Source colour
The single colour result appears in the output panel. Patch grid uses all loaded patches simultaneously.
Illuminants
Keyboard S swaps illuminants. Select "Custom CCT..." to reveal the temperature slider.
CAT method
Keyboard 1-8 cycles methods. CAT94 uses HPE cone primaries with S=Z; CAT97 is the CIECAM97s successor.
Adaptation degree - 100%
0% = no adaptation. 100% = full. HPE cone primaries preserve the S=Z relationship. Keyboard R resets to 100%.
Colour patches
Paste hex codes or select a built-in set. Click Apply to use custom patches.
Keyboard shortcuts
1-8 cycle CAT  |  S swap illuminants  |  R reset degree  |  E export CSV  |  C compare methods
White-point summary
Source illuminant
D65 - - -
→
Destination illuminant
A - - -
Single colour result
Source
#735244
→
Adapted
#735244
dE00-
dE76-
dE94-
Src XYZ-
Dst XYZ-
Src L*a*b*-
Dst L*a*b*-
Src LCH-
Dst LCH-
Gamut-
dE00 patch statistics
Min-
Max-
Mean-
Median-
Std Dev-
Patches-
Clipped-
Mean dE76-
Mean dE94-
Patch grid - source vs adapted
Source under D65
Adapted to A
Red borders indicate gamut-clipped patches.
SPD spectral power distribution (380-780 nm)
Blue = source SPD | Orange = destination SPD over 380-780 nm.
CIE 1931 chromaticity diagram
Spectral locus | sRGB gamut triangle (gold dashed) | Planckian locus | WP markers.
dE00 distribution histogram
Full adaptation matrix (M⁻¹ D M)
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det(M)-
k (condition)-
||M||_F-
Determinant near 1.0 confirms invertibility. Low condition number = numerically stable.
Transform matrices - M and M⁻¹
M (XYZ to LMS)
M⁻¹ (LMS to XYZ)
LMS cone-channel analysis
Scale factors (D)
L-
M-
S-
Src WP LMS
L-
M-
S-
Dst WP LMS
L-
M-
S-
For CAT94/HPE, S cone = Z directly (third row = [0,0,1]). Scale factors = dst/src cone ratios modulated by degree.
Per-patch results table
# Src Dst Src Hex Adapted dE00 dE76 dE94 Shift Gamut
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Export and share
CSV includes all patches with dE00/76/94 and gamut status. JSON includes full matrix diagnostics.
Multi-method comparison

Compare all 8 CAT methods against the same patch set and illuminant pair. Shows mean/median/min/max dE00, condition number, and determinant.

Method Mean dE00 Median Min Max Std Dev k(M) det(M) Best
Click "Compare all 8 methods" to run analysis.
Star marks lowest mean dE00. Keyboard C triggers comparison.
CIECAM94, HPE, and Chromatic Adaptation Standards
▶ CIECAM94 — Hunt-Pointer-Estevez Model

CIECAM94 is a colour appearance model developed by the CIE TC 1-34 committee (Hunt, 1994; Luo et al., 1996). It uses the Hunt-Pointer-Estevez (HPE) cone primary matrix as its chromatic adaptation step, converting CIE XYZ to physiologically-based LMS cone responses.

Key feature: The HPE matrix has [0, 0, 1] as its third row, meaning S (short-wavelength) cone response equals the Z tristimulus value directly. This is physiologically motivated — it ties the blue-sensitive cone channel directly to the CIE Z function.

Historical context: CIECAM94 preceded CIECAM97s (which used CAT97) and CIECAM02 (which introduced the sharpened CAT02 matrix). HPE cone fundamentals remain influential in physiological models of human colour vision.

▶ CIECAM97s — Successor with CAT97

CIECAM97s (CIE TC 1-34, 1998; Luo & Hunt, 1998) refined CIECAM94 with improved correlates of brightness, colourfulness, and saturation. It introduced the CAT97 matrix, which provides modest sharpening beyond the HPE basis.

