DOCSLIB.ORG

Colour Documentation Release 0.3.10

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Colour Documentation Release 0.3.10 Colour Documentation Release 0.3.10 Colour DeVELOPERS FEB 12, 2018 Contents 1 Features 3 2 Installation 5 3 Usage 7 3.1 Colour Manual............................................7 3.1.1 Tutorial...........................................7 3.1.1.1 Overview......................................8 3.1.1.2 From Spectral Power Distribution......................... 14 3.1.1.3 Convert to Tristimulus Values........................... 24 3.1.1.4 From CIE XYZ Colourspace............................ 25 3.1.1.5 Convert to Screen Colours............................. 25 3.1.1.6 Generate Colour Rendition Charts........................ 26 3.1.1.7 Convert to Chromaticity Coordinates....................... 29 3.1.1.8 And More. ..................................... 31 3.1.2 Reference.......................................... 31 3.1.2.1 Colour....................................... 31 3.1.2.2 Indices and tables................................. 452 3.1.3 Bibliography......................................... 452 3.1.3.1 Indirect References................................ 452 3.2 Examples............................................... 453 4 Contributing 461 5 Changes 463 6 Bibliography 465 7 See Also 467 8 About 469 Bibliography 471 I II Colour Documentation, Release 0.3.10 Colour is a Python colour science package implementing a comprehensive number of colour theory transfor- mations and algorithms. It is open source and freely available under the New BSD License terms. Contents 1 Colour Documentation, Release 0.3.10 2 Contents CHAPTER 1 FEATURES Colour features a rich dataset and collection of objects, please see the features page for more information. 3 Colour Documentation, Release 0.3.10 4 Chapter 1. FEATURES CHAPTER 2 Installation Anaconda from Continuum Analytics is the Python distribution we use to develop Colour: it ships all the scientific dependencies we require and is easily deployed cross-platform: $ conda create -y -n python-colour $ source activate python-colour $ conda install -y -c conda-forge colour-science Colour can be easily installed from the Python Package Index by issuing this command in a shell: $ pip install colour-science The detailed installation procedure is described in the Installation Guide. 5 Colour Documentation, Release 0.3.10 6 Chapter 2. Installation CHAPTER 3 Usage The two main references for Colour usage are the Colour Manual and the Jupyter Notebooks with detailed historical and theoretical context and images. 3.1 Colour Manual 3.1.1 TUTORIAL Colour spreads over various domains of Colour Science from colour models to optical phenomena, this tutorial will not give you a complete overview of the API but will still be a good introduction. Note: A directory full of examples is available at this path in your Colour installation: colour/examples. You can also explore it directly on Github: https://github.com/colour-science/colour/tree/master/colour/ examples from colour.plotting import * colour_plotting_defaults() visible_spectrum_plot() 7 Colour Documentation, Release 0.3.10 3.1.1.1 OvERVIEW Colour is organised around various sub-packages: • adaptation: Chromatic adaptation models and transformations. • algebra: Algebra utilities. • appearance: Colour