CN111854938B - Method and system for quantifying illumination color resolution capability of white light source - Google Patents
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Abstract
The invention discloses a method and a system for quantifying the illumination color resolution capability of a white light source, which comprises the steps of collecting the spectral power distribution of the light source to be evaluated; calculating the chromaticity information of the light source to be evaluated in a uniform color space; calculating a whiteness index S of a light source to be evaluated; judging whether the whiteness index S of the light source to be evaluated is in the whiteness range applicable to the method; calculating hue dislocation index R of light source to be evaluated in uniform color spaced(ii) a For the light source to be evaluated, according to the whiteness index S and the hue dislocation index RdAnd the corresponding estimated quantity value is obtained by combining the illumination color resolution model, so that the characterization of the illumination color resolution capability of the white light source is realized, and an accurate and targeted white light color resolution evaluation method is further provided for the field.
Description
Technical Field
The invention belongs to the technical field of LED intelligent illumination, and particularly relates to a method and a system for quantifying the illumination color resolution capability of a white light source.
Background
With the development of lighting technology and the increasing diversification of light source products, the color quality of a light source has become a hot spot problem in the international lighting field at present. The connotation of the color quality of the current light source has been gradually expanded from the traditional color reducibility to multi-dimensional visual attributes, and the contents of the connotation include color preference, color resolution, color naturalness, color comfort and the like.
The illumination color resolution capability is one of the core problems of the current light source color quality research, and the application of the illumination color resolution capability relates to the fields of museum exhibition, medical health, industrial detection and the like. At present, Farnsworth-Munsell 100(FM-100) hue chess experiment is the most mainstream way for researching illumination color resolution, and meanwhile, students also discuss the illumination color resolution problem by adopting color sample comparison or object comparison and other ways.
Researchers have suggested that color discrimination is good in natural light because the human visual system is gradually optimized to the environment during evolution. In addition, studies have found that white light perception is closely related to natural light adaptation. Therefore, there is reason to suspect that the color resolving power is closely related to the whiteness of the light source.
But using only the source whiteness to predict the illumination color resolving power is theoretically insufficient because the source whiteness does not take into account the effect of the source spectral characteristics on color resolution, i.e. light sources with similar chromaticity but different spectral power distributions may show completely different resolving powers but their source whiteness values are the same.
Therefore, researchers have proposed that the spectral characteristics of the light source be taken into account in quantifying the color resolution of the illumination. It is worth mentioning that recent work by Esposito et al points out the algorithm defects common in the illumination color resolution quantification of the FM-100 research at the present stage, and constructs the model index RdTo characterize the 'hue dislocation' problem caused by the spectral power distribution of the light source and to find RdThe corrected error score of the FM-100 test shows a positive correlation. But subsequent studies found RdThere is still a certain disadvantage that when R of a group of light sourcesdWhen the scores are the same or relatively close, RdThe difference in the illumination color resolving power between the light sources cannot be predicted or distinguished well.
In addition, in recent years, many scholars at home and abroad research the illumination color resolution capability, and have proposed or tested various light source color quality metrics such as CDI and CSD in order to predict the result of the subjective visual color resolution test and quantify the color resolution capability of the white light source. However, an optimal measure of the color resolution of illumination has not been found that is widely accepted and used by academia and industry.
In view of the above problems, a technical solution is needed to be provided to effectively quantify and characterize the illumination color resolution capability of a white light source, so as to provide guidance for exhibition and illumination design.
Disclosure of Invention
The invention aims to solve the problems in the background art and provides a method and a system for quantifying the illumination color resolution capability of a white light source.
The technical scheme of the invention is to provide a method for quantizing the illumination color resolution capability of a white light source, which comprises the following steps:
step 1, measuring the spectral power distribution of a light source to be evaluated;
step 2, calculating the chromaticity information of the light source to be evaluated in the uniform color space L;
and 3, constructing a light source whiteness index S by using the chromaticity information of the light source to be evaluated in the step 2, wherein the calculation mode of S is as follows:
S＝k*et
t＝-0.5[a1(u′-a3)2+a2(v′-a4)2+2a5(u′-a3)(v′-a4)]
wherein S is a whiteness index of the light source, u 'and v' are chromaticity coordinates of the light source to be evaluated in CIE1976 UCS color space, and k and a1、a2、a3、a4、a5Are all constants;
step 4, judging whether the whiteness index S of the light source to be evaluated is in a certain whiteness range, namely judging S1≤S≤S2Whether the judgment is true or not, if not, quitting, and if true, performing the next step;
step 5, calculating the hue dislocation index R of the light source to be evaluated in the uniform color space Ld；
Step 6, the whiteness index S and the hue dislocation index R of the light source to be evaluated in the steps 3 and 5dInputting the light source to the constructed quantitative model M of the illumination color resolution to obtain an estimated value of the illumination color resolution of the light source to be evaluated, and further realizing the quantification and characterization of the illumination color resolution of the white light source; the specific form of the illumination color resolution quantification model M is as follows:
M＝w1*Rd+w2*S
wherein, M is an estimated value of illumination color discrimination, and the larger the M value is, the stronger the illumination color discrimination performance of the light source is; rdThe hue dislocation fraction of the light source to be evaluated is obtained; s is the whiteness index score of the light source to be evaluated, and w1 and w2 are weights.
