CN116524103A - Method and device for establishing RGB-LED space color mixing model based on human eye visual characteristics - Google Patents
Method and device for establishing RGB-LED space color mixing model based on human eye visual characteristics Download PDFInfo
- Publication number
- CN116524103A CN116524103A CN202310463669.3A CN202310463669A CN116524103A CN 116524103 A CN116524103 A CN 116524103A CN 202310463669 A CN202310463669 A CN 202310463669A CN 116524103 A CN116524103 A CN 116524103A
- Authority
- CN
- China
- Prior art keywords
- color
- light
- model
- led
- space
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000000007 visual effect Effects 0.000 title claims abstract description 40
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000005259 measurement Methods 0.000 claims abstract description 42
- 230000003595 spectral effect Effects 0.000 claims abstract description 35
- 239000000203 mixture Substances 0.000 claims description 14
- 238000004590 computer program Methods 0.000 claims description 11
- 230000003287 optical effect Effects 0.000 claims description 7
- 238000001228 spectrum Methods 0.000 claims description 7
- 238000005286 illumination Methods 0.000 abstract description 6
- 230000007547 defect Effects 0.000 abstract description 3
- 238000013461 design Methods 0.000 abstract description 3
- 238000004088 simulation Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 9
- 239000003086 colorant Substances 0.000 description 8
- 230000004907 flux Effects 0.000 description 6
- 230000005855 radiation Effects 0.000 description 6
- 230000000694 effects Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 239000011324 bead Substances 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 239000006185 dispersion Substances 0.000 description 2
- 239000004973 liquid crystal related substance Substances 0.000 description 2
- 230000004382 visual function Effects 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000012942 design verification Methods 0.000 description 1
- 230000004438 eyesight Effects 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 229940097139 perfect choice Drugs 0.000 description 1
- 238000005375 photometry Methods 0.000 description 1
- 230000004310 photopic vision Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000035807 sensation Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 230000004936 stimulating effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/50—Lighting effects
- G06T15/506—Illumination models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/50—Lighting effects
- G06T15/55—Radiosity
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B20/00—Energy efficient lighting technologies, e.g. halogen lamps or gas discharge lamps
- Y02B20/40—Control techniques providing energy savings, e.g. smart controller or presence detection
Abstract
The invention relates to a method for establishing an RGB-LED space color mixing model based on human eye visual characteristics, which comprises the following steps of obtaining spectral energy distribution of each color of light in a target RGB-LED; according to the spectral energy distribution, solving corresponding coordinates of the monochromatic light in a chromaticity space; establishing a near-field light source distribution model of the tri-chromatic light; converting the near-field light source distribution model of the three-color light based on a human eye visual characteristic curve to establish a near-field luminosity quantity model of the color light; and solving the light measurement of each color light based on the near-field light measurement model, solving the color distribution of each color light in an actual three-dimensional space based on the light measurement, and establishing a space color mixing model of the RGB-LED according to a color mixing principle. According to the invention, the near-field distribution of the light source is calculated through the light propagation model, and is used as the intensity input of each color light, and the color mixing model of the light source in space is obtained according to the color mixing principle, so that the defect of the color model in the conventional RGB-LED simulation is supplemented, and more accurate color information is used in illumination design.
Description
Technical Field
The invention relates to the technical field of LEDs, in particular to a method and a device for establishing an RGB-LED space color mixing model based on human eye visual characteristics.
Background
The atmosphere lamp is also called as an LED atmosphere lamp, is a perfect choice of the LED lamp for theme parks, hotels, home, exhibitions, businesses and artistic lighting, and creates a required atmosphere for life. In the application of atmosphere lamps, RGB-LED beads are mostly adopted, wherein whether the colors of the RGB-LED beads are accurate or not, whether the colors are uniform or not is very important, and the use experience of users can be directly affected.