appearance models. • biochemistry: Biochemistry computations. • continuous: Base objects for continuous data representation. • characterisation: Colour fitting and camera characterisation. • colorimetry: Core objects for colour computations. • constants: CIE and CODATA constants. • corresponding: Corresponding colour chromaticities computations. • difference: Colour difference computations. • examples: Examples for the sub-packages. • io: Input / output objects for reading and writing data. • models: Colour models. • notation: Colour notation systems. • phenomena: Computation of various optical phenomena. 8 Chapter 3. Usage Colour Documentation, Release 0.3.10 • plotting: Diagrams, figures, etc. • quality: Colour quality computation. • recovery: Reflectance recovery. • temperature: Colour temperature and correlated colour temperature computation. • utilities: Various utilities and data structures. • volume: Colourspace volumes computation and optimal colour stimuli. Most of the public API is available from the root colour namespace: import colour print(colour.__all__[:5]+[ '...']) ['handle_numpy_errors', 'ignore_numpy_errors', 'raise_numpy_errors', 'print_numpy_errors', 'warn_numpy_ ,!errors', '...'] The various sub-packages also expose their public API: from pprint import pprint import colour.plotting for sub_package in ('adaptation', 'algebra', 'appearance', 'biochemistry', 'characterisation', 'colorimetry', 'constants', 'continuous', 'corresponding', 'difference', 'io', 'models', 'notation', 'phenomena', 'plotting', 'quality', 'recovery', 'temperature', 'utilities', 'volume'): print(sub_package.title()) pprint(getattr(colour, sub_package).__all__[:5]+[ '...']) print('\n') Adaptation ['CHROMATIC_ADAPTATION_TRANSFORMS', 'XYZ_SCALING_CAT', 'VON_KRIES_CAT', 'BRADFORD_CAT', 'SHARP_CAT', '...'] Algebra ['cartesian_to_spherical', 'spherical_to_cartesian', 'cartesian_to_polar', 'polar_to_cartesian', 'cartesian_to_cylindrical', '...'] Appearance ['Hunt_InductionFactors', 'HUNT_VIEWING_CONDITIONS', 'Hunt_Specification', 'XYZ_to_Hunt', 'ATD95_Specification', 3.1. Colour Manual 9 Colour Documentation, Release 0.3.10 '...'] Biochemistry ['reaction_rate_MichealisMenten', 'substrate_concentration_MichealisMenten', '...'] Characterisation ['RGB_SpectralSensitivities', 'RGB_DisplayPrimaries', 'CAMERAS_RGB_SPECTRAL_SENSITIVITIES', 'COLOURCHECKERS', 'COLOURCHECKER_INDEXES_TO_NAMES_MAPPING', '...'] Colorimetry ['SpectralShape', 'SpectralPowerDistribution', 'MultiSpectralPowerDistribution', 'DEFAULT_SPECTRAL_SHAPE', 'constant_spd', '...'] Continuous ['AbstractContinuousFunction', 'Signal', 'MultiSignal', '...'] Constants ['CIE_E', 'CIE_K', 'K_M', 'KP_M', 'AVOGADRO_CONSTANT', '...'] Corresponding ['BRENEMAN_EXPERIMENTS', 'BRENEMAN_EXPERIMENTS_PRIMARIES_CHROMATICITIES', 'corresponding_chromaticities_prediction_CIE1994', 'corresponding_chromaticities_prediction_CMCCAT2000', 'corresponding_chromaticities_prediction_Fairchild1990', '...'] Difference ['DELTA_E_METHODS', 'delta_E', 'delta_E_CIE1976', 'delta_E_CIE1994', 'delta_E_CIE2000', '...'] Io ['IES_TM2714_Spd', 'read_image', 'write_image', 'read_spectral_data_from_csv_file', 10 Chapter 3. Usage Colour Documentation, Release 0.3.10 'read_spds_from_csv_file', '...'] Models ['XYZ_to_xyY', 'xyY_to_XYZ', 'xy_to_xyY', 'xyY_to_xy', 'xy_to_XYZ', '...'] Notation ['MUNSELL_COLOURS_ALL', 