A measurement and analysis method for imaging illumination distribution

Abstract

The present invention relates to the field of optical property testing technology, specifically a method for measuring and analyzing imaging illumination distribution, comprising the following steps: using an imaging tester to shoot uniform diffuse reflection white screens one by one, controlling exposure parameters and focal length to ensure image clarity, gradually adjusting the shooting angle to cover the entire imaging area, collecting imaging data at each angle, and generating a multi-angle imaging data set; comparing the image grayscale value in the multi-angle imaging data set with a preset grayscale reflectivity curve, adjusting the grayscale value pixel by pixel to match the standard curve, calculating the reflectivity for each pixel, and obtaining a pixel reflectivity matrix. The present invention improves the accuracy of lighting effect evaluation, enhances the adaptability and real-time adjustment capability to complex lighting systems, and promotes the practicality and economy of lighting design.

Description

Technical Field

[0001] The invention relates to the technical field of optical property testing, and in particular to a method for measuring and analyzing imaging illumination distribution. Background Art

[0002] The field of optical property testing technology involves the use of various methods and instruments to evaluate the optical properties of materials. Research in this field focuses on measuring and analyzing how materials affect the propagation of light, including reflection, refraction, scattering and absorption of light. Optical testing can be applied to a variety of fields, such as lighting engineering, vision science, materials science, and the development of optoelectronic devices. The measurement of imaging illuminance distribution is used to measure and analyze the illuminance distribution of light emitted by a light source at different locations. By using a illuminance meter or related optical sensor system to measure the light intensity, it helps to evaluate the uniformity and efficiency of the light source, as well as the impact of light on the environment. It has a wide range of applications, such as in the design of lighting systems, monitoring plant growth environments, or evaluating the uniformity of light output of display devices.

[0003] However, existing technologies often only focus on a single angle or local area in light measurement, resulting in an incomplete understanding of the overall light distribution. The lack of multi-angle data support limits the evaluation of light source uniformity and efficiency, which may lead to a gap between the actual effect and the design goal. For example, the lighting design of museums or galleries often requires more detailed lighting data to ensure the protection and display of artworks. Such shortcomings not only waste resources, but also reduce efficiency. Therefore, improvements are needed. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings in the prior art and to propose a measurement and analysis method for imaging illumination distribution.

[0005] In order to achieve the above object, the present invention adopts the following technical solution, a method for measuring and analyzing imaging illumination distribution, comprising the following steps:

[0006] An imaging tester is used to shoot uniform diffuse reflective white screens one by one, and the exposure parameters and focal length are controlled to ensure a clear image. The shooting angle is gradually adjusted to cover the entire imaging area, and imaging data at each angle is collected to generate a multi-angle imaging data set.

[0007] Comparing the image grayscale values ​​in the multi-angle imaging data set with a preset grayscale reflectivity curve, adjusting the grayscale values ​​pixel by pixel to match the standard curve, calculating the reflectivity for each pixel, and obtaining a pixel reflectivity matrix;

[0008] Based on the pixel reflectivity matrix, by calculating the light reflection intensity of each pixel, the illumination value of each pixel is inverted angle by angle to obtain the multi-angle illumination value;

[0009] Utilizing the multi-angle illumination values, calculating the standard deviation and range of the illumination values, evaluating the illumination distribution uniformity in the imaging area through statistical indicators, and generating an illumination uniformity index;

[0010] Based on the illumination uniformity index, the illumination distribution data is analyzed, and by comparing the illumination data of each part with the expected light source output, the light source placement and angle are adjusted to optimize the lighting effect, and the light source characteristic analysis results are obtained.

[0011] Preferably, the steps of acquiring the multi-angle imaging data set are:

[0012] Use an imaging tester to shoot a uniform diffuse white screen, control exposure parameters and focal length to ensure image clarity, and generate preliminary shooting data;

[0013] Based on the preliminary shooting data, the shooting angle is gradually adjusted to cover the entire imaging area, and the imaging data of each angle is collected to obtain full-angle imaging information;

[0014] The full-angle imaging information is integrated using the formula: Calculate the average imaging information of each angle to obtain a multi-angle imaging data set, where: represents a multi-angle imaging dataset, Representative Imaging information from various angles, Represents the total angle.