Further, the specific implementation manner of step 2 is as follows,
step 2.1, calculating the tristimulus value of the light source to be evaluated, wherein the calculation formula is as follows:
wherein S (λ) d λ represents a relative power distribution of the light source within a wavelength interval λ — (λ + d λ),
corresponding to the tristimulus value of CIE1931 standard chromaticity observer, K is an adjusting factor, and is obtained by adjusting the Y value to 100, and the expression is as follows:
step 2.2, calculating chromaticity coordinates of the light source to be evaluated by using the tristimulus values obtained in the step 2.1, wherein a calculation formula is as follows:
step 2.3, calculating the chromaticity information of the light source to be evaluated in the uniform color space L, wherein the calculation formula is as follows:
further, in step 3, k is 8.1, a1＝1494.9，a2＝981.9，a3＝0.2081，a4＝0.4596，a5＝-722.2。
Further, the specific implementation manner of step 5 is as follows,
calculating hue dislocation indexes R of all light sources to be evaluated by using CIECAM02 UCS color spacedCalculating RdThe specific formula adopted is as follows:
CEtj＝|Ctj-Ctj-1|+|Ctj-Ctj+1|
wherein R isdThe total hue dislocation fraction of the light source is used for measuring the quantity of dislocation of the chessmen in the FM-100 hue chess caused by the light source; FM-100 hue chess comprises a horizontal board85 hue chess samples across the visual visible color range have consistent lightness and saturation and gradually changed hues, wherein 85 movable chess pieces are respectively arranged in 4 strip-shaped chess boards and are marked as a chessboard A, B, C, D; i is the serial number of four chessboard of FM-100 hue chess, i equals 1 to represent chessboard A, i equals 2 to represent chessboard B, i equals 3 to represent chessboard C, i equals 4 to represent chessboard D, R isd，AIn order to test the dislocation fraction of the chessboard A under the light source, the rest can be done in the same way; ctjThe position of the jth chess piece under the test light source; CEtjThe displacement fraction of the jth chess piece under the test light source is obtained; n is the number of movable pieces in each board, n is 22 in board a, and n is 21 in board B, C, D.
Further, in the step 1, the measured spectral power distribution of the light source to be evaluated adopts 400nm-700nm wave band information.
Further, in step 2, the uniform color space L adopts a CIE1976 UCS uniform color space; in step 5, the uniform color space L' is a CIECAM02 UCS uniform color space.
Further, in step 4, S1＝0.66，S2＝8.07。
Furthermore, the value of w1 is-0.07, and the value of w2 is 0.93.
The invention also provides a system for quantizing the illumination color resolution capability of the white light source, which comprises the following modules:
the device comprises a to-be-evaluated light source spectrum information acquisition module, a spectrum power acquisition module and a spectrum power acquisition module, wherein the to-be-evaluated light source spectrum information acquisition module is used for measuring the spectrum power distribution of a to-be-evaluated light source;
the device comprises a to-be-evaluated light source chromaticity information calculation module, a to-be-evaluated light source chromaticity information calculation module and a to-be-evaluated light source chromaticity information calculation module, wherein the to-be-evaluated light source chromaticity information calculation module is used for calculating chromaticity information of a to-be-evaluated light source in a uniform color space L;
the whiteness calculation module of the light source to be evaluated is used for constructing a light source whiteness index S by utilizing the chromaticity information of the light source to be evaluated, and the calculation mode of the S is as follows:
S＝k*et
t＝-0.5[a1(u′-a3)2+a2(v′-a4)2+2a5(u′-a3)(v′-a4)]
wherein S is the estimated value of the whiteness of the light sourceU 'and v' are the chromaticity coordinates of the light source to be evaluated in CIE1976 UCS color space, k, a1、a2、a3、a4、a5Are all constants;
a whiteness index range judgment module for judging whether the whiteness index S of the light source to be evaluated is in a certain whiteness range, namely judging S1≤S≤S2Whether the module is established or not, if not, exiting, and if so, entering the next module;
a hue dislocation calculation module for calculating hue dislocation index R of the light source to be evaluated in uniform color space Ld；
An illumination color discrimination quantification module for quantifying the whiteness index S and the hue dislocation index R of the light source to be evaluateddInputting the light source to the constructed quantitative model M of the illumination color resolution to obtain an estimated value of the illumination color resolution of the light source to be evaluated, and further realizing the quantification and characterization of the illumination color resolution of the white light source; the specific form of the illumination color resolution quantification model M is as follows:
M＝w1*Rd+w2*S
wherein, M is an estimated value of illumination color discrimination, and the larger the M value is, the stronger the illumination color discrimination performance of the light source is; rdThe hue dislocation fraction of the light source to be evaluated is obtained; s is the whiteness index score of the light source to be evaluated, and w1 and w2 are weights.
Furthermore, the value of w1 is-0.07, and the value of w2 is 0.93.
Compared with the prior art, the invention has the following beneficial effects:
the technical scheme for quantifying the illumination color resolution capability of the white light source provided by the invention is based on the spectral characteristics and whiteness attributes of the light source to be evaluated and takes the illumination color resolution estimation model as a means, so that the comprehensive and accurate representation of the illumination color resolution capability of the white light source is realized, and an accurate and targeted white light color resolution evaluation method is further provided for the field.
Drawings
FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is a real shot of the experimental visual environment in examples 1-3 of the present invention;
FIG. 3 is a real shot diagram of the experimental visual environment in example 4-6 of the present invention;
FIG. 4 is a comparison of the performance of the illumination color resolution model constructed in the embodiment of the present invention and the existing multiple color quality indexes in predicting the color resolution of the light source.
Detailed Description
The following provides a detailed description of embodiments of the invention, taken in conjunction with the accompanying drawings.
The technical scheme for quantifying the illumination color resolution capability of the white light source provided by the embodiment shown in fig. 1 is based on the spectral characteristics and whiteness attributes of the light source to be evaluated, and takes the illumination color resolution estimation model as a means, so that the comprehensive and accurate representation of the illumination color resolution capability of the white light source is realized, and an accurate and targeted white light color resolution evaluation method is provided for the field.