'MUNSELL_COLOURS_1929', 'MUNSELL_COLOURS_REAL', 'MUNSELL_COLOURS', 'munsell_value', '...'] Phenomena ['scattering_cross_section', 'rayleigh_optical_depth', 'rayleigh_scattering', 'rayleigh_scattering_spd', '...'] Plotting ['ASTM_G_173_ETR', 'PLOTTING_RESOURCES_DIRECTORY', 'DEFAULT_FIGURE_ASPECT_RATIO', 'DEFAULT_FIGURE_WIDTH', 'DEFAULT_FIGURE_HEIGHT', '...'] Quality ['TCS_SPDS', 'VS_SPDS', 'CRI_Specification', 'colour_rendering_index', 'CQS_Specification', '...'] Recovery ['SMITS_1999_SPDS', 'XYZ_to_spectral_Meng2015', 'RGB_to_spectral_Smits1999', 'REFLECTANCE_RECOVERY_METHODS', 'XYZ_to_spectral', '...'] Temperature ['CCT_TO_UV_METHODS', 'UV_TO_CCT_METHODS', 'CCT_to_uv', 'CCT_to_uv_Ohno2013', 'CCT_to_uv_Robertson1968', 3.1. Colour Manual 11 Colour Documentation, Release 0.3.10 '...'] Utilities ['handle_numpy_errors', 'ignore_numpy_errors', 'raise_numpy_errors', 'print_numpy_errors', 'warn_numpy_errors', '...'] Volume ['ILLUMINANTS_OPTIMAL_COLOUR_STIMULI', 'is_within_macadam_limits', 'is_within_mesh_volume', 'is_within_pointer_gamut', 'is_within_visible_spectrum', '...'] The code is documented and almost every docstrings have usage examples: print(colour.temperature.CCT_to_uv_Ohno2013.__doc__) Returns the *CIE UCS* colourspace *uv* chromaticity coordinates from given correlated colour temperature :math:`T_{cp}`, :math:`\Delta_{uv}` and colour matching functions using *Ohno (2013)* method. Parameters ---------- CCT : numeric Correlated colour temperature :math:`T_{cp}`. D_uv : numeric, optional :math:`\Delta_{uv}`. cmfs : XYZ_ColourMatchingFunctions, optional Standard observer colour matching functions. Returns ------- ndarray *CIE UCS* colourspace *uv* chromaticity coordinates. References ---------- .. [4] Ohno, Y. (2014). Practical Use and Calculation of CCT and Duv. LEUKOS, 10(1), 4755. doi:10.1080/15502724.2014.839020 Examples -------- >>> from colour import STANDARD_OBSERVERS_CMFS >>> cmfs = STANDARD_OBSERVERS_CMFS['CIE 1931 2 Degree Standard Observer'] >>> CCT = 6507.4342201047066 >>> D_uv = 0.003223690901513 >>> CCT_to_uv_Ohno2013(CCT, D_uv, cmfs) # doctest: +ELLIPSIS array([ 0.1977999..., 0.3122004...]) At the core of Colour is the colour.colorimetry sub-package, it defines the objects needed for spectral related computations and many others: 12 Chapter 3. Usage Colour Documentation, Release 0.3.10 import colour.colorimetry as colorimetry pprint(colorimetry.__all__) ['SpectralShape', 'SpectralPowerDistribution', 'MultiSpectralPowerDistribution', 'DEFAULT_SPECTRAL_SHAPE', 'constant_spd', 'zeros_spd', 'ones_spd', 'blackbody_spd', 'blackbody_spectral_radiance', 'planck_law', 'LMS_ConeFundamentals', 'RGB_ColourMatchingFunctions', 'XYZ_ColourMatchingFunctions', 'CMFS', 'LMS_CMFS', 'RGB_CMFS', 'STANDARD_OBSERVERS_CMFS', 'ILLUMINANTS', 'D_ILLUMINANTS_S_SPDS', 'HUNTERLAB_ILLUMINANTS', 'ILLUMINANTS_RELATIVE_SPDS', 'LIGHT_SOURCES', 'LIGHT_SOURCES_RELATIVE_SPDS', 'LEFS', 'PHOTOPIC_LEFS', 'SCOTOPIC_LEFS', 'BANDPASS_CORRECTION_METHODS', 'bandpass_correction', 'bandpass_correction_Stearns1988',
Load more

Recommended publications
  • Calculation of CCT and Duv and Practical Conversion Formulae
