TM-30 LINKS AND ADDITIONAL INFORMATION

@article{mundinger_fine_2023,
	title = {Fine art under low illuminance: {Gamut} and tint},
	issn = {1477-1535, 1477-0938},
	shorttitle = {Fine art under low illuminance},
	url = {http://journals.sagepub.com/doi/10.1177/14771535231172100},
	doi = {10.1177/14771535231172100},
	abstract = {Museum conservation guidelines restrict illuminance for sensitive artwork to levels that can cause objects to be perceived as less colourful, a phenomenon known as the Hunt effect. Previous colour rendering research identified red saturating gamuts that consistently increased perceived saturation and personal preference. A study was conducted to evaluate the visual experience of fine art illuminated by a red saturating gamut family constrained to be uniquely identified by their TM-30 gamut scores (denoted as [Formula: see text]) and position above or below the blackbody locus ( D
              uv
              ). [Formula: see text] and D
              uv
              were systematically varied according to response surface methodology, designed to map second-order terms and interactions, with 96 ⩽ [Formula: see text] ⩽ 124 and −0.0212 ⩽  D
              uv
               ⩽ 0.0036, all at 3000 K and 50 lx. Thirty-one naïve participants each evaluated a pair of paintings in a mock art gallery under nine independently presented scenes along semantic scales corresponding to preference, saturation and naturalness. The study identified a response surface for preference that maps an interaction between [Formula: see text] and D
              uv
              , predicting D
              uv
               = −0.013 was preferred at [Formula: see text] and D
              uv
               = −0.005 was preferred at [Formula: see text]. Increasing [Formula: see text] consistently increased both personal preference and perceived saturation.},
	language = {en},
	urldate = {2023-12-11},
	journal = {Lighting Research \& Technology},
	author = {Mundinger, J and Houser, K},
	month = jun,
	year = {2023},
	pages = {14771535231172100},
}

Museum conservation guidelines restrict illuminance for sensitive artwork to levels that can cause objects to be perceived as less colourful, a phenomenon known as the Hunt effect. Previous colour rendering research identified red saturating gamuts that consistently increased perceived saturation and personal preference. A study was conducted to evaluate the visual experience of fine art illuminated by a red saturating gamut family constrained to be uniquely identified by their TM-30 gamut scores (denoted as [Formula: see text]) and position above or below the blackbody locus ( D uv ). [Formula: see text] and D uv were systematically varied according to response surface methodology, designed to map second-order terms and interactions, with 96 ⩽ [Formula: see text] ⩽ 124 and −0.0212 ⩽  D uv  ⩽ 0.0036, all at 3000 K and 50 lx. Thirty-one naïve participants each evaluated a pair of paintings in a mock art gallery under nine independently presented scenes along semantic scales corresponding to preference, saturation and naturalness. The study identified a response surface for preference that maps an interaction between [Formula: see text] and D uv , predicting D uv  = −0.013 was preferred at [Formula: see text] and D uv  = −0.005 was preferred at [Formula: see text]. Increasing [Formula: see text] consistently increased both personal preference and perceived saturation.

@article{royer_tutorial_2022,
	title = {Tutorial: {Background} and {Guidance} for {Using} the {ANSI}/{IES} {TM}-30 {Method} for {Evaluating} {Light} {Source} {Color} {Rendition}},
	volume = {18},
	issn = {1550-2724, 1550-2716},
	shorttitle = {Tutorial},
	url = {https://www.tandfonline.com/doi/full/10.1080/15502724.2020.1860771},
	doi = {10.1080/15502724.2020.1860771},
	language = {en},
	number = {2},
	urldate = {2023-12-11},
	journal = {LEUKOS},
	author = {Royer, Michael P.},
	month = apr,
	year = {2022},
	pages = {191--231},
}

@misc{noauthor_ies_2022,
	title = {{IES} {TM}-30 {Calculator}},
	url = {https://www.ies.org/standards/standards-toolbox/tm-30-spectral-calculator/},
	abstract = {The official IES TM-30 calculator provides values and creates vector graphics based on the 2021 American National Standard, approved and maintained by the IES Color Committee.},
	urldate = {2022-09-21},
	year = {2022},
}

The official IES TM-30 calculator provides values and creates vector graphics based on the 2021 American National Standard, approved and maintained by the IES Color Committee.

@misc{spitschan_luox_2021,
	title = {luox (.spdx or .csv files) free online app},
	url = {https://luox.app/upload},
	abstract = {Illuminance [lx]
CIE 1931 xy chromaticity (x)
CIE 1931 xy chromaticity (y)
CIE 1964 x₁₀y₁₀ chromaticity (x₁₀)
CIE 1964 x₁₀y₁₀ chromaticity (y₁₀)
S-cone-opic irradiance (mW ⋅ m⁻²)
M-cone-opic irradiance (mW ⋅ m⁻²)
L-cone-opic irradiance (mW ⋅ m⁻²)
Rhodopic irradiance (mW ⋅ m⁻²)
Melanopic irradiance (mW ⋅ m⁻²)
S-cone-opic EDI [lx]
M-cone-opic EDI [lx]
L-cone-opic EDI [lx]
Rhodopic EDI [lx]
Melanopic EDI [lx]
S-cone-opic ELR
M-cone-opic ELR
L-cone-opic ELR
Rhodopic ELR
Melanopic ELR},
	author = {Spitschan, Manuel},
	year = {2021},
	keywords = {SPD},
}

Illuminance [lx] CIE 1931 xy chromaticity (x) CIE 1931 xy chromaticity (y) CIE 1964 x₁₀y₁₀ chromaticity (x₁₀) CIE 1964 x₁₀y₁₀ chromaticity (y₁₀) S-cone-opic irradiance (mW ⋅ m⁻²) M-cone-opic irradiance (mW ⋅ m⁻²) L-cone-opic irradiance (mW ⋅ m⁻²) Rhodopic irradiance (mW ⋅ m⁻²) Melanopic irradiance (mW ⋅ m⁻²) S-cone-opic EDI [lx] M-cone-opic EDI [lx] L-cone-opic EDI [lx] Rhodopic EDI [lx] Melanopic EDI [lx] S-cone-opic ELR M-cone-opic ELR L-cone-opic ELR Rhodopic ELR Melanopic ELR

@article{royer_tutorial_2021,
	title = {Tutorial: {Background} and {Guidance} for {Using} the {ANSI}/{IES} {TM}-30 {Method} for {Evaluating} {Light} {Source} {Color} {Rendition}},
	issn = {1550-2724, 1550-2716},
	shorttitle = {Tutorial},
	url = {https://www.tandfonline.com/doi/full/10.1080/15502724.2020.1860771},
	doi = {10.1080/15502724.2020.1860771},
	language = {en},
	urldate = {2021-10-27},
	journal = {LEUKOS},
	author = {Royer, Michael P.},
	month = mar,
	year = {2021},
	keywords = {Tutorial},
	pages = {1--41},
}