[0015] Preferably, the step of obtaining the pixel reflectivity matrix is:

[0016] Comparing the grayscale value of each image in the multi-angle imaging data set with a preset grayscale reflectivity curve to obtain preliminary matching grayscale value information;

[0017] Based on the preliminary matched gray value information, the gray value is adjusted pixel by pixel to match the standard curve, and the adjusted gray value information is obtained by calculating the corrected gray value;

[0018] Based on the adjusted gray value information, the reflectivity is calculated for each pixel to generate a pixel reflectivity matrix using the formula: Calculate the reflectivity of each pixel and get the pixel reflectivity matrix, where: represents the pixel reflectance matrix, Represents the adjusted grayscale value, Represents the reference gray value of the standard curve.

[0019] Preferably, the steps of obtaining the multi-angle illumination values ​​are:

[0020] Based on the pixel reflectivity matrix, the light reflection intensity of each pixel is calculated to obtain preliminary light reflection intensity data;

[0021] Based on the light reflection intensity, the illumination value of each pixel is calculated angle by angle to generate illumination value information for each angle;

[0022] Integrate the illumination value information of each angle to obtain the multi-angle illumination value, using the formula: Calculate the sum of the illuminance at each angle to get the multi-angle illuminance value, where: Represents the multi-angle illumination value, Representative The light reflection intensity at each angle, represents the area coefficient of the corresponding angle, Represents the distance to the light source.

[0023] Preferably, the steps for obtaining the standard deviation of the illumination value are:

[0024] Collect multi-angle illumination values ​​to form an illumination value data set;

[0025] Calculate the mean of the illumination values ​​using the formula: Get the average illumination value, where represents the mean illuminance value, Representative Illuminance value, is the number of illumination values;

[0026] To calculate the standard deviation from the mean, use the formula: Generates the standard deviation of illuminance values, where Represents the standard deviation of the illuminance values, represents the mean illuminance value, Representative Illuminance value, is the number of illumination values.

[0027] Preferably, the steps for obtaining the range of illumination values ​​are:

[0028] Extract the maximum and minimum values ​​from the multi-angle illumination values;

[0029] To calculate the range, use the formula: Get the range of illumination values, where Represents the extreme difference in illumination value, Represents the maximum illumination value, Represents the minimum illumination value;

[0030] The illumination uniformity index is generated through the standard deviation and range of the illumination value to judge the uniformity of the illumination distribution in the imaging area.

[0031] Preferably, the steps for obtaining the illumination uniformity index are:

[0032] Through the calculated standard deviation and range of illumination values, statistical analysis is performed to obtain the statistical data of illumination distribution;

[0033] Based on the uniformity of the statistical data of the illumination distribution, the formula is used: Calculate the illumination uniformity percentage and generate an illumination uniformity evaluation value, where: Represents the illumination uniformity index, Represents the standard deviation of the illuminance values, represents the mean illuminance value;

[0034] Based on the illumination uniformity evaluation value, an illumination uniformity index is formed, using the formula: Calculate the illumination uniformity score and obtain the illumination uniformity index, where: Represents the illumination uniformity index.

[0035] Preferably, the steps of obtaining the light source characteristic analysis result are:

[0036] By using the illumination uniformity index, the effects of the existing light source placement and angle are judged and recorded to obtain preliminary light source characteristic data;

[0037] Based on the preliminary light source characteristic data, comparing the illumination data of each part with the expected light source output, identifying the illumination deviation, and obtaining the deviation data of the illumination from the expected;

[0038] According to the deviation data, the light source placement and angle are adjusted to optimize the lighting effect, and a light source adjustment plan is generated, using the formula: Calculate the illumination deviation percentage and obtain the light source characteristic analysis results, where: Represents the percentage of illumination deviation, represents the measured illuminance value, An illuminance value representing the expected light source output.

