A method and system for quantifying the light source color resolution ability based on illuminance correction

Abstract

The present invention discloses a method and system for quantifying the color resolution ability of a light source based on illuminance correction, including measuring the illuminance E of the light source to be evaluated; determining whether the illuminance E of the light source to be evaluated is within the illuminance range applicable to the present invention; collecting the spectral power distribution of the light source to be evaluated; calculating the color resolution index CDM of the light source to be evaluated; determining whether the color resolution index CDM of the light source to be evaluated is within the color resolution range applicable to the present invention; for the light source to be evaluated, based on its illuminance E and color resolution index CDM, combining with the illuminance-corrected light source color resolution ability quantification model to obtain the corresponding estimated value, so as to realize the quantification and characterization of the light color resolution ability of white light sources under different illuminance levels.

Description

Technical Field

[0001] The present invention belongs to the technical field of LED intelligent lighting, and particularly relates to a method and system for quantifying the color resolution ability of a light source based on illuminance correction. Background Art

[0002] The color resolution ability of a light source aims to characterize the ability of the human eye to distinguish the differences in hue, brightness, and saturation of the colors of objects under different light sources, and it can be defined by a metric, which is the degree to which an illuminating light source allows a subject to distinguish a large number of different object colors observed simultaneously. Light sources with excellent color resolution ability have been widely used in many fields such as surgical operations, industrial inspections, and museum exhibitions. The quantification of the color resolution ability of light sources has become a hot issue in the field of lighting color quality evaluation and is closely related to the strategic research hot topic of the International Commission on Illumination (CIE strategy toppriority topic #2: “Colour Quality of Light Sources Related to Perception andPreference”).

[0003] In recent years, with the emergence of various LED light sources, many researchers in this field have aimed to investigate what light source conditions can enable an observer group to better distinguish the color details and texture details of objects, and to reveal the influencing factors of the color resolution ability of light sources. Therefore, domestic and foreign scholars have proposed or tested various color resolution ability quantification indexes of light sources, such as the color rendering index CRI, the gamut area index GAI, the color resolution index CDI, the cone sensitivity difference index CSD, etc.

[0004] It should be noted that the inventor conducted a meta-analysis of 5 visual studies related to color resolution in the previous work, and based on the visual adaptation of humans to the chromaticity of natural light and the consideration of the diversity of the spectral power distribution of modern light sources, a combined color resolution ability metric index CDM of light sources was constructed. The excellent effect of the newly established CDM index in predicting the color resolution ability of light sources was verified in 16 groups of psychophysical data from 8 color resolution studies, and its effect exceeded that of 29 existing typical light source color quality metric indexes and their linear combinations. However, it must be pointed out that in the process of establishing CDM, the influence of the illuminance level on the color resolution ability of light sources was not considered, and such a limitation is a problem faced by all existing indexes.

[0005] Reference 1: Q. Liu, Y. Liu, M. R. Pointer, Z. Huang, X. Wu, Z. Chen, M. R. Luo, “Color discrimination metric based on the neutrality of lighting and hue transposition quantification,” Optics Letters 45, 6062 - 6065 (2020).

[0006] According to existing research, the color discrimination ability of light sources is closely related to the illuminance level. For example, Knoblauch et al. found that lower illuminance leads to impaired color discrimination ability. They studied the performance of their subjects in the FM - 100 Hue Test at different illuminance levels (5.7 lx, 18 lx, 57 lx, 180 lx, and 1800 lx). The results showed that the average error score of the test gradually decreased as the illuminance level increased. Similarly, Rea and Freyssinier - Nova also tested the color discrimination ability of light sources at different illuminances. They asked their subjects to perform the FM - 100 Hue Test at illuminances of 54 lx or 540 lx and found that higher illuminance levels improved color discrimination ability. In addition, Mayr et al. and et al. both conducted color discrimination tests on participants under two different types of light sources and two different illuminance levels (70 lx and 1000 lx), and they both reached the conclusion that "regardless of the type of light source, higher illuminance levels correspond to better color discrimination of light sources." All of the above studies have confirmed the conclusion that illuminance level has a positive effect on the color discrimination ability of light sources.

[0007] Reference 2: K. Knoblauch, Saunders, F., Kusuda, M., Hynes, R., Podgor, M., Higgins, K. E., "Age and illuminance effects in the Farnsworth - Munsell 100 - hue test," Applied Optics 26, 1441–1448 (1987).

[0008] Reference 3: M. S. Rea, and J. P. Freyssinier - Nova, "Colour rendering: A tale of two metrics," Colour Research and Application 33, 192 - 202 (2008).

[0009] Reference 4: S. Mayr, M. Kopper, and A. Buchner, "Comparing colour discrimination and proofreading performance under compact fluorescent and halogen lamp lighting," Ergonomics 56, 1418-1429 (2013).

[0010] Reference 5: S. Königs, 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," Ergonomics 62, 1462-1473 (2019).

[0011] For the above problems, it is urgent to propose a technical solution to construct an illuminance correction model that considers the influence of illuminance on the color discrimination ability of light sources, effectively quantify the color discrimination ability of light sources at different illuminance levels, and thus provide a guiding basis for the design of different lighting scenarios. Summary of the Invention

[0012] The purpose of the present invention is to solve the problems described in the background technology and propose a method and system for quantifying the color discrimination ability of light sources based on illuminance correction.