To better illustrate the effectiveness and accuracy of the present invention, six examples are provided below.
Examples 1-3 each employed 3 groups of LED light sources with different chromaticity attributes as the light source to be evaluated: in example 1, 5 LED light sources with the same correlated color temperature (5500K) and different Duv characteristics are adopted, in example 2, 6 LED light sources with the same correlated color temperature (3000K) and different Duv characteristics are adopted, and in example 3, LED light sources with different correlated color temperatures and different Duv characteristics are adopted; the accuracy of the quantification method for the white light source illumination color resolution capability provided by the method is explained by taking 85 pieces of the FM-100 chess with consistent lightness and saturation and gradually changed hue as objects to be displayed and taking the result of the FM-100 color resolution test experiment as a model test basis. It should be noted that the present invention is not limited to the above light source and object, and the method is also applicable to other LED light sources or other objects.
The 3 studies used in examples 1-3 are described in the references:
Y.Liu,Q.Liu,Z.Huang,M.R.Pointer,L.Rao,and Z.Hou.Optimising colour preference and colour discrimination for jeans under 5500K light sources with different Duv values[J],Optik,2019,163916.
Y.Liu,L.Rao,Z.Huang,H.Gong,X.Wu,and Q.Liu.Correlations between colour discrimination and colour quality metrics,Lecture Notes in Electrical Engineering[J],2020,600:11-20.
Z.Huang,Q.Liu,Y.Liu,M.R.Pointer,M.R.Luo,Q.Wang,and B.Wu.Best lighting for jeans,Part 1:Optimizing colour preference and colour discrimination with multiple correlated colour temperatures[J],Lighting Research&Technology,2019,51:1208-1223.
when the technical scheme of the invention is implemented, the technical scheme can be automatically operated by a person skilled in the art by adopting a computer software technology. Examples 1-3 provide methods having substantially the same flow scheme, comprising the steps of:
1) in examples 1-3, the spectral power distributions of 3 groups of LED light sources to be evaluated having different chromaticity attributes were measured using an X-Rite i1 Pro spectrophotometer at wavelengths ranging from 400nm to 700nm, respectively. They are respectively:
example 1: 5 LED light sources with the same color temperature (5500K) and different Duv (0.020, 0.010, 0, -0.010, -0.020) characteristics;
example 2: 6 LED light sources with the same color temperature (3000K) and different Duv (0.010, 0.005, 0, -0.005, -0.010, -0.015) characteristics;
example 3: 5 LED light sources with different correlated color temperatures (2500K-6500K, evenly sampled at intervals of 1000K) and different Duv (-0.003-0.008) characteristics.
2) Calculating the tristimulus value of the light source to be evaluated, wherein the calculation formula is as follows:
wherein S (λ) d λ represents a relative power distribution of the light source within a wavelength interval λ — (λ + d λ),
corresponding to the tristimulus value of CIE1931 standard chromaticity observer, K is an adjusting factor, and is obtained by adjusting the Y value to 100, and the expression is as follows:
in examples 1 to 3, the integration interval used for calculating the tristimulus values of the light source was a wavelength band of 400nm to 700 nm.
3) Calculating chromaticity coordinates of the light source to be evaluated by using the tristimulus values obtained in the step 2), wherein the calculation formula is as follows:
4) and (3) calculating the chromaticity information of the light source to be evaluated in the uniform color space L, wherein the calculation formula is as follows:
in examples 1 to 3, the CIE1976 UCS color space was used to calculate the chromaticity coordinates (u 'and v') of all the light sources to be evaluated as the relevant chromaticity information.
5) Inputting the chromaticity information of the light source to be evaluated in the step 4) into the whiteness index of the light source constructed by the invention to obtain the whiteness index of the light source to be evaluated, wherein the calculation mode is as follows:
S＝k*et
t＝-0.5[a1(u′-a3)2+a2(v′-a4)2+2a5(uv-a3)(v′-a4)]
k＝8.1，a1＝1494.9，a2＝981.9，a3＝0.2081，a4＝0.4596，a5＝-722.2
wherein S is the estimated whiteness value of the light source, and u 'and v' are chromaticity coordinates of the light source to be estimated in CIE1976 UCS color space.
6) Judging whether the whiteness index S of the light source to be evaluated is in the whiteness range applicable to the invention, namely judging S1≤S≤SWhether the method is established or not, if not, the method is not applicable, and if so, the next step is carried out;
in examples 1 to 3, S1＝0.66，S2＝8.07。
7) Calculating hue dislocation index R of light source to be evaluated in uniform color space Ld；
In examples 1-3, the CIECAM02 UCS color space was used to calculate the hue shift index R for all light sources to be evaluatedd. Calculation of RdThe specific method adopted is as follows:
CEtj＝|Ctj-Ctj-1|+|Ctj-Ctj+1|
wherein R isdThe total hue dislocation fraction of the light source is tested and used for measuring the quantity of dislocation of the chessmen in the FM-100 hue chess caused by the light source. The FM-100 hue chess comprises 85 hue chess samples spanning a visual visible color range, and the lightness and the saturation of the hue chess samples are consistent and the hue of the hue chess samples is gradually changed. Wherein 85 movable chess pieces are respectively arranged in 4 elongated chess boards and are marked as chess boards A, B, C, D. Rd，AFor testing the dislocation fraction of the chessboard A under the light sourceAnd so on; i is the number of four chessboard of FM-100 hue chess (i equals 1 to chessboard A, i equals 2 to chessboard B, i equals 3 to chessboard C, i equals 4 to chessboard D); ctjThe position of the jth chess piece under the test light source; CEtjThe displacement fraction of the jth chess piece under the test light source is obtained; n is the number of movable playing pieces in each board (n is 22 in board a and 21 in board B, C, D).