[0039] Compared with the prior art, the advantages and positive effects of the present invention are:

[0040] The present invention uses an imaging tester to shoot uniform diffuse reflective white screens one by one to form a multi-angle imaging data set, making the illumination distribution measurement more detailed and comprehensive. By comparing the image grayscale value with the preset grayscale reflectivity curve, the grayscale value is adjusted pixel by pixel to match the standard curve, the reflectivity is calculated, and a pixel reflectivity matrix is ​​generated. The matrix is ​​used to calculate the illumination reflection intensity of each pixel, and the illumination value of each pixel is inverted to form multi-angle illumination values. With the help of these illumination values, the uniformity of illumination distribution is evaluated, and relevant indicators are generated. Finally, by comparing the illumination data with the expected light source output, the light source position and angle are optimized. The accuracy of illumination effect evaluation is improved, the adaptability and real-time adjustment capability to complex lighting systems are enhanced, and the practicality and economy of lighting design are promoted. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a schematic diagram of the steps of the present invention. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0043] See also Figure 1 The present invention provides a technical solution, a method for measuring and analyzing imaging illumination distribution, comprising the following steps:

[0044] An imaging tester is used to shoot uniform diffuse reflective white screens one by one, and the exposure parameters and focal length are controlled to ensure a clear image. The shooting angle is gradually adjusted to cover the entire imaging area, and imaging data at each angle is collected to generate a multi-angle imaging data set.

[0045] Compare the image grayscale values ​​in the multi-angle imaging data set with the preset grayscale reflectivity curve, adjust the grayscale value pixel by pixel to match the standard curve, calculate the reflectivity for each pixel, and obtain the pixel reflectivity matrix;

[0046] Based on the pixel reflectivity matrix, by calculating the light reflection intensity of each pixel, the illumination value of each pixel is inverted angle by angle to obtain the multi-angle illumination value;

[0047] Using multi-angle illumination values, the standard deviation and range of illumination values ​​are calculated, and the illumination distribution uniformity in the imaging area is evaluated through statistical indicators to generate illumination uniformity indicators;

[0048] Based on the illumination uniformity index, analyze the illumination distribution data, compare the illumination data of each part with the expected light source output, adjust the light source placement and angle to optimize the lighting effect, and obtain the light source characteristic analysis results.

[0049] The steps for acquiring the multi-angle imaging dataset are as follows:

[0050] Use an imaging tester to shoot a uniform diffuse white screen, control exposure parameters and focal length to ensure image clarity, and generate preliminary shooting data;

[0051] Based on the preliminary shooting data, the shooting angle is gradually adjusted to cover the entire imaging area, and the imaging data of each angle is collected to obtain full-angle imaging information;

[0052] Integrate all-angle imaging information using the formula: Calculate the average imaging information of each angle to obtain a multi-angle imaging data set, where: represents a multi-angle imaging dataset, Representative Imaging information from various angles, Represents the total angle.

[0053] Specifically, an imaging tester is used to shoot a uniform diffuse reflective white screen, and the exposure parameters and focal length are controlled to ensure a clear image. This process involves setting parameters such as exposure time, aperture size, and sensitivity to be suitable for the white screen with high reflectivity to avoid overexposure or underexposure, and to ensure that the resulting image has sufficient quality for subsequent analysis. This requires that the optical system and sensor of the imaging tester be able to be adjusted to the optimal state. At the same time, the operator needs to monitor the ambient light conditions to ensure that the light is evenly irradiated on the white screen. Through this series of operations, preliminary shooting data is generated.

[0054] Gradually adjust the shooting angle to cover the entire imaging area. This operation includes changing the azimuth and elevation of the camera in three-dimensional space to ensure that the reflected image of the white screen is captured from different perspectives. During this process, the operator needs to gradually optimize the shooting angle based on real-time preview and imaging quality feedback. The focus is on eliminating image distortion or uneven coverage caused by angle deviation. Through continuous adjustment and monitoring, imaging data at each angle is collected to obtain full-angle imaging information to ensure the accuracy of subsequent analysis.

[0055] formula: The calculation process:

[0056] The calculation of multi-angle imaging data sets uses an averaging algorithm, where Representatives from The image data obtained by shooting at different angles, It is the total number of shooting angles of the image. The average algorithm calculates the overall imaging quality index by taking the arithmetic mean of the image data from all angles.

[0057] There are 5 different shooting angles. The image data obtained from each angle are 20, 30, 25, 35, and 40 unit grayscale values. According to the formula, first add up these values ​​to get , then divide by the angle , calculated .

