Parametric spectral active light source colorimetric mapping method, product and medium

Abstract

The application discloses a parameterized spectrum active light-emitting light source chrominance mapping method, product and medium, relates to the LED display control technical field, and solves the problems that the prior art lacks a prediction method directly connecting the spectrum shape parameters of an active light source with chrominance coordinates, the design stage is inefficient, the existing model has poor applicability, and the internal law of spectrum-chrominance is not well understood. A spectrum vector is acquired; the acquired spectrum vector is normalized to generate a normalized spectrum of the active light-emitting light source; a standard color matching function is acquired; based on the generated normalized spectrum of the active light-emitting light source and the acquired standard color matching function, three stimulus values corresponding to the active light-emitting light source are calculated; and based on the calculated three stimulus values corresponding to the active light-emitting light source, chrominance coordinates of the active light-emitting light source and relative brightness values related to the light efficiency potential of a parameterized spectrum shape function of the active light-emitting light source are determined respectively.

Description

Technical Field

[0001] The present invention relates to the field of LED display control technology, and in particular to a method, product and medium for chromaticity mapping of an active luminous light source with a parameterized spectrum. Background Art

[0002] The rapid development of modern optoelectronic technologies, particularly solid-state lighting and display technologies, has placed unprecedented demands on light quality, particularly the precise control, prediction, and reproduction of color. Active light-emitting devices such as LEDs (light-emitting diodes), OLEDs (organic light-emitting diodes), QD (quantum dot) materials, and laser light sources, with their advantages of high efficiency, energy saving, long life, small size, and tunability, are gradually replacing traditional light sources and playing a central role in numerous fields. However, the SPDs (spectral power distributions) of these new light sources often exhibit complex and diverse morphologies, such as narrowband emission peaks, broadband fluorescence conversion, and multi-peak combinations. The color perception presented to human observers is closely related to the specific shape of the SPD. Therefore, accurately and efficiently bridging the gap between the physical properties of light sources (spectral characteristics) and their visually perceived properties (colorimetric quantities) has become a core technical challenge in this field.

[0003] The existing technology lacks an effective means to accurately and efficiently connect the controllable spectral shape parameters of active light sources and their colorimetric performance, that is, it lacks a key shape parameter that can input the light source spectrum, such as (peak wavelength), (full width at half maximum) and peak shape factor, etc., and directly calculate and output its corresponding CIExy (chromaticity coordinates) and relative brightness A systematic approach to analyzing the value of the active light source cannot quickly and effectively explore design solutions, predict performance, and perform optimization iterations by adjusting design parameters without physical samples. Existing models either oversimplify spectral details or are designed for completely different physical scenarios. They cannot accurately capture the characteristics of the active emission spectrum and its relationship with color perception. It is difficult to deeply understand the inherent laws of the changes in the spectral shape of a specific type of active light source and its color gamut coverage, brightness performance, and the complex comprehensive relationship between the two through systematic parameter scanning and visualization, and there is insufficient understanding of the inherent laws of spectrum-chromaticity.

[0004] In summary, the existing technology lacks a prediction method that directly links the spectral shape parameters and chromaticity coordinates of active light sources, the design stage is inefficient, the existing models have poor applicability, and there is insufficient understanding of the inherent laws of spectrum and chromaticity. Summary of the Invention

[0005] The present invention solves the problems in the prior art of lacking a prediction method for directly linking the spectral shape parameters of active light sources with chromaticity coordinates, low efficiency in the design stage, poor applicability of existing models, and insufficient understanding of the inherent laws of spectrum and chromaticity.

[0006] The method for chromaticity mapping of an active light source using a parameterized spectrum of the present invention comprises the following steps:

[0007] Step S1, constructing a parameterized spectral shape function of an active luminescent light source;

[0008] Step S2, obtaining a spectrum vector based on the parameterized spectrum shape function of the active light source constructed in step S1;

[0009] Step S3, normalizing the spectrum vector obtained in step S2 to generate a normalized spectrum of the active light source;

[0010] Step S4, obtaining a standard color matching function;

[0011] Step S5, calculating tristimulus values ​​corresponding to the active light source based on the normalized spectrum of the active light source generated in step S3 and the standard color matching function obtained in step S4;

[0012] Step S6, based on the tristimulus values ​​corresponding to the active light source calculated in step S5, respectively determine the chromaticity coordinates of the active light source and the relative brightness related to the light efficiency potential of the parameterized spectral shape function of the active light source value.