8) The whiteness index S and the hue dislocation index R of the light source to be evaluated obtained in the steps 5) and 7) are useddThe light source illumination color discrimination capability evaluation quantity is input into the quantitative model M of the illumination color discrimination capability constructed by the invention to obtain the illumination color discrimination estimation quantity value of the light source to be evaluated, and then the characterization of the illumination color discrimination capability of the light source is realized according to the output result. The quantitative model M of the illumination color resolving power is as follows:
M＝-0.07*Rd+0.93*S
wherein, M is an estimated value of illumination color discrimination, and the larger the M value is, the stronger the illumination color discrimination performance of the light source is; rdThe hue dislocation fraction of the light source to be evaluated is obtained; and S is the whiteness index score of the light source to be evaluated.
In order to further prove the technical advantages of the method in the aspect of illumination color resolution capability quantification, a PEARSON correlation coefficient between the error score of an observer in the FM-100 hue chess color resolution subjective experiment and the estimated illumination color resolution value M in 6) is calculated by adopting an FM-100 hue chess color resolution subjective experiment and a correlation coefficient R method. The specific implementation procedures of examples 1-3 are substantially the same, so example 1 is described as follows: in a darkroom, 5 Light sources to be evaluated are used as experimental Light sources, 24 observers with normal vision are invited to perform an FM-100 hue chess color discrimination experiment in a standard Light-Cube lamp box (50cm multiplied by 60cm, and the periphery and the bottom of the lamp box are all neutral gray), and an experimental visual environment real shot image is shown in fig. 2. For the related description of FM-100 color chess and the process description of color discrimination experiment, refer to Huang Z, Liu Q, Liu Y, et al. best Lighting for jeans, part 1: optimizing color prediction and color discrimination with multiple corrected color temperature [ J ]. Lighting Research & Technology,2019,51:1208-1223. the present invention is not repeated.
The wrong color discrimination score of the observer can be obtained by FM-100 hue chess experiment, and the results of examples 1-3 are shown in Table 1. And calculating PEARSON correlation coefficient between the light color resolution estimation quantity M and the light color resolution estimation quantity, wherein the closer the correlation coefficient between the light color resolution estimation quantity M and the light color resolution estimation quantity M is to-1, the better the model prediction effect is. The results show that the correlation coefficient R between the two is-0.85 in example 1, is-0.83 in example 2, and is-0.98 in example 3. The illumination color discrimination quantification model constructed by the method has extremely high accuracy, and further the method has strong technical advantages in the aspect of illumination color discrimination evaluation.
TABLE 1 average wrong score for observers of FM-100 hue chess experiment
Examples 4-6 each employed 3 groups of LED light sources with different chromaticity attributes as the light source to be evaluated: the first type is 7 LED light sources with the same color temperature (3000K) and different Duv characteristics, the second type is 7 LED light sources with the same color temperature (4000K) and different Duv characteristics, and the third type is 10 LED light sources with different correlated color temperatures (2700K-4300K) and different Duv characteristics; three typical bronze wares (incense burner, small incense burner and copper mirror) are used as objects to be displayed, and the accuracy of the quantification method for the illumination color resolution capability of the white light source provided by the invention is explained by taking the psychophysical experiment result as the model inspection basis. It should be noted that the present invention is not limited to the above light sources and objects, and the method is also applicable to other LED light sources or other display objects.
The 3 studies used in examples 4-6 are described in the references:
Z.Huang,Q.Liu,M.R.Pointer,W.Chen,Y.Liu,and Y.Wang.Color quality evaluation of Chinese bronzeware in typical museum lighting[J],J.Opt.Soc.Am.A,2020,37:A170-A180.
when the technical scheme of the invention is implemented, the technical scheme can be automatically operated by a person skilled in the art by adopting a computer software technology. The method flow provided by the embodiment comprises the following steps:
1) measuring the spectral power distribution of a light source to be evaluated, and adopting 400nm-700nm wave band information;
in examples 4-6, the spectral power distributions of 3 groups of LED light sources to be evaluated having different chromaticity attributes were measured using an X-Rite i1 Pro spectrophotometer, respectively, with wavelengths ranging from 400nm to 700 nm. They are respectively:
example 4: 7 LED light sources with the same color temperature (3000K) and different Duv (0.015, 0.010, 0.005, 0, -0.005, -0.010, -0.015) characteristics;
example 5: 7 LED light sources with the same color temperature (4000K) and different Duv (0.015, 0.010, 0.005, 0, -0.005, -0.010, -0.015) characteristics;
example 6: 10 LED light sources with different correlated color temperatures and different Duv characteristics are shown in Table 2.
TABLE 2 chromaticity Properties of light sources to be evaluated in example 6
| Serial number | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
| CCT | 3000K | 3000K | 3000K | 4000K | 4000K | 4000K | 2700K | 3300K | 3700K | 4300K |
| Duv | -0.015 | 0 | 0.005 | -0.015 | 0 | 0.005 | 0 | 0 | 0 | 0 |
2) Calculating the chromaticity information of the light source to be evaluated in the uniform color space L;
2.1) calculating the tristimulus value of the light source to be evaluated, wherein the calculation formula is as follows:
wherein S (λ) d λ represents a relative power distribution of the light source within a wavelength interval λ — (λ + d λ),
corresponding to the tristimulus value of CIE1931 standard chromaticity observer, K is an adjusting factor, and is obtained by adjusting the Y value to 100, and the expression is as follows:
in examples 4 to 6, the integration interval used in calculating the tristimulus values of the light source was a wavelength band of 400nm to 700 nm.
