Primary colour (A)
Comparison colour (B)
Illuminant
Sets the reference white for CIECAM02 forward model. Non-D65 illuminants apply Bradford chromatic adaptation to the input colour.
Viewing conditions
CIECAM02 surround parameters control the degree of adaptation (D), luminance-level adaptation factor (FL), and chromatic induction factor.
UCS variant — UCS
UCS = general purpose. LCD = Large Colour Difference. SCD = Small Colour Difference. Keyboard 1/2/3 to switch.
Keyboard shortcuts
1/2/3 UCS/LCD/SCD  |  X swap colours  |  R reset all  |  C copy JSON
Colour comparison
Primary (A)
#D3AF37
ΔE
ΔE(CAM02-UCS)
Comparison (B)
#4A90D9
ΔE₀₀
ΔE₇₆
CAM02-UCS J′a′b′ — a′ × b′ Plane (UCS)
a′ × b′ plane with M′ iso-circles. Gold dot = primary (A), Blue dot = comparison (B). Dashed line = ΔE vector. Hue sectors show approximate colour direction.
CIECAM02 appearance correlates
Attribute Primary (A) Comparison (B)
J (lightness)
C (chroma)
h (hue angle)
M (colourfulness)
s (saturation)
Q (brightness)
D (adaptation)
FL
Aw
CAM02-UCS J′a′b′ coordinates
Coordinate Primary (A) Comparison (B)
J′ (lightness)
a′ (red–green)
b′ (yellow–blue)
M′ (colourfulness)
h′ (hue angle)
All-variant ΔE comparison (UCS, LCD, SCD)
Variant c₁ c₂ J′(A) M′(A) J′(B) M′(B) ΔE Quality
Loading…
Star (★) marks the currently selected variant. All three computed simultaneously for side-by-side comparison.
CIELAB coordinates
Coordinate Primary (A) Comparison (B)
L*
a*
b*
C*ab
hab
CIE XYZ tristimulus
Channel Primary (A) Comparison (B)
X
Y
Z
Appearance correlates — J, J′, M, M′
Bar chart comparing CIECAM02 (J, M) with CAM02-UCS (J′, M′) for both colours. Shows compression effect of the UCS transform.
Colour difference metrics
ΔE(CAM02-UCS) vs CIEDE2000 vs ΔE₇₆. Threshold lines: JND=1 (green), Visible=5 (amber), Large=10 (red).
CIE 1931 chromaticity diagram
Spectral locus (white outline) | sRGB gamut triangle (gold dashed) | Gold dot = A | Blue dot = B | White dot = WP
Export and share
JSON includes all CIECAM02 correlates, CAM02-UCS J′a′b′, CIELAB, XYZ, and all three variant ΔE values. PNG exports the J′a′b′ canvas. Share URL encodes colours and settings.
Multi-variant comparison

Compare all three CAM02-UCS variants (UCS, LCD, SCD) side-by-side. Shows J′, M′, ΔE for each variant plus CIEDE2000 and ΔE₇₆ reference values.

Variant c₁ c₂ ΔE(CAM02) J′(A) M′(A) J′(B) M′(B) ΔE₀₀ ΔE₇₆ Best
Click "Compare UCS / LCD / SCD" to run analysis.
Star marks the variant with the lowest ΔE for this colour pair.
ΔE calculator

Enter two hex codes to compute ΔE across all three CAM02-UCS variants plus CIEDE2000 and ΔE₇₆.

vs
Enter hex codes and click Calculate.
CAM02-UCS and CIECAM02 Standards
CIECAM02 — CIE 159:2004

CIE 159:2004 specifies the CIECAM02 colour appearance model. The forward model takes CIE XYZ tristimulus values plus viewing condition parameters (LA, Yb, surround) and outputs six perceptual correlates: lightness J, chroma C, hue angle h, colourfulness M, saturation s, and brightness Q.

The chromatic adaptation step uses the CAT02 matrix to convert XYZ to sharpened LMS-like cone responses, applies a degree-of-adaptation D, then converts through Hunt-Pointer-Estevez (HPE) matrix to post-adaptation LMS for the non-linear response compression stage.