@misc{smet_luxpy_2021,
	title = {{LuxPy} (.spdx, .dat, .txt or .csv files) free online app},
	url = {https://luxpy.herokuapp.com/},
	abstract = {TM-30-18: CCT,Duv,x,y,u',v',LER,Rf,Rg,Rcsh1,Rcsh2,Rcsh3,Rcsh4,Rcsh5,Rcsh6,Rcsh7,Rcsh8,Rcsh9,Rcsh10,Rcsh11,Rcsh12,Rcsh13,Rcsh14,Rcsh15,Rcsh16,Rhsh1,Rhsh2,Rhsh3,Rhsh4,Rhsh5,Rhsh6,Rhsh7,Rhsh8,Rhsh9,Rhsh10,Rhsh11,Rhsh12,Rhsh13,Rhsh14,Rhsh15,Rhsh16,Rfh1,Rfh2,Rfh3,Rfh4,Rfh5,Rfh6,Rfh7,Rfh8,Rfh9,Rfh10,Rfh11,Rfh12,Rfh13,Rfh14,Rfh15,Rfh16,Rf1,Rf2,Rf3,Rf4,Rf5,Rf6,Rf7,Rf8,Rf9,Rf10,Rf11,Rf12,Rf13,Rf14,Rf15,Rf16,Rf17,Rf18,Rf19,Rf20,Rf21,Rf22,Rf23,Rf24,Rf25,Rf26,Rf27,Rf28,Rf29,Rf30,Rf31,Rf32,Rf33,Rf34,Rf35,Rf36,Rf37,Rf38,Rf39,Rf40,Rf41,Rf42,Rf43,Rf44,Rf45,Rf46,Rf47,Rf48,Rf49,Rf50,Rf51,Rf52,Rf53,Rf54,Rf55,Rf56,Rf57,Rf58,Rf59,Rf60,Rf61,Rf62,Rf63,Rf64,Rf65,Rf66,Rf67,Rf68,Rf69,Rf70,Rf71,Rf72,Rf73,Rf74,Rf75,Rf76,Rf77,Rf78,Rf79,Rf80,Rf81,Rf82,Rf83,Rf84,Rf85,Rf86,Rf87,Rf88,Rf89,Rf90,Rf91,Rf92,Rf93,Rf94,Rf95,Rf96,Rf97,Rf98,Rf99},
	urldate = {2021-11-08},
	author = {Smet, Kevin A. G.},
	year = {2021},
}

TM-30-18: CCT,Duv,x,y,u',v',LER,Rf,Rg,Rcsh1,Rcsh2,Rcsh3,Rcsh4,Rcsh5,Rcsh6,Rcsh7,Rcsh8,Rcsh9,Rcsh10,Rcsh11,Rcsh12,Rcsh13,Rcsh14,Rcsh15,Rcsh16,Rhsh1,Rhsh2,Rhsh3,Rhsh4,Rhsh5,Rhsh6,Rhsh7,Rhsh8,Rhsh9,Rhsh10,Rhsh11,Rhsh12,Rhsh13,Rhsh14,Rhsh15,Rhsh16,Rfh1,Rfh2,Rfh3,Rfh4,Rfh5,Rfh6,Rfh7,Rfh8,Rfh9,Rfh10,Rfh11,Rfh12,Rfh13,Rfh14,Rfh15,Rfh16,Rf1,Rf2,Rf3,Rf4,Rf5,Rf6,Rf7,Rf8,Rf9,Rf10,Rf11,Rf12,Rf13,Rf14,Rf15,Rf16,Rf17,Rf18,Rf19,Rf20,Rf21,Rf22,Rf23,Rf24,Rf25,Rf26,Rf27,Rf28,Rf29,Rf30,Rf31,Rf32,Rf33,Rf34,Rf35,Rf36,Rf37,Rf38,Rf39,Rf40,Rf41,Rf42,Rf43,Rf44,Rf45,Rf46,Rf47,Rf48,Rf49,Rf50,Rf51,Rf52,Rf53,Rf54,Rf55,Rf56,Rf57,Rf58,Rf59,Rf60,Rf61,Rf62,Rf63,Rf64,Rf65,Rf66,Rf67,Rf68,Rf69,Rf70,Rf71,Rf72,Rf73,Rf74,Rf75,Rf76,Rf77,Rf78,Rf79,Rf80,Rf81,Rf82,Rf83,Rf84,Rf85,Rf86,Rf87,Rf88,Rf89,Rf90,Rf91,Rf92,Rf93,Rf94,Rf95,Rf96,Rf97,Rf98,Rf99

@misc{royer_color_2021,
	title = {Color: {Double} {Play} – {Illuminating} {Engineering} {Society}},
	shorttitle = {Color},
	url = {https://www.ies.org/lda/color-double-play/},
	language = {en},
	urldate = {2021-07-27},
	author = {Royer, Michael P. and Ratafia, Holly},
	year = {2021},
}

@misc{illuminating_engineering_society_of_north_america_ansiies_2020,
	title = {{ANSI}/{IES} {TM}-30-18 {Advanced} {Calculation} {Tool}},
	url = {https://store.ies.org/product/tm-30-20-ies-method-for-evaluating-light-source-color-rendition/},
	urldate = {2021-10-27},
	author = {Illuminating Engineering Society of North America},
	year = {2020},
}

@misc{illuminating_engineering_society_ies_2020,
	title = {{IES} {TM}-30 to {Improve} {Your} {Lighting} {Design}},
	url = {https://www.ies.org/fires/using-tm-30-to-improve-your-lighting-design/},
	language = {en},
	urldate = {2021-03-18},
	author = {{Illuminating Engineering Society}},
	year = {2020},
	keywords = {Color quality},
}

@article{royer_experimental_2020,
	title = {Experimental validation of colour rendition specification criteria based on {ANSI}/{IES} {TM}-30-18},
	volume = {52},
	issn = {1477-1535, 1477-0938},
	url = {http://journals.sagepub.com/doi/10.1177/1477153519857625},
	doi = {10.1177/1477153519857625},
	abstract = {An experiment was conducted to examine colour rendition specification criteria. Twenty-five participants each evaluated 90 lighting scenes in a room filled with objects. The lighting scenes included nine chromaticity groups, each with 10 systematically-varied colour rendition conditions designed to meet or not meet previously proposed colour preference specification criteria using the ANSI/IES TM-30-18 measures: Fidelity Index ( R
              f
              ), Gamut Index ( R
              g
              ) and red Local Chroma Shift ( R
              cs,h1
              ). The colour rendition conditions did not meet the criterion for none, one, two or all three of these measures. Participants, who chromatically adapted to each chromaticity group, rated the objects' colour appearance on eight-point scales for saturated–dull, normal–shifted and like-dislike (preference), as well as a binary for acceptable or unacceptable. The findings corroborate past work, but also indicate that colour preference criteria could be adjusted slightly to improve performance, with Tier A having R
              f
               ≥ 78, R
              g
               ≥ 95 and −1\% ≤  R
              cs,h1
               ≤ 15\%, Tier B having R
              f
               ≥ 74, R
              g
               ≥ 92 and −7\% ≤  R
              cs,h1
               ≤ 19\%, and Tier C having R
              f
               ≥ 70, R
              g
               ≥ 89 and −12\% ≤  R
              cs,h1
               ≤ 23\%. A companion regression analysis shows models based on R
              f
              , R
              g
              and R
              cs,h1
              were superior in predicting colour preference compared to those using other measures of colour rendition.},
	language = {en},
	number = {3},
	urldate = {2022-01-29},
	journal = {Lighting Research \& Technology},
	author = {Royer, Mp and Wei, M and Wilkerson, A and Safranek, S},
	month = may,
	year = {2020},
	pages = {323--349},
}