CAT97 matrix: [[0.8562, 0.3372, -0.1934], [-0.8360, 1.8327, 0.0033], [0.0357, 0.0469, 0.9174]]. Unlike HPE, the third row is no longer [0,0,1], introducing cross-channel coupling.

Replaced by CIECAM02: CIECAM97s was superseded by CIE 159:2004 (CIECAM02). However, CAT97 data remains useful for comparative studies.

▶ HPE Cone Primaries — Physiological Basis

Hunt-Pointer-Estevez cone primaries derive from the Stiles & Burch (1959) 10° colour-matching functions, transformed to approximate physiological cone fundamentals via the Estevez (1979) procedure.

The S=Z property: Because the third row of the HPE matrix is [0, 0, 1], the S-cone channel response equals the CIE Z tristimulus value. This means changes in illuminant affect S-cone adaptation purely via the Z ratio.

Modern context: CIE 170-1:2006 and Stockman & Sharpe (2000) cone fundamentals provide updated physiological data, but HPE remains widely used in appearance models and education.

▶ ICC Profile Connection Space (PCS)

ICC v4: The ICC mandates Bradford for converting between device colour spaces and the PCS (D50). CAT94/HPE is for appearance calculations, not ICC PCS conversion.

▶ CIEDE2000 — Colour Difference Standard

CIE 142-2001: CIEDE2000 (dE00) is the current recommended colour-difference formula with corrections for lightness, chroma, hue, and the rotation term RT.

Guideline ranges: dE00 <1 imperceptible, 1-2 perceptible by trained observers, 2-5 visible, 5-10 large, >10 very large.

▶ CIE Standard Illuminants
  • A (2856 K): Tungsten. Planckian radiator.
  • B (4874 K): Direct noon sunlight (deprecated).
  • C (6774 K): Average daylight (deprecated, superseded by D65).
  • D50 (5003 K): ICC PCS, printing.
  • D55 (5503 K): Mid-morning daylight.
  • D65 (6504 K): Standard daylight, sRGB.
  • D75 (7504 K): North sky daylight.
  • E: Equal-energy (theoretical).
  • FL series: Fluorescent lamp spectral types.
▶ Von Kries Coefficient Law

The Von Kries law models chromatic adaptation as independent gain control of each cone type. All CATs implement this in different spaces — HPE (physiological), Bradford (sharpened), CAT02/16 (optimised). The choice of space determines cross-channel coupling and prediction accuracy.

Mathematical Models and Formulas

CAT94 / HPE Transform Matrix (Hunt-Pointer-Estevez, CIECAM94):

M_HPE (XYZ to physiological LMS):
| 0.38971 0.68898 -0.07868 |
|-0.22981 1.18340 0.04641 |
| 0.00000 0.00000 1.00000 | ← S = Z

Key property: Third row = [0, 0, 1]
S-cone response = Z tristimulus value directly

Derivation: Based on Stiles & Burch (1959) 10-degree
CMFs, via Estevez (1979) procedure.
Row sums: 1.00001, 1.00000, 1.00000 (luminance norm)

Used in: CIECAM94, Hunt Model, Nayatani Model
Research, Standards and Citations

CIECAM94, HPE, and Colour Appearance Models

[1] Hunt, R.W.G. (1994). An improved predictor of colourfulness in a model of colour vision. Color Res. App., 19(1), 23-26.

[2] Estevez, O. (1979). On the Fundamental Data-Base of Normal and Dichromatic Colour Vision. PhD thesis, University of Amsterdam.

[3] Hunt, R.W.G. & Pointer, M.R. (2011). Measuring Colour, 4th Ed. Wiley.

[4] Luo, M.R., Lo, M.-C., Kuo, W.-G. (1996). The LLAB(l:c) colour model. Color Res. App., 21(6), 412-429.

