Light source color evaluation method and device

Abstract

The invention provides a light source color evaluation method and device. The method comprises the following steps: acquiring a color temperature value CCT and a color cast value Duv of a target light source; judging a color temperature range type corresponding to the color temperature value CCT; determining a target light source color evaluation model corresponding to the color temperature range type according to the color temperature range type; and inputting the color temperature value CCT and the color cast value Duv into the target light source color evaluation model to obtain a color evaluation result of the target light source. According to the method, the lighting effect presented by light source irradiation can be quantified, and the evaluation standard for predicting the preference degree of human eyes to the light source is established, so that the lighting effect of the light source in the lighting scene is regulated and controlled based on the evaluation standard.

Description

Technical Field

[0001] The present disclosure relates to the field of intelligent lighting technology, and in particular to a method and device for evaluating light source color. Background Art

[0002] Compared with traditional light sources, LED light sources have many advantages such as high luminous efficiency, low radiation and long life. Its technical feature of adjustable light color has pointed out the development direction for intelligent lighting, which enables it to meet people's personalized lighting needs and adapt to various intelligent application scenarios.

[0003] Light quality research has become a hot topic in the lighting field. Light sources are often used in situations where there are no actual illuminated objects, directly illuminating the entire space. However, in these situations, due to the discrepancy between the light source's parameters and the human eye's perception, the lighting scene settings may not always match user needs. Therefore, a method that can accurately predict the illumination effect of light sources and the degree to which the human eye prefers light color is urgently needed. Summary of the Invention

[0004] The embodiments of the present application propose a light source color evaluation method and device, which can quantify the lighting effect presented by the light source illumination, establish an evaluation standard for predicting the degree of human eye preference for the light source, and regulate the lighting effect of the light source in the lighting scene based on this evaluation standard.

[0005] In one aspect, an embodiment of the present application provides a light source color evaluation method, comprising:

[0006] Get the color temperature value CCT and color deviation value Duv of the target light source;

[0007] Determine a color temperature range type corresponding to the color temperature value CCT, where the color temperature range type includes a first preset color temperature range, a second preset color temperature range, and a third preset color temperature range;

[0008] Determine the corresponding target light source color evaluation model according to the color temperature range type;

[0009] The color temperature value CCT and the color deviation value Duv are input into the target light source color evaluation model to obtain a color evaluation result of the target light source.

[0010] In a possible implementation, the first preset color temperature range, the second preset color temperature range, and the third preset color temperature range are 2500-3500K, 3500-5000K, and 5000-7000K, respectively.

[0011] In a possible implementation, the color temperature value CCT and the color deviation value Du vInput into the target light source color evaluation model includes:

[0012] When the color temperature CCT is determined to be within the range of 2500-3500K,

[0013] The color temperature value CCT is input into a first light source color evaluation model to obtain a color evaluation result of the target light source. The first light source color evaluation model is:

[0014] M1=p1+p2*Ln(CCT)+p3*Duv+p4*Duv 2

[0015] Where p1 = -4.728 × 10 1 , p2=6.415, p3=-1.079×10 2 , p4=-6.181×10 3 .

[0016] In a possible implementation, the color temperature value CCT and the color deviation value Du v Input into the target light source color evaluation model includes:

[0017] When the color temperature value CCT is determined to be within the range of 3500 to 5000K,

[0018] The color temperature value CCT is input into a second light source color evaluation model to obtain a color evaluation result of the target light source. The second light source color evaluation model is:

[0019]

[0020] Among them, p5 = 3.538, p6 = 4.735 × 10 -4 , p7=-5.782×10 -1 , p8=-9.420×10 -3 .

[0021] In a possible implementation, inputting the color temperature value CCT and the color deviation value Duv into the target light source color evaluation model includes:

[0022] When the color temperature CCT is determined to be within the range of 5000-7000K,

[0023] The color temperature value CCT is input into the third light source color evaluation model to obtain the color evaluation result of the target light source. The third light source color evaluation model is:

[0024] M3=p9+p10*CCT+p11*Duv+p12*Duv 2

[0025] Among them, p9 = 6.173, p10 = -1.489 × 10 -4 , p11=-3.584×10 1 , p12=-5.473×10 3 .

