Primary colour
Comparison colour
sRGB input, adapted to selected illuminant via CAT16. X swaps A ↔ B.
Source illuminant
D=1 → fully adapted. D=0 → no adaptation; colours appear as under source illuminant. CAT16 scales each channel by D·Yw/RGBw + (1−D).
Viewing conditions
FL (Hunt effect) is auto-computed from LA: larger LA raises FL, increasing colourfulness M.
Shortcuts
X — swap A ↔ B  ·  R — reset defaults  ·  C — copy JSON  ·  1 average · 2 dim · 3 dark · 4 D65 · 5 D50
Colours
#D3AF37 Primary
ΔEIPT
FL =
#4A90D9 Comparison
CIEDE2000: ΔE₇₆:
P × T Plane — CAT02 vs CAT16
Open circle = CAT02 (iCAM06). Filled dot = CAT16 (iCAM08). Dashed line = CAT02→CAT16 shift.
Hunt Effect — FL vs LA
FL = 0.2k&sup4;(5LA) + 0.1(1−k&sup4;)²(5LA) where k=1/(5LA+1). Vertical bar = current LA.
I (Intensity) Comparison
ΔE Multi-Metric Bar Chart
CIE 1931 Chromaticity Diagram
IPT Colour Space (CAT16 adaptation)
Colour I P T CIPT hIPT° MHunt
Primary
Comparison
I=intensity · P=protan · T=tritan · C=chroma · h=hue · MHunt=C×FL0.25
CAM16 Appearance Correlates
Colour J C M s Q
Primary
Comparison
J=lightness · C=chroma · h°=hue · M=colourfulness · s=saturation · Q=brightness
CAM16-UCS J′a′b′ (Uniform Colour Space)
Colour J′ a′ b′ C′UCS h′° ΔEUCS
Primary
Comparison
J′=(1+100·0.007)·J/(1+0.007·J) · M′=ln(1+0.0228·M)/0.0228 · ΔEUCS=√(ΔJ′²+Δa′²+Δb′²)
CIELAB D65 Reference
Colour L* a* b* C*
Primary
Comparison
Export & Share
Copy or export current colour data. Share URL encodes both colours, illuminant, viewing conditions, and D.
Multi-Surround Comparison

Compare ΔEIPT, ΔEUCS, CIEDE2000, and ΔE₇₆ across average, dim, and dark surround conditions for the current colour pair.

Surround ΔEIPT ΔEUCS CIEDE2000 ΔE₇₆ IA IB JA JB
iCAM08 Standards Overview
CAT16 vs CAT02 — Chromatic Adaptation Transforms

Both CAT02 (CIE 159:2004) and CAT16 (Li et al. 2017, CIE 248:2022) are von Kries diagonal chromatic adaptation transforms. They differ only in the 3×3 sharpening matrix. CAT16 was derived to reduce gamut-compression distortions observed with CAT02 under certain illuminant pairs (especially tungsten→daylight). It also avoids the negative cone-sharpening excursions that CAT02 can produce for highly saturated spectrally narrow stimuli.

In practice, most sRGB colours shift by less than 1 ΔE between CAT02 and CAT16 under D65 — but the difference becomes visible for non-D65 illuminants at high D.

CAM16 Forward Model (Li et al. 2017)

CAM16 is a direct replacement for CIECAM02 using CAT16 instead of CAT02. The pipeline: XYZ → CAT16 partial D scaling → MCAT16−1 → HPE LMS → sigmoidal compression → opponent channels (a, b) → achromatic response A → J, Q, C, M, s, h. Prediction accuracy is ~0.14 ΔE00 better than CIECAM02 across RIT-DuPont, Witt, and Leeds datasets.

Hunt Effect — Colourfulness & the FL Factor

The Hunt effect (Hunt 1952, 1994) describes the psychophysical observation that colours appear more colourful at higher luminance levels, even when chromaticity is identical. FL = 0.2k&sup4;(5LA) + 0.1(1−k&sup4;)²(5LA) where k=1/(5LA+1). Colourfulness: M = C · FL0.25. At LA=1 cd/m², FL≈0.02; at LA=1000, FL≈0.42.

CAM16-UCS J′a′b′ Uniform Colour Space

CAM16-UCS maps CAM16 correlates into a perceptually uniform space using lightness compression (cJ=0.007) and colourfulness compression (cM=0.0228). ΔEUCS = √(ΔJ′²+Δa′²+Δb′²). Euclidean (invertible) — a key advantage for gamut mapping and rendering pipelines. Error residuals comparable to CIEDE2000.

iCAM Framework Evolution: iCAM → iCAM06 → iCAM08

iCAM (2002): Bradford CAT, IPT, first spatial image appearance model.
iCAM06 (2007): CAT02, IPT, refined tone reproduction, ΔEIPT, Hunt/Stevens effects.
iCAM08 (2008+): CAT16, IPT + CAM16-UCS, improved spatial adaptation, colourfulness restoration step.

At point-scale (this tool), the spatial step collapses to global CAT16 + CAM16 correlates — demonstrating per-pixel behaviour at patch level.