In the present stage, in the design verification link of the atmosphere lamp based on the RGB-LED, illumination intensity distribution and radiation intensity distribution models are used more simply, and a mode of directly specifying color values is used more simply, so that the obtained color information is often inaccurate though the mode is simple, the requirements of the current market are difficult to be met, and a new model for describing the distribution condition of the RGB-LED colors in space is needed in the current market, so that more accurate color information can be used in illumination design.
Disclosure of Invention
The invention aims to at least solve one of the defects in the prior art and provides a method and a device for establishing an RGB-LED space color mixing model based on human eye visual characteristics.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
specifically, an RGB-LED space color mixing model building method based on human eye visual characteristics is provided, which comprises the following steps:
acquiring spectral energy distribution of each color of light in the target RGB-LED;
according to the spectral energy distribution, solving corresponding coordinates of the monochromatic light in a chromaticity space;
establishing a near-field light source distribution model of the tri-chromatic light;
converting the near-field light source distribution model of the three-color light based on a human eye visual characteristic curve to establish a near-field luminosity quantity model of the color light;
and solving the light measurement of each color light based on the near-field light measurement model, solving the color distribution of each color light in an actual three-dimensional space based on the light measurement, and establishing a space color mixing model of the RGB-LED based on the color distribution of each color light in the actual three-dimensional space and the color mixing principle.
Further, specifically, the spectral energy distribution of each color of light in the target RGB-LED is obtained by measuring a sample in an optical measurement environment or calculated by theoretical parameters of the RGB-LED.
Further, specifically, the coordinates of the monochromatic light corresponding to the chromaticity space are obtained by the following manner;
and integrating the stimulus of each wavelength component to human eyes in the spectral energy distribution of each color of light to obtain the equivalent color and light color coordinates of the monochromatic light, namely obtaining the coordinates corresponding to the monochromatic light in the chromaticity space.
Further, specifically, the near-field light source distribution model is calculated by geometric information and medium distribution conditions of each color light in a given space.
The invention also provides an RGB-LED space color mixing model building device based on the visual characteristics of human eyes, which comprises the following steps:
the spectrum energy distribution acquisition module is used for acquiring spectrum energy distribution of each color of light in the target RGB-LED;
the chromaticity space coordinate solving module is used for solving the corresponding coordinates of the monochromatic light in the chromaticity space according to the spectral energy distribution;
the near-field light source distribution model building module is used for building a near-field light source distribution model of the tri-chromatic light;
the near-field light measurement model building module is used for converting the near-field light source distribution model of the three-color light based on the human eye visual characteristic curve to build a near-field light measurement model of the color light;
the space color mixing model building module is used for obtaining the light measurement of each color light based on the near-field light measurement model, solving the color distribution of each color light in the actual three-dimensional space based on the light measurement, and building the space color mixing model of the RGB-LED according to the color mixing principle.
Further, the method, in particular,
the spectral energy distribution of each color light in the target RGB-LED in the spectral energy distribution acquisition module is obtained by measuring a sample in an optical measurement environment or calculating theoretical parameters of the RGB-LED.
Further, specifically, coordinates corresponding to monochromatic light in a chromaticity space in the chromaticity space coordinate solving module are obtained in the following manner;
and integrating the stimulus of each wavelength component to human eyes in the spectral energy distribution of each color of light to obtain the equivalent color and light color coordinates of the monochromatic light, namely obtaining the coordinates corresponding to the monochromatic light in the chromaticity space.
Further, specifically, the near-field light source distribution model established by the near-field light source distribution model establishing module calculates geometric information and medium distribution conditions of each color of light in a given space.
The invention also provides a computer readable storage medium storing a computer program which when executed by a processor realizes the steps of the RGB-LED space color mixing model building method based on human eye visual characteristics.