[0013] The technical solution of the present invention provides a method for quantifying the color discrimination ability of light sources based on illuminance correction, including the following steps:

[0014] Step 1, measure the illuminance E of the light source to be evaluated;

[0015] Step 2, determine whether the illuminance E of the light source to be evaluated is within the illuminance range applicable to the present invention, that is, determine whether a ≤ E ≤ b holds. If it does not hold, the present invention is not applicable. If it holds, proceed to the next step;

[0016] Step 3, measure the spectral power distribution of the light source to be evaluated;

[0017] Step 4, calculate the color discrimination index CDM of the light source to be evaluated;

[0018] Step 5: Determine whether the color discrimination metric CDM of the light source to be evaluated is within the color discrimination range applicable to the present invention, i.e., determine whether c ≤ CDM ≤ d holds. If it does not hold, the present invention is not applicable; if it holds, proceed to the next step;

[0019] Step 6: Input the illuminance E and the color discrimination metric CDM of the light source to be evaluated in Steps 1 and 4 into the quantization model M of the color discrimination ability of the illuminance-corrected light source constructed in the present invention to obtain the estimated value of the color discrimination ability of the illuminance-corrected light source to be evaluated, thereby realizing the quantization and characterization of the color discrimination ability of the white light source under different illuminance levels.

[0020] M is the estimation model of the color discrimination ability of the light source, and its specific form is as follows:

[0021] M = w 1 *0.01*E + w 2 *CDM

[0022] where M is the estimated value of the color discrimination ability of the illuminance-corrected light source. The larger the value of M, the stronger the color discrimination ability of the light source; E is the illuminance level of the light source to be evaluated, with the unit of lx; CDM is the color discrimination metric of the light source to be evaluated, and w 1 and w 2 are weights.

[0023] Furthermore, the specific implementation method of Step 4 is as follows:

[0024] Step 4.1: Calculate the whiteness index S of the light source to be evaluated in the CIE1976 UCS uniform color space neutral , and the calculation formula is as follows:

[0025] S neutral = x * e y

[0026] y = -0.5[n 1 (u′ - n 3 ) 2 + n 2 (v′ - n 4 ) 2 + 2n 5 (u′ - n 3 )(v′ - n 4 )]

[0027] x = 8.1, n 1 = 1494.9, n 2 = 981.9, n 3 = 0.2081, n 4 = 0.4596, n 5 = -722.2

[0028] Among them, S neutral is the whiteness index of the light source, and u′ and v′ are the chromaticity coordinates of the light source to be evaluated in the CIE1976 UCS uniform color space;

[0029] Step 4.2, calculate the hue misalignment index R of all light sources to be evaluated in the CAM02UCS uniform color space d , and the specific formula used to calculate R d is as follows:

[0030]

[0031] CEt j = |Ct j - Ct j-1 | + |Ct j - Ct j+1 |

[0032] Among them, R d is the total hue misalignment score of the light source, which is used to measure the number of misaligned pieces in the FM-100 hue chess caused by the light source; the 85 samples of the FM-100 hue chess are packed in 4 long strip chessboards A, B, C, and D; i is the serial number of the four chessboards of the FM-100 hue chess, i = 1 represents chessboard A, i = 2 represents chessboard B, i = 3 represents chessboard C, i = 4 represents chessboard D, and R d，A is the misalignment score of chessboard A under the test light source, and so on; Ct j is the position of the jth piece under the test light source; CEt j is the misalignment score of the jth piece under the test light source; n is the number of movable pieces in each chessboard, n = 22 in chessboard A, and n = 21 in chessboards B, C, and D;

[0033] Step 4.3, calculate the color discrimination index CDM of the light source to be evaluated through the whiteness index S neutral and the hue misalignment index Rd of the light source, and the calculation formula is as follows:

[0034] CDM = -p * R d + q * S neutral

[0035] p = 0.07, q = 0.93

[0036] Among them, CDM is the light source color discrimination index, S neutral is the light source whiteness index calculated in Step 4.1, and R d is the light source hue misalignment index calculated in Step 4.2.

[0037] Furthermore, in Step 2, a = 48, b = 1007.

[0038] Further, in step 3, the information in the 400nm - 700nm band is adopted for the measured spectral power distribution of the light source to be evaluated.

[0039] Further, in step 5, c = 0.83 and d = 7.08.

[0040] Further, in step 6, w 1 = 0.23, w 2 = 0.77.

[0041] The present invention also provides a quantization system for the color resolution ability of a light source based on illuminance correction, including the following modules:

[0042] An illuminance information acquisition module for the light source to be evaluated, which measures the illuminance E of the light source to be evaluated;

[0043] An illuminance range judgment module, which is used to judge whether the illuminance E of the light source to be evaluated is within the set illuminance range, that is, to judge whether a ≤ E ≤ b holds. If it does not hold, the process exits; if it holds, the next module is executed;

[0044] A spectral information acquisition module for the light source to be evaluated, which is used to measure the spectral power distribution of the light source to be evaluated;

[0045] A color resolution information calculation module for the light source to be evaluated, which is used to calculate the color resolution index of the light source to be evaluated;

[0046] A color resolution range judgment module, which is used to judge whether the color resolution index CDM of the light source to be evaluated is within the set color resolution range, that is, to judge whether c ≤ CDM ≤ d holds. If it does not hold, the process exits; if it holds, the next module is executed;