ΔE Comparison: ΔEIPT vs ΔEUCS vs CIEDE2000

ΔEIPT: √(ΔI²+ΔP²+ΔT²) — simple Euclidean, excellent hue uniformity, invertible.
ΔEUCS: √(ΔJ′²+Δa′²+Δb′²) — CAM16-based, perceptually uniform, invertible.
CIEDE2000: weighted, 5 correction terms, best psychophysical fit, not invertible.
ΔE₇₆: CIELAB Euclidean, simplest.

Applications: HDR, Gamut Mapping, Camera ISP, Material You
  • HDR tone mapping — spatially adaptive white maps preserve local contrast.
  • Gamut mapping — constant-hue rays in PT/J′a′b′ avoid hue rotation.
  • Cross-media matching — predict shifts from print to display to projection.
  • Camera ISP — model observer adaptation for white-balance and colour correction.
  • Material You (HCT) — Google draws from IPT hue-uniformity principles.
Mathematical Models and Formulas

CAT16 Chromatic Adaptation Transform (Li et al. 2017)

MCAT16 = [[ 0.401288,  0.650173, -0.051461],
           [-0.250268,  1.204414,  0.045854],
           [-0.002079,  0.048952,  0.953127]]

Degree of adaptation D:
D = F · [1 − (1/3.6) · e−(LA+42)/92] ∈ [0, 1]

Adapted cone responses:
Rc = (D·Yw/Rw + 1−D) · R
Gc = (D·Yw/Gw + 1−D) · G
Bc = (D·Yw/Bw + 1−D) · B
Research, Standards and Citations

CAM16 & CAT16

[1] Li, C., Li, Z., Wang, Z., Xu, Y., Zhang, M., Luo, M.R., Cui, G. & Melgosa, M. (2017). “Comprehensive color solutions: CAM16, CAT16, and S-decoupling and hue linearity in CAM16 and CAT16.” Color Research & Application, 42(6), 703–718.

[2] CIE 248:2022. “The CIE 2017 Colour Fidelity Index for accurate scientific use: Rf.” Includes CAT16 specification.

iCAM Framework

[3] Fairchild, M.D. & Johnson, G.M. (2007). “iCAM06: A refined image appearance model for HDR image rendering.” Journal of Electronic Imaging, 16(3), 033008.

[4] Fairchild, M.D. & Johnson, G.M. (2002). “Meet iCAM: A next-generation color appearance model.” IS&T/SID CIC10, 33–38.

[5] Ebner, F. & Fairchild, M.D. (1998). “Development and testing of a color space (IPT) with improved hue uniformity.” IS&T/SID CIC6, 8–13.

CIECAM02 & Colorimetry

[6] CIE Technical Report 159:2004. “A Colour Appearance Model for Colour Management Systems: CIECAM02.”

[7] CIE 15:2004. “Colorimetry.” 3rd edition.

[8] Sharma, G., Wu, W., Dalal, E.N. (2005). “The CIEDE2000 color-difference formula.” Color Research & Application, 30(1), 21–30.

[9] IEC 61966-2-1:1999. “Default RGB colour space — sRGB.”

Hunt Effect & Colour Appearance

[10] Hunt, R.W.G. (1994). “An improved predictor of colourfulness in a model of colour vision.” Color Research & Application, 19(1), 23–26.

[11] Luo, M.R., Cui, G. & Li, C. (2006). “Uniform colour spaces based on CIECAM02 colour appearance model.” Color Research & Application, 31(4), 320–330.

About this Tool

[12] Auric Artisan Color Science Platform. iCAM08 Research Laboratory. All maths from modular engine. Zero network calls — all computation runs on-device using IEEE 754 double-precision floating point.
Research Backend
On-Device
Batch Pairwise ΔE Analysis

Enter multiple hex colours (comma or newline separated). The engine computes pairwise ΔEIPT, ΔEUCS, CIEDE2000, and ΔE₇₆ for every combination using current illuminant, viewing conditions, and D. Minimum 2 colours.

Enter at least 2 valid hex colours to compute pairwise ΔE analysis.
ΔE Distribution Histogram
CAT02 vs CAT16 Shift Analysis

The P×T canvas superimposes both CAT02 (open circles) and CAT16 (filled dots) positions for each colour. The dashed connector shows the adaptation shift between the two matrices. For D65 sRGB colours, the shift is typically <1 ΔEIPT. For non-D65 illuminants at high D, the shift becomes significant — use this to quantify the practical difference between iCAM06 and iCAM08 adaptation.

Hunt Effect Exploration

The FL vs LA canvas shows how the Hunt luminance adaptation factor varies over the full luminance range (0.01–10000 cd/m²). Colourfulness M=C·FL0.25 is scaled accordingly. The vertical marker tracks the current LA setting. Use this to study how colours lose colourfulness in dim environments (cinema) and gain colourfulness outdoors.

Spatial iCAM08 Pipeline (Future)

Future: implement the full spatially-varying iCAM08 pipeline accepting image input. The image would be Gaussian-blurred to estimate local adaptation whites, enabling per-pixel CAT16 adaptation before the IPT/CAM16 transform. This enables research into local adaptation, HDR tone mapping quality, and colourfulness restoration after tone compression.

Research backend provides: batch pairwise ΔE analysis across four metrics, multi-surround comparison with CAM16 correlates, distribution histograms, CAT02/CAT16 shift visualisation, Hunt effect exploration, and export to JSON/CSV. All computation runs on-device — zero network calls, zero telemetry.