[5] Luo, M.R., Hunt, R.W.G. (1998). The structure of the CIE 1997 colour appearance model (CIECAM97s). Color Res. App., 23(3), 138-146.

Cone Fundamentals and Physiological Models

[6] Stiles, W.S. & Burch, J.M. (1959). NPL colour-matching investigation: final report (1958). Optica Acta, 6(1), 1-26.

[7] Stockman, A. & Sharpe, L.T. (2000). The spectral sensitivities of the middle- and long-wavelength-sensitive cones. Vision Research, 40(13), 1711-1737.

[8] CIE (2006). CIE 170-1:2006 Fundamental Chromaticity Diagram with Physiological Axes.

[9] Nayatani, Y. (1997). Simple estimation methods for the Helmholtz-Kohlrausch effect. Color Res. App., 22(6), 385-401.

Successor Models and Standards

[10] CIE (2004). CIECAM02. CIE Publication 159:2004.

[11] Li, C., et al. (2017). CAM16, CAT16. Color Res. App., 42(6), 703-718.

[12] Brill, M.H. & Susstrunk, S. (2008). Repairing gamut problems in CIECAM02. Color Res. App., 33(5), 424-426.

[13] Fairchild, M.D. (2013). Color Appearance Models, 3rd Ed. Wiley-Blackwell.

[14] CIE (2004). Colorimetry, 3rd Ed. CIE 15:2004.

[15] Sharma, G., et al. (2005). CIEDE2000 implementation notes. Color Res. App., 30(1), 21-30.

[16] Lam, K.M. (1985). Metamerism and colour constancy. PhD thesis, Bradford.

[17] ICC (2022). ICC.1:2022. International Color Consortium.

[18] IEC 61966-2-1:1999. sRGB.

About this tool

This tool implements 8 CATs with CAT94 (HPE) default, including unique CAT97 (CIECAM97s), full CIEDE2000/76/94, CIE 1931 chromaticity, SPD analysis, multi-method comparison — entirely client-side. Not a substitute for calibrated measurement.

Research Backend
Backend
HPE S=Z Property — Physiological Transparency

The defining feature of CAT94/HPE is the [0,0,1] third row:

For HPE: S_src = Z_src_wp, S_dst = Z_dst_wp
Scale_S = 1 + D * (Z_dst / Z_src - 1)

Example: D65 → A
Z_D65 = 1.08883, Z_A = 0.35585
Scale_S (full) = 0.35585/1.08883 = 0.3268

67% S-channel compression reflects dramatic
blue reduction under tungsten (warm) light.

Compare Bradford S row = [0.0389,-0.0685,1.0296]
Bradford includes X and Y cross-talk.
CAT94 vs CAT97 — Physiological vs Sharpened
HPE (CAT94): S = 0·X + 0·Y + 1·Z = Z (pure)
CAT97: S = 0.0357X + 0.0469Y + 0.9174Z (sharpened)

HPE det = 1.0000, cond ≈ 4.8
CAT97 det ≈ 0.999, cond ≈ 5.2

Sharpening trade-off:
+ Better prediction for large CCT shifts
+ Improved hue constancy
- Loss of physiological transparency (S≠Z)
- Risk of negative values for extreme stimuli
Advanced Spectral Reconstruction

Spectral-domain adaptation comparison (coming soon).

Click Analyse to compute spectral-domain adaptation.
Batch Chromatic Adaptation

Enter hex colours (one per line or comma-separated). Adapts all using current settings with full dE analysis.

Click Run Batch to analyse colours.
Gamut Mapping Research
Gamut mapping is automatically shown in the per-patch table and JSON export (gamutClipped field).
Research backend: 8 CAT methods (CAT94/HPE default), CIEDE2000/CIE76/CIE94, CIE 1931 chromaticity, SPD analysis, multi-method comparison, matrix diagnostics, gamut clipping, batch adaptation, JSON/CSV export. All on-device, zero network.