[0026] In a possible implementation, the method further includes:

[0027] Determine a corresponding target light source quality quantification model according to the color temperature range type;

[0028] The color temperature value CCT, the color deviation value Duv, and the maximum color deviation value are input into a target light source quality quantification model to obtain a quality quantification result of the target light source.

[0029] In a possible implementation, the quality quantification result of the target light source is a ratio between an evaluation result obtained by inputting the color deviation value Duv of the target light source into the target light source color evaluation model and an evaluation result obtained by inputting the maximum color deviation value.

[0030] In a possible implementation, the step of obtaining the color temperature value CCT and the color deviation value Duv of the target light source may then include:

[0031] Determining whether the color temperature value CCT is within a preset color temperature range, and determining whether the color deviation value Duv is within a preset color deviation range;

[0032] If both are within their corresponding preset ranges, the color temperature range type corresponding to the color temperature value CCT is determined.

[0033] In a possible implementation, the method further includes:

[0034] Acquire spectral power distribution information of the target light source, where the wavelength of the target light source is 400-700 nm;

[0035] The color temperature value CCT and the color deviation value Duv of the target light source are calculated according to the spectral power distribution information.

[0036] In one aspect, an embodiment of the present application provides a light source color evaluation device, comprising:

[0037] Color temperature range judgment unit: used to obtain the color temperature value CCT and color deviation value Duv of the target light source;

[0038] Determine a color temperature range type corresponding to the color temperature value CCT, where the color temperature range type includes a first preset color temperature range, a second preset color temperature range, and a third preset color temperature range;

[0039] Color evaluation quantification unit: used to determine the corresponding target light source color evaluation model according to the color temperature range type;

[0040] The color temperature value CCT and the color deviation value Duv are input into the target light source color evaluation model to obtain a color evaluation result of the target light source.

[0041] In an embodiment of the present application, the color temperature value CCT and color deviation value Duv of the target light source are first obtained; the color temperature range type corresponding to the color temperature value CCT is determined, and the color temperature range type includes a first preset color temperature range, a second preset color temperature range, and a third preset color temperature range; then, the corresponding target light source color evaluation model is determined according to the color temperature range type; finally, the color temperature value CCT and the color deviation value Duv are input into the target light source color evaluation model to obtain the color evaluation result of the target light source. As can be seen from this, the present application divides the color temperature value into multiple different color temperature ranges using corresponding dividing values, and introduces the color deviation value as a parameter to obtain the corresponding light source color evaluation model under different color temperature conditions, quantifying the different lighting quality evaluation results generated by the user under different color temperature ranges due to the different degree of color deviation of the light source, thereby stably and reliably predicting the human eye's preference for the light source color in a specific lighting scene, so as to achieve the regulation and optimization of the light source lighting scheme under different demand scene conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions and advantages of the embodiments of this specification or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0043] Figure 1 A flowchart of a light source color evaluation method provided in an embodiment of this specification;

[0044] Figure 2 This is a structural diagram of a light source color evaluation device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0045] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0046] In the field of lighting, color temperature and color cast are two important indicators that have a significant impact on the human eye's color perception. They intuitively reflect the relative position of the light source's color point and the blackbody locus in the chromaticity diagram. Since they are basic parameters of light sources in the industry, they have a strong theoretical basis for using them as a starting point for judging light source color preferences.

[0047] However, under different color temperature conditions, users' perception and mood will vary, resulting in different abilities to distinguish and accept color deviations, which directly affects users' judgment of the lighting effects of the lighting scene and their evaluation of the light source quality.

[0048] Therefore, in order to solve the above technical problems, this application proposes a light source color evaluation method, which simultaneously quantifies the impact of light source lighting scenes with different color temperature ranges and color deviation degrees on users, thereby accurately evaluating the user's preference for lighting effects based on the current lighting scheme, and thus providing guidance for light source color quality evaluation and control optimization in the field of lighting applications.