    CORM 2011 Conference, Gaithersburg, MD, May 3-5, 2011 Calculation of CCT and Duv and Practical Conversion Formulae Yoshi Ohno Group Leader, NIST Fellow Optical Technology Division National Institute of Standards and Technology Gaithersburg, Maryland USA CORM 2011 1 White Light Chromaticity Duv CCT CORM 2011 2 Duv often missing Lighting Facts Label CCT and CRI do not tell the whole story of color quality CORM 2011 3 CCT and CRI do not tell the whole story Triphosphor FL simulation Not acceptable Not preferred Neodymium (Duv=-0.005) Duv is another important dimension of chromaticity. CORM 2011 4 Duv defined in ANSI standard Closest distance from the Planckian locus on the (u', 2/3 v') diagram, with + sign for above and - sign for below the Planckian locus. (ANSI C78.377-2008) Symbol: Duv CCT and Duv can specify + Duv the chromaticity of light sources just like (x, y). - Duv The two numbers (CCT, Duv) provides color information intuitively. (x, y) does not. Duv needs to be defined by CIE. CORM 2011 5 ANSI C78.377-2008 Specifications for the chromaticity of SSL products CORM 2011 6 CCT- Duv chart 5000 K 3000 K 4000 K 6500 K 2700 K 3500 K 4500 K 5700 K ANSI 7-step MacAdam C78.377 ellipses quadrangles (CCT in log scale) CORM 2011 7 Correlated Color Temperature (CCT) Temperature [K] of a Planckian radiator whose chromaticity is closest to that of a given stimulus on the CIE (u’,2/3 v’) coordinate. (CIE 15:2004) CCT is based on the CIE 1960 (u, v) diagram, which is now obsolete.
    [Show full text]
  • Calculating Correlated Color Temperatures Across the Entire Gamut of Daylight and Skylight Chromaticities
    Calculating correlated color temperatures across the entire gamut of daylight and skylight chromaticities Javier Herna´ ndez-Andre´ s, Raymond L. Lee, Jr., and Javier Romero Natural outdoor illumination daily undergoes large changes in its correlated color temperature ͑CCT͒, yet existing equations for calculating CCT from chromaticity coordinates span only part of this range. To improve both the gamut and accuracy of these CCT calculations, we use chromaticities calculated from our measurements of nearly 7000 daylight and skylight spectra to test an equation that accurately maps CIE 1931 chromaticities x and y into CCT. We extend the work of McCamy ͓Color Res. Appl. 12, 285–287 ͑1992͔͒ by using a chromaticity epicenter for CCT and the inverse slope of the line that connects it to x and y. With two epicenters for different CCT ranges, our simple equation is accurate across wide chromaticity and CCT ranges ͑3000–106 K͒ spanned by daylight and skylight. © 1999 Optical Society of America OCIS codes: 010.1290, 330.1710, 330.1730. 1. Introduction term correlated color temperature ͑CCT͒ instead of A colorimetric landmark often included in the Com- color temperature to describe its appearance. Sup- mission Internationale de l’Eclairage ͑CIE͒ 1931 pose that x1, y1 is the chromaticity of such an off-locus chromaticity diagram is the locus of chromaticity co- light source. By definition, the CCT of x1, y1 is the ordinates defined by blackbody radiators ͑see Fig. 1, temperature of the Planckian radiator whose chro- inset͒. One can calculate this Planckian ͑or black- maticity is nearest to x1, y1. The colorimetric body͒ locus by colorimetrically integrating the Planck minimum-distance calculations that determine CCT function at many different temperatures, with each must be done within the color space of the CIE 1960 temperature specifying a unique pair of 1931 x, y uniformity chromaticity scale ͑UCS͒ diagram.