2.2) calculating chromaticity coordinates of the light source to be evaluated by utilizing the tristimulus values obtained in 2.1), wherein the calculation formula is as follows:
2.3) calculating the chromaticity information of the light source to be evaluated in the uniform color space N, wherein the calculation formula is as follows:
in examples 4 to 6, the CIE1976 UCS color space was used to calculate the chromaticity coordinates (u 'and v') of all the light sources to be evaluated as the relevant chromaticity information.
3) Inputting the chromaticity information of the light source to be evaluated in the step 2) into the whiteness index of the light source constructed by the invention to obtain the whiteness index of the light source to be evaluated, wherein the calculation mode is as follows:
S＝k*et
t＝-0.5[a1(u′-a3)2+a2(v′-a4)2+2a5(u′-a3)(v′-a4)]
k＝8.1，a1＝1494.9，a2＝981.9，a3＝0.2081，a4＝0.4596，a5＝-722.2
wherein S is the estimated whiteness value of the light source, and u 'and v' are chromaticity coordinates of the light source to be estimated in CIE1976 UCS color space.
4) Judging whether the whiteness index S of the light source to be evaluated is in the whiteness range applicable to the invention, namely judging S1≤S≤S2Whether the method is established or not, if not, the method is not applicable, and if so, the next step is carried out;
in examples 4 to 6, S1＝0.66，S2＝8.07。
5) Calculating hue dislocation index R of light source to be evaluated in uniform color space Ld；
In examples 4 to 6, the hue shift index R of all light sources to be evaluated was calculated using the CIECAM02 UCS color spaced. Calculation of RdThe specific method adopted is as follows:
CEtj＝|Ctj-Ctj-1|+|Ctj-Ctj+1|
wherein R isdThe total hue dislocation fraction of the light source is tested and used for measuring the quantity of dislocation of the chessmen in the FM-100 hue chess caused by the light source. The FM-100 hue chess comprises 85 hue chess samples spanning a visual visible color range, and the lightness and the saturation of the hue chess samples are consistent and the hue of the hue chess samples is gradually changed. Wherein 85 movable chess pieces are respectively arranged in 4 elongated chess boards and are marked as chess boards A, B, C, D. Rd，AIn order to test the dislocation fraction of the chessboard A under the light source, the rest can be done in the same way; i is the number of four chessboard of FM-100 hue chess (i equals 1 to chessboard A, i equals 2 to chessboard B, i equals 3 to chessboard C, i equals 4 to chessboard D); ctjThe position of the jth chess piece under the test light source; CEtjThe displacement fraction of the jth chess piece under the test light source is obtained; n is the number of movable playing pieces in each board (n is 22 in board a and 21 in board B, C, D).
6) The whiteness index S and the hue dislocation index R of the light source to be evaluated obtained in the steps 3) and 5)dThe light source illumination color discrimination capability evaluation quantity is input into the quantitative model M of the illumination color discrimination capability constructed by the invention to obtain the illumination color discrimination estimation quantity value of the light source to be evaluated, and then the characterization of the illumination color discrimination capability of the light source is realized according to the output result. The quantitative model M of the illumination color resolving power is as follows:
M＝-0.07*Rd+0.93*S
wherein, M is an estimated value of illumination color discrimination, and the larger the M value is, the stronger the illumination color discrimination performance of the light source is; rdThe hue dislocation fraction of the light source to be evaluated is obtained; and S is the whiteness index score of the light source to be evaluated.
In order to further prove the technical advantages of the method in the aspect of quantifying the illumination color resolution capability of the white light source, a PEARSON correlation coefficient between the subjective evaluation value of the identification degree of an observer on the bronze ware obtained by the subjective experiment and the illumination color resolution evaluation value M in 6) is calculated by adopting a subjective comparison experiment and a correlation coefficient R method. The specific implementation is as follows: and (3) taking the 3 groups of light sources to be evaluated as experimental light sources, and respectively carrying out 3 groups of subjective comparison experiments. The experimental mode of the subjective comparative experiments in examples 4-6 was the same, and the specific experimental mode was as follows:
1) and (3) carrying out experiments in a dark room, wherein the three types of bronze wares to be developed are used as experimental objects, and each type of experimental object comprises 2 bronze wares with consistent color and appearance, and 6 experimental objects are used in total. 3 different types of bronze wares are taken as a group and are placed in two adjacent standard Light boxes Light-Cube (50cm multiplied by 60cm, and the periphery and the bottom of the Light boxes are all neutral gray) according to the same placing mode. The experimental visual environment real shot image is shown in fig. 3, and the top of each lamp box is provided with a light-emitting hardware for generating a designated experimental light source. The observer sits on a chair located 90cm from the center of the two light boxes and simultaneously observes the bronze ware in the two light boxes.
2) In the experimentation, control the lamp house and can adopt different light sources to throw light on, the observer need evaluate the degree of discernment of bronze ware, notes the evaluation to each experimental scene in the experiment record table. The evaluation rule is specifically as follows:
after the observer observes the bronze wares in two light boxes simultaneously for a period of time, the observer considers that the bronze wares in which light box can exhibit more color and texture details, and hooks under the corresponding table.
3) In each of examples 4-6, 30 observers with normal vision (90 observers in total) were selected, and the same treatment was performed for each observer: dark adaptation was carried out 5 minutes before the start of the experiment, during which the experimenter introduced the experimental situation by oral means. During experiment, the observer evaluates each group of experiment scenes according to the evaluation rule in 2), the experiment scenes are randomly adjusted (the interval between every two different experiment scenes is debugged for 20 seconds), and the observer is in a closed-eye state during scene change until the observer finishes evaluating the last group of experiment scenes. In experiment 1, there were 21 groups in total
3000K experiment scene, 21 groups in experiment 2
4000K Experimental Scenario, total 45 groups in experiment 3
Experimental scenarios of different light source characteristics.