[0013] Furthermore, in one embodiment of the present invention, in step S1, the parameterized spectral shape function of the active light source is not limited to a Gaussian function, a Lorentz function, an approximate square wave function with a controllable transition band, a complement spectral function, a multi-peak combination, a spectral function based on a physical model, and a combination of a model based on data analysis.

[0014] Furthermore, in one embodiment of the present invention, in step S2, the parameterized spectral shape function of the active light source constructed in step S1 is used to obtain the spectral vector, specifically:

[0015] After assigning values ​​to the adjustable parameters in the parameterized spectral shape function of the active luminescent light source, the spectral intensity values ​​at discrete wavelength points are calculated based on the parameterized spectral shape function of the active luminescent light source to obtain a spectral vector.

[0016] Furthermore, in one embodiment of the present invention, in step S3, the spectrum vector obtained in step S2 is normalized to generate a normalized spectrum of the active light source, specifically:

[0017] Normalize the spectral vector obtained in step S2 and calculate ,like ,but ,like ,but ;

[0018] in, is the normalization factor, is an adjustable parameter Assign a set of specific values, is the peak shape function, is the step length, is a small positive number, is the normalized spectrum of the active luminescent light source, is the amplitude factor, Discrete wavelength points The spectral intensity value on Discrete wavelength points The spectral intensity value on Discrete wavelength points The spectral intensity value on Is a positive integer.

[0019] Furthermore, in one embodiment of the present invention, in step S5, the tristimulus values ​​corresponding to the active light source are calculated as follows:

[0020] ;

[0021] ;

[0022] ;

[0023] in, 、 and is the tristimulus value corresponding to the active light source, is an adjustable parameter Assign a set of specific values, is a positive integer, is the normalized spectrum of the active luminescent light source, For the discrete wavelength points, is the step length, Tristimulus values , Tristimulus values , Tristimulus values , is the color matching function , is the color matching function , for color matching function .

[0024] Further, in one embodiment of the present application, in the step S6, the chromaticity coordinates of the active light emitting source are determined, specifically:

[0025] Let , if , then:

[0026] ;

[0027] ;

[0028] wherein, , and are the tristimulus values corresponding to the active light emitting source, is an adjustable parameter assigned a specific numerical value, is a positive integer, is the tristimulus value , is the tristimulus value , is the tristimulus value , is a small positive threshold value, and are the chromaticity coordinates of the active light emitting source, is the chromaticity coordinate , is the chromaticity coordinate .

[0029] Further, in one embodiment of the present application, in the step S6, the relative luminance value is proportional to the lumen efficiency of the active light emitting source under the normalized spectrum.

[0030] The color gamut mapping method of the present application is implemented by using the active light emitting source chromaticity mapping method of the parameterized spectrum of any of the above methods, specifically:

[0031] The adjustable parameter in the parameterized spectrum shape function of the active light emitting source is defined, the scanning range and step size are defined respectively, the parameter grid is formed based on the scanning range and step size, the data points corresponding to each parameter point in the parameter grid are calculated and plotted in the three-dimensional coordinates, and the adjacent parameter points in the three-dimensional coordinates are connected to form a color gamut surface.

[0032] The present invention provides a non-transitory computer-readable storage medium having computer-executable instructions stored thereon. When the instructions are executed by a processor, the processor executes the chromaticity mapping method of the active luminous light source with a parameterized spectrum as described in any of the above methods.

[0033] A computer program product according to the present invention includes a computer program or instructions, which, when executed by a processor, implements the chromaticity mapping method of the parameterized spectrum of the active luminous light source described in any of the above methods.