[0049] like Figure 1 As shown, the present application provides a light source color evaluation method, comprising:

[0050] S100: Obtain the color temperature value CCT and color deviation value Duv of the target light source;

[0051] In one embodiment, before step S100 of obtaining the color temperature value CCT and the color deviation value Duv of the target light source, the following steps are included: obtaining spectral power distribution information of the target light source, where the wavelength of the target light source is 400-700 nm;

[0052] The color temperature value CCT and the color deviation value Duv of the target light source are calculated according to the spectral power distribution information.

[0053] Specifically, the above method is implemented based on a light source color evaluation device, which includes a spectral reflectance acquisition module for measuring the spectral reflectance of the light source to be used; and a Duv value calculation module for calculating the Duv value of the light source to be used. The light source to be used is the target light source in this application.

[0054] In one embodiment, step S100 obtains the color temperature value CCT and the color deviation value Duv of the target light source, and then includes:

[0055] Determining whether the color temperature value CCT is within a preset color temperature range, and determining whether the color deviation value Duv is within a preset color deviation range;

[0056] If both are within their corresponding preset ranges, the color temperature range type corresponding to the color temperature value CCT is determined.

[0057] Determine whether the Duv value of the light source to be used is within the chromaticity deviation range applicable to the present invention, that is, determine whether Duv1≤Duv≤Duv2 is established. If not, the present invention is not applicable. If so, proceed to the next step. Wherein, Duv1 = -0.01, Duv2 = 0.01.

[0058] Determine whether the correlated color temperature (CCT) of the light source to be used is within the range of correlated color temperatures applicable to the present invention, that is, determine whether CCT1 ≤ CCT ≤ CCT4 holds. If not, the present invention is not applicable. If so, proceed to the next step. Where CCT1 = 2500K and CCT4 = 7000K.

[0059] S200: Determine the color temperature range type corresponding to the color temperature value CCT, where the color temperature range type includes a first preset color temperature range, a second preset color temperature range, and a third preset color temperature range;

[0060] The first preset color temperature range CCT1≤CCT≤CCT2, the second preset color temperature range CCT2≤CCT≤CCT3, and the third preset color temperature range CCT3≤CCT≤CCT4 are 2500-3500K, 3500-5000K, and 5000-7000K, respectively.

[0061] S300: Determine a corresponding target light source color evaluation model according to the color temperature range type;

[0062] S400: Inputting the color temperature value CCT and the color deviation value Duv into the target light source color evaluation model to obtain a color evaluation result of the target light source.

[0063] In one embodiment, step S400 of inputting the color temperature value CCT and the color deviation value Duv into the target light source color evaluation model includes:

[0064] When the color temperature CCT is determined to be within the range of 2500-3500K,

[0065] The color temperature value CCT is input into a first light source color evaluation model to obtain a color evaluation result of the target light source. The first light source color evaluation model is:

[0066] M1=p1+p2*Ln(CCT)+p3*Duv+p4*Duv 2

[0067] Where p1 = -4.728 × 10 1 , p2=6.415, p3=-1.079×10 2 , p4=-6.181×10 3 .

[0068] In one embodiment, step S400 of inputting the color temperature value CCT and the color deviation value Duv into the target light source color evaluation model includes:

[0069] When the color temperature value CCT is determined to be within the range of 3500 to 5000K,

[0070] The color temperature value CCT is input into a second light source color evaluation model to obtain a color evaluation result of the target light source. The second light source color evaluation model is:

[0071]

[0072] Among them, p5 = 3.538, p6 = 4.735 × 10 -4 , p7=-5.782×10 -1 , p8=-9.420×10 -3 .

[0073] In one embodiment, step S400 of inputting the color temperature value CCT and the color deviation value Duv into the target light source color evaluation model includes:

[0074] When the color temperature CCT is determined to be within the range of 5000-7000K,

[0075] The color temperature value CCT is input into the third light source color evaluation model to obtain the color evaluation result of the target light source. The third light source color evaluation model is:

[0076] M3=p9+p10*CCT+p11*Duv+p12*Duv 2

[0077] Among them, p9 = 6.173, p10 = -1.489 × 10 -4 , p11=-3.584×10 1 , p12=-5.473×10 3 .

[0078] Specifically, M1, M2, and M3 represent the absolute color preference models of light sources under different color temperature conditions, which are suitable for estimating the absolute value of light source color preference. Where CCT is the correlated color temperature of the light source to be used, and Duv is the color difference between the color point of the light source to be used and the point with the same color temperature on the blackbody locus.