4) The subjective evaluation of the observers in each experiment is subjected to numerical normalization by adopting a Thurston V statistical method so as to calculate a PEARSON correlation coefficient between the subjective evaluation value and the illumination quality model estimation value constructed by the invention, and the normalization result is shown in Table 3, wherein the larger the numerical value is, the more the observers selecting the light source in the dimension are. For a relevant introduction to the Thurston V statistical method and methods of use, see: L.L. Thurstone, "A law of comparative details," pharmacological review 101,266(1994), the present invention is not repeated.
TABLE 3 subjective evaluation normalization of observer identification
Through the subjective experiment, the subjective evaluation value of the identification degree of the observer on the bronze ware can be obtained, and the PEARSON correlation coefficient between the subjective evaluation value and the illumination color identification evaluation value M constructed by the invention is further calculated, wherein the closer the correlation coefficient between the two is to 1, the better the model prediction effect is. The results show that the correlation coefficient R is 0.94 in example 4, 0.99 in example 5, and 0.97 in example 6. The illumination color discrimination quantification model constructed by the method has extremely high accuracy, and further the method has strong technical advantages in the aspect of illumination color discrimination evaluation.
In order to further prove the superiority and technical innovation of the model constructed by the invention in the aspect of quantifying the illumination color resolution capability, the invention also collects 6 color discrimination research data from international scholars except 6 embodiments, the research method is similar to the method, the data source is described in the reference documents, and the details are not repeated herein.
Reference documents: and S.
S.Mayr,and A.Buchner.A common type of commercially available LED light source allows for colour discrimination performance at a level comparable to halogen lighting[J],Ergonomics 62,1462-1473(2019).
P.J.Pardo,E.M.Cordero,M.I.Suero,and
L.Pérez.Influence of the correlated color temperature of a light source on the color discrimination capacity of the observer[J],JOSA A 29,A209-A215(2012).
T.Dan,H.Komatsubara,S.Kobayashi,and N.Nasuno.Evaluation Of Color Discrimination Under Led Lighting By Two Types Of 100-Hue Test[J],light-emitting diode(2013).
Esposito T and Houser K.A new measure of colour discrimination for LEDs and other light sources[J].Lighting Research&Technology,51(1),5-23(2019).
The illumination color resolution quantification model M constructed by the invention is systematically compared with 29 existing classical color quality indexes such as CCT, Duv, CRI, GAI, CQS-Qa, CQS-Qf, CQS-Qp, CQS-Qg, FSCI, CPI, FCI, CDI, CSA, CRI-CAM02UCS, CRI2012, MCRI, IES-Rf, IES-Rg, Delta C, CQI, CQI', GAI-CRI, GVI, S, WS, Percent of tint, DSI, CSD and Rd in the aspect of color resolution prediction precision. Since many references are available, one skilled in the art can easily retrieve the relevant technical details by its name, which is not given here.
Fig. 4 shows the illumination color discrimination quantification model M constructed by the present invention in the above 12 groups of color discrimination related studies and the average PEARSON correlation coefficient between the existing 29 color quality metrics and the illumination color discrimination capability obtained by subjective tests. It is obvious from the figure that the prior 29 single indexes are not as good as the illumination color resolution quantification model M constructed by the invention, and the average correlation coefficient R of M and the illumination color resolution is 0.93. The model M constructed by the invention has remarkable superiority in color discrimination quantification because the model M is constructed based on the influence of white light perception and artificial light source spectral characteristics on color discrimination. On the aspect of predicting the illumination color resolution, the two factors of white light perception and artificial light source spectral characteristics support each other and complement each other, so that the technology for building the white light perception and the artificial light source spectral characteristics into a new model obtains excellent effects, and the combined technical effect is better and superior to that of each single technical effect.
In addition, the invention also evaluates the total weight of the indexes based on the two-dimensional fitting and transformation between every two of the prior 29 indexes
101 × 4 ═ 164,024 combination indices. Tests show that for the existing color discrimination research data, the performance of the model M constructed by the invention is still better than any other fitted indexes. The illumination color discrimination quantification model constructed by the method has extremely high accuracy, and further the method has strong technical advantages in the aspect of illumination color discrimination evaluation.
The invention also provides a system for quantizing the illumination color resolution capability of the white light source, which comprises the following modules:
the device comprises a to-be-evaluated light source spectrum information acquisition module, a spectrum power acquisition module and a spectrum power acquisition module, wherein the to-be-evaluated light source spectrum information acquisition module is used for measuring the spectrum power distribution of a to-be-evaluated light source;
the device comprises a to-be-evaluated light source chromaticity information calculation module, a to-be-evaluated light source chromaticity information calculation module and a to-be-evaluated light source chromaticity information calculation module, wherein the to-be-evaluated light source chromaticity information calculation module is used for calculating chromaticity information of a to-be-evaluated light source in a uniform color space L;
the whiteness calculation module of the light source to be evaluated is used for constructing a light source whiteness index S by utilizing the chromaticity information of the light source to be evaluated, and the calculation mode of the S is as follows:
S＝k*et
t＝-0.5[a1(u′-a3)2+a2(v′-a4)2+2a5(u′-a3)(v′-a4)]
wherein S is the estimated whiteness value of the light source, u 'and v' are chromaticity coordinates of the light source to be evaluated in CIE1976 UCS color space, and k, a1、a2、a3、a4、a5Are all constants；
A whiteness index range judgment module for judging whether the whiteness index S of the light source to be evaluated is in a certain whiteness range, namely judging S1≤S≤S2Whether the module is established or not, if not, exiting, and if so, entering the next module;
a hue dislocation calculation module for calculating hue dislocation index R of the light source to be evaluated in uniform color space Ld；
An illumination color discrimination quantification module for quantifying the whiteness index S and the hue dislocation index R of the light source to be evaluateddInputting the light source to the constructed quantitative model M of the illumination color resolution to obtain an estimated value of the illumination color resolution of the light source to be evaluated, and further realizing the quantification and characterization of the illumination color resolution of the white light source; the specific form of the illumination color resolution quantification model M is as follows:
M＝w1*Rd+w2*S
wherein, M is an estimated value of illumination color discrimination, and the larger the M value is, the stronger the illumination color discrimination performance of the light source is; rdThe hue dislocation fraction of the light source to be evaluated is obtained; s is the whiteness index score of the light source to be evaluated, and w1 and w2 are weights.