[0047] A quantization module for the color resolution ability of a light source based on illuminance correction, which inputs the illuminance E and the color resolution index CDM of the light source to be evaluated into the constructed quantization model M of the color resolution ability of the illuminance - corrected light source, to obtain the estimated value of the color resolution ability of the illuminance - corrected light source of the light source to be evaluated, and further realizes the quantization and characterization of the color resolution ability of the white light source under different lighting levels; the specific form of the quantization model M of the color resolution ability of the illuminance - corrected light source is as follows:

[0048] M = w 1 *0.01*E + w 2 *CDM

[0049] Wherein, M is the estimated value of the color resolution ability of the illuminance - corrected light source. The larger the M value, the stronger the color resolution ability of the light source illumination; E is the illuminance level of the light source to be evaluated, with the unit of lx; CDM is the color resolution index of the light source to be evaluated, and w 1 and w 2 are weights.

[0050] Moreover, the specific implementation method of the light source color discrimination information calculation module to be evaluated is as follows:

[0051] Calculate the whiteness index S of the light source to be evaluated in the CIE1976 UCS uniform color space neutral , and the calculation formula is as follows:

[0052] S neutral =x*e y

[0053] y = -0.5[n 1 (u′-n 3 ) 2 +n 2 (v′-n 4 ) 2 +2n 5 (u′-n 3 )(v′-n 4 )]

[0054] x = 8.1, n 1 = 1494.9, n 2 = 981.9, n 3 = 0.2081, n 4 = 0.4596, n 5 = -722.2

[0055] Among them, S neutral is the light source whiteness index, and u′ and v′ are the chromaticity coordinates of the light source to be evaluated in the CIE1976 UCS uniform color space;

[0056] Calculate the hue misalignment index R of all light sources to be evaluated in the CAM02 UCS uniform color space d , and the specific formula used to calculate R d is as follows:

[0057]

[0058] CEt j =|Ct j -Ct j-1 |+|Ct j -Ct j+1 |

[0059] Among them, R dis the total hue misalignment score of the light source, which is used to measure the number of chess piece misalignments in the FM-100 hue chess caused by the light source; 85 samples of FM-100 hue chess are divided into four long chessboards A, B, C, and D; i is the sequence number of the four chessboards of FM-100 hue chess, i=1 represents chessboard A, i=2 represents chessboard B, i=3 represents chessboard C, i=4 represents chessboard D, R d，A is the misalignment score of chessboard A under the test light source, and so on; Ct j is the position of the jth chess piece under the test light source; CEt j is the misalignment score of the jth chess piece under the test light source; n is the number of movable chess pieces in each chessboard, n=22 in chessboard A, and n=21 in chessboards B, C, and D;

[0060] Through the whiteness index S of the light source to be evaluated neutral And the hue misalignment index Rd, calculate the color resolution index CDM of the light source to be evaluated, the calculation formula is as follows:

[0061] CDM=-p*R d +q*S neutral

[0062] p=0.07, q=0.93

[0063] Among them, CDM is the light source color resolution index, D neutral is the whiteness index of the light source, R d It is an indicator of the hue misalignment of the light source.

[0064] Moreover, in the illumination range judgment module, a=48, b=1007.

[0065] Moreover, in the spectrum information acquisition module of the light source to be evaluated, the measured spectrum power distribution of the light source to be evaluated adopts the 400nm-700nm band information.

[0066] Moreover, in the color resolution range judgment module, c=0.83, d=7.08.

[0067] Moreover, in the light source color resolution quantification module based on illumination correction, w 1 =0.23, w 2 =0.77.

[0068] Compared with the prior art, the present invention has the following beneficial effects:

[0069] A technical solution for quantifying the color discrimination ability of a light source based on illuminance correction proposed by the present invention relies on the illuminance and color discrimination attributes of the light source to be evaluated, and uses an estimation model for the color discrimination ability of the illuminance-corrected light source as a means to achieve a comprehensive and accurate characterization of the color discrimination ability of white light sources under different illuminance levels, thereby providing an accurate and targeted method for evaluating the color discrimination ability of light sources in this field. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 It is a flowchart of an embodiment of the present invention;

[0071] Figure 2 It is a real-shot picture of the experimental visual environment of an embodiment of the present invention;

[0072] Figure 3 It is a schematic diagram of the distribution of the test result TESadj of the light source FM-100 in the test data set composed of 38 light sources in an embodiment of the present invention and the model M constructed by the present invention and its Pearson correlation coefficient;

[0073] Figure 4 It is a schematic diagram of the Pearson correlation coefficient between the test result TESadj of FM-100 in the 128 groups of test data sets generated in an embodiment of the present invention and the quantification model M of the color discrimination ability of the illuminance-corrected light source constructed by the present invention.

[0074] Figure 5 It is a comparison chart of the Pearson correlation coefficients between the test result TESadj of FM-100 in the 128 groups of test data sets generated in an embodiment of the present invention and the model related to the color discrimination of light source illumination constructed by the inventors in the early stage of the present invention and the model constructed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0075] Combined with the accompanying drawings, the embodiments of the present invention are specifically described as follows.

[0076] As Figure 1 shown, an embodiment provides a technical solution for quantifying the color discrimination ability of a light source based on illuminance correction. Relying on the illuminance and color discrimination attributes of the light source to be evaluated, and using an estimation model for the color discrimination ability of the illuminance-corrected light source as a means, it realizes a comprehensive and accurate characterization of the color discrimination ability of white light sources under different illuminance levels, thereby providing an accurate and targeted method for evaluating the color discrimination ability of light sources in this field.