[0079] According to the corresponding CCT range that meets the conditions, the Duv value and the correlated color temperature CCT of the light source to be used are input into the light source color evaluation models M1, M2 and M3 constructed by the present invention, so as to calculate the absolute preference quantitative value of the light source color.

[0080] In one embodiment, the light source color evaluation method of the present application further includes:

[0081] Determine a corresponding target light source quality quantification model according to the color temperature range type;

[0082] The color temperature value CCT, the color deviation value Duv, and the maximum color deviation value are input into a target light source quality quantification model to obtain a quality quantification result of the target light source.

[0083] The quality quantification result of the target light source is the ratio between the evaluation result obtained by inputting the color deviation value Duv of the target light source into the target light source color evaluation model and the evaluation result obtained by inputting the maximum color deviation value.

[0084] The light source quality quantification model includes a first light source quality quantification model, a second light source quality quantification model, and a third light source quality quantification model corresponding to the first preset color temperature range, the second preset color temperature range, and the third preset color temperature range, respectively.

[0085] M4 is a light source quality quantification model under 2500K-3500K, and its specific form is as follows:

[0086]

[0087] M5 is a light source quality quantification model under 3500K-5000K, and its specific form is as follows:

[0088]

[0089] M6 is a light source quality quantification model under 5000K-7000K, and its specific form is as follows:

[0090]

[0091] Since different CCT light sources cannot be directly compared in actual production applications, it is necessary to develop a relative model for light sources with the same CCT.

[0092] Among them, the relative models M4, M5 and M6 correspond to the absolute models M1, M2 and M3 respectively, representing the relative preference models of light source colors under different color temperature conditions, and are suitable for estimating the relative value of light source color preference.

[0093] Where CCT is the correlated color temperature of the light source to be used, Duv is the color difference between the color point of the light source to be used and the point with the same color temperature on the blackbody locus, and Duv_max is the maximum color deviation of the light source to be used. In this embodiment, the value is -0.00873.

[0094] This application uses an absolute value quantification method for light source color preference based on the light source's correlated color temperature (CCT) and color deviation (Duv), as well as a relative value quantification method using CCT as the demarcation. Relying on the correlated color temperature (CCT) and Duv indicators of the color point light source to be used, and using multiple predictive quantification models, this application achieves a comprehensive and accurate quantitative assessment of the color preference of the light source to be used based on the light source's CCT and Duv, thereby providing a comprehensive and targeted light source color preference quantification solution for the field.

[0095] To further demonstrate the technical advantages of the light source color preference prediction model in the light source color preference quantitative evaluation scheme described in the present invention, a psychophysics experiment was conducted to calculate the PEARSON correlation coefficient between the human eye's preference for color point light sources of different color temperatures and the light source color absolute preference models M1, M3, and M5.

[0096] The correlated color temperatures of the light sources to be used in the embodiments are 2700K, 3000K, 4000K, 5000K, 5500K and 6500K, and the Duv of the light sources are -0.01, -0.007, -0.004, -0.002, 0, 0.002, 0.004, 0.007 and 0.01, respectively.

[0097] The specific implementation is as follows: Using the aforementioned 6 CCT and 9 Duv combinations, totaling 54 color point light sources to be used, as experimental light sources, observers with normal color vision who have passed the Ishihara test carefully observe an empty light box and use the light color as the observation object to conduct a psychophysical preference evaluation experiment. The specific experimental method is as follows:

[0098] 1) The light box was the only luminous object, and the entire experiment was conducted in a completely dark laboratory. Observers were required to observe the color of the light from the empty light box and rate their preference using a Likert scale ranging from +1 to +7.

[0099] 2) The light source color temperatures used in the experiment were categorized into three categories: 2500K-3500K, 3500K-5000K, and 5000K-7000K. These correspond to the conditional color temperatures of the light source color absolute preference models M1, M3, and M5, respectively. These are suitable for quantitatively estimating people's absolute preference under different light sources. The calculated Duv values ​​and corresponding CCT values ​​were then substituted into the values.