An experiment was conducted to examine colour rendition specification criteria. Twenty-five participants each evaluated 90 lighting scenes in a room filled with objects. The lighting scenes included nine chromaticity groups, each with 10 systematically-varied colour rendition conditions designed to meet or not meet previously proposed colour preference specification criteria using the ANSI/IES TM-30-18 measures: Fidelity Index ( R f ), Gamut Index ( R g ) and red Local Chroma Shift ( R cs,h1 ). The colour rendition conditions did not meet the criterion for none, one, two or all three of these measures. Participants, who chromatically adapted to each chromaticity group, rated the objects' colour appearance on eight-point scales for saturated–dull, normal–shifted and like-dislike (preference), as well as a binary for acceptable or unacceptable. The findings corroborate past work, but also indicate that colour preference criteria could be adjusted slightly to improve performance, with Tier A having R f  ≥ 78, R g  ≥ 95 and −1% ≤  R cs,h1  ≤ 15%, Tier B having R f  ≥ 74, R g  ≥ 92 and −7% ≤  R cs,h1  ≤ 19%, and Tier C having R f  ≥ 70, R g  ≥ 89 and −12% ≤  R cs,h1  ≤ 23%. A companion regression analysis shows models based on R f , R g and R cs,h1 were superior in predicting colour preference compared to those using other measures of colour rendition.

@article{smet_luxpy_2020,
	title = {{LuxPy} {Tutorial}: {The} {LuxPy} {Python} {Toolbox} for {Lighting} and {Color} {Science}},
	volume = {16},
	issn = {1550-2724, 1550-2716},
	shorttitle = {Tutorial},
	url = {https://www.tandfonline.com/doi/full/10.1080/15502724.2018.1518717},
	doi = {10.1080/15502724.2018.1518717},
	language = {en},
	number = {3},
	urldate = {2021-11-08},
	journal = {LEUKOS},
	author = {Smet, Kevin A. G.},
	month = jul,
	year = {2020},
	pages = {179--201},
}

@article{david_methods_2019,
	title = {Methods for {Assessing} {Quantity} and {Quality} of {Illumination}},
	volume = {5},
	issn = {2374-4642, 2374-4650},
	url = {https://www.annualreviews.org/doi/10.1146/annurev-vision-091718-015018},
	doi = {10.1146/annurev-vision-091718-015018},
	abstract = {Human vision provides useful information about the shape and color of the objects around us. It works well in many, but not all, lighting conditions. Since the advent of human-made light sources, it has been important to understand how illumination affects vision quality, but this has been surprisingly difficult. The widespread introduction of solid-state light emitters has increased the urgency of this problem. Experts still debate how lighting can best enable high-quality vision—a key issue since about one-fifth of global electrical power production is used to make light. Photometry, the measurement of the visual quantity of light, is well established, yet significant uncertainties remain. Colorimetry, the measurement of color, has achieved good reproducibility, but researchers still struggle to understand how illumination can best enable high-quality color vision. Fortunately, in recent years, considerable progress has been made. Here, we summarize the current understanding and discuss key areas for future study.},
	language = {en},
	number = {1},
	urldate = {2021-10-27},
	journal = {Annual Review of Vision Science},
	author = {David, Aurelien and Smet, Kevin A.G. and Whitehead, Lorne},
	month = sep,
	year = {2019},
	keywords = {Color quality},
	pages = {479--502},
}

Human vision provides useful information about the shape and color of the objects around us. It works well in many, but not all, lighting conditions. Since the advent of human-made light sources, it has been important to understand how illumination affects vision quality, but this has been surprisingly difficult. The widespread introduction of solid-state light emitters has increased the urgency of this problem. Experts still debate how lighting can best enable high-quality vision—a key issue since about one-fifth of global electrical power production is used to make light. Photometry, the measurement of the visual quantity of light, is well established, yet significant uncertainties remain. Colorimetry, the measurement of color, has achieved good reproducibility, but researchers still struggle to understand how illumination can best enable high-quality color vision. Fortunately, in recent years, considerable progress has been made. Here, we summarize the current understanding and discuss key areas for future study.

@article{boyce_lrt_2019,
	title = {{LRT} {Digest} 3: {New} colour metrics and their use},
	volume = {51},
	issn = {1477-1535, 1477-0938},
	shorttitle = {{LRT} {Digest} 3},
	url = {http://journals.sagepub.com/doi/10.1177/1477153519850006},
	doi = {10.1177/1477153519850006},
	abstract = {Executive summary
            The two metrics traditionally used to quantify the colour properties of light sources are the correlated colour temperature and the CIE General Colour Rendering Index. With the arrival of LEDs as a major light source questions began to be asked about the merits of both of these metrics.
            The question asked about correlated colour temperature was how far should the chromaticity of a light source be allowed to depart from the Planckian locus before the light emitted could no longer be said to be white? A tolerance to such a departure ( Duv) already existed but now gathered much more attention.
            The questions asked about the CIE General Colour Rendering Index were more searching. The limitations of the CIE General Colour Rendering Index were explored and, as a result, several alternative approaches to quantifying the colour rendition properties of light sources were proposed. The most comprehensive approach was produced by the Illuminating Engineering Society of North America, first in its Technical Memorandum IES TM-30-15 and more recently in its revision, Technical Memorandum ANSI/IES TM-30-18, which has been accepted as an American Standard. Both these documents describe a system that contains two high-level summary metrics: One for the average fidelity, i.e. how accurately a test light source renders 99 colour samples relative to how they are rendered under a reference illuminant, and the other for the average colourfulness, i.e. the overall increase or decrease in colourfulness of the same colour samples under the same test light source compared to the same reference illuminant. Associated with these overall average metrics are a number of more detailed metrics and graphical presentations. These aim to quantify and illustrate the variations in fidelity and the direction and magnitude of the shifts in chroma and hue around the hue circle.
            Compared to the CIE General Colour Rendering Index or the CIE Fidelity Index, a metric published by the CIE in 2017, ANSI/IES TM-30-18 provides a more comprehensive approach to quantifying and understanding the effects of light source spectrum on the perception of colour. Unfortunately, the new colour metrics described in IES TM-30-15 and ANSI/IES TM-30-18 have not yet been accepted by the CIE. Despite this, some light source manufacturers have started to provide information on their products expressed in terms of the ANSI/IES TM-30-18 colour metrics and designers are beginning to request them. The expectation is that, eventually, the ANSI/IES TM-30-18 metrics will be adopted by many countries and authorities, because they provide a much more comprehensive description of the colour properties of a light source than the CIE General Colour Rendering Index. This will be of value to light source manufacturers and lighting designers as well as those who prepare lighting codes and guides. It is expected that in the future the minimum set of data considered acceptable for describing the colour properties of a light source are likely to be the correlated colour temperature and the associated Duv value, the CIE Fidelity Index or the matching ANSI/IES TM-30-18 Fidelity Index, together with the ANSI/IES TM-30-18 Gamut Index and the ANSI/IES TM-30-18 Colour Vector Graphic.},
	language = {en},
	number = {5},
	urldate = {2020-02-05},
	journal = {Lighting Research \& Technology},
	author = {Boyce, Pr and Stampfli, Jr},
	month = aug,
	year = {2019},
	keywords = {Colorimetry},
	pages = {657--681},
}