[0077] In the embodiment, 38 LED light sources with different combinations of illuminance and correlated color temperature from 4 light source color discrimination studies are used as the light sources to be evaluated. Study 1 includes 5 light sources with a correlated color temperature of 5500K and Duv values of 0.020, 0.010, 0, -0.010, and -0.020 respectively. Study 2 includes 6 light sources with a correlated color temperature of 3000K and Duv values of 0.010, 0.005, 0, -0.005, -0.010, and -0.015 respectively. Study 3 includes 18 light sources, namely, light sources with illuminances of 50, 100, 200, 500, 800, and 1000 lx at a correlated color temperature of 3000K, light sources with illuminances of 50, 100, 200, 500, 800, and 1000 lx at a correlated color temperature of 4500K, and light sources with illuminances of 50, 100, 200, 500, 800, and 1000 lx at a correlated color temperature of 6000K. Study 4 includes 9 light sources, namely, light sources with illuminances of 50, 200, and 600 lx at a correlated color temperature of 3500K, light sources with illuminances of 50, 200, and 600 lx at a correlated color temperature of 5000K, and light sources with illuminances of 50, 200, and 600 lx at a correlated color temperature of 6500K. 85 chess pieces with consistent lightness and saturation and gradually changing hues on the FM-100 hue chess are used as the objects to be displayed. Based on the experimental results of the FM-100 color discrimination ability test as the model verification basis, the accuracy of a method for quantifying the color discrimination ability of light sources based on illuminance correction proposed in this paper is illustrated. It should be noted that the present invention is not limited to the above light sources and objects, and this method is also applicable to other LED light sources or other display objects.

[0078] When the technical solution of the present invention is specifically implemented, those skilled in the art can use computer software technology to achieve automatic operation. The method flow provided by the embodiment includes the following steps:

[0079] 1) Measure the illuminance E of the light source to be evaluated;

[0080] In the embodiment, a SPIC-300 spectral color illuminance meter is used to measure the illuminance of 38 LED light sources to be evaluated with different combinations of illuminance and correlated color temperature.

[0081] 2) Determine whether the illuminance E of the light source to be evaluated is within the illuminance range applicable to the present invention, that is, determine whether a ≤ E ≤ b holds. If it does not hold, the present invention is not applicable. If it holds, proceed to the next step;

[0082] In the embodiment, a = 48 lx and b = 1007 lx.

[0083] 3) Measure the spectral power distribution of the light source to be evaluated, using the information in the 400nm - 700nm band;

[0084] In the embodiment, an X-Rite il Pro 2 spectrophotometer is used to measure the spectral power distribution of 38 LED light sources to be evaluated with different combinations of illuminance and correlated color temperature, and the wavelength range is 400 nm - 700 nm.

[0085] 4) Calculate the color discrimination index CDM of the light source to be evaluated;

[0086] In the embodiment, the whiteness index S of the light source to be evaluated is calculated in the CIE1976 UCS color space neutral and the hue shift index Rd of the light source to be evaluated is calculated in the CAM02UCS color space, so as to calculate the color discrimination index CDM of all light sources to be evaluated.

[0087] Step 4.1, calculate the whiteness index S of the light source to be evaluated in the CIE1976 UCS uniform color space neutral , and the calculation formula is as follows:

[0088] S neutral =x*e y

[0089] y=-0.5[n 1 (u′-n 3 ) 2 +n 2 (v′-n 4 ) 2 +2n 5 (u′-n 3 (v′-n 4 )]

[0090] x = 8.1, n 1 = 1494.9, n 2 = 981.9, n 3 = 0.2081, n 4 = 0.4596, n 5 =-722.2

[0091] where S neutral is the whiteness index of the light source, and u′ and v′ are the chromaticity coordinates of the light source to be evaluated in the CIE1976 UCS uniform color space;

[0092] Step 4.2, calculate the hue shift index R of all light sources to be evaluated in the CAM02 UCS uniform color space d , and the specific formula used to calculate R d is as follows:

[0093]

[0094] CEt j=|Ct j -Ct j-1 |+|Ct j -Ct j+1 |

[0095] Among them, R d is the total hue misalignment score of the light source, which is used to measure the number of chess piece misalignments in the FM-100 hue chess caused by the light source; 85 samples of FM-100 hue chess are divided into four long chessboards A, B, C, and D; i is the sequence number of the four chessboards of FM-100 hue chess, i=1 represents chessboard A, i=2 represents chessboard B, i=3 represents chessboard C, i=4 represents chessboard D, R d，A is the misalignment score of chessboard A under the test light source, and so on; Ct j is the position of the jth chess piece under the test light source; CEt j is the misalignment score of the jth chess piece under the test light source; n is the number of movable chess pieces in each chessboard, n=22 in chessboard A, and n=21 in chessboards B, C, and D;

[0096] Step 4.3, through the whiteness index S of the light source to be evaluated neutral And the hue misalignment index Rd, calculate the color resolution index CDM of the light source to be evaluated, the calculation formula is as follows:

[0097] CDM=-p*R d +q*S neutral

[0098] p=0.07, q=0.93

[0099] Among them, CDM is the light source color resolution index, S neutral is the light source whiteness index calculated in step 4.1, R d is the light source hue misalignment index calculated in step 4.2.