[0058] The results show that the average imaging information of all angles is 30 units of grayscale value, reflecting the overall performance of the imaging system at different angles.

[0059] The steps to obtain the pixel reflectance matrix are:

[0060] Compare the grayscale value of each image with a preset grayscale reflectance curve from the multi-angle imaging data set to obtain preliminary matching grayscale value information;

[0061] Based on the preliminary matched gray value information, the gray value is adjusted pixel by pixel to match the standard curve, and the adjusted gray value information is obtained by calculating the corrected gray value;

[0062] Based on the adjusted gray value information, the reflectivity is calculated for each pixel to generate a pixel reflectivity matrix using the formula: Calculate the reflectivity of each pixel and get the pixel reflectivity matrix, where: represents the pixel reflectance matrix, Represents the adjusted grayscale value, Represents the reference gray value of the standard curve.

[0063] Specifically, the grayscale value of each image in the multi-angle imaging data set is compared with the preset grayscale reflectivity curve. First, a correspondence table between grayscale value and reflectivity needs to be established. This table lists the corresponding standard reflectivity based on different levels of grayscale value. In order to achieve this, it is necessary to systematically shoot the white screen and record the image data under different exposure conditions. These data are preliminarily processed, including color correction and grayscale adjustment, to form a complete image data set. Through this data set, each image is analyzed separately, the grayscale value of the image is extracted, and it is compared with the preset grayscale reflectivity curve. During the comparison process, the comparison tool in the image processing software is used to make a preliminary estimate of the reflectivity based on the grayscale value difference to obtain preliminary matching grayscale value information.

[0064] Adjust the grayscale value pixel by pixel to match the standard curve. According to the grayscale value information of the preliminary match, adjust the grayscale value of each pixel one by one. The purpose of the adjustment is to make the grayscale value of each pixel closer to the corresponding value on the standard curve. This process needs to be based on the mathematical model between the grayscale value and the reflectivity. The specific operation includes using linear or nonlinear adjustment methods to make subtle adjustments to the grayscale value. The choice of adjustment method is based on the difference between the current grayscale value of the pixel and the standard curve. After each adjustment, it is necessary to recalculate the deviation between the adjusted grayscale value and the standard curve to ensure the correctness of the adjustment direction and amplitude, and finally obtain the adjusted grayscale value information.

[0065] formula: The calculation process:

[0066] The formula is used to calculate the reflectivity of each pixel, where represents the pixel reflectance, is the adjusted grayscale value, is the gray value corresponding to the standard curve, where and These are actual data obtained through image processing software.

[0067] The adjusted grayscale value of a specific pixel is 120, while the corresponding standard curve grayscale value is 100. Substituting the formula into the calculation, the reflectivity of the pixel is 1.2. This result shows that the reflectivity of the pixel is higher than the standard grayscale reflectivity, reflecting the reflective characteristics of the point during the imaging process.

[0068] The steps for obtaining multi-angle illumination values ​​are:

[0069] Based on the pixel reflectivity matrix, the light reflection intensity of each pixel is calculated to obtain preliminary light reflection intensity data;

[0070] Based on the light reflection intensity, the illumination value of each pixel is calculated at each angle to generate the illumination value information for each angle;

[0071] Integrate the illumination value information of each angle to obtain the multi-angle illumination value, using the formula: Calculate the sum of the illuminance at each angle to get the multi-angle illuminance value, where: Represents the multi-angle illumination value, Representative The light reflection intensity at each angle, represents the area coefficient of the corresponding angle, Represents the distance to the light source.

[0072] Specifically, based on the pixel reflectance matrix, the light reflection intensity of each pixel is obtained by measurement and calculation. First, the reflectance data of each pixel under different lighting conditions are collected by imaging instruments, and the average reflectance of each pixel is calculated based on these data. These reflectance data will serve as the basis for the reflection intensity calculation. Then, the physical model is applied to link these reflectance data with the actual illumination intensity of the light source to ensure that each calculated value can accurately reflect the lighting conditions of each pixel in the actual environment. This process includes consideration of light scattering and absorption rate. During the calculation process, the light intensity of each pixel is calculated using the formula Calculated, where Indicates the light intensity, represents the reflectivity, It is a constant adjusted according to the material characteristics. Through this method, preliminary light reflection intensity data is obtained.