Surround parameters: Average (F=1.0, c=0.69, Nc=1.0), Dim (F=0.9, c=0.59, Nc=0.9), Dark (F=0.8, c=0.525, Nc=0.8).

CAM02-UCS — Luo, Cui & Li (2006)

Luo, Cui & Li (2006) derived a perceptually uniform colour space from CIECAM02, published in Color Research and Application 31(4):320–330. The transform applies a non-linear compression to J and M, then projects to Cartesian coordinates:

J′ = (1 + 100c₁) × J / (1 + c₁ × J)
M′ = ln(1 + c₂ × M) / c₂
a′ = M′ × cos(h)
b′ = M′ × sin(h)

Three variants were optimised for different ΔE scales:

  • UCS: c₁=0.007, c₂=0.0228 — general purpose.
  • LCD: c₁=0.0053, c₂=0.0158 — large colour differences.
  • SCD: c₁=0.0102, c₂=0.0228 — small colour differences.

ΔE in the uniform space is Euclidean: ΔE = √(ΔJ′² + Δa′² + Δb′²).

Perceptual Uniformity and Colour Metrics

A colour space is perceptually uniform when equal Euclidean distances correspond to equal perceived colour differences. CIELAB (1976) was the first major attempt, but has known non-uniformities especially in the blue region.

CAM02-UCS improves on CIELAB by deriving the uniform space from a full colour appearance model (CIECAM02) rather than from tristimulus values alone, and by optimising the uniformity parameters against large-scale visual assessment datasets (BFD, Leeds, Witt, RIT-DuPont).

CIEDE2000 — CIE 142-2001

CIE 142-2001: CIEDE2000 (ΔE₀₀) is the recommended colour-difference formula. It adds corrections for lightness, chroma, hue, and a rotation term RT that addresses the problematic blue region. ΔE₀₀ <1 is imperceptible, 1–2 just noticeable, 2–5 visible, 5–10 large, >10 very large.

CIE Standard Illuminants
  • D65 (6504 K): Standard daylight, sRGB reference white.
  • D50 (5003 K): ICC PCS standard, printing industry.
  • D55 (5503 K): Mid-morning/afternoon daylight.
  • D75 (7504 K): North sky daylight.
  • A (2856 K): Tungsten/incandescent (Planckian radiator).
  • B (4874 K): Direct noon sunlight (deprecated).
  • C (6774 K): Average daylight (deprecated, superseded by D65).
  • E: Equal-energy, all wavelengths equal power.
  • F2 (4230 K): Cool white fluorescent.
  • F7 (6500 K): Broadband fluorescent.
  • F11 (4000 K): Narrow tri-phosphor fluorescent.
CIE 15:2004 — Colorimetry

CIE 15:2004 is the fundamental reference for colorimetric computation. It defines the CIE 1931 standard observer, illuminant SPDs (A, D50, D65, etc.), the XYZ colour space, CIELAB, and chromatic adaptation procedures. All calculations in this tool conform to CIE 15:2004 specifications.

ISO 11664 Series — CIE Colorimetry

The ISO 11664 series (parts 1–6) codifies CIE colorimetric standards into ISO format: standard observers, XYZ tristimulus computation, CIELAB, and colour-difference formulas including CIEDE2000.

Mathematical Models and Formulas

CAM02-UCS Transform (Luo et al., 2006)

Given CIECAM02 correlates J (lightness), M (colourfulness), and h (hue angle in degrees), the CAM02-UCS transform computes perceptually uniform J′a′b′ coordinates:

J′ = (1 + 100 × c₁) × J / (1 + c₁ × J)

M′ = ln(1 + c₂ × M) / c₂

a′ = M′ × cos(h × π/180)
b′ = M′ × sin(h × π/180)

Variant Parameters

UCS: c₁ = 0.007,   c₂ = 0.0228
LCD: c₁ = 0.0053, c₂ = 0.0158
SCD: c₁ = 0.0102, c₂ = 0.0228

Colour Difference

ΔE(CAM02-UCS) = √( ΔJ′² + Δa′² + Δb′² )

The logarithmic compression on M ensures colourfulness differences at high chroma levels are perceptually scaled. UCS is the general-purpose default; LCD was optimised against large colour differences (BFD dataset); SCD was optimised against small colour differences (Witt dataset).