[0100] 3) During the experiment, the order in which each light source appears is random. The experimenter will ask the observer to observe carefully for at least 5 seconds before evaluating. The observer needs to record the evaluation of the light color in the empty light box in each experimental scenario in the experimental record sheet according to the evaluation rules specified in the experiment. The evaluation rules are as follows:

[0101] The rating scale used was seven points, with 1 for "very dislike" and 7 for "very like," with higher numbers indicating a higher degree of preference. After observing the light in the empty light box for a while, the observers were asked to rate the light accordingly. Other experimenters provided continuous reminders to ensure the observers focused on the light in the light box and eliminated distractions from external factors, such as the surrounding environment.

[0102] 4) A total of 31 observers were selected for the experiment. They were young students aged 18-24 years old, with an average age of 22.13 and a standard deviation of 1.70. All of them had normal vision. Before each experiment, the experimenter will orally introduce the experimental conditions. During the experiment, the observer observed the color of the light in the empty light box under the corresponding light source and made a preference evaluation. Then he closed his eyes until the experimenter replaced the next set of experimental light sources. The observer observed again for a period of time and made a preference evaluation. This step was repeated until the last set of experimental scenes. Each observer needed to observe a total of 60 color points of light (54+5 repetitions), of which it took about 20 seconds under each light source, and a total of 20 minutes per person.

[0103] 5) After the experiment, the observers' scores on their light color preferences in the light box were collected to calculate the PEARSON correlation coefficients between the subjective evaluation values ​​and the absolute light color preference models M1, M3, and M5. The experimental parameters and calculation results are shown in the following table.

[0104]

[0105]

[0106]

[0107] Observer preference subjective evaluation experiment and calculation results

[0108] The above psychophysical experiments provide subjective evaluations of light source preferences by different observers at different CCTs. Furthermore, the PEARSON correlation coefficients between these nine scores at each color temperature and the absolute light source color preference models M1, M2, and M3 constructed in the present invention are calculated, as shown in the table below. The results show that the correlation coefficients between the nine subjective evaluations and the absolute light source color preference models M4, M5, and M6 at each color temperature are all greater than 0.85, demonstrating the high accuracy of the light source color preference prediction model constructed in the present invention based on the correlated color temperature and Duv. This demonstrates the strong technical advantages of the method described in the present invention in predicting light source color preferences.

[0109] Color Temperature CCT PEARSON correlation coefficient 2700K 0.940 3000K 0.971 4000K 0.953 5000K 0.929 5500K 0.968 6500K 0.876

[0110] Correlation coefficients between the average preference scores at different color temperatures and the absolute preference models M1, M2, and M3 for light source colors.

[0111] See also Figure 2 , Figure 2 2 is a schematic diagram of the structure of a light source color evaluation device provided in an embodiment of the present application. In specific implementation, the light source color evaluation device 200 may specifically include:

[0112] Color temperature range judgment unit 201: used to obtain the color temperature value CCT and color deviation value Duv of the target light source;

[0113] Determine a color temperature range type corresponding to the color temperature value CCT, where the color temperature range type includes a first preset color temperature range, a second preset color temperature range, and a third preset color temperature range;

[0114] Color evaluation quantization unit 202: used to determine the corresponding target light source color evaluation model according to the color temperature range type;

[0115] The color temperature value CCT and the color deviation value Duv are input into the target light source color evaluation model to obtain a color evaluation result of the target light source.

[0116] An embodiment of the present application provides a computer device comprising: a storage device and a processor;

[0117] a memory storing one or more computer programs;

[0118] The processor is used to load the one or more computer programs to implement the light source color evaluation method in this application.

[0119] In addition, it should be pointed out here that: the embodiment of the present application also provides a computer storage medium, and the computer storage medium stores a computer program, and the computer program includes program instructions. When the processor executes the above program instructions, it can execute the method in the corresponding embodiment above. Therefore, it will not be repeated here.

[0120] For technical details not disclosed in the computer storage medium embodiments involved in this application, please refer to the description of the method embodiments of this application. As an example, the program instructions can be deployed on a computer device, or executed on multiple computer devices located in a single location, or executed on multiple computer devices distributed in multiple locations and interconnected by a communication network.