[0073] Starting from the light reflection intensity data, the illuminance value at each angle is calculated by angle-weighting the light intensity of each pixel. The pixel illuminance at each angle is calculated independently. Taking into account that different angles of the diffuse reflection surface will affect the light intensity, the illuminance value at each angle is calculated by taking the average value of the light reflection intensity of each pixel after angle weighting. In this process, the calculation of the illuminance value at each angle not only considers the intensity and distance of the light source, but also considers the changes in the impact of the angle on the illuminance, which ensures the practicality and accuracy of the data obtained. The illuminance value information for each angle finally generated provides basic data for further analysis. By statistically analyzing these data, we can better understand the uniformity of light distribution and potential areas for improvement.

[0074] formula The calculation process:

[0075] Represents the multi-angle illumination value, It is The light reflection intensity at each angle, represents the area coefficient of the corresponding angle, is the distance to the light source. For example, there are 5 angles, and the reflection intensity at each angle is The corresponding area coefficients are 200, 180, 190, 210, 205. The distance is 1, 0.9, 1.1, 1.05, 0.95. is 2m. Then the illumination value at each angle is calculated as:

[0076] The results show that, considering the changes in the light reflection intensity and area coefficient at each angle, as well as the fixed value of the light source distance, the multi-angle illuminance value obtained by comprehensive calculation is 250.675, which reflects the sum of the multi-angle illuminance values ​​under the set parameters.

[0077] The steps to obtain the standard deviation of the illumination value are:

[0078] Collect multi-angle illumination values ​​to form an illumination value data set;

[0079] Calculate the mean of the illumination values ​​using the formula: Get the average illuminance value, where represents the mean illuminance value, Representative Illuminance value, is the number of illumination values;

[0080] To calculate the standard deviation from the mean, use the formula: Generates the standard deviation of illuminance values, where Represents the standard deviation of the illuminance values, represents the mean illuminance value, Representative Illuminance value, is the number of illumination values.

[0081] Specifically, to collect multi-angle illuminance values ​​to form a data set, first deploy imaging instruments to collect illuminance information in all directions, and systematically measure the test environment from different angles and positions. Each measurement point needs to record the time, angle and specific light intensity value in detail to ensure the comprehensiveness and accuracy of the data, and provide the necessary original data basis for subsequent data analysis. The key to this process is how to ensure that the collected data can represent the lighting conditions of the entire imaging area. The collection of each data point must be strictly carried out in accordance with the preset measurement protocol to ensure the consistency and repeatability of the data. In addition, the collected data needs to be preliminarily screened and cleaned to exclude obvious outliers or erroneous data to ensure the quality of the data set. This data set provides the basis for the subsequent calculation of the mean and standard deviation of the illuminance value.

[0082] formula The calculation process:

[0083] Obtain the illumination value at each angle through actual measurement ,in Indicates a specific angle. is the total measured angle.

[0084] There are 5 angles with measured illuminance values ​​of 100, 200, 150, 250, and 300 lx respectively. Substituting these values ​​into the formula to calculate the mean ,Right now This mean indicates that the average illuminance value is 200 lx and provides a basis for calculating the standard deviation.

[0085] formula The calculation process:

[0086] Continue to use the mean calculated above , using the same illumination data , substitute into the standard deviation formula for calculation.

[0087] The specific steps are as follows:

[0088] The square of the difference between each illumination value and the mean is , , , , , then average these values ​​and take the square root to get:

[0089]

[0090] This standard deviation indicates the degree of dispersion of the data. The numerical results indicate that the consistency of the illumination distribution in the test environment is high, which is crucial for evaluating the uniformity of the illumination distribution in the imaging area.

[0091] The steps to obtain the range of illumination values ​​are as follows:

[0092] Extract the maximum and minimum values ​​from the multi-angle illumination values;

[0093] To calculate the range, use the formula: Get the range of illumination values, where Represents the extreme difference in illumination value, Represents the maximum illumination value, Represents the minimum illumination value;

[0094] The illumination uniformity index is generated through the standard deviation and range of the illumination value to judge the uniformity of the illumination distribution in the imaging area.