[0034] This invention solves the problems of the existing technology, such as the lack of a prediction method that directly links the spectral shape parameters of active light sources with chromaticity coordinates, low efficiency in the design phase, poor applicability of existing models, and insufficient understanding of the inherent laws of spectrum and chromaticity. Specific beneficial effects include:

[0035] 1. The parametric spectrum active light source chromaticity mapping method of the present invention provides a systematic and calculable method to directly convert the intrinsic, controllable and adjustable parameters of the active light source into It is precisely related to its appearance in the external, perceptual CIExyY color space. The adjustable parameters are established A direct, quantitative bridge to chromaticity, thus solving the problem of the existing technology lacking a prediction method that directly links the spectral shape parameters of active light sources with chromaticity coordinates;

[0036] 2. The parametric spectrum active light source chromaticity mapping method of the present invention can be used to map the chromaticity of the active light source without the need to manufacture physical samples, simply by adjusting the adjustable parameters. (These adjustable parameters can be correlated with the physical design parameters of actual devices) to quickly and accurately predict the chromaticity coordinates and relative brightness of active light sources. This greatly accelerates the iterative development process of new light sources (such as specific color point LEDs, high color gamut display backlights, and customized spectrum lighting), reduces trial and error costs, improves design efficiency and success rates, and enables predictive design and efficient optimization. Parameter sweeps can be performed to explore the design space, or optimization calculations can be performed to find the optimal parameter combination that meets specific chromaticity / brightness targets.

[0037] 3. The parametric spectrum active light source chromaticity mapping method of the present invention is to systematically change the adjustable parameters The visualization reveals the inherent laws of spectrum and chromaticity and the boundaries of the color gamut. It can generate a complete color gamut diagram in xyY space for a specific type of parameterized light source. This not only shows the color range that this type of light source can achieve, but more importantly, it reveals how spectral shape parameters (such as peak wavelength and bandwidth) nonlinearly and coupledly affect chromaticity (hue, saturation) and relative brightness, helping to deepen our understanding of the inherent mechanisms of color expression in spectral engineering.

[0038] 4. The color gamut mapping method described in the present invention can be visualized using point clouds, grid lines (connecting adjacent points in parameter space), or fitted surfaces. It intuitively shows the parameterized spectral shape function of the active light source. The color gamut range and internal structure of a class of active luminescent light sources defined by the paper reveal the parameterized spectral shape function of the active luminescent light source. How to affect chroma simultaneously and relative brightness Values ​​to better understand the color characteristics of this type of light source;

[0039] The parameterized spectrum of the active light source chromaticity mapping method of the present invention is aimed at the emission spectrum of the active light source. established, accurately applicable to active luminous sources, its physical basis and the interpretation of the results (especially the relative brightness The relative brightness meaning of the values ​​is completely consistent with the characteristics of active luminescence, which is fundamentally different from the model based on passive object reflection / transmission, avoiding misuse of concepts and misinterpretation of results. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0041] Figure 1 It is the Bandpass-likewithTransitions diagram described in the first embodiment;

[0042] Figure 2 This is an area normalized graph of the spectrum vector described in the first embodiment;

[0043] Figure 3 This is a peak normalization graph of the spectrum vector described in the first embodiment;

[0044] Figure 4 This is a visualized three-dimensional spectrum trajectory diagram generated by another spectrum shape described in the second embodiment;

[0045] Figure 5 This is the standard parameterized coordinate system model diagram described in the second implementation mode. DETAILED DESCRIPTION

[0046] The following will clearly and completely describe various embodiments of the present invention in conjunction with the accompanying drawings. The embodiments described with reference to the accompanying drawings are exemplary and intended to be used to explain the present invention, but should not be understood as limiting the present invention.

[0047] Embodiment 1: The method for chromaticity mapping of an active light source using a parameterized spectrum described in this embodiment includes the following steps:

[0048] Step S1, constructing a parameterized spectral shape function of an active luminescent light source;

[0049] Step S2, obtaining a spectrum vector based on the parameterized spectrum shape function of the active light source constructed in step S1;

[0050] Step S3, normalizing the spectrum vector obtained in step S2 to generate a normalized spectrum of the active light source;

[0051] Step S4, obtaining a standard color matching function;

[0052] Step S5, calculating tristimulus values ​​corresponding to the active light source based on the normalized spectrum of the active light source generated in step S3 and the standard color matching function obtained in step S4;

[0053] Step S6, based on the tristimulus values ​​corresponding to the active light source calculated in step S5, respectively determine the chromaticity coordinates of the active light source and the relative brightness related to the light efficiency potential of the parameterized spectral shape function of the active light source value.