Executive summary The two metrics traditionally used to quantify the colour properties of light sources are the correlated colour temperature and the CIE General Colour Rendering Index. With the arrival of LEDs as a major light source questions began to be asked about the merits of both of these metrics. The question asked about correlated colour temperature was how far should the chromaticity of a light source be allowed to depart from the Planckian locus before the light emitted could no longer be said to be white? A tolerance to such a departure ( Duv) already existed but now gathered much more attention. The questions asked about the CIE General Colour Rendering Index were more searching. The limitations of the CIE General Colour Rendering Index were explored and, as a result, several alternative approaches to quantifying the colour rendition properties of light sources were proposed. The most comprehensive approach was produced by the Illuminating Engineering Society of North America, first in its Technical Memorandum IES TM-30-15 and more recently in its revision, Technical Memorandum ANSI/IES TM-30-18, which has been accepted as an American Standard. Both these documents describe a system that contains two high-level summary metrics: One for the average fidelity, i.e. how accurately a test light source renders 99 colour samples relative to how they are rendered under a reference illuminant, and the other for the average colourfulness, i.e. the overall increase or decrease in colourfulness of the same colour samples under the same test light source compared to the same reference illuminant. Associated with these overall average metrics are a number of more detailed metrics and graphical presentations. These aim to quantify and illustrate the variations in fidelity and the direction and magnitude of the shifts in chroma and hue around the hue circle. Compared to the CIE General Colour Rendering Index or the CIE Fidelity Index, a metric published by the CIE in 2017, ANSI/IES TM-30-18 provides a more comprehensive approach to quantifying and understanding the effects of light source spectrum on the perception of colour. Unfortunately, the new colour metrics described in IES TM-30-15 and ANSI/IES TM-30-18 have not yet been accepted by the CIE. Despite this, some light source manufacturers have started to provide information on their products expressed in terms of the ANSI/IES TM-30-18 colour metrics and designers are beginning to request them. The expectation is that, eventually, the ANSI/IES TM-30-18 metrics will be adopted by many countries and authorities, because they provide a much more comprehensive description of the colour properties of a light source than the CIE General Colour Rendering Index. This will be of value to light source manufacturers and lighting designers as well as those who prepare lighting codes and guides. It is expected that in the future the minimum set of data considered acceptable for describing the colour properties of a light source are likely to be the correlated colour temperature and the associated Duv value, the CIE Fidelity Index or the matching ANSI/IES TM-30-18 Fidelity Index, together with the ANSI/IES TM-30-18 Gamut Index and the ANSI/IES TM-30-18 Colour Vector Graphic.

@inproceedings{royer_analysis_2019,
	address = {San Francisco, United States},
	title = {Analysis of color rendition specification criteria},
	isbn = {978-1-5106-2522-8 978-1-5106-2523-5},
	url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10940/2507283/Analysis-of-color-rendition-specification-criteria/10.1117/12.2507283.full},
	doi = {10/gf35dp},
	language = {en},
	urldate = {2019-06-20},
	booktitle = {Light-{Emitting} {Devices}, {Materials}, and {Applications}},
	publisher = {SPIE},
	author = {Royer, Michael},
	editor = {Strassburg, Martin and Kim, Jong Kyu and Krames, Michael R.},
	month = mar,
	year = {2019},
	keywords = {Colorimetry},
	pages = {55},
}

@inproceedings{royer_spectral_2019,
	address = {Washington D.C.},
	title = {Spectral {Characteristics} {Influencing} the {Metameric} {Uncertainty} {Index}},
	url = {http://www.cie.co.at/publications/cie-session-washington-2019?page=2},
	doi = {DOI 10.25039/x46.2019.PP01},
	abstract = {This article examines the relationship between various attributes of light source spectral power distributions (SPDs) and a recently proposed measure of colour rendition, the Metameric Uncertainty Index (Rt). For SPDs comprised of discrete spectral emissions (primaries), the maximum achievable Rt value (corresponding to a reduced likelihood of metameric mismatch) increases with both the number of primaries and their bandwidth. This work also explores how Rt relates to and interacts with other measures of colour rendition—in particular, the Fidelity Index (Rf)—and luminous efficacy of radiation (k). This is important, because there is an intrinsic tradeoff between luminous efficacy of radiation and colour rendition, which informs the application-dependent optimization of illumination. When whitelight SPDs are engineered to maximize k, subject to maintaining a minimum required Rf value, the result is a small number of narrow primaries and hence a comparatively poor Rt value. This can only be mitigated by including Rt among the colour rendition optimization constraints. Therefore, from this perspective, Rt is an independent and key aspect of colour rendition.  Keywords: Colour Rendition, Metameric Uncertainty, Spectral Optimization, Luminous Efficacy of Radiation, Colour Fidelity},
	language = {en},
	author = {Royer, Michael},
	year = {2019},
	keywords = {Colorimetry},
}

This article examines the relationship between various attributes of light source spectral power distributions (SPDs) and a recently proposed measure of colour rendition, the Metameric Uncertainty Index (Rt). For SPDs comprised of discrete spectral emissions (primaries), the maximum achievable Rt value (corresponding to a reduced likelihood of metameric mismatch) increases with both the number of primaries and their bandwidth. This work also explores how Rt relates to and interacts with other measures of colour rendition—in particular, the Fidelity Index (Rf)—and luminous efficacy of radiation (k). This is important, because there is an intrinsic tradeoff between luminous efficacy of radiation and colour rendition, which informs the application-dependent optimization of illumination. When whitelight SPDs are engineered to maximize k, subject to maintaining a minimum required Rf value, the result is a small number of narrow primaries and hence a comparatively poor Rt value. This can only be mitigated by including Rt among the colour rendition optimization constraints. Therefore, from this perspective, Rt is an independent and key aspect of colour rendition. Keywords: Colour Rendition, Metameric Uncertainty, Spectral Optimization, Luminous Efficacy of Radiation, Colour Fidelity

@article{royer_comparing_2019,
	title = {Comparing {Measures} of {Gamut} {Area}},
	volume = {15},
	issn = {1550-2724, 1550-2716},
	url = {https://www.tandfonline.com/doi/full/10.1080/15502724.2018.1500485},
	doi = {10/gf3zrb},
	language = {en},
	number = {1},
	urldate = {2019-06-17},
	journal = {LEUKOS},
	author = {Royer, Michael P.},
	month = jan,
	year = {2019},
	keywords = {Colorimetry},
	pages = {29--53},
}

@article{smet_tutorial_2019,
	title = {Tutorial: {The} {LuxPy} {Python} {Toolbox} for {Lighting} and {Color} {Science}},
	issn = {1550-2724, 1550-2716},
	shorttitle = {Tutorial},
	url = {https://www.tandfonline.com/doi/full/10.1080/15502724.2018.1518717},
	doi = {10/gf3zq5},
	language = {en},
	urldate = {2019-06-17},
	journal = {LEUKOS},
	author = {Smet, Kevin A. G.},
	month = may,
	year = {2019},
	keywords = {Colorimetry, Tutorial},
	pages = {1--23},
}