[0095] Specifically, the maximum and minimum values ​​are extracted from the multi-angle illuminance values ​​to evaluate the range of illuminance distribution. First, the highest and lowest illuminance values ​​measured at each angle need to be screened out from the collected multi-angle illuminance data. This screening process must ensure the integrity and accuracy of the data to avoid accurate extraction of extreme values ​​due to data errors. During the screening process, each data point must be verified to confirm that it is a valid measurement result, rather than abnormal data caused by equipment errors or operational errors. This process ensures that the extracted maximum and minimum values ​​can truly reflect the illuminance limits in the imaging area, providing an accurate data basis for subsequent calculation of the range.

[0096] formula The calculation process:

[0097] The maximum illuminance value extracted from the data is 500lx and the minimum illuminance value is 150lx, so the calculation formula for the range is: This range represents the maximum fluctuation range of the illumination distribution in the imaging area and is an important indicator for judging the uniformity of illumination. A larger range may indicate that there is obvious uneven illumination in the imaging area. This result indicates that the illumination distribution is relatively uneven and further investigation of the light source layout or environmental factors is required.

[0098] The illumination uniformity index is generated through the standard deviation and range of the illumination value to judge the uniformity of the illumination distribution in the imaging area. In this step, the calculated illumination standard deviation and range are first used to establish the illumination uniformity index. This index is evaluated by comparing the size of the standard deviation and the range. The illumination uniformity evaluation requires a detailed analysis of the ratio of these two parameters and a comparison with the preset uniformity standard. During this analysis process, the value of each calculation needs to be recorded in detail to ensure the accuracy of the evaluation result.

[0099] The steps to obtain the illumination uniformity index are:

[0100] Through the calculated standard deviation and range of illumination values, statistical analysis is performed to obtain the statistical data of illumination distribution;

[0101] Based on the uniformity of the statistical data of the illumination distribution, the formula is adopted: Calculate the illumination uniformity percentage and generate an illumination uniformity evaluation value, where: Represents the illumination uniformity index, Represents the standard deviation of the illuminance values, represents the mean illuminance value;

[0102] Based on the illumination uniformity evaluation value, the illumination uniformity index is formed using the formula: Calculate the illumination uniformity score and obtain the illumination uniformity index, where: Represents the illumination uniformity index.

[0103] Specifically, the standard deviation and range of the calculated illumination values ​​are used to conduct a preliminary analysis of the illumination distribution using statistical analysis methods. These data are input into statistical software to perform basic data descriptive analysis, such as calculating the mean, median, mode, and distribution type of the data, and analyzing the impact of extreme values ​​in the data set on the uniformity of illumination distribution. The preliminary results show the distribution of illumination values ​​and their contribution to the overall uniformity.

[0104] formula The calculation process:

[0105] in is the standard deviation of the illuminance values, is the mean of the illuminance values. Both parameters are calculated from the actual measured illuminance values ​​at multiple angles.

[0106] The illumination value data is as follows: [20, 22, 23, 21, 22], first calculate the mean , then calculate the sum of the squares of the deviations of each value from the mean, average them, and take the square root to get the standard deviation:

[0107]

[0108] Substituting these values ​​into the formula we get ,This result shows that the illumination distribution is relatively uniform, and the correlation with the step result is the illumination uniformity percentage obtained by calculation, which can quantitatively reflect the uniformity level of illumination distribution;

[0109] formula The calculation process:

[0110] in is the illuminance uniformity percentage calculated previously, which is 4.72% in this example, and the final uniformity score is calculated from this , indicating that the uniformity of illumination is very high. This process involves the actual statistical analysis obtained from The direct use of the values ​​​​does not require additional data acquisition or, for example. The calculation results show that the illumination distribution in the imaging area has a high uniformity, which is crucial for optimizing the light source configuration and ensuring image quality. The correlation between the numerical results and the step results lies in the direct derivation of the illumination uniformity score from the illumination uniformity percentage.