[0054] In this embodiment, in step S1, the parameterized spectral shape function of the active light source is not limited to a Gaussian function, a Lorentz function, an approximate square wave function with a controllable transition band, a complement spectral function, a multi-peak combination, a spectral function based on a physical model, and a combination of a model based on data analysis.

[0055] In this embodiment, in step S2, the parameterized spectral shape function of the active light source constructed in step S1 is used to obtain the spectral vector, specifically:

[0056] After assigning values ​​to the adjustable parameters in the parameterized spectral shape function of the active luminescent light source, the spectral intensity values ​​at discrete wavelength points are calculated based on the parameterized spectral shape function of the active luminescent light source to obtain a spectral vector.

[0057] In this embodiment, in step S3, the spectrum vector obtained in step S2 is normalized to generate a normalized spectrum of the active light source, specifically:

[0058] Normalize the spectral vector obtained in step S2 and calculate ,like ,but ,like ,but ;

[0059] in, is the normalization factor, is an adjustable parameter Assign a set of specific values, is the peak shape function, is the step length, is a small positive number, is the normalized spectrum of the active luminescent light source, is the amplitude factor, Discrete wavelength points The spectral intensity value on Discrete wavelength points The spectral intensity value on Discrete wavelength points The spectral intensity value on Is a positive integer.

[0060] In this embodiment, in step S5, the tristimulus values ​​corresponding to the active light source are calculated as follows:

[0061] ;

[0062] ;

[0063] ;

[0064] in, 、 and is the tristimulus value corresponding to the active light source, is an adjustable parameter Assign a set of specific values, is a positive integer, is the normalized spectrum of the active luminescent light source, For the discrete wavelength points, is the step length, Tristimulus values , Tristimulus values , Tristimulus values , is the color matching function , is the color matching function , is the color matching function .

[0065] In this embodiment, in step S6, the chromaticity coordinates of the active light source are determined as follows:

[0066] make ,like ,but:

[0067] ;

[0068] ;

[0069] in, 、 and is the tristimulus value corresponding to the active light source, is an adjustable parameter Assign a set of specific values, is a positive integer, Tristimulus values , Tristimulus values , Tristimulus values , is a small positive threshold, and are the chromaticity coordinates of the active light source, is the chromaticity coordinate , is the chromaticity coordinate .

[0070] In this embodiment, in step S6, the relative brightness The value is proportional to the lumen efficiency of the active light source under the normalized spectrum.

[0071] The existing technology lacks a prediction method that directly links the spectral shape parameters and chromaticity coordinates of active light sources, the design stage is inefficient, the existing models have poor applicability, and there is insufficient understanding of the inherent laws of spectrum and chromaticity.

[0072] In order to solve the above technical problems, this embodiment proposes a chromaticity mapping method for an active light source with a parameterized spectrum, comprising the following steps:

[0073] Step S1, select or construct a parameterized spectral shape function of an active luminous light source ,in, is the spectral intensity, is the wavelength, is an adjustable parameter, which is used to describe the target type active luminous light source in the visible spectrum wavelength The core of this function is that it consists of a set of adjustable parameters. controlled, among which are positive integers not equal to 1 and 2. These adjustable parameters It should be able to capture the key spectral features that affect the color and brightness of active luminescent light sources, and can have clear physical meanings such as peak wavelength, bandwidth or fitting parameters.

[0074] The parameterized spectral shape function of the active luminescent light source Can be selected from but not limited to the following types or combinations thereof:

[0075] GaussianFunction (Gaussian function): ,in, is the amplitude factor, which can be handled in normalization, is an exponential function. Adjustable parameters ,in, is the peak wavelength, is the same as the full width at half maximum ( ) is suitable for simulating the line shape of many monochromatic LEDs and lasers.

[0076] LorentzianFunction (Lorentzian function): Adjustable parameters ,in, HWHM (half the full width at half maximum). The peak shape is sharper and the tail is longer than that of GaussianFunction.

[0077] Bandpass-likewithTransitions (approximate square wave function with controllable transition band): such as Figure 1 As shown, Adjustable parameters ,in, is the flat top width, Transition band sharpness. Applicable to analog bandpass filter outputs or specific broadband emissions.

[0078] ComplementarySpectrum (complementary spectrum function): The adjustable parameters are the same as Bandpass-likewithTransitions. It simulates the remaining spectrum after removing a specific band from the broad spectrum.

[0079] Multi-peakCombination: ,in, is a peak shape function, specifically GaussianFunction, LorentzianFunction or other peak shape functions, For the The peak wavelength of each peak, For the The standard deviation of the peaks, For the The amplitude factor of the peak. Adjustable parameter Contains parameters for all peaks. Suitable for simulating multi-chip LEDs, phosphor conversion spectra, etc.

[0080] Spectral functions based on physical models: For example, the LED emission spectrum model derived from semiconductor band theory has adjustable parameters. It may directly correspond to physical quantities such as material band gap and carrier temperature.

[0081] Models based on data analysis: For example, low-dimensional parameterization learned from a large amount of measured spectral data using PCA (principal component analysis), NMF (non-negative matrix factorization) or neural networks ,in, is the latent variable or weight coefficient of the model.

[0082] Therefore, the parameterized spectral shape function of an actively luminescent light source is Flexible selection or construction is possible as needed to accommodate various types of active light-emitting devices (LEDs, OLEDs (organic laser displays), lasers, and quantum dots (QDs), among others) and their complex spectral configurations (single-peak, multi-peak, broadband, narrowband, etc.). New spectral models or more sophisticated physical models can be easily integrated.

[0083] Step S2, according to application requirements, is an adjustable parameter Assign a set of specific values Utilize the parameterized spectral shape function of the active luminescent light source constructed in step S1 , calculated at the preset discrete wavelength points ( is a positive integer, , A positive integer not equal to 1, covering the visible light range, such as 380nm to 780nm, step size ) on the spectral intensity value , get the spectrum vector .

[0084] Step S3, obtaining the spectrum vector in step S2 Normalization is performed to eliminate the influence of the absolute total power or total luminous flux of the active light source, so that subsequent calculations focus on the contribution of the spectrum shape itself to chromaticity and relative brightness. Normalization can be done in many ways, and a preferred way is area normalization: calculate the spectrum in the visible light range. The integral or discrete sum within is used as a normalization factor ,like ,but ,like ,but ,in, is the minimum value, is the maximum value, is the integral wavelength variable, is a small positive number, is the normalized spectrum of the active luminescent light source, Discrete wavelength points The spectral intensity value on Discrete wavelength points The spectral intensity value on is a positive integer. This normalization method makes the total "energy" of all spectra of different shapes equal, which is convenient for comparing the chromaticity characteristics and relative luminous efficacy of different shapes. Other possible normalization methods include peak normalization, which normalizes the maximum value of the spectrum to 1, but it has little effect on relative brightness. Special attention should be paid to the interpretation of the impact of the value.

[0085] The spectrum vector obtained in step S2 is For normalization, in addition to area normalization, you can also select the following according to specific needs:

[0086] Peak normalization: At this time, the relative brightness The value will depend strongly on Is it close to the 555nm area where the human eye is most sensitive? That is, the relative brightness of the energy concentrated near 555nm is higher than that of the dispersed one. The values ​​are high, and the relative width of the spectrum.

[0087] like Figure 2 and Figure 3 As shown, in the three-dimensional CIExyY space, the spectrum vector is area normalized and peak normalized, and the and When the calculated series of chromaticity points Two different three-dimensional trajectories are formed, where the black solid line is the square wave trajectory and the blue solid line is the complement trajectory.

[0088] Normalized to a specific physical quantity: If the total radiant power of an active light source is known or total luminous flux With adjustable parameters relationship (e.g., efficiency obtained from device models or measurements) ), a more physically meaningful normalization can be performed, for example, The integral of is equal to the unit radiant power, or the calculated relative brightness The value directly corresponds to the luminous efficacy (lm / W) per unit input power. However, this requires additional information beyond the spectral shape model. The core of this implementation lies in the mapping of shape to chromaticity, preferably using normalization of the shape itself (such as area normalization).

[0089] Step S4, load the standard observer color matching function data published by CIE (International Commission on Illumination), that is, or ,in, CIE1931 2° standard observer color matching function , CIE1931 2° standard observer color matching function , CIE1931 2° standard observer color matching function , CIE1964 10° standard observer color matching function , CIE1964 10° standard observer color matching function , CIE1964 10° standard observer color matching function 。 Ensure wavelength sampling points of CMFs (color matching functions) The discrete wavelength points used to generate the spectrum in step S2 If they are not consistent, CMFs need to be accurately interpolated (such as linear interpolation or spline interpolation).

[0090] Step S5, using the normalized spectrum obtained in step S3 The tristimulus values ​​corresponding to the active light source are calculated by numerical integration (discrete summation) using the CMFs obtained in step S4, specifically:

[0091] ;

[0092] ;

[0093] ;

[0094] in, 、 and is the tristimulus value corresponding to the active light source, Tristimulus values , Tristimulus values , Tristimulus values , is the color matching function , is the color matching function , is the color matching function In this calculation, since the input spectrum It is obtained by a specific method such as area normalization. The value has a special meaning: it directly reflects the relative efficiency of an active luminous source with a specific spectral shape in stimulating the human eye's photopic system to produce brightness sensation under the condition that the unit "total energy" is defined in a normalized way. Therefore, It can be considered as a relative brightness factor of the spectral shape or a shape-related light efficiency factor.

[0095] Step S6: tristimulus values ​​corresponding to the active light source calculated in step S5 、 and , calculate CIExy, specifically:

[0096] make ,like ,but:

[0097] ;

[0098] ;

[0099] in, is a small positive threshold to prevent division by zero errors, and is the chromaticity coordinate of the active luminous light source, is the chromaticity coordinate , is the chromaticity coordinate .

[0100] Otherwise, CIExy is undefined or can be assigned a special value (for example, corresponding to the failure of the active light source or no visible light output). Finally, for each set of input parameters , this implementation outputs a complete set of chromaticity characteristic descriptions: .

[0101] It can serve as a reliable input for more advanced color science applications, for example: input into CAMs (color appearance models) to predict actual perceived effects; used in computer graphics to build more physically accurate light source models to improve rendering realism; used in color management systems to characterize devices and provide accurate input for downstream applications.

[0102] Therefore, this embodiment can establish a direct, quantitative, and calculable mapping relationship between the key shape parameters of the spectrum of the active light source and its position in CIExyY, thereby realizing rapid prediction, systematic analysis, and optimized design of the chromaticity performance of the active light source.

[0103] Implementation 2: A color gamut mapping method described in this implementation is implemented using the parameterized spectrum active light source chromaticity mapping method described in Implementation 1, specifically:

[0104] The adjustable parameters in the parameterized spectral shape function of the active luminous light source are defined, and the scanning range and step size are defined respectively. A parameter grid is formed based on the scanning range and step size. The corresponding data point is calculated based on each parameter point in the parameter grid and plotted in three-dimensional coordinates. The adjacent parameter points in the three-dimensional coordinates are connected to form a color gamut surface.

[0105] This embodiment proposes a color gamut mapping method, including the following steps:

[0106] Step S1, select or construct a parameterized spectral shape function of an active luminous light source , whose goal is to select or construct a Parameterized spectral shape functions that accurately or approximately describe active luminescent light sources .

[0107] Adjustable parameters Associated with controllable physical properties or design variables of an active light source. For example, can be related to the band gap energy of semiconductor materials, Can be correlated to quantum well size distribution or phosphor particle size distribution, relative peak intensity It can be correlated to the multi-chip current ratio or phosphor concentration, making the model practical for guiding design.

[0108] Step S2, setting adjustable parameters This can be assigned a specific value. Used to predict a specific active luminous source, or a grid point in parameter space Used for system scans.

[0109] It needs to be determined based on the possible range of the actual active light source. For example, for visible light LED, It may vary between 400nm (blue-violet) and 700nm (red). Or FWHM may range from a few nanometers (laser) to tens of nanometers (direct emission LED) or even hundreds of nanometers (phosphor converted LED).

[0110] Discretize the wavelength axis and select the appropriate wavelength range (e.g. 380nm to 780nm) and step size (e.g. 1nm or 5nm). The smaller the size, the higher the calculation accuracy, but the greater the amount of calculation. Usually 5nm is sufficient to meet most colorimetric calculation needs, and 1nm is even better.

[0111] For a given and discrete wavelength points , using step S1 to select or construct a parameterized spectral shape function of an active luminescent light source , calculate the spectral intensity value , get the spectrum vector .

[0112] Step S3, the obtained spectrum vector Normalize. Calculate ,like ,but ,like ,but This normalization ensures that the total shape area of ​​all spectra is 1.

[0113] Step S4, ensure the wavelength sampling point of the CMFs data table The discrete wavelength points used to generate the spectrum in step S2 If they are not consistent, the CMFs must be interpolated. For example, if the CMFs provide a value every 5nm, and the spectrum is calculated every 1nm, then the CMFs need to be interpolated to a grid every 1nm using linear interpolation or, better yet, spline interpolation to obtain .

[0114] Step S5, calculating the tristimulus values ​​corresponding to the active light source, specifically:

[0115] ;

[0116] ;

[0117] ;

[0118] When using area normalization Under the premise of The value directly quantifies the light source with this spectral shape, converting its total energy (area) into brightness perceived by the human eye (given by It is a dimensionless value that reflects the relative efficiency of the spectrum shape and the visual sensitivity curve of the human eye. degree of matching.

[0119] Step S6, for each input , get the final chromaticity feature vector {x,y,Y}, and output a complete set of chromaticity feature descriptions: , specifically:

[0120] make ,like ,but:

[0121] ;

[0122] .

[0123] Step S7, in the adjustable parameter Define a scan range and step size in . For example, ,set up From 380nm to 780nm ( ), From 1nm to 400nm ( ), repeat steps S2 to S6 to form a parameter grid. For each parameter point in the parameter grid , calculate the point . All calculated points Drawing in 3D In the coordinate system.

[0124] Connect adjacent points in parameter space. For example, for a fixed (i.e. Δλ), connect all Point, where , forming a The trajectory of change, such as Figure 5 As shown, the black and blue solid lines represent the boundaries of the maximum relative light intensity, and the inward extending grids represent different Chromaticity parameter, which is perpendicular to The red dotted line on the plane is the range of relative light intensity at that point. (Right now , connect all Point, where , forming a The trajectory of change, such as Figure 4 As shown, these grid lines together outline the color gamut surface composed of this type of parameterized spectrum.

[0125] For each point Draw a line projected perpendicularly from this point to The dotted line of the plane, the length of the line intuitively represents the relevant brightness The size of the value.

[0126] By observing the color gamut surface, we can analyze:

[0127] The chromaticity range that this type of active light source can cover Planar projection and relative brightness Value range.

[0128] Changes in spectral parameters How to cause the chromaticity point Movement on the plane (changing hue and saturation).

[0129] How changes in spectral parameters affect relative brightness For example, usually Relevant brightness near 555nm Higher value; Increasing the color point may move the color point toward the white point, but the relative brightness How the value changes depends on and specific normalization methods.

[0130] Is there chromaticity degeneration phenomenon, that is, different adjustable parameters Produces the same Coordinates but relative brightness The values ​​are different.

[0131] Embodiment 3: A non-transitory computer-readable storage medium described in this embodiment stores computer-executable instructions. When the instructions are executed by a processor, the processor executes the parameterized spectrum active light source chromaticity mapping method as described in embodiment 1.

[0132] Embodiment 4: A computer program product described in this embodiment includes a computer program or instructions, which, when executed by a processor, implements the chromaticity mapping method for active light source with parameterized spectrum described in embodiment 1.

[0133] The above is a detailed introduction to the parameterized spectrum active light source chromaticity mapping method, product and medium proposed in the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A chromaticity mapping method for an active luminous light source with a parameterized spectrum, characterized in that: The following steps are involved: Step S1: Constructing a parameterized spectral shape function of an active luminescent light source ,in, is the spectral intensity, is the wavelength, is an adjustable parameter, which is used to describe the target type active luminous light source in the visible spectrum wavelength The relative distribution shape of the spectral power or energy at , which is determined by a set of adjustable parameters controlled, among which are positive integers not equal to 1 and 2. These adjustable parameters It should be able to capture the key spectral features that affect the color and brightness of active light sources; Step S2, obtaining a spectrum vector based on the parameterized spectrum shape function of the active light source constructed in step S1; Step S3, normalizing the spectrum vector obtained in step S2 to generate a normalized spectrum of the active light source; Step S4, obtaining a standard color matching function; Step S5, calculating tristimulus values ​​corresponding to the active light source based on the normalized spectrum of the active light source generated in step S3 and the standard color matching function obtained in step S4; Step S6, based on the tristimulus values ​​corresponding to the active light source calculated in step S5, respectively determine the chromaticity coordinates of the active light source and the relative brightness related to the light efficiency potential of the parameterized spectral shape function of the active light source value; In step S5, the tristimulus values ​​corresponding to the active light source are calculated as follows: ； ； ； in, 、 and is the tristimulus value corresponding to the active light source, is an adjustable parameter Assign a set of specific values, is a positive integer, is the normalized spectrum of the active luminescent light source, For the discrete wavelength points, is the step length, Tristimulus values , Tristimulus values , Tristimulus values , is the color matching function , is the color matching function , is the color matching function ; In step S6, the chromaticity coordinates of the active light source are determined as follows: make ,like ,but: ； ； in, 、 and is the tristimulus value corresponding to the active light source, is an adjustable parameter Assign a set of specific values, is a positive integer, Tristimulus values , Tristimulus values , Tristimulus values , is a small positive threshold, and are the chromaticity coordinates of the active light source, is the chromaticity coordinate , is the chromaticity coordinate .

2. The method for chromaticity mapping of an active light source using a parameterized spectrum according to claim 1, wherein: In step S1, the parameterized spectral shape function of the active light source is not limited to a Gaussian function, a Lorentz function, an approximate square wave function with a controllable transition band, a complement spectral function, a multi-peak combination, a spectral function based on a physical model, and a combination of a model based on data analysis.

3. The method for chromaticity mapping of an active light source using a parameterized spectrum according to claim 1, wherein: In the step S2, the parameterized spectral shape function of the active light source constructed in step S1 is used to obtain the spectral vector, specifically: After assigning values ​​to the adjustable parameters in the parameterized spectral shape function of the active luminescent light source, the spectral intensity values ​​at discrete wavelength points are calculated based on the parameterized spectral shape function of the active luminescent light source to obtain a spectral vector.

4. The method for chromaticity mapping of an active light source using a parameterized spectrum according to claim 1, wherein: In step S3, the spectrum vector obtained in step S2 is normalized to generate a normalized spectrum of the active light source, specifically: Normalize the spectral vector obtained in step S2 and calculate ,like ,but ,like ,but ; in, is the normalization factor, is an adjustable parameter Assign a set of specific values, is the peak shape function, is the step length, is a small positive number, is the normalized spectrum of the active luminescent light source, is the amplitude factor, Discrete wavelength points The spectral intensity value on Discrete wavelength points The spectral intensity value on Discrete wavelength points The spectral intensity value on Is a positive integer.

5. The method for chromaticity mapping of an active light source using a parameterized spectrum according to claim 1, wherein: In step S6, the relative brightness The value is proportional to the lumen efficiency of the active light source under the normalized spectrum.

6. A color gamut mapping method, wherein the method is implemented by using the parameterized spectrum active light source chromaticity mapping method according to any one of claims 1 to 5, characterized in that: Specifically: The adjustable parameters in the parameterized spectral shape function of the active luminous light source are defined, and the scanning range and step size are defined respectively. A parameter grid is formed based on the scanning range and step size. The corresponding data point is calculated based on each parameter point in the parameter grid and plotted in three-dimensional coordinates. The adjacent parameter points in the three-dimensional coordinates are connected to form a color gamut surface.

7. A non-transitory computer-readable storage medium having computer-executable instructions stored thereon, wherein when the instructions are executed by a processor, The processor is enabled to execute the chromaticity mapping method of the active luminous light source with parameterized spectrum as described in any one of claims 1 to 5.

8. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed by a processor, the method for chromaticity mapping of an active luminous light source with a parameterized spectrum as claimed in any one of claims 1 to 5 is implemented.

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