Determination method and device, electronic equipment and storage medium
By acquiring and fusing the local spectral attribute information of monochromatic light and complex light, and determining the reconstruction matrix, the problem of inaccurate spectral reconstruction in the prior art is solved, and the reduction effect of actual light sources is improved.
Patent Information
- Application Number
- CN202310867967.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-07-14
- Publication Date
- 2025-01-14
AI Technical Summary
The existing spectral reconstruction methods use monochromator light sources to determine the reconstruction matrix, resulting in the inaccurate effect of the actual light source, because the monochromator light source has only one wavelength, and in actual life, the light source is complex light.
By obtaining local spectral attribute information of monochromatic light and complex light, fusion processing is performed to obtain target attribute information, and the reconstruction matrix is determined based on this information, so as to accurately fit the entire spectrum of the actual light source.
It improves the accuracy of the reduction effect of the actual light source and can more effectively fit the real light spectrum of the actual light source.
Smart Images
Figure CN119309675A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of electronic technology, and in particular to a determination method, device, electronic device and storage medium. Background Art
[0002] At present, with the widespread application of spectral technology, the spectral information technology of obtaining light sources is becoming more and more important. However, most spectral sensors can only obtain local spectral information of the light source. To know the complete spectral information of the light source, it is necessary to reconstruct the spectrum.
[0003] The existing reconstruction spectrum uses a monochromator to emit a series of monochromatic lights with a step size of 1 nanometer (nm), such as 350nm-1000nm, and records the values of each channel of the spectral sensor and the actual spectrum of the spectrometer at the same time, and then uses the least squares method to calculate the reconstruction matrix, and reconstructs the spectrum using the reconstruction matrix. However, the monochromator light source is a light source with only one wavelength, which does not exist in real life. Therefore, using the monochromator light source to determine the reconstruction matrix and using the reconstruction matrix to reconstruct the spectrum is relatively rough, and the restoration effect of the actual light source is not accurate enough. Summary of the invention
[0004] Embodiments of the present application provide a determination method, device, electronic device, and storage medium.
[0005] The technical solution of this application is implemented as follows:
[0006] The present application embodiment provides a determination method, including:
[0007] Acquire property information of a local spectrum of monochromatic light and property information of a local spectrum of polychromatic light; the monochromatic light refers to light containing only one wavelength; the polychromatic light refers to light containing at least two wavelengths;
[0008] fusing the attribute information of the local spectrum of the monochromatic light and the attribute information of the local spectrum of the polychromatic light to obtain target attribute information;
[0009] Based on the target attribute information, a reconstruction matrix is determined; the reconstruction matrix is used to determine the entire spectrum of the light source to be measured.
[0010] The present application provides a determination device, including:
[0011] An acquisition module, used to acquire property information of a local spectrum of monochromatic light and property information of a local spectrum of polychromatic light; the monochromatic light refers to light containing only one wavelength; the polychromatic light refers to light containing at least two wavelengths;
[0012] A processing module, used for fusing the attribute information of the local spectrum of the monochromatic light and the attribute information of the local spectrum of the polychromatic light to obtain target attribute information;
[0013] The determination module is used to determine a reconstruction matrix based on the target attribute information; the reconstruction matrix is used to determine the entire spectrum of the light source to be measured.
[0014] An embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can be run on the processor to execute the determination method provided above.
[0015] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program enables a computer to execute the determination method provided above.
[0016] In the technical solutions provided in some embodiments of the present application, the attribute information of the local spectrum of monochromatic light with only one wavelength and the attribute information of the local spectrum of polychromatic light with at least two wavelengths are obtained, and the attribute information of the local spectrum of the monochromatic light and the attribute information of the local spectrum of the polychromatic light are fused to obtain target attribute information, and a reconstruction matrix is determined according to the target attribute information, and the entire spectrum of the light source to be measured is determined using the reconstruction matrix. In this way, by fusing the attribute information of the local spectra of the two lights, a reconstruction matrix is determined according to the fused attribute information of the two light sources, and the reconstruction matrix can be used to effectively fit the real spectrum of the actual light source, thereby improving the accuracy of the restoration effect of the actual light source. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] Figure 1 A structural diagram of a spectral sensor provided in an embodiment of the present application;
[0018] Figure 2 A spectral response curve provided in the embodiment of the present application Figure 1 ;
[0019] Figure 3 A determination method process provided in the embodiment of the present application Figure 1 ;
[0020] Figure 4 A determination method process provided in the embodiment of the present application Figure 2 ;
[0021] Figure 5 A schematic diagram of a collection device provided in an embodiment of the present application;
[0022] Figure 6 A determination method process provided in the embodiment of the present application Figure 3 ;
[0023] Figure 7 A spectral response curve provided in the embodiment of the present application Figure 2 ;
[0024] Figure 8 A schematic diagram of mean filtering provided in an embodiment of the present application;
[0025] Fig. 9 A determination method process provided in the embodiment of the present application Figure 4 ;
[0026] Fig.10 A determination method process provided in the embodiment of the present application Figure 5 ;
[0027] Fig.11 A determination method process provided in the embodiment of the present application Figure 6 ;
[0028] Fig.12 A schematic diagram of a reconstruction matrix provided in an embodiment of the present application;
[0029] Fig.13 A determination method process provided in the embodiment of the present application Figure 7 ;
[0030] Fig.14 A determination method process provided in the embodiment of the present application Figure 8 ;
[0031] Fig.15 A weighted summation schematic diagram provided for an embodiment of the present application;
[0032] Fig.16 A schematic diagram of the structure of a determination device provided in an embodiment of the present application;
[0033] Fig.17 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0034] The following will describe the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0035] To facilitate understanding of the technical solutions of the embodiments of the present application, the relevant technologies of the embodiments of the present application are described below. The following related technologies can be arbitrarily combined with the technical solutions of the embodiments of the present application as optional solutions, and they all belong to the protection scope of the embodiments of the present application.
[0036] In addition, in the embodiments of the present application, "first", "second", etc. are used to distinguish similar objects and are not necessarily used for a specific order or sequence.
[0037] First, the professional terms involved in the embodiments of the present application are explained.