[0100] 5) Determine whether the color resolution index CDM of the light source to be evaluated is within the color resolution range applicable to the present invention, that is, determine whether c≤CDM≤d is established. If not, the present invention is not applicable. If yes, proceed to the next step;

[0101] In the embodiment, c=0.83, d=7.08.

[0102] 6) The illuminance E and color resolution index CDM of the light source to be evaluated in 1) and 4) are input into the quantification model M of the color resolution ability of the illuminance-corrected light source constructed by the present invention to obtain the estimated value of the illuminance-corrected color resolution ability of the light source to be evaluated, thereby realizing the quantification and characterization of the light source's illumination color resolution ability under different illuminance levels.

[0103] Let M be the estimation model for the ability to distinguish light colors, and its specific form is as follows:

[0104] M = w 1 *0.01*E + w 2 *CDM

[0105] Among them, M is the estimated value of the ability to distinguish the light color of the illuminance-corrected light source. The larger the M value, the stronger the ability of the light source to distinguish light colors; E is the illuminance level of the light source to be evaluated; CDM is the color discrimination score of the light source to be evaluated, and w 1 and w 2 are weights.

[0106] To further confirm the technical advantages of the method described in the present invention in quantifying the ability to distinguish light colors of light sources at different illuminance levels, the FM-100 hue test experiment is adopted, and by means of the correlation coefficient R, the PEARSON correlation coefficient between the average error score of the observers in the FM-100 color discrimination ability test experiment and the estimated value M of the ability to distinguish the light color of the illuminance-corrected light source in 6) is calculated. The specific implementation process is as follows:

[0107] (1) The specific implementation processes of the four color discrimination experimental studies are basically the same. Therefore, taking Study 1 as an example, it is introduced as follows: In a darkroom, 5 light sources to be evaluated are used as experimental light sources, and 24 observers with normal vision and normal color vision are invited to conduct the FM-100 hue test experiment in a standard light box LED Cube (50cm × 50cm × 60cm, with neutral gray on the four sides and the bottom of the light box). The actual picture of the experimental visual environment is as Figure 2 shown. For the relevant introduction and experimental process of the FM-100 hue test experiment, reference can be made to 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," Optik 208 (2020). The present invention will not elaborate.

[0108] (2) The average error score of the observers' color discrimination ability can be obtained through the FM-100 hue test experiment. Table 1 summarizes the number of observers, the number of light sources, the light source numbers, the light source indicators (correlated color temperature CCT, illuminance E, color discrimination index CDM, and the model M for quantifying the ability to distinguish the light color of the illuminance-corrected light source proposed in the present invention) in the four studies of the embodiments, as well as the FM-100 hue test results under the light source conditions, that is, the average adjusted error score TESadj of the observers.

[0109] Table 1. Basic information of each study in the examples

[0110]

[0111]

[0112] (3) A total of 128 groups of test data sets were generated by combining the FM-100 tests conducted under 38 light sources in the above 4 studies. Test data sets #1 to #13 are the mutual combinations of the four studies; the generation method of data sets #14 to #113 is to randomly select 10 light sources from 38 light sources, and a total of 100 samplings are carried out; data sets #114 to #122 are 9 groups of light source combinations selected from Study 3 and Study 4, and the light sources in each combination have the same illuminance level but different color temperatures; data sets #123 to #128 are 6 groups of light source combinations selected from Study 3 and Study 4, and the light sources in each combination have the same color temperature but different illuminance levels. The light source numbers corresponding to the above 128 groups of test data sets are shown in Table 2. Only the first 10 groups of random samplings in data sets #14 to #113 are shown, and the sampling methods of the remaining 90 groups are similar, so they are not shown in detail here.

[0113] Table 2. Light source composition of 128 groups of test data sets and Pearson correlation coefficient between TESadj and model M in each group of tests

[0114]

[0115]

[0116]

[0117] (4) Calculate the Pearson correlation coefficient between the FM-100 test result TESadj of each group in the above 128 groups of data sets and the estimated value M of the light color resolution ability corrected by the illuminance of the light source in this group. The closer the correlation coefficient between the two is to -1, the better the model prediction effect. The results show that the Pearson correlation coefficient R between the FM-100 test result TESadj of 38 light sources in the combination of four studies in the examples and model M is -0.89. The distribution of the FM-100 test result TESadj of 38 light sources and model M is as Figure 3 shown. Moreover, Figure 4The Pearson correlation coefficient between the average corrected error score TESadj of each group of light sources in 128 light source combinations in the embodiment and the estimated value M of the illuminance-corrected light source color discrimination ability is shown. The average correlation coefficient is -0.92, ranging from -0.80 to -1.00. The average Pearson correlation coefficient of the test data sets #14 to #113 is -0.90. The average Pearson correlation coefficient of 9 test data sets with the same illuminance but different color temperatures (#114 to #122) is -0.99. The average correlation coefficient of 6 test data sets with the same color temperature but different illuminances (#123 to #128) is -0.87. This proves that the illuminance-corrected light source color discrimination ability quantification model constructed by the present invention has extremely high accuracy, and further proves that the method of the present invention has strong technical advantages in the evaluation of light source color discrimination ability.