The beneficial effects of the invention are as follows:
the invention provides a method for establishing an RGB-LED space color mixing model based on human eye visual characteristics, which comprises the steps of obtaining spectral energy distribution of each color of light in a target RGB-LED; according to the spectral energy distribution, solving corresponding coordinates of the monochromatic light in a chromaticity space; establishing a near-field light source distribution model of the tri-chromatic light; converting the near-field light source distribution model of the three-color light based on a human eye visual characteristic curve to establish a near-field luminosity quantity model of the color light; and solving the light measurement of each color light based on the near-field light measurement model, solving the color distribution of each color light in an actual three-dimensional space based on the light measurement, and establishing a space color mixing model of the RGB-LED according to a color mixing principle. A new model describing the distribution of RGB-LED colors in space and a construction process thereof are provided for using more accurate color information in illumination design.
Drawings
The above and other features of the present disclosure will become more apparent from the detailed description of the embodiments illustrated in the accompanying drawings, in which like reference numerals designate like or similar output voltages, it is apparent that the accompanying drawings in which the following description is given only by way of example of the present disclosure, and that other drawings may be obtained by those skilled in the art without undue effort, in which:
FIG. 1 is a flow chart of a method for establishing RGB-LED space color mixing model based on human eye visual characteristic;
FIG. 2 is a schematic diagram showing spectral energy distribution of a light source involved in a method for creating an RGB-LED spatial color mixing model based on visual characteristics of human eyes;
FIG. 3 is a schematic diagram of a light source near field distribution model according to the method for creating an RGB-LED spatial color mixing model based on human visual characteristics of the present invention;
FIG. 4 is a schematic diagram of a light dispersion model according to the present invention, which is a method for creating a RGB-LED spatial color mixing model based on visual characteristics of human eyes;
FIG. 5 is a schematic diagram of a model of the near-field distribution of a three-color light source according to the method for creating a RGB-LED spatial color mixture model based on the visual characteristics of human eyes;
FIG. 6 is a schematic diagram of a three-color light source spatial color mixing model according to the method for creating an RGB-LED spatial color mixing model based on human visual characteristics of the present invention;
FIG. 7 is a graph showing spectral tristimulus values of the CIE1931XYZ system in one embodiment of chromaticity space related to an RGB-LED space color mixing model creation method based on human visual characteristics according to the present invention;
FIG. 8 is a chromaticity space diagram of the CIE1931XYZ system according to one embodiment of chromaticity space according to the RGB-LED space color mixture model creation method based on human visual characteristics of the present invention;
FIG. 9 is a schematic diagram showing the distribution of near-field light sources in an embodiment of a method for creating an RGB-LED spatial color mixture model based on visual characteristics of human eyes according to the present invention;
FIG. 10 is a schematic diagram showing the visual function of the bright/dark vision of the human eye used for solving the approach photometry model in the RGB-LED space color mixing model building method based on the visual characteristics of the human eye;
fig. 11 is a schematic diagram of a method for creating an RGB-LED spatial color mixture model based on visual characteristics of human eyes, which is used for solving color distribution of each color light in an actual three-dimensional space.
Detailed Description
The conception, specific structure, and technical effects produced by the present invention will be clearly and completely described below with reference to the embodiments and the drawings to fully understand the objects, aspects, and effects of the present invention. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The same reference numbers will be used throughout the drawings to refer to the same or like parts.
Referring to fig. 1, embodiment 1 of the present invention provides a method for creating an RGB-LED spatial color mixing model based on visual characteristics of human eyes, comprising the following steps:
step 110, obtaining the spectral energy distribution of each color of light in the target RGB-LED;
step 120, according to the spectral energy distribution, solving the corresponding coordinates of the monochromatic light in the chromaticity space;
130, establishing a near-field light source distribution model of the tri-chromatic light;
step 140, converting the near-field light source distribution model of the three-color light based on a human eye visual characteristic curve to establish a near-field luminosity quantity model of the color light;
step 150, obtaining the light measurement of each color light based on the near-field light measurement model, solving the color distribution of each color light in the actual three-dimensional space based on the light measurement, establishing a space color mixing model of the RGB-LED based on the color distribution of each color light in the actual three-dimensional space and combining the color mixing principle, and obtaining the three-light-source near-field distribution model shown in fig. 5 by integrating the near-field distribution models of three monochromatic light sources, wherein the color mixing situation of any point in the solving space is shown in fig. 6, namely the space color mixing model of the whole RGB-LED.