The specific implementation manner of the module for calculating the chromaticity information of the light source to be evaluated is as follows,
step 2.1, calculating the tristimulus value of the light source to be evaluated, wherein the calculation formula is as follows:
wherein S (λ) d λ represents a relative power distribution of the light source within a wavelength interval λ — (λ + d λ),
corresponding to the tristimulus value of CIE1931 standard chromaticity observer, K is an adjusting factor, and is obtained by adjusting the Y value to 100, and the expression is as follows:
step 2.2, calculating chromaticity coordinates of the light source to be evaluated by using the tristimulus values obtained in the step 2.1, wherein a calculation formula is as follows:
step 2.3, calculating the chromaticity information of the light source to be evaluated in the uniform color space N, wherein the calculation formula is as follows:
in the module for calculating whiteness of light source to be evaluated, k is 8.1, a1＝1494.9，a2＝981.9，a3＝0.2081，a4＝0.4596，a5＝-722.2。
The specific implementation manner of the module for calculating hue dislocation of the light source to be evaluated is as follows,
calculating hue dislocation indexes R of all light sources to be evaluated by using CIECAM02 UCS color spacedCalculating RdThe specific formula adopted is as follows:
CEtj＝|Ctj-Ctj-1|+|Ctj-Ctj+1|
wherein R isdThe total hue dislocation fraction of the light source is used for measuring the quantity of dislocation of the chessmen in the FM-100 hue chess caused by the light source; the FM-100 hue chess comprises 85 hue chess samples crossing a visual visible color range, wherein the lightness and the saturation of the hue chess samples are consistent, the hue of the hue chess samples is gradually changed, and 85 movable chess pieces are respectively arranged in 4 strip-shaped chessboard and are marked as chessboard A, B, C, D; i is the serial number of four chessboard of FM-100 hue chess, i equals 1 to represent chessboard A, i equals 2 to represent chessboard B, i equals 3 to represent chessboard C, i equals 4 to represent chessboard D, R isd，AIn order to test the dislocation fraction of the chessboard A under the light source, the rest can be done in the same way; ctjThe position of the jth chess piece under the test light source; CEtjThe displacement fraction of the jth chess piece under the test light source is obtained; n is the number of movable pieces in each board, n is 22 in board a, and n is 21 in board B, C, D.
The specific implementation of each module corresponds to each step, and the detailed description of the invention is omitted.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (9)
1. A method for quantizing the illumination color resolution capability of a white light source is characterized by comprising the following steps:
step 1, measuring the spectral power distribution of a light source to be evaluated;
step 2, calculating the chromaticity information of the light source to be evaluated in the uniform color space L;
and 3, constructing a light source whiteness index S by using the chromaticity information of the light source to be evaluated in the step 2, wherein the calculation mode of S is as follows:
S＝k*et
t＝-0.5[a1(u′-a3)2+a2(v′-a4)2+2a5(u′-a3)(v′-a4)]
wherein S is a whiteness index of the light source, u 'and v' are chromaticity coordinates of the light source to be evaluated in CIE1976 UCS color space, and k and a1、a2、a3、a4、a5Are all constants;
step 4, judging whether the whiteness index S of the light source to be evaluated is in a certain whiteness range, namely judging S1≤S≤S2Whether the judgment is true or not, if not, quitting, and if true, performing the next step;
step 5, calculating the hue dislocation index R of the light source to be evaluated in the uniform color space Ld；
The specific implementation of step 5 is as follows,
calculating hue dislocation indexes R of all light sources to be evaluated by using CIECAM02 UCS color spacedCalculating RdThe specific formula adopted is as follows:
CEtj＝|Ctj-Ctj-1|+|Ctj-Ctj+1|
wherein R isdThe total hue dislocation fraction of the light source is used for measuring the quantity of dislocation of the chessmen in the FM-100 hue chess caused by the light source; the FM-100 hue chess comprises 85 hue chess samples crossing a visual visible color range, wherein the lightness and the saturation of the hue chess samples are consistent, the hue of the hue chess samples is gradually changed, and 85 movable chess pieces are respectively arranged in 4 strip-shaped chessboard and are marked as chessboard A, B, C, D; i is the serial number of four chessboard of FM-100 hue chess, i equals 1 to represent chessboard A, i equals 2 to represent chessboard B, i equals 3 to represent chessboard C, i equals 4 to represent chessboard D, R isd,AIn order to test the dislocation fraction of the chessboard A under the light source, the rest can be done in the same way; ctjThe position of the jth chess piece under the test light source; CEtjFor testing jth chess under light sourceDislocation fraction of children; n is the number of movable chessmen in each chessboard, n is 22 in the chessboard A, and n is 21 in the chessboard B, C, D;
step 6, the whiteness index S and the hue dislocation index R of the light source to be evaluated in the steps 3 and 5dInputting the light source to the constructed quantitative model M of the illumination color resolution to obtain an estimated value of the illumination color resolution of the light source to be evaluated, and further realizing the quantification and characterization of the illumination color resolution of the white light source; the specific form of the illumination color resolution quantification model M is as follows:
M＝w1*Rd+w2*S
wherein, M is an estimated value of illumination color discrimination, and the larger the M value is, the stronger the illumination color discrimination performance of the light source is; rdThe hue dislocation fraction of the light source to be evaluated is obtained; s is the whiteness index score of the light source to be evaluated, and w1 and w2 are weights.