[0111] The steps to obtain the light source characteristic analysis results are:

[0112] Through the illumination uniformity index, judge and record the effect of the existing light source placement and angle, and obtain preliminary light source characteristic data;

[0113] Based on the preliminary light source characteristic data, compare the illumination data of each part with the expected light source output, identify the illumination deviation, and obtain the deviation data between the illumination and the expected;

[0114] According to the deviation data, adjust the light source position and angle to optimize the lighting effect and generate a light source adjustment plan using the formula: Calculate the illumination deviation percentage and obtain the light source characteristic analysis results, where: Represents the percentage of illumination deviation, represents the measured illuminance value, An illuminance value representing the expected light source output.

[0115] Specifically, through the generated illumination uniformity index, the effects of the existing light source placement and angle are evaluated and recorded to obtain preliminary light source characteristic data. First, the illumination measurement value at each angle is obtained, and analysis is performed to determine whether the effect of the existing light source meets the expected illumination requirements. This includes statistical analysis of illumination values, such as average illumination, coefficient of variation of illumination, etc., to evaluate the degree of optimization of light source placement; then, the placement positions and angles of all light sources are recorded and compared with the illumination uniformity index to analyze the specific effects of different positions and angles on illumination uniformity. In this process, the coordinates of the light source position, the degree of the angle and the corresponding illumination value are recorded in detail to establish a detailed light source characteristic database and obtain preliminary light source characteristic data.

[0116] Comparing the illuminance data of each part with the expected light source output, identifying the illuminance deviation, and obtaining the illuminance and expected deviation data involves extracting the illuminance data of each part from the multi-angle illuminance values, and comparing it with the light source output value preset in the design phase. Determine whether the illuminance at each angle reaches the expected target through difference analysis. During the difference analysis process, specifically calculate the difference between the actual illuminance and the expected illuminance at each measuring point, and evaluate the statistical distribution of these differences, such as calculating the mean and standard deviation of the differences, to judge the consistency and reliability of the light source output, thereby obtaining the illuminance and expected deviation data.

[0117] formula The calculation process:

[0118] Determine the actual illuminance at each measurement point and the illuminance of the expected light source output The actual illuminance can be directly measured by a photometer, and the expected illuminance is determined according to the design specification or the data provided by the light source manufacturer. The illuminance deviation percentage of each measuring point is calculated. To evaluate and adjust the light source position and angle as needed;

[0119] The actual illuminance at a particular location is 450 lx, while the expected illuminance is 500 lx. The calculation of is as follows: This result indicates that the illumination of the light source at this position is lower than expected, and the position or output of the light source needs to be adjusted to achieve a more uniform illumination distribution.

[0120] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for measuring and analyzing imaging illumination distribution, characterized in that: The following steps are involved: An imaging tester is used to shoot uniform diffuse reflective white screens one by one, and the exposure parameters and focal length are controlled to ensure a clear image. The shooting angle is gradually adjusted to cover the entire imaging area, and imaging data at each angle is collected to generate a multi-angle imaging data set. Comparing the image grayscale values ​​in the multi-angle imaging data set with a preset grayscale reflectivity curve, adjusting the grayscale values ​​pixel by pixel to match the standard curve, calculating the reflectivity for each pixel, and obtaining a pixel reflectivity matrix; Based on the pixel reflectivity matrix, by calculating the light reflection intensity of each pixel, the illumination value of each pixel is inverted angle by angle to obtain the multi-angle illumination value; Utilizing the multi-angle illumination values, calculating the standard deviation and range of the illumination values, evaluating the illumination distribution uniformity in the imaging area through statistical indicators, and generating an illumination uniformity index; Based on the illumination uniformity index, the illumination distribution data is analyzed, and by comparing the illumination data of each part with the expected light source output, the light source placement and angle are adjusted to optimize the lighting effect, and the light source characteristic analysis results are obtained.

2. The method for measuring and analyzing imaging illumination distribution according to claim 1, characterized in that: The steps of acquiring the multi-angle imaging data set are: Use an imaging tester to shoot a uniform diffuse white screen, control exposure parameters and focal length to ensure image clarity, and generate preliminary shooting data; Based on the preliminary shooting data, the shooting angle is gradually adjusted to cover the entire imaging area, and the imaging data of each angle is collected to obtain full-angle imaging information; The full-angle imaging information is integrated using the formula: Calculate the average imaging information of each angle to obtain a multi-angle imaging data set, where: represents a multi-angle imaging dataset, Representative Imaging information from various angles, Represents the total angle.