[0118] (5) Calculate the verification effect of the light source illumination color discrimination related models (Model 1, Model 2, and Model 3) previously constructed by the inventors in the field on the 128 groups of test data sets in the embodiments of the present invention. The results are shown as Figure 5 shown. It should be noted that the expected performance of Model 2 and Model 3 should be that "the greater the observer corrected error score, that is, the worse the light source color discrimination ability, the higher the model score", that is, the model is positively correlated with the observer corrected error score. For the convenience of comparison, the prediction results of Model 2 and Model 3 for the 128 groups of test data sets are taken as their opposites here, which are unified with Model 1 and the present invention.

[0119] Table 3 statistics the prediction effects of the three previously constructed models and the present invention on the FM-100 experiment in the 128 groups of test data sets in the embodiment, that is, the distribution of the Pearson correlation coefficient between the observer corrected error score TESadj and the illuminance-corrected light source color discrimination ability quantification model constructed in the invention. The results show that the average Pearson correlation coefficient of the present invention is closest to -1 and the effect is the most stable. Especially in terms of the maximum error level, the method of the present invention has obvious advantages. This is because there are certain defects in the construction of the previous three models. Model 1 does not consider the influence of the illuminance level on the light source color discrimination ability; Model 2 does not consider the metamerism problem of the light source, and it cannot compare the difference in color discrimination ability between light sources with the same color temperature but different spectral power distributions; Model 3 has limited scalability due to the limited number of samples used in its construction.

[0120] Table 3. Prediction effects of four models on the test results of 128 groups of FM-100

[0121] Pearson r Model 1 Model 2 Model 3 The present invention Average value -0.47 -0.85 -0.87 -0.92 Minimum value -1.00 -1.00 -1.00 -1.00 Maximum value 0.27 -0.09 -0.53 -0.80

[0122] Patent for Invention 1: Yan Aili, Liu Qiang, Liu Ying, Huang Zheng, Hu Bo, Hao Yongli, A method and system for quantifying the light color discrimination ability of a white light source, 2020107162089

[0123] Patent Invention 2: Chen Zhiyu, Liu Ying, Li Zhenzhen, Hu Bo, Hao Yongli, Zou Pengzhi, Liu Qiang, Zhang Zhe, Liu Peng, Zhou Yawen, Yan Aili, Sun Chenglong; A method and system for quantifying the light color discrimination ability based on light source illuminance and chromaticity information, 2021103642908

[0124] Patent Invention 3: Rao Lianjiang, Liu Ying, Yang Zhibing, Li Zhenzhen, Liu Qiang, Lu Bingqing, A method and system for quantifying the light color discrimination ability of white light sources based on illuminance optimization, 202110663931X

[0125] The present invention also provides a system for quantifying the light source color discrimination ability based on illuminance correction, including the following modules:

[0126] An illuminance information acquisition module for the light source to be evaluated, measuring the illuminance E of the light source to be evaluated;

[0127] An illuminance range judgment module, used to judge whether the illuminance E of the light source to be evaluated is within the set illuminance range, that is, to judge whether a ≤ E ≤ b holds. If it does not hold, exit. If it holds, proceed to the next module;

[0128] A spectral information acquisition module for the light source to be evaluated, used to measure the spectral power distribution of the light source to be evaluated;

[0129] A color discrimination information calculation module for the light source to be evaluated, used to calculate the color discrimination index of the light source to be evaluated;

[0130] A color discrimination range judgment module, used to judge whether the color discrimination index CDM of the light source to be evaluated is within the set color discrimination range, that is, to judge whether c ≤ CDM ≤ d holds. If it does not hold, exit. If it holds, proceed to the next module;

[0131] A module for quantifying the light source color discrimination ability based on illuminance correction, used to input the illuminance E and color discrimination index CDM of the light source to be evaluated into the constructed quantization model M of the illuminance-corrected light source color discrimination ability, obtaining the estimated value of the illuminance-corrected color discrimination ability of the light source to be evaluated, and further realizing the quantization and characterization of the light color discrimination ability of white light sources under different lighting levels; the specific form of the quantization model M of the illuminance-corrected light source color discrimination ability is as follows:

[0132] M = w 1 *0.01*E + w 2 *CDM

[0133] Among them, M is the estimated value of the illuminance-corrected light source color discrimination ability. The larger the M value, the stronger the light color discrimination ability of the light source; E is the illuminance level of the light source to be evaluated; CDM is the color discrimination index of the light source to be evaluated, w 1 and w 2is the weight.

[0134] Moreover, the specific implementation method of the color resolution information calculation module of the light source to be evaluated is as follows:

[0135] Calculate the whiteness index S of the light source to be evaluated in the CIE1976 UCS uniform color space neutral , the calculation formula is as follows:

[0136] S neutral =x*e y

[0137] y=-0.5[n 1 (u′-n 3 ) 2 +n 2 (v′-n 4 ) 2 +2n 5 (u′-n 3 )(v′-n 4 )]

[0138] x=8.1,n 1 =1494.9, n 2 =981.9,n 3 =0.2081, n 4 =0.4596, n 5 =-722.2

[0139] Among them, S neutral is the whiteness index of the light source, u′ and v′ are the chromaticity coordinates of the light source to be evaluated in the CIE1976 UCS uniform color space;

[0140] The hue misalignment index Rd of all light sources to be evaluated is calculated in the CAM02 UCS uniform color space. The specific formula used to calculate Rd is as follows:

[0141]