2. The method for quantifying the illumination color resolving power of a white light source according to claim 1, wherein: the specific implementation of step 2 is as follows,
step 2.1, calculating the tristimulus value of the light source to be evaluated, wherein the calculation formula is as follows:
wherein S (λ) d λ represents a relative power distribution of the light source within a wavelength interval λ — (λ + d λ),
corresponding to CIE1931 standard chromaticity observer with three thornsThe laser value, K is an adjustment factor, obtained by adjusting the value of Y to 100, and is expressed as:
step 2.2, calculating chromaticity coordinates of the light source to be evaluated by using the tristimulus values obtained in the step 2.1, wherein a calculation formula is as follows:
step 2.3, calculating the chromaticity information of the light source to be evaluated in the uniform color space L, wherein the calculation formula is as follows:
3. the method for quantifying the illumination color resolving power of a white light source according to claim 1, wherein: in step 3, k is 8.1, a1＝1494.9，a2＝981.9，a3＝0.2081，a4＝0.4596，a5＝-722.2。
4. The method for quantifying the illumination color resolving power of a white light source according to claim 1, wherein: in the step 1, the measured spectral power distribution of the light source to be evaluated adopts the information of the 400nm-700nm wave band.
5. The method for quantifying the illumination color resolving power of a white light source according to claim 1, wherein: in the step 2, the uniform color space L adopts CIE1976 UCS uniform color space; in step 5, the uniform color space L' is a CIECAM02 UCS uniform color space.
6. The method for quantifying the illumination color resolving power of a white light source according to claim 1, wherein: in step 4, S1＝0.66，S2＝8.07。
7. The method for quantifying the illumination color resolving power of a white light source according to claim 1, wherein: the value of w1 is-0.07, and the value of w2 is 0.93.
8. A system for quantifying the illumination color resolution capability of a white light source is characterized by comprising the following modules:
the device comprises a to-be-evaluated light source spectrum information acquisition module, a spectrum power acquisition module and a spectrum power acquisition module, wherein the to-be-evaluated light source spectrum information acquisition module is used for measuring the spectrum power distribution of a to-be-evaluated light source;
the device comprises a to-be-evaluated light source chromaticity information calculation module, a to-be-evaluated light source chromaticity information calculation module and a to-be-evaluated light source chromaticity information calculation module, wherein the to-be-evaluated light source chromaticity information calculation module is used for calculating chromaticity information of a to-be-evaluated light source in a uniform color space L;
the whiteness calculation module of the light source to be evaluated is used for constructing a light source whiteness index S by utilizing the chromaticity information of the light source to be evaluated, and the calculation mode of the S is as follows:
S＝k*et
t＝-0.5[a1(u′-a3)2+a2(v′-a4)2+2a5(u′-a3)(v′-a4)]
wherein S is the estimated whiteness value of the light source, u 'and v' are chromaticity coordinates of the light source to be evaluated in CIE1976 UCS color space, and k, a1、a2、a3、a4、a5Are all constants;
a whiteness index range judgment module for judging whether the whiteness index S of the light source to be evaluated is in a certain whiteness range, namely judging S1≤S≤S2Whether the module is established or not, if not, exiting, and if so, entering the next module;
a hue error calculation module for calculating hue error of the light source to be evaluated in the uniform color space LBit index Rd；
Hue shift index RdThe specific calculation method is as follows:
calculating hue dislocation indexes R of all light sources to be evaluated by using CIECAM02 UCS color spacedCalculating RdThe specific formula adopted is as follows:
CEtj＝|Ctj-Ctj-1|+|Ctj-Ctj+1|
wherein R isdThe total hue dislocation fraction of the light source is used for measuring the quantity of dislocation of the chessmen in the FM-100 hue chess caused by the light source; the FM-100 hue chess comprises 85 hue chess samples crossing a visual visible color range, wherein the lightness and the saturation of the hue chess samples are consistent, the hue of the hue chess samples is gradually changed, and 85 movable chess pieces are respectively arranged in 4 strip-shaped chessboard and are marked as chessboard A, B, C, D; i is the serial number of four chessboard of FM-100 hue chess, i equals 1 to represent chessboard A, i equals 2 to represent chessboard B, i equals 3 to represent chessboard C, i equals 4 to represent chessboard D, R isd,AIn order to test the dislocation fraction of the chessboard A under the light source, the rest can be done in the same way; ctjThe position of the jth chess piece under the test light source; CEtjThe displacement fraction of the jth chess piece under the test light source is obtained; n is the number of movable chessmen in each chessboard, n is 22 in the chessboard A, and n is 21 in the chessboard B, C, D;
an illumination color discrimination quantification module for quantifying the whiteness index S and the hue dislocation index R of the light source to be evaluateddInputting the light source to the constructed quantitative model M of the illumination color resolution to obtain an estimated value of the illumination color resolution of the light source to be evaluated, and further realizing the quantification and characterization of the illumination color resolution of the white light source; the specific form of the illumination color resolution quantification model M is as follows:
M＝w1*Rd+w2*S
wherein, M is an estimated value of illumination color discrimination, and the larger the M value is, the stronger the illumination color discrimination performance of the light source is; rdHue error of light source to be evaluatedA bit fraction; s is the whiteness index score of the light source to be evaluated, and w1 and w2 are weights.
9. The system of claim 8, wherein the white light source comprises: the value of w1 is-0.07, and the value of w2 is 0.93.
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