    [Show full text]
  • Cooledge Light Quality Metrics Fabricated
    COOLEDGE LIGHT QUALITY METRICS: FABRICATED LUMINAIRES - 3500K NOTES ABOUT LIGHT QUALITY METRICS DATA: ― Values shown are TYPICAL – actual performance of individual units may vary ― The data presented has been generated in accordance with LM-79-08 ― A complete summary of LM-79-08 data is provided for nominal 4x8 (1200x2400) FABRICated Luminaire models only; however, spectral and color rendering data is applicable to all luminaire sizes, models, and flux levels including: ― Spectral Power Distribution (SPD) ― Nominal CCT ― Chromaticity ― Rf and Rg (TM-30-15) ― CRI (Ra) and R-values ― Duv SELECTED DEFINITIONS ― Candlepower: As presented in this document it is the same as “candela” the SI unit of measurement for light intensity. ― CRI (Ra): The general Color Rendering Index based on 8 CIE reference pastel color samples. ― Duv: The American National Standards Institute (ANSI) references Duv, a metric based on the CIE 1976 color space that quantifies the distance between the chromaticity of a given light source and a blackbody radiator of equal CCT. A negative Duv indicates that the source is “below” the Planckian locus (blackbody curve), potentially having a red/ blue tint, whereas a positive Duv indicates that the source is “above” the curve, potentially exhibiting a green tint. ― Nominal CCT Quadrangles: ANSI has defined acceptable chromaticity quadrangles for LED binning in relation to the blackbody curve within CIE color space. The data presented shows the typical chromaticity coordinate within the relevant quadrangle. ― R-value (Ri): The R-value is a mathematical calculation measuring how similar a light source renders a particular color compared to a reference blackbody source of the same CCT.
    [Show full text]
  • A Correlated Color Temperature for Illuminants
    . (R P 365) A CORRELATED COLOR TEMPERATURE FOR ILLUMINANTS By Raymond Davis ABSTRACT As has long been known, most of the artificial and natural illuminants do not match exactly any one of the Planckian colors. Therefore, strictly speaking, they can not be assigned a color temperature. A color of this type may, however, be correlated with a representative Planckian color. The method of determining correlated color temperature described in this paper consists in comparing the relative luminosities of each of the three primary red, green, and blue components of the source with similar values for the Planckian series. With such a comparison three component temperatures are obtained; that is, the red component of the source corresponds with that of the Planckian radiator at one temperature, its green component with that of the Planckian radiator at a second temperature, and its blue component with that of the Planckian radiator at a third temperature. The average of these three component temperatures is designated as the correlated color temperature of the source. The mean devia- tion of the component temperatures from the average temperature is used as a basis for specifying the color (chromaticity) departure of the source from that of the Planckian radiator at the correlated color temperature. The conjunctive wave length indicates the kind of color departure. CONTENTS Page I. Introduction 659 II. The proposed method 662 III. Procedure 665 1. The Planckian radiator evaluated in terms of relative lumi- nosity of the primary components 665 2. Computation of the correlated color temperature 670 3. Calculation of color departure in terms of sensation steps 672 4.
    [Show full text]
  • Calculating Color Temperature and Illuminance Using the TAOS TCS3414CS Digital Color Sensor Contributed by Joe Smith February 27, 2009 Rev C
    TAOS Inc. is now ams AG The technical content of this TAOS document is still valid. Contact information: Headquarters: ams AG Tobelbader Strasse 30 8141 Premstaetten, Austria Tel: +43 (0) 3136 500 0 e-Mail: [email protected] Please visit our website at www.ams.com NUMBER 25 INTELLIGENT OPTO SENSOR DESIGNER’S NOTEBOOK Calculating Color Temperature and Illuminance using the TAOS TCS3414CS Digital Color Sensor contributed by Joe Smith February 27, 2009 Rev C ABSTRACT The Color Temperature and Illuminance of a broad band light source can be determined with the TAOS TCS3414CS red, green and blue digital color sensor with IR blocking filter built in to the package. This paper will examine Color Temperature and discuss how to calculate the Color Temperature and Illuminance of a given light source. Color Temperature information could be useful in feedback control and quality control systems. COLOR TEMPERATURE Color temperature has long been used as a metric to characterize broad band light sources. It is a means to characterize the spectral properties of a near-white light source. Color temperature, measured in degrees Kelvin (K), refers to the temperature to which one would have to heat a blackbody (or planckian) radiator to produce light of a particular color. A blackbody radiator is defined as a theoretical object that is a perfect radiator of visible light. As the blackbody radiator is heated it radiates energy first in the infrared spectrum and then in the visible spectrum as red, orange, white and finally bluish white light. Incandescent lights are good models of blackbody radiators, because most of the light emitted from them is due to the heating of their filaments.