@article{david_vector_2019,
	title = {A {Vector} {Field} {Color} {Rendition} {Model} for {Characterizing} {Color} {Shifts} and {Metameric} {Mismatch}},
	issn = {1550-2724, 1550-2716},
	url = {https://www.tandfonline.com/doi/full/10.1080/15502724.2018.1554369},
	doi = {10/gf344q},
	language = {en},
	urldate = {2019-06-20},
	journal = {LEUKOS},
	author = {David, Aurelien and Esposito, Tony and Houser, Kevin and Royer, Michael and Smet, Kevin A. G. and Whitehead, Lorne},
	month = feb,
	year = {2019},
	pages = {1--16},
}

@article{hu_effect_2019,
	title = {The {Effect} of {Control} {Resolution} on the {Usability} of {Color}-{Tunable} {Lighting} {Systems}},
	volume = {15},
	issn = {1550-2724, 1550-2716},
	url = {https://www.tandfonline.com/doi/full/10.1080/15502724.2018.1477053},
	doi = {10/gf3zrf},
	language = {en},
	number = {1},
	urldate = {2019-06-17},
	journal = {LEUKOS},
	author = {Hu, Wenye and Davis, Wendy},
	month = jan,
	year = {2019},
	pages = {3--16},
}

@book{illuminating_engineering_society_of_north_america_ies_2018,
	title = {{IES} {TM}-30-18:  {Method} for {Evaluating} {Light} {Source} {Color} {Rendition}},
	isbn = {978-0-87995-379-9},
	url = {https://www.ies.org/product/ies-method-for-evaluating-light-source-color-rendition/},
	language = {en},
	urldate = {2018-11-28},
	author = {Illuminating Engineering Society of North America},
	year = {2018},
	keywords = {Colorimetry},
}

@misc{bernstaedt_ies_2018,
	title = {{IES} {TM}-30-15 {Farbwiedergabe}: {TM}-30-15, {CRI} und {Co}.},
	url = {https://www.production-partner.de/basics/farbwiedergabe-tm-30-15-cri-und-co/},
	language = {de},
	urldate = {2018-09-16},
	author = {Bernstaedt, Herbert},
	year = {2018},
}

@misc{ebu_television_2018,
	title = {Television {Lighting} {Consistency} {Index} 2012},
	url = {https://tech.ebu.ch/tlci-2012},
	abstract = {Television Lighting Consistency Index 2012},
	urldate = {2022-02-21},
	author = {EBU},
	year = {2018},
}

Television Lighting Consistency Index 2012

@misc{illuminating_engineering_society_of_north_america_ies_2018-1,
	title = {{IES} {TM}-30-18 {Position} on {TM}-30-18, {IES} {Method} for {Evaluating} {Light} {Source} {Color} {Rendition}},
	shorttitle = {{PS}-11-18},
	url = {https://www.ies.org/policy/position-statements/ps-11-18-ies-position-on-tm-30-18-ies-method-for-evaluating-light-source-color-rendition/},
	language = {en},
	urldate = {2018-11-28},
	author = {Illuminating Engineering Society of North America},
	year = {2018},
	keywords = {Colorimetry},
}

@article{livingston_how_2018,
	title = {How to {Use} {TM}-30},
	url = {https://leducation.org/LED2018_Presentations/LED2018_Panel_TM30.pd},
	language = {en},
	author = {Livingston, Jason and Luedtke, Wendy and Royer, Michael},
	year = {2018},
	keywords = {Tutorial},
	pages = {72},
}

@misc{ohno_color_2018,
	title = {Color {Quality} {Metrics} and {Spectral} {Design} of {SSL} {Sources}},
	language = {en},
	author = {Ohno, Yoshi},
	year = {2018},
}

@misc{royer_ies_2017,
	title = {{IES} {TM}-30-15 {What} {Have} {We} {Learned} {About} {TM}-30 in the {Past} {Two} {Years}?},
	url = {https://energy.gov/eere/ssl/color-rendition},
	language = {en},
	urldate = {2017-10-06},
	author = {Royer, Michael P.},
	month = dec,
	year = {2017},
}

@misc{energygov_ies_2017,
	title = {{IES} {TM}-30-15 {Ressources} {Color} {Rendition}},
	url = {https://energy.gov/eere/ssl/color-rendition},
	language = {en},
	urldate = {2017-10-06},
	author = {energy.gov},
	year = {2017},
	keywords = {LED},
}

@misc{houser_ies_2017,
	title = {{IES} {TM}-30-15 {Resources} maintained by {Houser}},
	url = {http://www.personal.psu.edu/kwh101/TM30/main.htm},
	language = {en},
	urldate = {2017-10-08},
	author = {Houser, Kevin W.},
	year = {2017},
}

@misc{leclairagefr_ies_2017,
	title = {{IES} {TM} 30-15 introduction in french},
	url = {http://leclairage.fr/tm-30-15/},
	abstract = {SommaireIntroductionPourquoi un nouvel indice ?Comparaison entre IRC et TM 30-15Tableau récapitulatif IRC versus TM 30-15TM 30-15Détails de la méthode de calculTeintes, Saturation et représentation vectorielleExemples de représentations graphiquesConclusion Introduction Pourquoi un nouvel indice ? Depuis l'arrivée de la LED, les limitations de l'IRC ont été de plus en plus évidentes, comme par exemple l'indice moyen... Lire plus →},
	language = {fr},
	urldate = {2017-10-06},
	journal = {Guide de l'éclairage},
	author = {leclairage.fr},
	month = sep,
	year = {2017},
}

SommaireIntroductionPourquoi un nouvel indice ?Comparaison entre IRC et TM 30-15Tableau récapitulatif IRC versus TM 30-15TM 30-15Détails de la méthode de calculTeintes, Saturation et représentation vectorielleExemples de représentations graphiquesConclusion Introduction Pourquoi un nouvel indice ? Depuis l'arrivée de la LED, les limitations de l'IRC ont été de plus en plus évidentes, comme par exemple l'indice moyen... Lire plus →

@book{cie_cie_2017,
	title = {{CIE} 224:2017  {CIE} 2017 {Colour} {Fidelity} {Index} for accurate scientific use},
	isbn = {ISBN 978-3-902842-61-9},
	url = {http://www.cie.co.at/publications/cie-2017-colour-fidelity-index-accurate-scientific-use-0},
	abstract = {CIE - INTERNATIONAL COMMISSION ON ILLUMINATION
 This colour fidelity index, based on the fidelity index of the Illuminating Engineering Society of North America, defined in TM-30-15, addresses aspects for only the first part of the limitations of the CRI – it does not address the need for perception-related colour quality measure(s) beyond fidelity. However, it does address several previously reported inaccuracies of the CRI as a colour fidelity measure. The important improvements of this measure, relative to the CRI, are the update of the colour difference calculation, in particular the object colour space, and the incorporation of 99 test-colour samples which provide a more uniform distribution of slope and curvature values as a function of wavelength and which have colour appearance values that are more widely and uniformly distributed in the three dimensions of a uniform colour space. 
The general colour fidelity index, Rf, represents how closely the colour appearances of the entire sample set are reproduced (rendered) on average by a test light as compared to those under a reference illuminant. Thus, similar to the general colour rendering index, Ra, the general colour fidelity index, Rf, combines the computed colour differences for all test-colour samples in one single average index value, and is only one aspect of colour quality not considering perception/preference effects. Therefore, it is considered that such unintended uses of CRI as an overall colour quality measure for end users is not better fulfilled by the more scientifically accurate general colour fidelity index, Rf. This is because the users’ evaluation is influenced by factors beyond colour fidelity such as chroma effects, and the detailed nature of specific illumination tasks.},
	language = {en},
	urldate = {2017-10-06},
	author = {CIE},
	month = jan,
	year = {2017},
	keywords = {Colorimetry},
}

