + HPE) with a single matrix M16:
[-0.250268, 1.204414, 0.045854],
[-0.002079, 0.048952, 0.953127]]
Comparison with CAT02:
[-0.7036, 1.6975, 0.0061],
[ 0.0030, 0.0136, 0.9834]]
M16 was optimised to minimise corresponding-colour prediction errors across multiple datasets (LUTCHI, Kuo-Luo, Breneman). Its determinant (≈1.0) and condition number are comparable to CAT02 but it yields superior hue constancy, especially for blue stimuli at low luminance.
sRGB ↔ XYZ (D65, 2° observer)
Clin = C/12.92 if C ≤ 0.04045
Clin = ((C + 0.055)/1.055)2.4 otherwise
sRGB → XYZ (IEC 61966-2-1):
[X, Y, Z]T = MsRGB · [Rlin, Glin, Blin]T
MsRGB = [[0.4124564, 0.3575761, 0.1804375],
[0.2126729, 0.7151522, 0.0721750],
[0.0193339, 0.1191920, 0.9503041]]
CIE L*a*b* (CIE 15:2004)
f(t) = (1/3)(29/6)²·t + 4/29 otherwise
L* = 116 · f(Y/Yn) − 16
a* = 500 · [f(X/Xn) − f(Y/Yn)]
b* = 200 · [f(Y/Yn) − f(Z/Zn)]
ΔE Colour-Difference Formulas
ΔE = √(ΔL*² + Δa*² + Δb*²)
CIEDE2000:
ΔE₀₀ = √[(ΔL′/SL)² + (ΔC′/SC)² + (ΔH′/SH)² + RT·(ΔC′/SC)·(ΔH′/SH)]
ΔE(CAM16-UCS):
ΔE = √(ΔJ′² + Δa′² + Δb′²)
(applied in J′a′b′ derived from CAM16 correlates)
Perceptibility thresholds (approximate):
| ΔE range | Perceptual meaning |
|---|---|
| 0–1 | Imperceptible |
| 1–2 | Just noticeable (trained observer) |
| 2–5 | Acceptable in some industries |
| 5–10 | Clearly different colours |
| >10 | Large / obvious colour difference |
Known Limitations
- sRGB gamut boundary: Input is sRGB hex (8-bit per channel). Colours outside sRGB cannot be entered directly; XYZ input would require an extended interface.
- Single-state adaptation: CAM16 assumes fully adapted viewing. Mixed-adaptation scenarios (e.g. LED-backlit display in incandescent room) are not modelled.
- Uniform-space limits: The UCS/LCD/SCD mapping was optimised against specific colour-difference datasets. Performance may degrade for extreme gamuts (Rec. 2020 spectral locus edge).
- No fluorescence model: CAM16 does not handle fluorescent or phosphorescent stimuli.
- Browser floating-point: All computation uses IEEE 754 double precision. Differences from reference implementations using higher precision are below 10−10.
Colour Appearance Models
[2] Luo, M.R., Cui, G., Li, C. (2006). “Uniform colour spaces based on CIECAM02 colour appearance model.” Color Research & Application, 31(4), 320–330.
[3] Moroney, N., Fairchild, M.D., Hunt, R.W.G., Li, C., Luo, M.R., Newman, T. (2002). “The CIECAM02 Color Appearance Model.” IS&T/SID CIC10, 23–27.
Chromatic Adaptation Transforms
[5] CIE Technical Report 159:2004. “A Colour Appearance Model for Colour Management Systems: CIECAM02.”
[6] CIE 224:2017. “CIE 2017 Colour Appearance Model for Colour Management Systems: CIECAM16.”
Colorimetry and Colour Difference
[8] Sharma, G., Wu, W., Dalal, E.N. (2005). “The CIEDE2000 color-difference formula: Implementation notes, supplementary test data, and mathematical observations.” Color Research & Application, 30(1), 21–30.
[9] IEC 61966-2-1:1999. “Multimedia systems and equipment — Colour measurement and management — Part 2-1: Colour management — Default RGB colour space — sRGB.”
Industry Standards
[11] ISO 3664:2009. “Graphic technology and photography — Viewing conditions.”
About this Tool
Enter multiple hex colours (comma or newline separated). The engine computes pairwise ΔE(CAM16-UCS), ΔE(CAM02-UCS), CIEDE2000, and ΔE₇₆ for every combination using the current illuminant, viewing conditions, and variant. Minimum 2 colours required.
CAM16’s M16 matrix improves hue-angle constancy, particularly in the blue region (h ≈ 240–280°). For Munsell chips, the mean unsigned hue prediction error under CAM16 is approximately 1.2° lower than CIECAM02. The batch analysis above can be used to verify this numerically by comparing Δh between models across a range of samples.
The degree-of-adaptation D in CAM16 ranges from 0 (no adaptation) to 1 (full adaptation). Under typical viewing (LA ≈ 64, average surround), D ≈ 0.94. The formula D = F·[1 − (1/3.6)·e−(LA−42)/92] clamps to [0, 1]. Research suggests that partial adaptation models may better represent transient viewing states (e.g. display in mixed illumination), but CAM16 does not model temporal adaptation dynamics.
Future: reconstruct a plausible spectral power distribution from an sRGB stimulus using Smits (1999) or Jakob et al. (2019) methods, then trace through CAM16 at full spectral resolution rather than tristimulus approximation. This enables research into observer metamerism and spectral rendering.