    [Show full text]
  • Estimation of Illuminants from Projections on the Planckian Locus Baptiste Mazin, Julie Delon, Yann Gousseau
    Estimation of Illuminants From Projections on the Planckian Locus Baptiste Mazin, Julie Delon, Yann Gousseau To cite this version: Baptiste Mazin, Julie Delon, Yann Gousseau. Estimation of Illuminants From Projections on the Planckian Locus. IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2015, 24 (6), pp. 1944 - 1955. 10.1109/TIP.2015.2405414. hal-00915853v3 HAL Id: hal-00915853 https://hal.archives-ouvertes.fr/hal-00915853v3 Submitted on 9 Oct 2014 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. 1 Estimation of Illuminants From Projections on the Planckian Locus Baptiste Mazin, Julie Delon and Yann Gousseau Abstract—This paper introduces a new approach for the have been proposed, restraining the hypothesis to well chosen automatic estimation of illuminants in a digital color image. surfaces of the scene, that are assumed to be grey [41]. Let The method relies on two assumptions. First, the image is us mention the work [54], which makes use of an invariant supposed to contain at least a small set of achromatic pixels. The second assumption is physical and concerns the set of color coordinate [20] that depends only on surface reflectance possible illuminants, assumed to be well approximated by black and not on the scene illuminant.
    [Show full text]
  • Standard Illuminant
    Standard illuminant From Wikipedia, the free encyclopedia A standard illuminant is a profile or spectrum of visible light which is published in order to allow images or colors recorded under different lighting to be compared. Contents 1 CIE illuminants 1.1 Illuminant A 1.2 Illuminants B and C 1.3 Illuminant series D 1.4 Illuminant E Relative spectral power distributions (SPDs) of CIE 1.5 Illuminant series F illuminants A, B, and C from 380nm to 780nm. 2 White point 2.1 White points of standard illuminants 3 References 4 External links CIE illuminants The International Commission on Illumination (usually abbreviated CIE for its French name) is the body responsible for publishing all of the well-known standard illuminants. Each of these is known by a letter or by a letter-number combination. Illuminants A, B, and C were introduced in 1931, with the intention of respectively representing average incandescent light, direct sunlight, and average daylight. Illuminants D represent phases of daylight, Illuminant E is the equal-energy illuminant, while Illuminants F represent fluorescent lamps of various composition. There are instructions on how to experimentally produce light sources ("standard sources") corresponding to the older illuminants. For the relatively newer ones (such as series D), experimenters are left to measure to profiles of their sources and compare them to the published spectra:[1] At present no artificial source is recommended to realize CIE standard illuminant D65 or any other illuminant D of different CCT. It is hoped that new developments in light sources and filters will eventually offer sufficient basis for a CIE recommendation.