CIE - INTERNATIONAL COMMISSION ON ILLUMINATION This colour fidelity index, based on the fidelity index of the Illuminating Engineering Society of North America, defined in TM-30-15, addresses aspects for only the first part of the limitations of the CRI – it does not address the need for perception-related colour quality measure(s) beyond fidelity. However, it does address several previously reported inaccuracies of the CRI as a colour fidelity measure. The important improvements of this measure, relative to the CRI, are the update of the colour difference calculation, in particular the object colour space, and the incorporation of 99 test-colour samples which provide a more uniform distribution of slope and curvature values as a function of wavelength and which have colour appearance values that are more widely and uniformly distributed in the three dimensions of a uniform colour space. The general colour fidelity index, Rf, represents how closely the colour appearances of the entire sample set are reproduced (rendered) on average by a test light as compared to those under a reference illuminant. Thus, similar to the general colour rendering index, Ra, the general colour fidelity index, Rf, combines the computed colour differences for all test-colour samples in one single average index value, and is only one aspect of colour quality not considering perception/preference effects. Therefore, it is considered that such unintended uses of CRI as an overall colour quality measure for end users is not better fulfilled by the more scientifically accurate general colour fidelity index, Rf. This is because the users’ evaluation is influenced by factors beyond colour fidelity such as chroma effects, and the detailed nature of specific illumination tasks.

@article{royer_chroma_2017,
	title = {Chroma {Shift} and {Gamut} {Shape}: {Going} {Beyond} {Average} {Color} {Fidelity} and {Gamut} {Area}},
	volume = {0},
	issn = {1550-2724},
	shorttitle = {Chroma {Shift} and {Gamut} {Shape}},
	url = {http://dx.doi.org/10.1080/15502724.2017.1372203},
	doi = {10.1080/15502724.2017.1372203},
	abstract = {Though sometimes referred to as a two-measure system for evaluating color rendition, IES TM-30-15 includes key components that go beyond the two high-level average values, Fidelity Index (IES Rf) and Gamut Index (IES Rg). This article focuses on the Color Vector Graphic and Local Chroma Shift (IES Rcs,hj), discussing the calculation methods for these evaluation tools and providing context for the interpretation of the values. We illustrate why and how the Color Vector Graphic and Local Chroma Shift values capture information about color rendition that is impossible to describe with average measures (such as CIE Ra, IES Rf, or IES Rg) but that is pertinent to more completely quantifying color rendition and to understanding human evaluations of color quality in the built environment. We also present alternatives for quantifying the Color Vector Graphic and Local Chroma Shift values, which can inform the development of future measures.},
	language = {en},
	number = {0},
	urldate = {2017-10-30},
	journal = {LEUKOS},
	author = {Royer, Michael P. and Houser, Kevin W. and David, Aurélien},
	month = oct,
	year = {2017},
	note = {00000},
	keywords = {Colorimetry, SPD},
	pages = {1--17},
}

Though sometimes referred to as a two-measure system for evaluating color rendition, IES TM-30-15 includes key components that go beyond the two high-level average values, Fidelity Index (IES Rf) and Gamut Index (IES Rg). This article focuses on the Color Vector Graphic and Local Chroma Shift (IES Rcs,hj), discussing the calculation methods for these evaluation tools and providing context for the interpretation of the values. We illustrate why and how the Color Vector Graphic and Local Chroma Shift values capture information about color rendition that is impossible to describe with average measures (such as CIE Ra, IES Rf, or IES Rg) but that is pertinent to more completely quantifying color rendition and to understanding human evaluations of color quality in the built environment. We also present alternatives for quantifying the Color Vector Graphic and Local Chroma Shift values, which can inform the development of future measures.

@misc{leclairagefr_ansiies_2017,
	title = {{ANSI}/{IES} {TM} 30-20 introduction in french},
	url = {https://leclairage.fr/tm-30-15/},
	abstract = {SommaireIntroductionPourquoi un nouvel indice ?Comparaison entre IRC et TM 30-20Tableau récapitulatif IRC versus TM 30-20TM 30-20Détails de la méthode de calculTeintes, Saturation et représentation vectorielleExemples de représentations graphiquesConclusion Introduction Pourquoi un nouvel indice ? Depuis l’arrivée de la LED, les limitations de l’IRC ont été de plus en plus évidentes, comme par exemple l’indice moyen […]},
	language = {fr},
	urldate = {2022-03-05},
	journal = {le guide de l'éclairage},
	author = {leclairage.fr},
	month = aug,
	year = {2017},
}

SommaireIntroductionPourquoi un nouvel indice ?Comparaison entre IRC et TM 30-20Tableau récapitulatif IRC versus TM 30-20TM 30-20Détails de la méthode de calculTeintes, Saturation et représentation vectorielleExemples de représentations graphiquesConclusion Introduction Pourquoi un nouvel indice ? Depuis l’arrivée de la LED, les limitations de l’IRC ont été de plus en plus évidentes, comme par exemple l’indice moyen […]

@article{reisinger_lighting_2017,
	title = {Lighting to {Achieve} {Optimal} {Appearance}},
	url = {https://www.led-professional.com/resources-1/articles/lighting-to-achieve-optimal-appearance},
	abstract = {Visual appearance of an object or space depends on the characteristics of the lighting applied. The objective definition of light quality often doesn’t tell the whole story. Light intensity, its spectral composition and distribution in space, as well as individual preference, must be considered. Nevertheless, aiming for the absolute optimum is only recommended when private rooms are concerned. As visual appearance is key in driving consumer demand, it is important to tune the light to maximize effectiveness and visual pleasure for most consumers. Markus Reisinger, owner and CEO of the reisinger studios, discusses this complex situation with examples.},
	language = {en},
	number = {63},
	urldate = {2017-10-06},
	journal = {LED professional},
	author = {Reisinger, Markus},
	month = sep,
	year = {2017},
	keywords = {Color preference, LED, Lighting research},
	pages = {88--91},
}

Visual appearance of an object or space depends on the characteristics of the lighting applied. The objective definition of light quality often doesn’t tell the whole story. Light intensity, its spectral composition and distribution in space, as well as individual preference, must be considered. Nevertheless, aiming for the absolute optimum is only recommended when private rooms are concerned. As visual appearance is key in driving consumer demand, it is important to tune the light to maximize effectiveness and visual pleasure for most consumers. Markus Reisinger, owner and CEO of the reisinger studios, discusses this complex situation with examples.