3. The method for measuring and analyzing imaging illumination distribution according to claim 1, characterized in that: The steps for obtaining the pixel reflectivity matrix are: Comparing the grayscale value of each image in the multi-angle imaging data set with a preset grayscale reflectivity curve to obtain preliminary matching grayscale value information; Based on the preliminary matched gray value information, the gray value is adjusted pixel by pixel to match the standard curve, and the adjusted gray value information is obtained by calculating the corrected gray value; Based on the adjusted gray value information, the reflectivity is calculated for each pixel to generate a pixel reflectivity matrix using the formula: Calculate the reflectivity of each pixel and get the pixel reflectivity matrix, where: represents the pixel reflectance matrix, Represents the adjusted grayscale value, Represents the reference gray value of the standard curve.

4. The method for measuring and analyzing imaging illumination distribution according to claim 1, characterized in that: The steps for obtaining the multi-angle illumination values ​​are: Based on the pixel reflectivity matrix, the light reflection intensity of each pixel is calculated to obtain preliminary light reflection intensity data; Based on the light reflection intensity, the illumination value of each pixel is calculated angle by angle to generate illumination value information for each angle; Integrate the illumination value information of each angle to obtain the multi-angle illumination value, using the formula: Calculate the sum of the illuminance at each angle to get the multi-angle illuminance value, where: Represents the multi-angle illumination value, Representative The light reflection intensity at each angle, represents the area coefficient of the corresponding angle, Represents the distance to the light source.

5. The method for measuring and analyzing imaging illumination distribution according to claim 1, characterized in that: The steps to obtain the standard deviation of the illumination value are: Collect multi-angle illumination values ​​to form an illumination value data set; Calculate the mean of the illumination values ​​using the formula: Get the average illuminance value, where represents the mean illuminance value, Representative Illuminance value, is the number of illumination values; To calculate the standard deviation from the mean, use the formula: Generates the standard deviation of illuminance values, where Represents the standard deviation of the illuminance values, represents the mean illuminance value, Representative Illuminance value, is the number of illumination values.

6. The method for measuring and analyzing imaging illumination distribution according to claim 1, characterized in that: The steps to obtain the range of illumination values ​​are as follows: Extract the maximum and minimum values ​​from the multi-angle illumination values; To calculate the range, use the formula: Get the range of illumination values, where Represents the extreme difference in illumination value, Represents the maximum illumination value, Represents the minimum illumination value; The illumination uniformity index is generated through the standard deviation and range of the illumination value to judge the uniformity of the illumination distribution in the imaging area.

7. The method for measuring and analyzing imaging illumination distribution according to claim 1, characterized in that: The steps for obtaining the illumination uniformity index are: Through the calculated standard deviation and range of illumination values, statistical analysis is performed to obtain the statistical data of illumination distribution; Based on the uniformity of the statistical data of the illumination distribution, the formula is used: Calculate the illumination uniformity percentage and generate an illumination uniformity evaluation value, where: Represents the illumination uniformity index, Represents the standard deviation of the illuminance values, represents the mean illuminance value; Based on the illumination uniformity evaluation value, an illumination uniformity index is formed, using the formula: Calculate the illumination uniformity score and obtain the illumination uniformity index, where: Represents the illumination uniformity index.

8. The method for measuring and analyzing imaging illumination distribution according to claim 1, characterized in that: The steps for obtaining the light source characteristic analysis result are: By using the illumination uniformity index, the effects of the existing light source placement and angle are judged and recorded to obtain preliminary light source characteristic data; Based on the preliminary light source characteristic data, comparing the illumination data of each part with the expected light source output, identifying the illumination deviation, and obtaining the deviation data of the illumination from the expected; According to the deviation data, the light source placement and angle are adjusted to optimize the lighting effect, and a light source adjustment plan is generated using the formula: Calculate the illumination deviation percentage and obtain the light source characteristic analysis results, where: Represents the percentage of illumination deviation, represents the measured illuminance value, An illuminance value representing the expected light source output.

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