    [Show full text]
  • Development of the IES Method for Evaluating the Color Rendition of Light Sources
    Development of the IES method for evaluating the color rendition of light sources Aurelien David Paul T. Fini Kevin W. Houser Yoshi Ohno Michael P. Royer Kevin A.G. Smet Minchen Wei Lorne Whitehead We have developed a two-measure system for evaluating light sources’ color rendition that builds upon conceptual progress of numerous researchers over the last two decades. The system quantifies the color fidelity and color gamut (i.e. change in object chroma) of a light source in comparison to a reference illuminant. The calculations are based on a newly developed set of reflectance data from real samples uniformly distributed in color space (thereby fairly representing all colors) and in wavelength space (thereby precluding artificial optimization of the color rendition scores by spectral engineering). The color fidelity score Rf is an improved version of the CIE color rendering index. The color gamut score Rg is an improved version of the Gamut Area Index. In combination, they provide two complementary assessments to guide the optimization of future light sources and allow lighting specifiers to appropriately match sources with applications. 1. Introduction Limitations of the general color rendering index (CRI) [CIE95], developed by the International Lighting Commission (CIE), have been extensively documented [e.g., Worthey03, CIE07, DiLaura11]. Despite many past efforts to develop complimentary or alternative ways for evaluating light sources’ color rendition1 [Guo04, Smet11b, Houser13b], a suitable alternative has not yet been widely adopted; efforts by the CIE to revise the CRI in the 1980s-90s did not succeed [CIE99]. Yet, with the proliferation of solid- state lighting—a family of light sources with tremendous opportunities for spectral engineering and optimization—the need for a method to evaluate color rendition is greater than ever [Houser13a].
    [Show full text]
  • Estimation of Illuminants from Projections on the Planckian Locus Baptiste Mazin, Julie Delon, Yann Gousseau
    Estimation of Illuminants From Projections on the Planckian Locus Baptiste Mazin, Julie Delon, Yann Gousseau To cite this version: Baptiste Mazin, Julie Delon, Yann Gousseau. Estimation of Illuminants From Projections on the Planckian Locus. 2013. hal-00915853v1 HAL Id: hal-00915853 https://hal.archives-ouvertes.fr/hal-00915853v1 Preprint submitted on 9 Dec 2013 (v1), last revised 9 Oct 2014 (v3) HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. 1 Estimation of Illuminants From Projections on the Planckian Locus Baptiste Mazin, Julie Delon and Yann Gousseau Abstract—This paper introduces a new approach for the restraining the hypothesis to well chosen surfaces of the scene, automatic estimation of illuminants in a digital color image. that are assumed to be grey [39]. Potentially grey pixels can The method relies on two assumptions. First, the image is also be selected as the points close to the Planckian locus 1 in supposed to contain at least a small set of achromatic pixels. The second assumption is physical and concerns the set of a given chromaticity space [37]. This approach may fail when possible illuminants, assumed to be well approximated by black two potentially grey surfaces are present in the scene.
    [Show full text]
  • Assessing the Colour Quality of LED Sources
    XML Template (2014) [17.11.2014–9:44am] [1–26] //blrnas3.glyph.com/cenpro/ApplicationFiles/Journals/SAGE/3B2/LRTJ/Vol00000/140055/APPFile/SG-LRTJ140055.3d (LRT) [PREPRINTER stage] Lighting Res. Technol. 2014; 0: 1–26 Assessing the colour quality of LED sources: Naturalness, attractiveness, colourfulness and colour difference S Jost-Boissard PhDa, P Avouac MSca and M Fontoynont PhDb aLaboratoire Ge´ nie Civil et Baˆ timent, Ecole Nationale des Travaux Publics de l’Etat, Universite´ de Lyon, Lyon, France bDepartment of Energy and Environment, Danish Building Research Institute, Aalborg University, Aalborg, Denmark Received 10 June 2014; Revised 26 August 2014; Accepted 23 September 2014 The CIE General Colour Rendering Index is currently the criterion used to describe and measure the colour-rendering properties of light sources. But over the past years, there has been increasing evidence of its limitations particularly its ability to predict the perceived colour quality of light sources and especially some LEDs. In this paper, several aspects of perceived colour quality are investigated using a side-by-side paired comparison method, and the following criteria: naturalness of fruits and vegetables, colourfulness of the Macbeth Color Checker chart, visual appreciation (attractiveness/ preference) and colour difference estimations for both visual scenes. Forty-five observers with normal colour vision evaluated nine light sources at 3000 K, and 36 observers evaluated eight light sources at 4000 K. Our results indicate that perceived colour differences are better dealt by the CIECAM02 Uniform Colour Space. Naturalness is better described by fidelity indices even if they did not give perfect predictions for all differences between LED light sources.