Research References
[1] M. R. Luo, G. Cui, C. Li, "Uniform colour spaces based on CIECAM02 colour appearance model," Color Research and Application, vol. 31, no. 4, pp. 320–330, 2006.
[2] CIE 159:2004, "A colour appearance model for colour management systems: CIECAM02," CIE Central Bureau, Vienna, 2004.
[3] M. R. Luo, G. Cui, B. Rigg, "The development of the CIE 2000 colour-difference formula: CIEDE2000," Color Research and Application, vol. 26, no. 5, pp. 340–350, 2001.
[4] CIE 142-2001, "Improvement to industrial colour-difference evaluation," CIE Central Bureau, Vienna, 2001.
[5] CIE 15:2004, "Colorimetry," 3rd ed., CIE Central Bureau, Vienna, 2004.
[6] C. Li, Z. Li, Z. Wang, Y. Xu, M. R. Luo, G. Cui, M. Melgosa, M. H. Brill, M. Pointer, "Comprehensive color solutions: CAM16, CAT16, and s-CIELAB and beyond," Color Research and Application, vol. 42, no. 6, pp. 703–720, 2017.
[7] M. H. Brill, S. Süsstrunk, "Repairing gamut problems in CIECAM02: A progress report," Color Research and Application, vol. 33, no. 5, pp. 424–426, 2008.
[8] R. W. G. Hunt, M. R. Pointer, Measuring Colour, 4th ed., John Wiley & Sons, Chichester, 2011.
[9] K. M. Lam, "Metamerism and colour constancy," Ph.D. thesis, University of Bradford, 1985. (Origin of the Bradford chromatic adaptation transform.)
[10] IEC 61966-2-1:1999, "Multimedia systems and equipment — Colour measurement and management — Part 2-1: Colour management — Default RGB colour space — sRGB," International Electrotechnical Commission, 1999.
[11] G. Sharma, W. Wu, E. N. Dalal, "The CIEDE2000 color‐difference formula: Implementation notes, supplementary test data, and mathematical observations," Color Research and Application, vol. 30, no. 1, pp. 21–30, 2005.
Research Backend
ON-DEVICE All computation runs locally. No network calls.
Batch ΔE Analysis

Enter hex colours (one per line or comma-separated). Computes CAM02-UCS J′a′b′ for each colour, builds a full pairwise ΔE matrix, and derives statistics (min, max, mean, median, std dev) plus a histogram.

Click Run Batch to analyse colours.
UCS vs LCD vs SCD — Usage Guidance
UCS (c₁=0.007, c₂=0.0228):
 General-purpose uniform colour space.
 Balanced performance across all ΔE scales.

LCD (c₁=0.0053, c₂=0.0158):
 Optimised for Large Colour Differences.
 Better correlation with visual data for ΔE > 5.
 Reference datasets: BFD, Leeds.

SCD (c₁=0.0102, c₂=0.0228):
 Optimised for Small Colour Differences.
 Better correlation with visual data for ΔE < 5.
 Reference datasets: Witt, RIT-DuPont.

Recommendation: Start with UCS. Use LCD for
cross-media comparison or print proofing. Use SCD
for QC tolerance workflows where differences are
known to be small (near JND threshold).
CIECAM02 Blue Defect Impact on CAM02-UCS
The CAT02 matrix used in CIECAM02 can produce
negative cone responses for spectral blues near
460 nm. This produces erroneous J, M, and h values
which propagate into the CAM02-UCS J′a′b′ space.

Li et al. (2017) proposed CAM16 with CAT16 matrix
to fix this defect. CAM16-UCS is the recommended
successor for applications where saturated blues
are critical.

For most practical sRGB workflows, the blue defect
does not manifest as sRGB cannot represent spectral
blues at the problematic saturation levels.
Research backend provides: CIECAM02 forward model, CAM02-UCS (UCS/LCD/SCD), ΔE(CAM02-UCS), CIEDE2000, ΔE76, CIELAB, Bradford chromatic adaptation, CIE 1931 chromaticity, multi-variant comparison, batch analysis with pairwise ΔE matrix, histograms, and full JSON/CSV export. All computation is on-device with zero network dependency.