[0142] CE j =|Ct j -Ct j-1 |+|Ct j -Ct j+1 |

[0143] Among them, R d is the total hue misalignment score of the light source, which is used to measure the number of chess piece misalignments in the FM-100 hue chess caused by the light source; 85 samples of FM-100 hue chess are divided into four long chessboards A, B, C, and D; i is the sequence number of the four chessboards of FM-100 hue chess, i=1 represents chessboard A, i=2 represents chessboard B, i=3 represents chessboard C, i=4 represents chessboard D, Rd，A For the misalignment score of the chessboard A under the test light source, and so on; Ct j is the position of the j-th chess piece under the test light source; CEt j is the misalignment score of the j-th chess piece under the test light source; n is the number of movable chess pieces in each chessboard. In chessboard A, n = 22, and in chessboards B, C, and D, n = 21;

[0144] Through the whiteness index S of the light source to be evaluated neutral and the hue misalignment index Rd, calculate the color discrimination index CDM of the light source to be evaluated. The calculation formula is as follows:

[0145] CDM = -p * R d + q * S neutral

[0146] p = 0.07, q = 0.93

[0147] where CDM is the light source color discrimination index, S neutral is the light source whiteness index, and R d is the light source hue misalignment index.

[0148] Moreover, in the illuminance range judgment module, a = 48, b = 1007.

[0149] Moreover, in the light source spectral information acquisition module to be evaluated, the spectral power distribution of the light source to be evaluated measured is adopted with the information in the 400nm - 700nm band.

[0150] Moreover, in the color discrimination range judgment module, c = 0.83, d = 7.08.

[0151] Moreover, in the module for quantifying the color discrimination ability of the light source based on illuminance correction, w 1 = 0.23, w 2 = 0.77.

[0152] The specific implementation of each module corresponds to each step, and the present invention will not elaborate.

[0153] The specific embodiments described herein are merely illustrative of the spirit of the present invention. Those skilled in the art of the present invention can make various modifications or supplements to the described specific embodiments or use similar methods to replace them, but will not deviate from the spirit of the present invention or exceed the scope defined by the appended claims.

Claims

1. A method for quantifying the color resolution ability of a light source based on illuminance correction, characterized in that, it includes the following steps: Step 1, measure the illuminance E of the light source to be evaluated; Step 2, determine whether the illuminance E of the light source to be evaluated is within the applicable illuminance range, that is, determine whether a ≤ E ≤ b holds. If it does not hold, exit. If it holds, proceed to the next step; Step 3, measure the spectral power distribution of the light source to be evaluated; Step 4, calculate the color resolution index CDM of the light source to be evaluated; Step 5, determine whether the color resolution index CDM of the light source to be evaluated is within the applicable color resolution range, that is, determine whether c ≤ CDM ≤ d holds. If it does not hold, exit. If it holds, proceed to the next step; Step 6, input the illuminance E and the color resolution index CDM of the light source to be evaluated in Steps 1 and 4 into the quantification model M of the color resolution ability of the illuminance-corrected light source constructed, and obtain the estimated value of the color resolution ability of the illuminance-corrected light source to be evaluated, thereby realizing the quantification and characterization of the color resolution ability of the white light source under different illuminance levels; M is an estimation model of the color resolution ability of the light, and the specific form is as follows: M = w 1 * 0.01 * E + w 2 * CDM Among them, M is the estimated value of the light source color resolution ability after illuminance correction. The larger the value, the stronger the light source color resolution ability; E is the illuminance level of the light source to be evaluated, with the unit of lx; CDM is the color resolution index of the light source to be evaluated, and w 1 and w 2 are weights.

2. A method for quantifying the color resolution ability of a light source based on illuminance correction according to claim 1, characterized in that: The specific implementation method of Step 4 is as follows, Step 4.1, calculate the whiteness index S of the light source to be evaluated in the CIE1976 UCS uniform color space neutral , and the calculation formula is as follows: S neutral = x * e y y = -0.5[n 1 (u′ - n 3 ) 2 + n 2 (v′ - n 4 ) 2 + 2n 5 (u′ - n 3 (v′ - n 4 )] x = 8.1, n 1 = 1494.9, n 2 = 981.9, n 3 = 0.2081, n 4 = 0.4596, n 5 = -722.2 Among them, S neutral is the whiteness index of the light source, and u′ and v′ are the chromaticity coordinates of the light source to be evaluated in the CIE1976 UCS uniform color space; Step 4.2, calculate the hue dislocation index R of all light sources to be evaluated in the CAM02 UCS uniform color space d , calculate R d The specific formula used when calculating is as follows: CEt j = |Ct j - Ct j-1 | + |Ct j - Ct j+1 | Among them, R d is the total hue misalignment score of the light source, which is used to measure the number of chess piece misalignments in the FM-100 hue chess caused by the light source; 85 samples of FM-100 hue chess are divided into four long chessboards A, B, C, and D; i is the sequence number of the four chessboards of FM-100 hue chess, i=1 represents chessboard A, i=2 represents chessboard B, i=3 represents chessboard C, i=4 represents chessboard D, R d，A is the misalignment score of chessboard A under the test light source, and so on; Ct j is the position of the jth chess piece under the test light source; CEt j is the misalignment score of the jth chess piece under the test light source; n is the number of movable chess pieces in each chessboard, n=22 in chessboard A, and n=21 in chessboards B, C, and D; Step 4.3, through the whiteness index S of the light source to be evaluated neutral and the hue misalignment index R d , calculate the color discrimination index CDM of the light source to be evaluated. The calculation formula is as follows: CDM = -p * R d +q * S neutral p = 0.07, q = 0.93 Among them, CDM is the light source color resolution index, S neutral is the light source whiteness index calculated in step 4.1, and R d is the light source hue misalignment index calculated in step 4.