In this embodiment 1, considering that the color of light is generated by stimulating the visual cells of the human eyes by light rays with different wavelengths, one light tends to contain components with multiple wavelengths, and different wavelength components may show the same color light, and when light propagates in different media, the light propagation paths with different wavelengths are different, and the chromatic dispersion phenomenon shown in fig. 4 is formed, so that a detailed light source near-field distribution model needs to be built to describe the distribution situation of light with different wavelengths at various points in space, and then a color mixing model can be built on this basis.
Therefore, the near-field distribution of the light source is calculated through the light propagation model, the light source is used as the intensity input of each color light, and the color mixing model of the light source in space is obtained according to the color mixing principle, so that the defect of the color model in the conventional RGB-LED simulation is overcome.
The process of calculating the near-field light measurement model includes that the light measurement method is divided into radiation measurement and light measurement, the radiation measurement describes the radiation energy of light in unit area, and the intensity of light perceived by human eyes is described by the light measurement, since the near-field distribution model is under the radiation measurement, we convert the radiation flux into the light flux by the following formula:
Φ v (λ)＝V(λ)Φ e (λ)＝K m φ(λ)Φ e (λ)
wherein V (λ) =k m Phi (lambda) is the CIE recommended average human eye spectral luminous efficacy, phi (lambda) is the normalized human eye spectral luminous efficacy, called the visual function, which corresponds to a luminous flux phi of 555nm wavelength for photopic vision e (555) The radiant flux phi which can generate the same luminous stimulus to the average human eye with a certain wavelength lambda e The ratio of (lambda) is shown in figure 10.
The radiant flux is carried into the above calculation to obtain luminous flux, thus obtaining a near-field photometric model of light, and the light exitance corresponding to the two-dimensional coordinates can be usedAnd (3) representing.
After the near-field photometric model is obtained, how to solve the color distribution in the space by the near-field photometric model is as follows,
the calculation results in a near-field photometric model of light, i.e., the light emittance M at each position v (u, v). Each planar element can be regarded as an ideal lambertian body, so its brightness L v Not changing with the observation angle, and has:
as shown in FIG. 11, dA is a surface element of the light emitting surface at a point p in space, and the normal direction n of dA 1 The included angle with the propagation direction is beta, the p point takes a plane parallel to the RGB-LED light-emitting surface as a virtual light-measuring surface, and the normal direction n of the virtual light-measuring surface 2 When the included angle between the p point and the propagation direction is alpha and the distance between the p point and the dA is l, the p point emits illumination obtained by irradiation of one point dA on a monochromatic light source, and the illumination obtained by irradiation of the one point dA on the monochromatic light source is:
wherein I is β The luminous intensity of the surface element dA in the beta direction is equal to the luminous brightness L in the beta direction β The following relationship exists:
I β ＝L β dAcosβ
and due to its brightness L v Not changing with the observation angle, so there are:
wherein, the liquid crystal display device comprises a liquid crystal display device,the p-point corresponds to the solid angle of dA.
The illuminance of p point illuminated by the whole monochromatic light source is:
wherein M is v The near-field light measurement model of the light source obtained by the above process is obtained by using the color coordinates (x, y) of each monochromatic light source, and the illuminance E of a point p in space p That is, the color distribution in space of each monochromatic light is represented by the values of three variables (x (u, v, w), y (u, v, w), E (u, v, w)) in three-dimensional space coordinates.
Then, the process of solving the three-light source near-field distribution model is that for any point p (u, v, w) in the space, the color distribution of red, green and blue monochromatic light is (x) r ,y r ,E r ),(x g ,y g ,E g ),(x b ,y b ,E b ) The tristimulus values of the respective colors corresponding to p points can be calculated by the following equation:
Y XYZ ＝E
Z XYZ ＝(1-x-y)/y*Y XYZ
the tristimulus values of the combined colors at point P are added as the tristimulus values of the respective colors:
X mix ＝X r +X g +X b
Y mix ＝Y r +Y g +Y b
Z mix ＝Z r +Z g +Z b
and then the color coordinates of the mixed colors are obtained by the following formula:
illuminance E at the point mix ＝Y mix The resulting (x mix ,y mix ,E mix ) The real color corresponding to one point in the space is obtained, and the space color mixing model of the RGB-LED is obtained.