[0121] According to one aspect of the present application, embodiments of the present application further provide a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, so that the computer device can perform the methods described in the corresponding embodiments above. Therefore, these methods will not be described in detail here.

[0122] Those skilled in the art will appreciate that the units and algorithmic steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technical personnel may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0123] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted via a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data processing device such as a server or data center that includes one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0124] The above disclosure is only a preferred embodiment of the present application, and certainly cannot be used to limit the scope of rights of the present application. Therefore, equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A light source color evaluation method, characterized in that: include: Get the color temperature value CCT and color deviation value Duv of the target light source; Determine the color temperature range type corresponding to the color temperature value CCT; Determine the corresponding target light source color evaluation model according to the color temperature range type; The color temperature value CCT and the color deviation value Duv are input into the target light source color evaluation model to obtain a color evaluation result of the target light source.

2. The light source color evaluation method according to claim 1, wherein: The color temperature range types include at least a first preset color temperature range, a second preset color temperature range, and a third preset color temperature range.

3. The light source color evaluation method according to claim 2, wherein: The first preset color temperature range, the second preset color temperature range and the third preset color temperature range are 2500-3500K, 3500-5000K and 5000-7000K respectively.

4. The light source color evaluation method according to claim 2 or 3, characterized in that: Inputting the color temperature value CCT and the color deviation value Duv into the target light source color evaluation model includes: When it is determined that the color temperature value CCT is within the first preset color temperature range, The color temperature value CCT is input into a first light source color evaluation model to obtain a color evaluation result of the target light source. The first light source color evaluation model is: M1=p1+p2*Ln(CCT)+p3*Duv+p4*Duv 2 Where p1 = -4.728 × 10 1 , p2=6.415, p3=-1.079×10 2 , p4=-6.181×10 3 .

5. The light source color evaluation method according to claim 2 or 3, characterized in that: Inputting the color temperature value CCT and the color deviation value Duv into the target light source color evaluation model includes: When it is determined that the color temperature value CCT is within the second preset color temperature range, The color temperature value CCT is input into a second light source color evaluation model to obtain a color evaluation result of the target light source. The second light source color evaluation model is: Among them, p5 = 3.538, p6 = 4.735 × 10 -4 , p7=-5.782×10 -1 , p8=-9.420×10 -3 .

6. The light source color evaluation method according to claim 2 or 3, characterized in that: Inputting the color temperature value CCT and the color deviation value Duv into the target light source color evaluation model includes: When it is determined that the color temperature value CCT is within the third preset color temperature range, The color temperature value CCT is input into the third light source color evaluation model to obtain the color evaluation result of the target light source. The third light source color evaluation model is: M3=p9+p10*CCT+p11*Duv+p12*Duv 2 Among them, p9 = 6.173, p10 = -1.489 × 10 -4 , p11=-3.584×10 1 , p12=-5.473×10 3 .

7. The light source color evaluation method according to claim 1, wherein: Also includes: Determine a corresponding target light source quality quantification model according to the color temperature range type; The color temperature value CCT, the color deviation value Duv, and the maximum color deviation value are input into a target light source quality quantification model to obtain a quality quantification result of the target light source.

8. The light source color evaluation method according to claim 7, wherein: The quality quantification result of the target light source is a ratio between an evaluation result obtained by inputting the color deviation value Duv of the target light source into the target light source color evaluation model and an evaluation result obtained by inputting the maximum color deviation value.

9. The light source color evaluation method according to claim 1, wherein: The step of obtaining the color temperature value CCT and the color deviation value Duv of the target light source further includes: Determining whether the color temperature value CCT is within a preset color temperature range, and determining whether the color deviation value Duv is within a preset color deviation range; If both are within their corresponding preset ranges, the color temperature range type corresponding to the color temperature value CCT is determined.

10. A light source color evaluation device, characterized in that: include: Color temperature range judgment unit: used to obtain the color temperature value CCT and color deviation value Duv of the target light source; Determine the color temperature range type corresponding to the color temperature value CCT; Color evaluation quantification unit: used to determine the corresponding target light source color evaluation model according to the color temperature range type; The color temperature value CCT and the color deviation value Duv are input into the target light source color evaluation model to obtain a color evaluation result of the target light source.

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