@article{royer_role_2017,
	title = {The {Role} of {Presented} {Objects} in {Deriving} {Color} {Preference} {Criteria} from {Psychophysical} {Studies}},
	issn = {1550-2724, 1550-2716},
	url = {https://www.tandfonline.com/doi/full/10.1080/15502724.2016.1271339},
	doi = {10.1080/15502724.2016.1271339},
	language = {en},
	urldate = {2017-02-28},
	journal = {LEUKOS},
	author = {Royer, Michael P. and Wei, Minchen},
	month = jan,
	year = {2017},
	note = {00000},
	keywords = {Color preference},
	pages = {1--15},
}

@article{zhang_optimizing_2017,
	title = {Optimizing spectral compositions of multichannel {LED} light sources by {IES} color fidelity index and luminous efficacy of radiation},
	volume = {56},
	copyright = {© 2017 Optical Society of America},
	issn = {2155-3165},
	url = {https://www.osapublishing.org/abstract.cfm?uri=ao-56-7-1962},
	doi = {10.1364/AO.56.001962},
	abstract = {The trade-off between the color fidelity index (Rf) released recently by the Illuminating Engineering Society of North America (IES) and luminous efficacy of radiation (LER) was investigated by adjusting the peak wavelengths, spectral widths, and intensities of four-channel LEDs utilizing a multiobjective optimization algorithm based on differential evolution in the correlated color temperature (CCT) ranging from 2800 to 6500 K for general lighting. The results indicate that Rf at a specific LER value decreases with the increasing CCT, and vice versa, and that Rf has significant improvements over the Commission Internationale de l’Eclairage (CIE) color rendering index (CRI) in avoiding spectral gaming and evaluating the light sources even with negative CIE general CRI (Ra). Further, the optimal peak wavelengths with regard to Rf were identified as 629 nm, 568 nm, 504 nm, and 447 nm, yielding high color rendering in terms of Rf(93∼94) and Ra(95∼97) and relatively excellent LER (299 lm/W∼339 lm/W) over a wide range of CCTs from 2800 to 6500 K. This suggests that Rf can be compatible with Ra, making it possible to obtain a common set of optimal peak wavelengths for Rf and Ra. Besides, the IES method could assess saturated red and skin tones more fairly than the CIE CRI. With a practical 17-channel LED array covering the resulted four optimal peak wavelengths, the improvements of the IES method over the CIE CRI were validated further.},
	language = {en},
	number = {7},
	urldate = {2017-10-06},
	journal = {Applied Optics},
	author = {Zhang, Fuzheng and Xu, Haisong and Wang, Zhehong},
	month = mar,
	year = {2017},
	keywords = {Color quality, LED},
	pages = {1962--1971},
}

The trade-off between the color fidelity index (Rf) released recently by the Illuminating Engineering Society of North America (IES) and luminous efficacy of radiation (LER) was investigated by adjusting the peak wavelengths, spectral widths, and intensities of four-channel LEDs utilizing a multiobjective optimization algorithm based on differential evolution in the correlated color temperature (CCT) ranging from 2800 to 6500 K for general lighting. The results indicate that Rf at a specific LER value decreases with the increasing CCT, and vice versa, and that Rf has significant improvements over the Commission Internationale de l’Eclairage (CIE) color rendering index (CRI) in avoiding spectral gaming and evaluating the light sources even with negative CIE general CRI (Ra). Further, the optimal peak wavelengths with regard to Rf were identified as 629 nm, 568 nm, 504 nm, and 447 nm, yielding high color rendering in terms of Rf(93∼94) and Ra(95∼97) and relatively excellent LER (299 lm/W∼339 lm/W) over a wide range of CCTs from 2800 to 6500 K. This suggests that Rf can be compatible with Ra, making it possible to obtain a common set of optimal peak wavelengths for Rf and Ra. Besides, the IES method could assess saturated red and skin tones more fairly than the CIE CRI. With a practical 17-channel LED array covering the resulted four optimal peak wavelengths, the improvements of the IES method over the CIE CRI were validated further.

@article{murdoch_characterization_2017,
	title = {Characterization and control of a multi-primary {LED} light lab},
	volume = {25},
	issn = {1094-4087},
	url = {https://www.osapublishing.org/abstract.cfm?URI=oe-25-24-29605},
	doi = {10.1364/OE.25.029605},
	language = {en},
	number = {24},
	urldate = {2017-12-10},
	journal = {Optics Express},
	author = {Murdoch, Michael J.},
	month = nov,
	year = {2017},
	note = {00000},
	pages = {29605},
}

@article{windisch_impact_2017,
	title = {Impact of spectral features of common {LED} lighting systems on {TM}-30 color indices},
	volume = {25},
	issn = {1094-4087},
	url = {https://www.osapublishing.org/abstract.cfm?URI=oe-25-3-1824},
	doi = {10.1364/OE.25.001824},
	language = {en},
	number = {3},
	urldate = {2017-02-28},
	journal = {Optics Express},
	author = {Windisch, Reiner and Heidel, Günther and Binder, Ulrich and Bergenek, Krister},
	month = feb,
	year = {2017},
	note = {00000},
	keywords = {LED, Lighting research},
	pages = {1824},
}

@misc{raynham_introducing_2016,
	title = {Introducing {TM}-30 - the new way to measure colour rendering},
	url = {http://luxreview.com/global/all/webinar},
	language = {en},
	urldate = {2016-02-03},
	author = {Raynham, Peter},
	year = {2016},
	note = {00000},
	keywords = {Visual appearance},
}

@misc{reisinger_communicating_2016,
	title = {Communicating {IES} {TM}-30-15 evaluation results},
	url = {http://info.lightingresearch.eu/tm-30-15},
	language = {en},
	urldate = {2017-02-24},
	author = {Reisinger, Markus},
	year = {2016},
	note = {00000},
	keywords = {Communication, LED, Lighting design},
}

@misc{illuminating_engineering_society_of_north_america_ies_2016,
	title = {{IES} {TM}-30-15 {Advanced} {Calculation} {Tool} (replaced by tm-30-18)},
	url = {about:newtab},
	abstract = {1.02 from 9.6.2016},
	urldate = {2017-02-24},
	author = {{Illuminating Engineering Society of North America}},
	year = {2016},
	note = {00000},
	keywords = {SPD},
}

1.02 from 9.6.2016

@techreport{miller_oled_2016,
	title = {{OLED} {Lighting} {Products}: {Capabilities}, {Challenges}, {Potential} - ssl\_oled-products\_2016.pdf},
	url = {https://energy.gov/sites/prod/files/2016/06/f33/ssl_oled-products_2016.pdf},
	language = {en},
	urldate = {2017-06-28},
	author = {Miller, NJ and Leon, FA},
	year = {2016},
	note = {00000},
}

@misc{reichelt_ies_2016,
	title = {{IES} {TM}-30-15 {Neuer} {Standard} zur {Farbwiedergabe}-{Bestimmung}},
	url = {http://www.ledclusive.de/blog/ies-tm-30-15-farbwiedergabeindex-rf-rg/#},
	language = {de},
	urldate = {2016-04-24},
	author = {Reichelt, Tom},
	year = {2016},
	note = {00000},
	keywords = {Visual appearance},
}