Referring to fig. 2, as a preferred embodiment of the present invention, in particular, the spectral energy distribution of each color light in the target RGB-LED is obtained by measuring a sample in an optical measuring environment or calculated by theoretical parameters of the RGB-LED.
As a preferred embodiment of the present invention, specifically, coordinates of monochromatic light corresponding to the chromaticity space are obtained by the following means;
and integrating the stimulus of each wavelength component to human eyes in the spectral energy distribution of each color of light to obtain the equivalent color and light color coordinates of the monochromatic light, namely obtaining the coordinates corresponding to the monochromatic light in the chromaticity space.
Specifically, referring to fig. 8, chromaticity space: that is, a space having one-to-one correspondence between color and space coordinates, such as the CIE1931XYZ color space, and taking the CIE1931XYZ color space as an example, the coordinates of monochromatic light with a known spectral energy distribution in the CIE1931XYZ color space can be calculated by the following steps:
solving CIE tristimulus values of the color to be measured:
where k is a constant (normalization coefficient), phi (lambda) is the spectral energy emitted by the light source into the human eye to produce a color sensation, i.e. the measured spectral energy distribution of monochromatic light,a spectrum tristimulus value graph of the CIE1931XYZ system, as shown in fig. 7,
the obtained X, Y and Z are tristimulus values of the color light to be detected in the CIE1931XYZ system.
And (3) calculating chromaticity coordinates of the color light to be measured under the CIE1931x and y coordinate system according to the tristimulus values:
Y＝Y
the (x, Y) obtained is the chromaticity coordinate of the color light to be measured in the CIE1931XYZ color space, and Y is the value representing the color brightness.
Referring to fig. 3, as a preferred embodiment of the present invention, specifically, the near-field light source distribution model is calculated by geometric information of each color light in a given space and medium distribution.
Specifically, referring to fig. 9, the light source near field distribution model regards a light source as a complex surface light source. The morphology of the light source is represented by a plane, and all light rays emerge from the surface of the light source. The near field model is closer to the actual light out of the LED light source. The light source near field model can be measured by a near field distribution photometer, the measurement result reflects the radiance of each position of the light source light emitting surface, and the radiance corresponding to the two-dimensional coordinates can be used And (3) representing.
The invention also provides an RGB-LED space color mixing model building device based on the visual characteristics of human eyes, which comprises the following steps:
the spectrum energy distribution acquisition module is used for acquiring spectrum energy distribution of each color of light in the target RGB-LED;
the chromaticity space coordinate solving module is used for solving the corresponding coordinates of the monochromatic light in the chromaticity space according to the spectral energy distribution;
the near-field light source distribution model building module is used for building a near-field light source distribution model of the tri-chromatic light;
the near-field light measurement model building module is used for converting the near-field light source distribution model of the three-color light based on the human eye visual characteristic curve to build a near-field light measurement model of the color light;
the space color mixing model building module is used for obtaining the light measurement of each color light based on the near-field light measurement model, solving the color distribution of each color light in the actual three-dimensional space based on the light measurement, and building the space color mixing model of the RGB-LED according to the color mixing principle.
As a preferred embodiment of the present invention, in particular,
the spectral energy distribution of each color light in the target RGB-LED in the spectral energy distribution acquisition module is obtained by measuring a sample in an optical measurement environment or calculating theoretical parameters of the RGB-LED.
As a preferred embodiment of the present invention, specifically, coordinates corresponding to monochromatic light in a chromaticity space in the chromaticity space coordinate solving module are obtained by the following means;
and integrating the stimulus of each wavelength component to human eyes in the spectral energy distribution of each color of light to obtain the equivalent color and light color coordinates of the monochromatic light, namely obtaining the coordinates corresponding to the monochromatic light in the chromaticity space.