2.

3. A method for quantifying the color resolution ability of a light source based on illuminance correction according to claim 1, characterized in that: In Step 2, a = 48, b = 1007; in Step 5, c = 0.83, d = 7.

08.

4. A method for quantifying the color resolution ability of a light source based on illuminance correction according to claim 1, characterized in that: In Step 3, the 400nm - 700nm band information is used for the measured spectral power distribution of the light source to be evaluated.

5. A method for quantifying the color resolution ability of a light source based on illuminance correction according to claim 1, characterized in that: In step 6, w 1 = 0.23, w 2 = 0.

77.

6. A system for quantifying the color resolution ability of a light source based on illuminance correction, characterized in that, it includes the following modules: An acquisition module for the illuminance information of the light source to be evaluated, which measures the illuminance E of the light source to be evaluated; An illuminance range judgment module, which is used to judge whether the illuminance E of the light source to be evaluated is within the set illuminance range, that is, judge whether a ≤ E ≤ b holds. If it does not hold, exit. If it holds, proceed to the next module; An acquisition module for the spectral information of the light source to be evaluated, which is used to measure the spectral power distribution of the light source to be evaluated; A calculation module for the color resolution information of the light source to be evaluated, which is used to calculate the color resolution index of the light source to be evaluated; A color resolution range judgment module, which is used to judge whether the color resolution index CDM of the light source to be evaluated is within the set color resolution range, that is, judge whether c ≤ CDM ≤ d holds. If it does not hold, exit. If it holds, proceed to the next module; The illuminance-corrected light source color resolution ability quantization module is used to input the illuminance E and color resolution index CDM of the light source to be evaluated into the quantization model M of the illuminance-corrected light source color resolution ability, obtain the estimated value of the illuminance-corrected color resolution ability of the light source to be evaluated, and further realize the quantization and characterization of the light color resolution ability of white light sources under different lighting levels; the specific form of the illuminance-corrected light source color resolution ability quantization model M is as follows: M = w 1 * 0.01 * E + w 2 * CDM Among them, M is the estimated value of the light source color resolution ability after illuminance correction. The larger the M value, the stronger the light source color resolution ability; E is the illuminance level of the light source to be evaluated, with the unit of lx; CDM is the color resolution index of the light source to be evaluated, and w 1 and w 2 are weights.

7. A quantization system for the color resolution ability of a light source based on illuminance correction according to claim 6, characterized in that: The specific implementation method of the calculation module for the color resolution information of the light source to be evaluated is as follows, Calculate the whiteness index S of the light source to be evaluated in the CIE1976 UCS uniform color space neutral , and the calculation formula is as follows: S neutral = x * e y y = -0.5[n 1 (u′ - n 3 ) 2 + n 2 (v′ - n 4 ) 2 + 2n 5 (u′ - n 3 (v′ - n 4 )] x = 8.1, n 1 = 1494.9, n 2 = 981.9, n 3 = 0.2081, n 4 = 0.4596, n 5 = -722.2 where S neutral is the whiteness index of the light source, and u′ and v′ are the chromaticity coordinates of the light source to be evaluated in the CIE1976 UCS uniform color space; Calculate the hue dislocation index R of all light sources to be evaluated in the CAM02 UCS uniform color space d , and calculate R d using the following specific formula: CEt j = |Ct j - Ct j-1 | + |Ct j - Ct j+1 | Among them, R d is the total hue misalignment score of the light source, which is used to measure the number of chess piece misalignments in the FM-100 hue chess caused by the light source; 85 samples of FM-100 hue chess are divided into four long chessboards A, B, C, and D; i is the sequence number of the four chessboards of FM-100 hue chess, i=1 represents chessboard A, i=2 represents chessboard B, i=3 represents chessboard C, i=4 represents chessboard D, R d，A is the misalignment score of chessboard A under the test light source, and so on; Ct j is the position of the jth chess piece under the test light source; CEt j is the misalignment score of the i-th chess piece under the test light source; n is the number of movable chess pieces in each chessboard, n=22 in chessboard A, and n=21 in chessboards B, C, and D; Step 4.3, through the whiteness index S of the light source to be evaluated neutral and the hue misalignment index R d , calculate the color discrimination index CDM of the light source to be evaluated. The calculation formula is as follows: CDM = -p * R d +q * S neutral p = 0.07, q = 0.93 Among them, CDM is the light source color resolution index, S neutral is the light source whiteness index, R d is the light source hue misalignment index.

8. A quantization system for the color resolution ability of a light source based on illuminance correction according to claim 6, characterized in that: In the illuminance range judgment module, a = 48, b = 1007, and in the color resolution range judgment module, c = 0.83, d = 7.

08.

9. A quantization system for the color resolution ability of a light source based on illuminance correction according to claim 6, characterized in that: In the spectral information acquisition module of the light source to be evaluated, the spectral power distribution of the light source to be evaluated measured is adopted with the information in the 400nm - 700nm band.

10. A quantization system for the color resolution ability of a light source based on illuminance correction according to claim 6, characterized in that: In the illuminance correction-based light source color resolution ability quantization module, w 1 = 0.23, w 2 = 0.77.

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