@misc{indie_cinema_academy_ies_2016,
	title = {{IES} {TM}-30-15 {LED} lights for {Filmmaking}},
	url = {http://indiecinemaacademy.com/complete-led-color-database-cri-tlci-cqs-tm30-15/},
	language = {en},
	urldate = {2017-02-08},
	author = {Indie Cinema Academy},
	year = {2016},
	note = {00000},
	keywords = {Visual appearance},
}

@misc{eaton_ies_2016,
	title = {{IES} {TM}-30-15 {Spectral} tuning},
	url = {http://thelightingresource.eaton.com/features/2016/spectral-tuning-and-ies-tm-30-15},
	language = {en},
	urldate = {2017-02-08},
	author = {Eaton},
	year = {2016},
	note = {00000},
	keywords = {SPD},
}

@techreport{babelcolor_ies_2016,
	title = {{IES} {TM}-30-15 {The} effects of a 10 nm bandwidth on data derived from spectrophotometer measurements},
	url = {http://www.babelcolor.com/index_htm_files/AN-11%20The%20effects%20of%20a%2010%20nm%20bandwidth%20on%20data.pdf},
	language = {en},
	urldate = {2016-09-12},
	author = {BabelColor},
	year = {2016},
	note = {00000},
	keywords = {SPD},
}

@misc{ashdown_spectraldatareader_2015,
	title = {{SpectralDataReader} (.spdx files) {Freeware}},
	url = {http://www.helios32.com/resources.htm#Software},
	urldate = {2016-04-26},
	author = {Ashdown, Ian},
	year = {2015},
	note = {original-date: 2015-03-08},
	keywords = {SPD},
}

@article{david_development_2015,
	title = {Development of the {IES} method for evaluating the color rendition of light sources},
	volume = {23},
	issn = {1094-4087},
	url = {https://www.osapublishing.org/oe/abstract.cfm?uri=oe-23-12-15888},
	doi = {10.1364/OE.23.015888},
	language = {en},
	number = {12},
	urldate = {2016-01-31},
	journal = {Optics Express},
	author = {David, Aurelien and Fini, Paul T. and Houser, Kevin W. and Ohno, Yoshi and Royer, Michael P. and Smet, Kevin A. G. and Wei, Minchen and Whitehead, Lorne},
	month = jun,
	year = {2015},
	note = {00000},
	keywords = {Colorimetry, Visual appearance},
	pages = {15888},
}

@book{illuminating_engineering_society_of_north_america_ies_2015,
	title = {{IES} method for evaluating light source color rendition: {IES} {TM}-30-15.},
	isbn = {978-0-87995-312-6},
	shorttitle = {{IES} method for evaluating light source color rendition},
	language = {en},
	author = {{Illuminating Engineering Society of North America}},
	year = {2015},
	note = {00000 
OCLC: 929914475},
}

@misc{energy.gov_ies_2015,
	title = {{IES} {TM}-30-15 {FREQUENTLY} {ASKED} {QUESTIONS}},
	url = {http://energy.gov/eere/ssl/tm-30-frequently-asked-questions},
	language = {en},
	urldate = {2016-04-27},
	author = {energy.gov},
	year = {2015},
	note = {00000},
	keywords = {Visual appearance},
}

@techreport{energy.gov_ies_2015-1,
	title = {{IES} {TM}-30-15 {Fact}-sheet.pdf},
	url = {http://energy.gov/sites/prod/files/2016/04/f30/tm-30_fact-sheet.pdf},
	language = {en},
	urldate = {2016-04-27},
	author = {energy.gov},
	year = {2015},
	note = {00000},
	keywords = {Visual appearance},
}

@misc{illuminating_engineering_society_of_north_america_ies_2014,
	title = {{IES} {TM}-27-14 {Data} {Input} / {Output} (.spdx files)},
	url = {http://colour.readthedocs.org/en/develop/colour.io.ies_tm2714.html},
	abstract = {Defines the IES\_TM2714\_Spd class handling IES TM-27-14 spectral data XML files.

References
[1]	IES Computer Committee, \& TM-27-14 Working Group. (2014). IES Standard Format for the Electronic Transfer of Spectral Data Electronic Transfer of Spectral Data (pp. 1–16). ISBN:978-0879952952},
	urldate = {2016-04-26},
	author = {{Illuminating Engineering Society of North America}},
	year = {2014},
	note = {00000},
	keywords = {SPD},
}

Defines the IES_TM2714_Spd class handling IES TM-27-14 spectral data XML files. References [1] IES Computer Committee, & TM-27-14 Working Group. (2014). IES Standard Format for the Electronic Transfer of Spectral Data Electronic Transfer of Spectral Data (pp. 1–16). ISBN:978-0879952952

@misc{houser_advances_nodate,
	title = {Advances in {Characterizing} {Color} {Rendition} of {Light} {Sources}},
	url = {https://www.osa.org/en-us/meetings/webinar/2021/03_march/advances_in_characterizing_color_rendition_of_ligh/},
	abstract = {Light source spectrum is one component of lighting quality. Among other attributes, spectrum influences the color appearance of objects, rendering objects with more or less saturation, shifting their hue, and/or increasing or decreasing their lightness. The pattern and regularity of these varying shifts can be predicted, which is important because the color shifts can be desirable or undesirable depending on the circumstance. This webinar, hosted by the OSA Color Technical Group, will begin with a description of the theoretical and practical considerations that are important when characterizing how light sources render object colors. Our presenters, Kevin Houser and Michael Royer, will then describe TM-30-18: IES Method for Evaluating Light Source Color Rendition, including the characterization of average color fidelity and color gamut, and hue-specific changes in chroma, hue, or fidelity. Recommended specification criteria for different end-use applications will be explained and demonstrated, including a summary of the research that led to the consensus recommendations. Attendees will become knowledgeable in interpreting the numerical and graphical output from TM-30-18 and understand how the measures can be used to predict and design for human perceptions.},
	language = {en},
	urldate = {2021-03-09},
	author = {Houser, Kevin W. and Royer, Michael P.},
	note = {issued: 2021-03-09
year:2021},
}

Light source spectrum is one component of lighting quality. Among other attributes, spectrum influences the color appearance of objects, rendering objects with more or less saturation, shifting their hue, and/or increasing or decreasing their lightness. The pattern and regularity of these varying shifts can be predicted, which is important because the color shifts can be desirable or undesirable depending on the circumstance. This webinar, hosted by the OSA Color Technical Group, will begin with a description of the theoretical and practical considerations that are important when characterizing how light sources render object colors. Our presenters, Kevin Houser and Michael Royer, will then describe TM-30-18: IES Method for Evaluating Light Source Color Rendition, including the characterization of average color fidelity and color gamut, and hue-specific changes in chroma, hue, or fidelity. Recommended specification criteria for different end-use applications will be explained and demonstrated, including a summary of the research that led to the consensus recommendations. Attendees will become knowledgeable in interpreting the numerical and graphical output from TM-30-18 and understand how the measures can be used to predict and design for human perceptions.