As a preferred embodiment of the present invention, specifically, the near-field light source distribution model established by the near-field light source distribution model establishing module calculates geometric information and medium distribution conditions of each color light in a given space.
The invention also provides a computer readable storage medium storing a computer program which when executed by a processor realizes the steps of the RGB-LED space color mixing model building method based on human eye visual characteristics.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution in this embodiment.
In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module. The integrated modules may be implemented in hardware or in software functional modules.
The integrated modules, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on this understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth.
While the present invention has been described in considerable detail and with particularity with respect to several described embodiments, it is not intended to be limited to any such detail or embodiments or any particular embodiment, but is to be construed as providing broad interpretation of such claims by reference to the appended claims in view of the prior art so as to effectively encompass the intended scope of the invention. Furthermore, the foregoing description of the invention has been presented in its embodiments contemplated by the inventors for the purpose of providing a useful description, and for the purposes of providing a non-essential modification of the invention that may not be presently contemplated, may represent an equivalent modification of the invention.
The present invention is not limited to the above embodiments, but is merely preferred embodiments of the present invention, and the present invention should be construed as being limited to the above embodiments as long as the technical effects of the present invention are achieved by the same means. Various modifications and variations are possible in the technical solution and/or in the embodiments within the scope of the invention.
Claims (9)
1. The method for establishing the RGB-LED space color mixing model based on the visual characteristics of human eyes is characterized by comprising the following steps of:
acquiring spectral energy distribution of each color of light in the target RGB-LED;
according to the spectral energy distribution, solving corresponding coordinates of the monochromatic light in a chromaticity space;
establishing a near-field light source distribution model of the tri-chromatic light;
converting the near-field light source distribution model of the three-color light based on a human eye visual characteristic curve to establish a near-field luminosity quantity model of the color light;
and solving the light measurement of each color light based on the near-field light measurement model, solving the color distribution of each color light in an actual three-dimensional space based on the light measurement, and establishing a space color mixing model of the RGB-LED based on the color distribution of each color light in the actual three-dimensional space and the color mixing principle.
2. The method for building the RGB-LED spatial color mixing model based on the visual characteristics of the human eye according to claim 1, wherein the spectral energy distribution of each color of light in the target RGB-LED is obtained by measuring a sample in an optical measuring environment or by calculating theoretical parameters of the RGB-LED.
3. The method for establishing the RGB-LED space color mixing model based on the visual characteristics of human eyes according to claim 1, wherein the specific coordinates of monochromatic light corresponding to the color space are obtained by the following modes;
and integrating the stimulus of each wavelength component to human eyes in the spectral energy distribution of each color of light to obtain the equivalent color and light color coordinates of the monochromatic light, namely obtaining the coordinates corresponding to the monochromatic light in the chromaticity space.
4. The method for building the RGB-LED spatial color mixing model based on the human eye visual characteristics according to claim 1, wherein the near-field light source distribution model is specifically calculated by geometric information and medium distribution conditions of each color light in a given space.
5. An RGB-LED space color mixing model building device based on human eye visual characteristics is characterized by comprising the following steps:
the spectrum energy distribution acquisition module is used for acquiring spectrum energy distribution of each color of light in the target RGB-LED;
the chromaticity space coordinate solving module is used for solving the corresponding coordinates of the monochromatic light in the chromaticity space according to the spectral energy distribution;
the near-field light source distribution model building module is used for building a near-field light source distribution model of the tri-chromatic light;
the near-field light measurement model building module is used for converting the near-field light source distribution model of the three-color light based on the human eye visual characteristic curve to build a near-field light measurement model of the color light;
the space color mixing model building module is used for obtaining the light measurement of each color light based on the near-field light measurement model, solving the color distribution of each color light in the actual three-dimensional space based on the light measurement, and building the space color mixing model of the RGB-LED according to the color mixing principle.