    [Show full text]
  • Estimation of Chromaticity Differences and Nearest Color Temperature On
    U. S. DEPARTMENT OF COMMERCE NATIONAL BUREAU OP STANDARDS RESEARCH PAPER RP944 Part of Journal of.Research of the N.ational Bureau of Standards, Volume 17, N.ovember 1936 ESTIMA nON OF CHROMATICITY DIFFERENCES AND NEAREST COLOR TEMPERATURE ON THE STANDARD 1931 ICI COLORIMETRIC COORDINATE SYSTEM By Deane B. Judd ABSTRACT Estimation of chromaticity differences has been facilitat.ed by the preparation of a standard mixture diagram showing by a group of ellipses the scale of per­ ceptibility at the various parts of the diagram. The distances from the bound­ aries of the ellipses to their respective "centers" all correspond approximately to the same number (100) of "least perceptible differences." The estimation of nearest color temperature has been facilitated by the prep­ aration of a mixture diagram on which is shown a family of straight lines inter­ secting the Planckian locus; each straight line corresponds approximately to the locus of points representing stimuli of chromaticity more closely resembling that of the Planckian radiator at the intersection tha,n that of any other Planckian radiator. CONTENTS Page I. Introduction ______ ______ _______ _________ ______________ ________ _ 771 II. Estimation of chromaticity differences_ _ _ _ _ _ _ _ _ _ __ _ _ _ _ __ _ _ _ _ _ _ _ _ _ _ _ 773 III. Nearest color temperature ____ _______ _____ ___________ _______ ____ __ 774 I. INTRODUCTION Since the adoption, in 1931, by the International Commission on Illumination of a standard colorimetric coordinate system, by far the majority of fundamental colorimetric specifications have been ex­ pressed in that system.1 A minor defect which is coming to be more keenly felt as the use of the system becomes more extended is the difficulty of interpreting differences in position on the standard mixture diagram in terms of degree and kind of chromaticity dif­ ference.
    [Show full text]
  • An Examination of Alternatives to the Reference Sources Used in IES TM-30-15
    What is the Reference? An examination of alternatives to the reference sources used in IES TM-30-15 1 Michael P Royer, Ph.D. 1Pacific Northwest National Laboratory 620 SW 5th Avenue, Suite 810 Portland, OR 97204 [email protected] This is an archival copy of an article published in LEUKOS. Please cite as: Royer MP. 2016. What is the Reference? An examination of alternatives to the reference sources used in IES TM-30-15. LEUKOS 13(2):71-89. DOI: 10.1080/15502724.2016.1255146. Abstract This paper documents the role of the reference illuminant in the IES TM-30-15 method for evaluating color rendition. TM-30-15 relies on a relative reference scheme; that is, the reference illuminant and test source always have the same correlated color temperature (CCT). The reference illuminant is a Planckian radiator, model of daylight, or combination of those two, depending on the exact CCT of the test source. Three alternative reference schemes were considered: 1) either using all Planckian radiators or all daylight models, while maintaining the CCT match of the test and reference; 2) using only one of ten possible illuminants (Planckian, daylight, or equal energy), regardless of the CCT of the test source; 3) using an off-Planckian reference illuminant (i.e., a source with a negative Duv). No reference scheme is inherently superior to another, with differences in metric values largely a result of small differences in gamut shape of the reference alternatives. While using any of the alternative schemes is more reasonable in the TM-30-15 evaluation framework than it was with the CIE Test Color Method, the differences still ultimately manifest only as changes in interpretation of the results.
    [Show full text]