[0038] Spectrum: It is the pattern in which the dispersed monochromatic light is arranged in order of wavelength (or frequency) after the complex light is split by a dispersion system (such as a prism or grating). The full name is optical spectrum. The spectrum does not include all the colors that the human brain can distinguish, such as brown and pink.
[0039] Monochromator: It generates monochromatic light of a single wavelength, such as monochromatic light with a wavelength of 351nm.
[0040] Spectrometer: It is an optical instrument that separates complex color light into a spectrum. For example, a spectrometer can decompose sunlight to obtain seven colors of light visible to the naked eye arranged by wavelength. And the spectrometer can obtain the spectral curve of the light source, which is a graph of the corresponding relationship between wavelength and the spectral intensity of the wavelength.
[0041] Spectral sensor: a sensor that obtains spectral channel response, see Figure 1 As shown, Figure 1 This is the structure of a spectral sensor. There are many small partitions inside a spectral sensor, and each small partition responds to different wavelengths of light. The spectral response curve of each wavelength is as follows: Figure 2 As shown, Figure 2 The horizontal axis is the wavelength. The wavelength range of the spectral sensor is 350nm-1000nm. The vertical axis is the response value of each wavelength in different partitions. Figure 2 One of the curves represents the response value of a small partition.
[0042] Optical power meter: An instrument used to measure optical power. It can be used for direct measurement of optical power as well as for relative measurement of optical attenuation.
[0043] Monochromatic light is a component of complex light. It is light of a single wavelength and cannot produce dispersion. Each of the seven colors of light from red to purple has a fairly wide wavelength range. It is not truly monochromatic light. White light can be decomposed into various colors, and then an adjustable long row of slits is used to allow only one wavelength of light to pass through while blocking other wavelengths of light. The light that passes through this wavelength is monochromatic light.
[0044] At present, in the prior art, the spectrum is reconstructed by using a monochromator to emit a series of monochromatic lights with a step size of 1 nanometer (nm). For example, in 350nm-1000nm, the monochromator can emit monochromatic lights of each integer wavelength, and simultaneously record the values of each channel of the spectrum sensor and the actual spectrum of the spectrometer, and then calculate the reconstruction matrix using the least squares method, and reconstruct the spectrum using the reconstruction matrix. In the prior art, the light source emitted by the monochromator can ensure that the probability of each wavelength of light appearing is the same, so it can be ensured that each wavelength of light can get the same weight.
[0045] However, the light source emitted by the monochromator is a light source with only one wavelength. In real life, there is no single wavelength light source, but rather monochromatic light of a band. Therefore, using the monochromator light source to determine the reconstruction matrix and using the reconstruction matrix to reconstruct the spectrum is relatively rough, and the restoration effect of the actual light source is not accurate enough.
[0046] Based on the relevant problems existing in the prior art, an embodiment of the present application provides a determination method, by fusing the attribute information of the local spectrum of monochromatic light and the attribute information of the local spectrum of complex light to obtain target attribute information, and determining a reconstruction matrix based on the target attribute information. The reconstruction matrix can be used to effectively fit the real spectrum of the actual light source, thereby improving the accuracy of the restoration effect of the actual light source.
[0047] The determination method provided in the embodiment of the present application can be applied to any field requiring spectral technology, such as medicine, chemistry, geology, imaging, physics and astronomy.
[0048] Figure 3 The present invention provides a flow chart of a determination method, which includes:
[0049] Step S110: Acquire property information of a local spectrum of monochromatic light and property information of a local spectrum of polychromatic light; the monochromatic light refers to light containing only one wavelength; the polychromatic light refers to light containing at least two wavelengths.
[0050] In the embodiment of the present application, monochromatic light refers to light with only one wavelength. By adjusting the long row of slits in the monochromator, it can only pass light with one wavelength. In the range of 350nm-1000nm, the monochromator emits a series of monochromatic lights with a step of 1nm, such as light with a wavelength of 351nm, light with a wavelength of 352nm, etc. In real life, there is no light with a single wavelength, so the monochromatic light here can be understood as light simulating a light source.
[0051] In the embodiments of the present application, polychromatic light refers to light including at least two wavelengths. In real life, most light is polychromatic light. Therefore, the polychromatic light here can be understood as light from an actual light source.
[0052] In the embodiment of the present application, an ordinary spectral sensor cannot obtain the entire spectrum of the light source. Therefore, the local spectrum of monochromatic light refers to the partial spectrum of monochromatic light, which can be regarded as several sampling points in the monochromatic light spectrum. The local spectrum of complex light refers to the partial spectrum of complex light, which can be regarded as several sampling points in the complex light spectrum, wherein the points in the partial spectrum may be several continuous points in the spectrum, or may be several discontinuous points in the spectrum, or several randomly sampled points, and the embodiment of the present application does not make any specific limitation on this.
[0053] In the embodiment of the present application, monochromatic light can be multiple monochromatic lights or one monochromatic light, and complex light can be multiple monochromatic lights or one complex light. The number of light sources can be determined according to actual conditions, and the embodiment of the present application does not make any specific limitations on this.
[0054] In the embodiment of the present application, the attribute information of the local spectrum includes channel data of the local spectrum and / or the spectral intensity of the local spectrum, and the channel data of the local spectrum and the spectral intensity of the local spectrum correspond to the same band.
[0055] In the embodiment of the present application, the channel data of the local spectrum refers to the response value corresponding to each channel in the spectral sensor, and the spectral intensity of the local spectrum refers to the spectral intensity corresponding to each wavelength in the spectral curve recorded in the spectrometer.
[0056] In an embodiment of the present application, when the same light source passes through a spectral sensor and a spectrometer respectively, the channel data of the local spectrum of the light source (the response value of each channel) and the spectral intensity of the local spectrum are obtained respectively. It should be understood that the channel data of the local spectrum and the spectral intensity of the local spectrum here are the response value and spectral intensity of the channel of the light source of the same wavelength.
[0057] It should be understood that whether it is monochromatic light or polychromatic light, it is necessary to collect two sets of data: channel data and spectral intensity of the local spectrum. Therefore, the attribute information of each light source is a data pair consisting of two pieces of data: channel data and spectral intensity, which come from the channel data of the spectral sensor and the spectral intensity data of the spectrometer respectively.
[0058] Step S120: fusing the attribute information of the local spectrum of the monochromatic light and the attribute information of the local spectrum of the polychromatic light to obtain target attribute information.
[0059] In the embodiment of the present application, target attribute information refers to attribute information obtained after a series of processing is performed on the acquired attribute information.
[0060] In an embodiment of the present application, the target attribute information includes: target channel data and / or target spectral intensity.
[0061] In the embodiment of the present application, the attribute information of the local spectrum is the channel data of the local spectrum and the light intensity of the local spectrum. The attribute information is a data pair consisting of two pieces of data: channel data and spectral intensity. Therefore, the attribute information of the local spectrum of monochromatic light and the attribute information of the local spectrum of polychromatic light are fused, and the obtained target attribute information is also a data pair consisting of two pieces of data: channel data and spectral intensity. The target attribute information includes target channel data and / or target spectral intensity.
[0062] In the embodiment of the present application, fusion refers to combining the attribute information of the local spectrum of monochromatic light and the attribute information of the local spectrum of polychromatic light to obtain one attribute information (target attribute information).
[0063] In the embodiment of the present application, after acquiring the attribute information of the local spectrum of the monochromatic light and the attribute information of the local spectrum of the polychromatic light, the two attribute information are fused to obtain the target attribute information.
[0064] Step S130: determining a reconstruction matrix based on the target attribute information; the reconstruction matrix is used to determine the entire spectrum of the light source to be measured.
[0065] In the embodiment of the present application, the reconstruction matrix here is substantially a parameter matrix in the spectral sensor. After the parameter matrix in the spectral sensor is acquired, the entire spectrum of the light source to be measured can be determined according to the parameter matrix of the sensor.
[0066] In the embodiment of the present application, the light source to be tested can be any light source in nature, such as natural light including sunlight, lightning, fireflies, etc.; artificial light sources include lamps, candles, etc., and the embodiment of the present application does not make specific limitations on this.
[0067] In the embodiment of the present application, after the target attribute information is obtained, a reconstruction matrix is determined according to the target attribute information, and the reconstruction matrix is used to determine the entire spectrum of the light source to be measured.
[0068] In the embodiment of the present application, in addition to using the least squares method, the reconstruction matrix can also be calculated using other methods, and the embodiment of the present application does not make any specific limitations on this.
[0069] In an embodiment of the present application, by acquiring the attribute information of the local spectrum of monochromatic light with only one wavelength and the attribute information of the local spectrum of polychromatic light with at least two wavelengths, the attribute information of the local spectrum of the monochromatic light and the attribute information of the local spectrum of the polychromatic light are fused to obtain target attribute information, and a reconstruction matrix is determined based on the target attribute information, and the entire spectrum of the light source to be measured is determined using the reconstruction matrix. In this way, by fusing the attribute information of the local spectra of the two lights, a reconstruction matrix is determined based on the fused attribute information of the two light sources, and the reconstruction matrix can be used to effectively fit the real spectrum of the actual light source, thereby improving the accuracy of the restoration effect of the actual light source.
[0070] In the examples of this application, refer to Figure 4 , before step S110, acquiring the property information of the local spectrum of the monochromatic light and the property information of the local spectrum of the polychromatic light, the method further comprises:
[0071] Step S101: using a spectrum collection device to respectively collect initial attribute information of the local spectrum of the monochromatic light and initial attribute information of the local spectrum of the polychromatic light.
[0072] In the embodiment of the present application, the spectrum acquisition device includes a spectrometer and a spectrum sensor. The spectrum acquisition device here can be an integrated device of the spectrometer and the spectrum sensor, or can be two separate devices of the spectrometer and the spectrum sensor. The embodiment of the present application does not make any specific limitation on this.
[0073] Exemplary, reference Figure 5 As shown, Figure 5 It is a spectrum collection device. Figure 5 The monochromator light source is simulated monochromatic light, and the integrating sphere can evenly distribute the monochromator light source to the spectrometer, spectrum sensor, and optical power meter. The spectrometer is used to record the spectral intensity of the light source spectrum, the spectrum sensor is used to record the channel data (response value) of the light source spectrum, and the optical power meter is used to record the optical power value. Among them, the spectrometer, spectrum sensor, and optical power meter record the data of the same light source, and the three have a corresponding relationship. The recorded spectral intensity of the light source spectrum, the channel data, and the optical power value belong to the same band.
[0074] In the embodiment of the present application, the initial attribute information refers to the raw data collected by the device, which is not processed. The initial attribute information of the local spectrum of monochromatic light includes the initial channel data of the local spectrum of monochromatic light and / or the initial spectrum intensity of the local spectrum of monochromatic light. The initial attribute information of the local spectrum of polychromatic light includes the initial channel data of the local spectrum of polychromatic light and / or the initial spectrum intensity of the local spectrum of polychromatic light.
[0075] In the embodiment of the present application, a spectral sensor is used to collect initial channel data of a local spectrum, and a spectrometer is used to collect initial spectral intensity of the local spectrum.
[0076] Step S102: based on the optical power value corresponding to the monochromatic light, remove the illumination intensity parameter of the initial attribute information of the local spectrum of the monochromatic light to obtain the attribute information of the local spectrum of the monochromatic light.
[0077] Step S103: based on the optical power value corresponding to the polychromatic light, remove the illumination intensity parameter of the initial attribute information of the local spectrum of the polychromatic light to obtain the attribute information of the local spectrum of the polychromatic light.
[0078] In the embodiment of the present application, the optical power value is used to represent the optical power value of a certain wavelength, and the optical power value can be recorded by an optical power meter.
[0079] In an embodiment of the present application, different light intensities will affect the attribute information of the local spectrum of the same light source. Therefore, it is necessary to remove the light intensity parameters of the initial attribute information of the local spectrum of each light source to obtain the attribute information of the local spectrum of monochromatic light and the attribute information of the local spectrum of polychromatic light, respectively.
[0080] In an embodiment of the present application, before acquiring the attribute information of the local spectrum of monochromatic light and the attribute information of the local spectrum of polychromatic light, the initial spectral intensity of the local spectrum of each light source, the initial channel data of the local spectrum and the corresponding optical power value are respectively collected by the spectrometer, the spectral sensor and the optical power meter in the spectrum acquisition device, and the initial spectral intensity of the local spectrum of each light source and the initial channel data of the local spectrum are processed to remove the illumination intensity parameter according to the optical power value, so as to obtain the local spectral intensity and the channel data of the local spectrum of each light source. By removing the illumination intensity parameter from the attribute information of the local spectrum based on the optical power value, it is avoided that the light intensity of the light source is inconsistent after each wavelength switching, resulting in inaccurate attribute information of the local spectrum of the light source.
[0081] In the examples of this application, refer to Figure 6 As shown, step S102: based on the optical power value corresponding to the monochromatic light, remove the illumination intensity parameter of the initial attribute information of the local spectrum of the monochromatic light to obtain the attribute information of the local spectrum of the monochromatic light, including
[0082] Step S1021: based on the optical power value corresponding to the monochromatic light, remove the illumination intensity parameter of the initial attribute information of the local spectrum of the monochromatic light to obtain the intermediate attribute information of the local spectrum of the monochromatic light.
[0083] Step S1022: filtering the intermediate attribute information of the local spectrum of the monochromatic light to obtain the attribute information of the local spectrum of the monochromatic light.
[0084] In the embodiment of the present application, filtering processing refers to filtering out noise data in the intermediate attribute information through a filter.
[0085] In the embodiment of the present application, the monochromatic light is a very narrow broadband, referring to Figure 7 As shown, Figure 7 It is the correspondence between the wavelength and response of the monochromatic light spectrum. There are three colors of light. The spectrum of each color is equivalent to a light source that switches its wavelength once. It is a very narrow light source that needs to pass through a filter to simulate the response of the spectral sensor under a slightly wider light source and the corresponding spectral intensity of the light source.
[0086] In the embodiment of the present application, the filtering process may be any process such as mean filtering, median filtering or Gaussian filtering. The embodiment of the present application does not specifically limit the filtering process method.
[0087] Exemplary, reference Figure 8 As shown, Figure 8 is the channel data obtained by monochromatic light passing through the spectral sensor, Figure 8 Each row of data represents a monochromatic light. Different monochromatic lights pass through the spectral sensor and obtain different channel data. In other words, Figure 8 Each time the monochromator switches to a single color light, a piece of data is recorded. After collecting the channel data, the channel data is filtered using a mean filter, and the width of the mean filter is 5. Figure 8 The one in the vertical frame is the mean filter.
[0088] It should be understood that this example is only one of the implementations and is not intended to be limiting.
[0089] In the embodiment of the present application, it is necessary to filter both the channel data of the local spectrum and the spectral intensity of the local spectrum. Here, the filtering operation of the spectral intensity of the local spectrum is consistent with the filtering operation of the channel data of the local spectrum, which will not be elaborated here.
[0090] It should be noted that the filtering method used for the channel data of the local spectrum should be exactly the same as the filtering method used for the spectral intensity of the local spectrum. In this way, it can be ensured that the attribute information of the local spectrum collected at the same wavelength still maintains a corresponding relationship after filtering.
[0091] In an embodiment of the present application, after removing the illumination intensity parameter of the initial attribute information of the local spectrum of the monochromatic light, the intermediate attribute information of the local spectrum of the monochromatic light is obtained, and then the intermediate attribute information of the local spectrum of the monochromatic light is filtered to obtain the attribute information of the local spectrum of the monochromatic light. By filtering the intermediate attribute information of the local spectrum after removing the illumination intensity parameter, the very narrow spectrum of the monochromatic light can be adjusted to the channel data and corresponding spectral intensity of the spectrum under a slightly wider light source. In this way, the determined reconstruction matrix will make the reconstructed spectrum curve smoother.
[0092] In the embodiment of the present application, the light intensity parameter of the initial attribute information of the local spectrum of the monochromatic light is removed based on the optical power value corresponding to the monochromatic light to obtain the attribute information of the local spectrum of the monochromatic light, including:
[0093] Dividing the initial property information of the local spectrum of the monochromatic light by the optical power value corresponding to the monochromatic light to obtain the property information of the local spectrum of the monochromatic light;
[0094] The method of removing the illumination intensity parameter of the initial attribute information of the local spectrum of the polychromatic light based on the optical power value corresponding to the polychromatic light to obtain the attribute information of the local spectrum of the polychromatic light includes:
[0095] The initial property information of the local spectrum of the polychromatic light is divided by the optical power value corresponding to the polychromatic light to obtain the property information of the local spectrum of the polychromatic light.
[0096] In an embodiment of the present application, a method for removing the light intensity parameters of the initial attribute information of the local spectrum of monochromatic light is to divide the initial attribute information of the local spectrum of monochromatic light by the light power value corresponding to the monochromatic light to obtain the attribute information of the local spectrum of monochromatic light; a method for removing the light intensity parameters of the initial attribute information of the local spectrum of complex light is to divide the initial attribute information of the local spectrum of complex light by the light power value corresponding to the monochromatic light to obtain the attribute information of the local spectrum of monochromatic light.
[0097] By dividing the initial attribute information of the local spectrum of each light source by its corresponding optical power value, it is avoided that the light intensity of each light source is inconsistent, thereby affecting the attribute information of the local spectrum of each light source.
[0098] In the examples of this application, refer to Fig. 9 As shown, step S120, fusing the attribute information of the local spectrum of the monochromatic light and the attribute information of the local spectrum of the polychromatic light to obtain target attribute information, includes:
[0099] Step S121: performing weighted summation on the attribute information of the local spectrum of the monochromatic light and the attribute information of the local spectrum of the polychromatic light to obtain the target attribute information.
[0100] In an embodiment of the present application, when weighted summation is performed on the attribute information of the local spectrum of monochromatic light and the attribute information of the local spectrum of complex light, the weights used may be set in advance by the staff, or the device may automatically adjust the weight values according to actual conditions. The embodiment of the present application does not specifically limit the setting of the weights.
[0101] In an embodiment of the present application, when performing weighted summation, the weight values of monochromatic light and complex light respectively range from 0 to 1, and the sum of the two weight values is 1. The larger the weight value, the more important the light source corresponding to the weight value, and the smaller the weight, the less important the light source corresponding to the weight value.
[0102] After determining the weight values of the monochromatic light and the polychromatic light, multiply the attribute information of the local spectrum of the monochromatic light by the corresponding weight value of the monochromatic light, and multiply the attribute information of the local spectrum of the polychromatic light by the corresponding weight value of the polychromatic light, and add the two products to obtain the target attribute information. For example, if the attribute information of the local spectrum of the monochromatic light is A, the corresponding weight value of the monochromatic light is a, and the attribute information of the local spectrum of the polychromatic light is B, and the corresponding weight value of the polychromatic light is b, then the weighted sum is aA+bB.
[0103] In the embodiment of the present application, monochromatic light is used to ensure that under ideal conditions, the probability of each wavelength of light appearing is the same, and each wavelength of light can be given the same weight. According to actual conditions, the attribute information of the local spectrum of the actual light source is collected, and the monochromatic light (ideal light source) and the polychromatic light (actual light source) are fused together by weighted summation. The fitting tendency of the local spectrum of the monochromatic light and the local spectrum of the polychromatic light is flexibly adjusted according to actual needs to ensure that the reconstructed matrix can effectively fit the real spectrum of the actual light source, thereby improving the accuracy of the restoration effect of the actual light source.
[0104] In the examples of this application, refer to Fig.10 As shown, the method also includes:
[0105] Step S140: filtering at least part of the elements of the reconstruction matrix to obtain a target reconstruction matrix.
[0106] In the embodiment of the present application, the target reconstruction matrix refers to a reconstruction matrix obtained after processing the reconstruction matrix.
[0107] In the embodiment of the present application, since the curve formed by each channel data in the actual situation is not smooth enough, the value of the obtained reconstruction matrix will also be not smooth. Therefore, it is necessary to filter at least part of the elements of the determined reconstruction matrix to obtain the target reconstruction matrix.
[0108] In the embodiment of the present application, the filtering process may be any process such as mean filtering, median filtering or Gaussian filtering. The embodiment of the present application does not specifically limit the filtering process method.
[0109] In the embodiment of the present application, after determining the reconstruction matrix according to the target attribute information, filtering is performed on at least some elements of the reconstruction matrix to obtain the target reconstruction matrix. By filtering the reconstruction matrix, it is avoided that the curve formed by the channel data is not smooth, resulting in the value of the reconstruction matrix being not smooth, thereby causing the entire reconstructed spectrum to be not smooth, further improving the accuracy of the true restoration effect of the actual light source.
[0110] In the examples of this application, refer to Fig.11 As shown, step S140: filtering at least part of the elements of the reconstruction matrix to obtain a target reconstruction matrix includes:
[0111] Step S141: Based on at least part of the channel data of the target channel data, determine the width of the filter used by at least part of the elements of the reconstruction matrix.
[0112] Step S142: Based on the width of the filter used by at least some of the elements of the reconstruction matrix, filter processing is performed on at least some of the elements of the reconstruction matrix to obtain the target reconstruction matrix.
[0113] In the embodiment of the present application, the width of the filter refers to the amount of data that the filter can process at one time.
[0114] In an embodiment of the present application, the width of the filter used for at least some elements of the reconstruction matrix is determined according to at least some channel data in the target channel data. After the width of the filter is determined, at least some elements of the reconstruction matrix are filtered to obtain the target reconstruction matrix.
[0115] In the embodiment of the present application, the width of the filter can be appropriately adjusted according to the roughness of at least part of the channel data of the target channel data, and the roughness of the channel data refers to the smoothness of the curve formed by the channel data. The less smooth the curve is, the rougher the channel data is, and the smoother the curve is, the less rough the channel data is; the rougher the channel data is, the smaller the width of the filter is; the smoother the channel data is, the larger the width of the filter is.
[0116] Exemplary, reference Fig.12 As shown, Fig.12is a schematic diagram of the reconstruction matrix. The number of rows in the reconstruction matrix is the number of channels, and the number of columns is the spectrum length. Fig.12 In the process of filtering each row in the reconstructed matrix, a different mean filter is set for each row. Fig.12 The small box in the middle is a filter. The filter in each row can be different. The width of the filter can be appropriately adjusted according to the roughness of the channel data in each row of the channel data to filter each row of the reconstructed matrix.
[0117] In the examples of this application, refer to Fig.13 As shown, step S142, based on the width of the filter used by at least some elements of the reconstruction matrix, filtering is performed on at least some elements of the reconstruction matrix to obtain the target reconstruction matrix, including
[0118] Step S1421: Based on the width of the filter used by at least some of the elements of the reconstruction matrix, filter processing is performed on at least some of the elements of the reconstruction matrix to obtain an intermediate reconstruction matrix.
[0119] Step S1422: adding a proportional coefficient to at least part of the elements of the intermediate reconstruction matrix to obtain a target reconstruction matrix; the proportional coefficient is used to adjust the entire spectrum.
[0120] In the embodiment of the present application, the proportionality coefficient is a non-zero constant. The larger the proportionality coefficient is, the larger the channel data obtained is, and the smaller the proportionality coefficient is, the smaller the channel data obtained is.
[0121] In the embodiment of the present application, after filtering at least part of the elements of the reconstruction matrix, an intermediate reconstruction matrix is obtained, and then a proportional coefficient is added to at least part of the elements of the intermediate reconstruction matrix to obtain a target reconstruction matrix.
[0122] In the embodiment of the present application, by adding a proportional coefficient to the intermediate reconstruction matrix and strengthening the data of a certain channel, different proportional coefficients can be set according to actual conditions. In this way, the reconstructed spectrum can be adjusted according to actual needs to obtain a more accurate true spectrum of the actual light source.
[0123] In an embodiment of the present application, channel data and corresponding spectral intensity of the local spectrum of monochromatic light, and channel data and corresponding spectral intensity of the local spectrum of polychromatic light are respectively obtained; wherein, the data pair of the local spectrum of monochromatic light can be obtained through filtering processing; the product of the channel data of the local spectrum of monochromatic light multiplied by weight 1 is added to the product of the channel data of the local spectrum of polychromatic light multiplied by weight 2 to obtain target channel data; the product of the spectral data of the local light of monochromatic light multiplied by weight 1 is added to the product of the spectral intensity of the local spectrum of polychromatic light multiplied by weight 2 to obtain target spectral intensity, wherein the sum of weight 1 and weight 2 is 1; based on the target channel data and the target spectral intensity, a reconstruction matrix is calculated using the least squares method; the reconstruction matrix is smoothed using a filter to obtain a target reconstruction matrix.
[0124] After determining the target reconstruction matrix, the target reconstruction matrix can be used to infer the entire spectrum of any light source.
[0125] In the present embodiment, different proportional coefficients can be added to the target reconstruction matrix according to actual needs to enhance the response effect of a certain channel and change the shape of the reconstructed spectrum.
[0126] The following describes in detail the determination method provided in the embodiment of the present application in conjunction with specific application scenarios.
[0127] In this application scenario, the calibration of the reconstruction matrix of the spectral sensor is to calibrate the spectral sensor with a standard instrument spectrometer under the premise of clarifying the input and output relationship. In other words, the spectrometer collects the real spectral curve of the spectrum, and the spectral channel data collected by the spectral sensor is fitted with the reconstruction matrix to obtain a real spectral curve close to the real spectral curve collected by the spectrometer. In the case of the closest to the real spectral curve, the reconstruction matrix is optimal. The spectrum is reconstructed using the reconstruction matrix to obtain the entire spectrum of the light source.
[0128] In this application scenario, Figure 3 The spectrum acquisition device shown is also called a calibration device. The monochromator light source in the spectrum acquisition device is used to generate a narrow-band light source with a step length of 1nm. The integrating sphere is equivalent to a light homogenizing device, which evenly reflects the light source to the integrating sphere outlet. There are three devices at the integrating sphere outlet. The spectrometer is used to detect the output spectrum, the spectrum sensor is our device to be calibrated, and the optical power meter is used to detect the current optical power.
[0129] The calibration of the spectral reconstruction matrix is to calibrate a parameter matrix so that the actual real spectrum can be effectively fitted using the channel values of the spectral sensor.
[0130] refer to Fig.14 As shown, Fig.14 It is the implementation step of determining the method in this application scenario.
[0131] S1: The spectral sensor continuously collects the channel data of the light source, the spectrometer continuously collects the spectrum of the light source, and the optical power meter continuously records the optical power value.
[0132] It should be understood that the light source here can be monochromatic light and polychromatic light in the embodiments of the present application, the monochromatic light is the monochromator light source, and the polychromatic light is the actual light source.
[0133] The monochromator is used as the light source. According to the design range of the spectral sensor, the wavelength of the light source is continuously switched from the beginning to the end (such as 350nm-1000nm). At the same time, the spectral sensor continuously collects the channel data of the monochromator light source each time it is switched, the spectrometer continuously collects the spectrum, and the optical power meter continuously records the optical power value.
[0134] Use several actual light sources and switch the light sources. At the same time, the spectrum sensor continuously collects channel data of the actual light source, the spectrometer continuously collects the spectrum, and the optical power meter continuously records the optical power value.
[0135] There are two branches in the upper part of the flowchart because the calibration data source is designed to come from two parts, one is the monochromator and the other is the actual light source. Figure 7 As shown in the figure, the spectrum of each color is equivalent to a light source that switches wavelengths once, which is a very narrow light source. The reason why we use a monochromator light source to collect calibration data is that it can ensure that in an ideal situation (the probability of each wavelength of light appearing is the same), each wavelength of light can get the same calibration weight. In addition, we have added data of actual real light sources, such as Fig.14 The upper part, right branch. And manually set and adjust the actual light source weight value, so that the design can flexibly adjust the fitting tendency of the ideal spectrum and the actual spectrum according to actual needs.
[0136] S2: For all channel data collected each time, divide it by the optical power value recorded at the same time.
[0137] It should be understood that the channel data of the monochromator light source is divided by the optical power value of the monochromator light source recorded at the same time. The channel data of the actual light source is divided by the optical power value of the actual light source recorded at the same time.
[0138] S3: For each acquired spectral curve value, divide it by the optical power value recorded at the same time.
[0139] It should be understood that the spectrum curve value of the monochromator light source is divided by the optical power value of the monochromator light source recorded at the same time. The spectrum curve value of the actual light source is divided by the optical power value of the actual light source recorded at the same time.
[0140] It should be understood that S2 and S3 are data processing for two light sources. Because the monochromator cannot guarantee that the light intensity of the light source is consistent after each wavelength switch, it is necessary to pre-process the values of all channels and the spectrometer data according to the optical power meter value. The specific operation is to divide the data by the optical power value. For example, if the spectrum sensor has 13 channels, then the values of these 13 channels are divided by the optical power value collected under the light source. The spectral data is also represented by an array, and each value represents a sample of the spectral curve at that wavelength. For example, the spectrum of 350nm-1000nm can be represented by an array of 650 length. The pre-processing is to divide each value of the array by the optical power value.
[0141] S4: Mean filter applied to the channel data of the monochromator source and the spectrometer data.
[0142] It should be understood that the monochromator light source is used to generate a narrow-band light source with a step length of 1 nm. Therefore, the data processing of the monochromator light source also includes filtering processing. Taking the spectral sensor channel data as an example, each time the monochromator switches the light source, a channel data will be generated, which is equivalent to Figure 8 Each row of data. Then set a filter window width, such as Figure 8 For example, the width is 5, that is, the number of data framed by the red frame is 5, and each data is mean filtered with this width.
[0143] The same filter operation is used for the spectrometer data. The spectral data collected by the spectrometer is also composed of arrays. The main reason for this set of filtering operations is that the light source emitted by the monochromator is a very narrow narrow-band light. In this way, the response of the spectral sensor under a light source with a slightly wider spectrum and the corresponding light source spectrum can be simulated. The reconstruction matrix calibrated in this way will reconstruct a smoother spectral curve.
[0144] S5: Combine the channel data and spectral data collected by the two light sources and set different weights.
[0145] It should be understood that the calibration data from the two sources are combined with different weights. Generally speaking, the data from the monochromator is given the same weight, which means that the weight of each band is the same. If you want to strengthen the fitting weight in a certain band, you can select the color temperature sensor channel data and the corresponding spectral data recorded when the monochromator switches to this band and set a higher weight.
[0146] The specific weight setting method is as follows Fig.15As shown. Each light source, whether it comes from a monochromator or an actual light source, will generate a data pair consisting of two pieces of data, channel data and spectral intensity. The data pairs come from the channel data of the spectral sensor and the data of the spectrometer. According to the set weight value, each array of this pair of data is multiplied by this weight value to generate a new data pair. The main purpose of setting the weight is to enhance the fitting effect of the spectral sensor for certain light sources, but it may cause the effect of other light sources to deteriorate.
[0147] S6: Using the channel data and spectral data, calculate the reconstruction matrix CM using the least squares method.
[0148] It should be understood that the channel data and spectral data here are obtained through weighted summation, which can be regarded as the target attribute information in the embodiment of the present application, and the least square method is used to calculate the reconstruction matrix. The least square method is a common method for solving linear fitting problems. It searches for the best function matching of data by minimizing the square sum of errors. The least square method can be used to easily obtain unknown data, and the square sum of errors between the data obtained and the actual data is minimized.
[0149] In order to use the least squares method, construct the expression (1) to minimize the error, Raw i Represents the i-th channel data, represented by a row vector. i Represents the ith spectral data, also represented by a row vector, and Raw i is a pair of data from the same light source. n represents the total number of light source data collected for calibration. CM is the spectrum reconstruction matrix. The number of rows in the reconstruction matrix is the same as the number of spectral sensor channels, and the number of columns is the same as the length of the spectrum array. i *CM is matrix multiplication, and the result is the reconstructed spectrum, S i It is equivalent to the true value of the spectrum, so to minimize the value of expression (1), the sum of the squares of the errors between the obtained data and the actual data is minimized. The next step is to solve CM using the existing method of least squares.
[0150]
[0151] S7: Set a mean filter with different widths for each CM channel.
[0152] It should be understood that in reality, the spectral response curve of each channel is not smooth enough, such as Figure 2 As shown, the value of the reconstructed matrix CM is not smooth enough, and a filtering system is required to filter the reconstructed matrix.
[0153] The specific operation method is as follows Fig.12As shown, the number of rows in the reconstruction matrix CM is the number of channels, and the number of columns is the length of the spectrum. For each row, a different mean filter is set, and the width of the filter is appropriately adjusted according to the coarseness of the channel data to filter each row of data.
[0154] S8: Set a different proportional coefficient for each CM channel to scale the channel value.
[0155] It should be understood that different scaling factors are set to meet some special needs, such as deliberately strengthening the response effect of a certain channel to artificially change the reconstructed spectrum shape. The specific operation is to set a different scaling factor for each row of CM to multiply each value of this row. If there is no such requirement, usually all are set to 1, that is, this step does not work.
[0156] Through the above steps, the target reconstruction matrix is determined, which can make the reconstructed spectrum smooth and accurate. In addition, when using a weighted combination of multiple light sources for calculation, two filter systems are set to ensure that the reconstructed spectrum is smooth and accurate.
[0157] The present application also provides a determination device, referring to Fig.16 As shown, the determining device may include:
[0158] An acquisition module 1601 is used to acquire property information of a local spectrum of monochromatic light and property information of a local spectrum of polychromatic light; the monochromatic light refers to light containing only one wavelength; the polychromatic light refers to light containing at least two wavelengths;
[0159] The processing module 1602 is used to fuse the attribute information of the local spectrum of the monochromatic light and the attribute information of the local spectrum of the polychromatic light to obtain target attribute information;
[0160] The determination module 1603 is used to determine a reconstruction matrix based on the target attribute information; the reconstruction matrix is used to determine the entire spectrum of the light source to be measured.
[0161] In some embodiments, the acquisition module is also used to respectively collect the initial attribute information of the local spectrum of the monochromatic light and the initial attribute information of the local spectrum of the polychromatic light through a spectral acquisition device; based on the light power value corresponding to the monochromatic light, remove the light intensity parameter of the initial attribute information of the local spectrum of the monochromatic light to obtain the attribute information of the local spectrum of the monochromatic light; based on the light power value corresponding to the polychromatic light, remove the light intensity parameter of the initial attribute information of the local spectrum of the polychromatic light to obtain the attribute information of the local spectrum of the polychromatic light.
[0162] In some embodiments, the acquisition module is also used to remove the light intensity parameter of the initial attribute information of the local spectrum of the monochromatic light based on the light power value corresponding to the monochromatic light, so as to obtain the intermediate attribute information of the local spectrum of the monochromatic light; and to filter the intermediate attribute information of the local spectrum of the monochromatic light to obtain the attribute information of the local spectrum of the monochromatic light.
[0163] In some embodiments, the acquisition module is further used to divide the initial property information of the local spectrum of the monochromatic light by the light power value corresponding to the monochromatic light to obtain the property information of the local spectrum of the monochromatic light; and divide the initial property information of the local spectrum of the complex light by the light power value corresponding to the complex light to obtain the property information of the local spectrum of the complex light.
[0164] In some embodiments, the processing module is further used to perform weighted summation on the attribute information of the local spectrum of the processed monochromatic light and the attribute information of the local spectrum of the processed polychromatic light to obtain the target attribute information.
[0165] In some embodiments, the attribute information of the local spectrum includes: channel data of the local spectrum and / or spectral intensity of the local spectrum; the channel data of the local spectrum and the spectral intensity of the local spectrum correspond to the same band.
[0166] In some embodiments, the target attribute information includes: target channel data and / or target spectral intensity.
[0167] In some embodiments, the determination module is further used to perform filtering processing on at least part of the elements of the reconstruction matrix to obtain a target reconstruction matrix.
[0168] In some embodiments, the determination module is also used to determine the width of the filter used by at least part of the elements of the reconstruction matrix based on at least part of the channel data of the target channel data; and filter at least part of the elements of the reconstruction matrix based on the width of the filter used by at least part of the elements of the reconstruction matrix to obtain the target reconstruction matrix.
[0169] In some embodiments, the determination module is further used to filter at least part of the elements of the reconstruction matrix based on the width of the filter used by at least part of the elements of the reconstruction matrix to obtain an intermediate reconstruction matrix; add a proportional coefficient to at least part of the elements of the intermediate reconstruction matrix to obtain a target reconstruction matrix; the proportional coefficient is used to adjust the entire spectrum.
[0170] Of course, in practical applications, Fig.17As shown, the various components in the electronic device are coupled together via a bus system 1702. It is understood that the bus system 1702 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 1702 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Fig.17 The various buses are collectively labeled bus system 1702 .
[0171] It can be understood that the memory in this embodiment can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disk, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memories described in the embodiments of the present application are intended to include, but are not limited to, these and any other suitable types of memories.
[0172] The method disclosed in the above embodiment of the present application can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor may be a general-purpose processor, a DSP, or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiment of the present application, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.
[0173] The present application also provides a computer storage medium, specifically a computer-readable storage medium, on which computer instructions are stored. As a first implementation, when the computer storage medium is located in an electronic device, the computer instructions are executed by a processor to implement any step of the above determination method in the present application.
[0174] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.
[0175] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.
[0176] In addition, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be separately configured as a unit, or at least two units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.
[0177] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium, which, when executed, executes the steps of the above-mentioned method embodiment; and the aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, disks or optical disks.
[0178] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiment of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.
[0179] It should be noted that the technical solutions described in the embodiments of the present application can be combined arbitrarily without conflict.
[0180] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.
Claims
1. A determination method, characterized in that: The method comprises: Acquire property information of a local spectrum of monochromatic light and property information of a local spectrum of polychromatic light; the monochromatic light refers to light containing only one wavelength; the polychromatic light refers to light containing at least two wavelengths; fusing the attribute information of the local spectrum of the monochromatic light and the attribute information of the local spectrum of the polychromatic light to obtain target attribute information; Based on the target attribute information, a reconstruction matrix is determined; the reconstruction matrix is used to determine the entire spectrum of the light source to be measured.
2. The method according to claim 1, characterized in that Before acquiring the property information of the local spectrum of the monochromatic light and the property information of the local spectrum of the polychromatic light, the method further includes: The initial property information of the local spectrum of the monochromatic light and the initial property information of the local spectrum of the polychromatic light are respectively collected by a spectrum collection device; Based on the optical power value corresponding to the monochromatic light, the illumination intensity parameter of the initial attribute information of the local spectrum of the monochromatic light is removed to obtain the attribute information of the local spectrum of the monochromatic light; Based on the optical power value corresponding to the polychromatic light, the illumination intensity parameter of the initial attribute information of the local spectrum of the polychromatic light is removed to obtain the attribute information of the local spectrum of the polychromatic light.
3. The method according to claim 2, characterized in that The method of removing the illumination intensity parameter of the initial attribute information of the local spectrum of the monochromatic light based on the optical power value corresponding to the monochromatic light to obtain the attribute information of the local spectrum of the monochromatic light includes: Based on the optical power value corresponding to the monochromatic light, removing the illumination intensity parameter of the initial attribute information of the local spectrum of the monochromatic light, to obtain the intermediate attribute information of the local spectrum of the monochromatic light; The intermediate attribute information of the local spectrum of the monochromatic light is filtered to obtain the attribute information of the local spectrum of the monochromatic light.
4. The method according to claim 2, characterized in that: The method of removing the illumination intensity parameter of the initial attribute information of the local spectrum of the monochromatic light based on the optical power value corresponding to the monochromatic light to obtain the attribute information of the local spectrum of the monochromatic light includes: Dividing the initial property information of the local spectrum of the monochromatic light by the optical power value corresponding to the monochromatic light to obtain the property information of the local spectrum of the monochromatic light; The method of removing the illumination intensity parameter of the initial attribute information of the local spectrum of the polychromatic light based on the optical power value corresponding to the polychromatic light to obtain the attribute information of the local spectrum of the polychromatic light includes: The initial property information of the local spectrum of the polychromatic light is divided by the optical power value corresponding to the polychromatic light to obtain the property information of the local spectrum of the polychromatic light.
5. The method according to any one of claims 1 to 4, characterized in that: The fusing the attribute information of the local spectrum of the monochromatic light and the attribute information of the local spectrum of the polychromatic light to obtain the target attribute information includes: The target attribute information is obtained by performing a weighted summation on the attribute information of the local spectrum of the monochromatic light and the attribute information of the local spectrum of the polychromatic light.
6. The method according to any one of claims 1 to 4, characterized in that: The attribute information of the local spectrum includes: channel data of the local spectrum and / or spectral intensity of the local spectrum; the channel data of the local spectrum and the spectral intensity of the local spectrum correspond to the same band.
7. The method according to any one of claims 1 to 4, characterized in that: The target attribute information includes: target channel data and / or target spectrum intensity.
8. The method according to claim 7, characterized in that The method further comprises: At least part of the elements of the reconstruction matrix are filtered to obtain a target reconstruction matrix.
9. The method according to claim 8, characterized in that The filtering process is performed on at least part of the elements of the reconstruction matrix to obtain a target reconstruction matrix, including: Determining, based on at least a portion of the channel data of the target channel data, a width of a filter used by at least a portion of the elements of the reconstruction matrix; Based on the width of the filter used by at least some of the elements of the reconstruction matrix, filtering processing is performed on at least some of the elements of the reconstruction matrix to obtain the target reconstruction matrix.
10. The method according to claim 9, characterized in that The filtering process is performed on at least some of the elements of the reconstruction matrix based on the width of the filter used by at least some of the elements of the reconstruction matrix to obtain the target reconstruction matrix, including: Based on the width of the filter used by at least some of the elements of the reconstruction matrix, filtering at least some of the elements of the reconstruction matrix to obtain an intermediate reconstruction matrix; A target reconstruction matrix is obtained by adding a proportional coefficient to at least some elements of the intermediate reconstruction matrix; the proportional coefficient is used to adjust the entire spectrum.
11. A determination device, characterized in that: The device comprises: An acquisition module, used to acquire property information of a local spectrum of monochromatic light and property information of a local spectrum of polychromatic light; the monochromatic light refers to light containing only one wavelength; the polychromatic light refers to light containing at least two wavelengths; A processing module, used for fusing the attribute information of the local spectrum of the monochromatic light and the attribute information of the local spectrum of the polychromatic light to obtain target attribute information; The determination module is used to determine a reconstruction matrix based on the target attribute information; the reconstruction matrix is used to determine the entire spectrum of the light source to be measured.
12. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the determination method according to any one of claims 1 to 10 is implemented.
13. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the program, the determination method according to any one of claims 1 to 10 is implemented.