6. The device for building the RGB-LED spatial color mixing model based on the human eye visual characteristics according to claim 5, wherein the device comprises, in particular,
the spectral energy distribution of each color light in the target RGB-LED in the spectral energy distribution acquisition module is obtained by measuring a sample in an optical measurement environment or calculating theoretical parameters of the RGB-LED.
7. The device for establishing the RGB-LED space color mixture model based on the visual characteristics of human eyes according to claim 5, wherein the coordinates of the monochromatic light in the chromaticity space coordinate solving module corresponding to the color space are obtained by the following method;
and integrating the stimulus of each wavelength component to human eyes in the spectral energy distribution of each color of light to obtain the equivalent color and light color coordinates of the monochromatic light, namely obtaining the coordinates corresponding to the monochromatic light in the chromaticity space.
8. The device for building a spatial color mixture model of RGB-LED based on visual characteristics of human eyes according to claim 5, wherein specifically, the near-field light source distribution model built by the near-field light source distribution model building module is calculated by geometric information and medium distribution conditions of each color of light in a given space.
9. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310463669.3A CN116524103A (en) | 2023-04-26 | 2023-04-26 | Method and device for establishing RGB-LED space color mixing model based on human eye visual characteristics |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310463669.3A CN116524103A (en) | 2023-04-26 | 2023-04-26 | Method and device for establishing RGB-LED space color mixing model based on human eye visual characteristics |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116524103A true CN116524103A (en) | 2023-08-01 |
Family
ID=87400549
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310463669.3A Pending CN116524103A (en) | 2023-04-26 | 2023-04-26 | Method and device for establishing RGB-LED space color mixing model based on human eye visual characteristics |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116524103A (en) |
-
2023
- 2023-04-26 CN CN202310463669.3A patent/CN116524103A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8497871B2 (en) | Color generation using multiple illuminant types | |
| Smet et al. | Colour appearance rating of familiar real objects | |
| Viénot et al. | LEDs as a tool to enhance faded colours of museums artefacts | |
| David et al. | LED-based white light | |
| CN103279948B (en) | A kind of data processing method of high-spectrum remote sensing data True color synthesis | |
| US10364964B2 (en) | Lighting apparatus | |
| CN106104375A (en) | Tool optimizes the flashing light light of ripple spectral power distributions | |
| US10378709B2 (en) | Illumination system for reproducing the color temperature range of solar light for illuminating exhibits | |
| Yang et al. | The yellow ring measurement for the phosphor-converted white LED | |
| Tanaka et al. | Color control of a lighting system using RGBW LEDs | |
| Thorseth | Characterization, modeling, and optimization of light-emitting diode systems | |
| CN116524103A (en) | Method and device for establishing RGB-LED space color mixing model based on human eye visual characteristics | |
| RU91761U1 (en) | REFERENCE DEVICE FOR TRANSFER OF THE SIZE OF THE UNITS OF COORDINATES OF COLOR OF SELF-LIGHTING OBJECTS | |
| ES2939861T3 (en) | Procedure for generating light spectra and corresponding device | |
| JP2015133220A (en) | Control device and lighting system | |
| RavindraKumar et al. | A Tunable LED Daylight Luminaire for Textile and Printing Light Booth Application with Optimum LEDs | |
| US10085320B1 (en) | Pre-calibrated light box | |
| Gorbunova et al. | Automated hardware and software complex for extended light sources verification | |
| Thompson | Psychophysical evaluations of modulated color rendering for energy performance of LED-based architectural lighting | |
| Huguet Ferran | Algorithms for light applications: from theoretical simulations to prototyping | |
| Prechaveerakul et al. | Optical and electrical performance comparisons between high power LED and HMI studio lighting including the engineering economics analysis | |
| Miller et al. | Scenes and Lighting | |
| Tazehmahaleh et al. | A Multi Channel LED Luminaire with Bluethooth Control for Optimal Retail Lighting | |
| Ashdown | The influence of color interreflections on lighting simulations | |
| Li et al. | Quality of LED based daylight simulators |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |