A method, device, system and storage medium for calculating stimulus value

Abstract

The present application discloses a stimulus value calculation method, device, system and storage medium for calculating stimulus values ​​of different filters. The present application method includes: shooting the first, second and third integrating sphere image sets of the filters under their respective exposure time sets; shooting the fourth integrating sphere image set of the Z filter under the exposure time corresponding to the X filter; taking the grayscale mean of the integrating sphere images of the first, second, third and fourth integrating sphere image sets; detecting the X / Y / Z calibration stimulus value of the integrating sphere; fitting the image grayscale mean of the second integrating sphere image set with the corresponding exposure time set to obtain a first fitting straight line; fitting the image grayscale mean of the third integrating sphere image set with the corresponding exposure time set to obtain a second fitting straight line; fitting the image grayscale mean of the first and fourth integrating sphere image sets with the corresponding exposure time to obtain a third fitting straight line; calculating the X, Y and Z stimulus values ​​to be measured.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of chromaticity measurement, and in particular to a stimulus value calculation method, device, system and storage medium. Background Art

[0002] In modern scientific research, industrial production and many application fields, light is an extremely important physical phenomenon and energy form, and accurate measurement of its characteristics is of irreplaceable importance. In scientific research, whether it is the in-depth exploration of optical phenomena in physics, such as the study of light interference, diffraction, polarization and other properties, or the analysis of the optical activity and photochemical reactions of substances in the field of chemistry, or the optical imaging of biological tissues and the study of photosynthesis mechanisms in biology, all are inseparable from the accurate measurement of light characteristics. Industrial production is highly dependent on the accurate measurement of light characteristics. In the lighting industry, accurate measurement of light characteristics such as luminous flux, color rendering, and color temperature of light sources is the key to producing high-quality lamps.

[0003] Traditional colorimetric devices may be interfered by various factors during the measurement process, such as the differences in the characteristics of different filters and inaccurate control of exposure time. When measuring the colorimetry involving multiple filters (such as X / Y / Z filters), since each filter has different light transmission and absorption characteristics, it is necessary to accurately consider their responses under different exposure times.

[0004] Existing measurement technologies lack a systematic method to comprehensively consider the image data of multiple filters at different exposure times. When measuring the chromaticity of the object to be measured, it is difficult to accurately combine multiple factors such as the characteristics of the filter, exposure time, and grayscale information of the integrating sphere image for precise calculation. During the measurement process, there is a lack of effective integration methods for the relationship between different filters and their connection with the calibrated stimulus values. With the growing demand for high-precision chromaticity measurement, existing technologies are difficult to meet the requirements of accurately measuring the X / Y / Z stimulus values ​​to be measured. In addition, traditional chromaticity measurement is relatively simple in data processing and does not fully utilize the relationship between the image grayscale mean and exposure time to improve the accuracy of the measurement. Summary of the invention

[0005] The present application discloses a stimulation value calculation method, device, system and storage medium, which are used to calculate the stimulation values ​​of different filters.

[0006] The first aspect of the present application discloses a method for calculating a stimulus value, comprising:

[0007] Using a filter wheel colorimeter to photograph a first integrating sphere image set, a second integrating sphere image set, and a third integrating sphere image set of the X / Y / Z filters at respective exposure time sets;

[0008] Using a filter wheel colorimeter to photograph a fourth integrating sphere image set of the Z filter at an exposure time corresponding to the X filter;

[0009] Taking grayscale mean values ​​of the first integrating sphere image set, the second integrating sphere image set, the third integrating sphere image set, and the fourth integrating sphere image set integrating sphere images;

[0010] Detect the X / Y / Z calibration stimulus value of the integrating sphere;

[0011] Fitting the image grayscale mean of the second integrating sphere image set with the corresponding exposure time set to obtain a first fitting straight line;

[0012] Fitting the image grayscale mean of the third integrating sphere image set with the corresponding exposure time set to obtain a second fitting straight line;

[0013] Fitting the image grayscale means of the first integrating sphere image set and the fourth integrating sphere image set with the corresponding exposure time to obtain a third fitting straight line;

[0014] The X stimulus value to be measured, the Y stimulus value to be measured and the Z stimulus value to be measured are calculated according to the X / Y / Z calibration stimulus values, the first fitting straight line, the second fitting straight line and the third fitting straight line.

[0015] Optionally, before using a filter wheel colorimeter to capture the first integrating sphere image set, the second integrating sphere image set, and the third integrating sphere image set of the X / Y / Z filters at respective exposure time sets, the stimulus value calculation method further includes:

[0016] Determining a first light transmittance, a second light transmittance, and a third light transmittance of the X / Y / Z filter;

[0017] Determine the first eye stimulation weight, the second eye stimulation weight and the third eye stimulation weight of the X / Y / Z filter;

[0018] A self-exposure time set of the X / Y / Z filters is calculated according to the first transmittance, the second transmittance, the third transmittance, the first human eye stimulation weight, the second human eye stimulation weight, and the third human eye stimulation weight.

[0019] Optionally, before taking grayscale mean values ​​of the integrating sphere images of the first integrating sphere image set, the second integrating sphere image set, the third integrating sphere image set, and the fourth integrating sphere image set, the method further includes:

[0020] Each image is denoised using the median filter algorithm.

[0021] Optionally, each image is denoised using a median filter algorithm, including:

[0022] Determine the window size of the median filter;

[0023] For each integrating sphere image to be processed, start from the upper left corner of the image with the set window size and move the window pixel by pixel in the order from left to right and from top to bottom;

[0024] In each window, sort the grayscale values ​​of all pixels in the window;

[0025] Select the sorted middle value as the new grayscale value of the center pixel of the window;

[0026] Complete the median filtering denoising process for the entire image.

[0027] Optionally, calculating the X stimulus value to be measured, the Y stimulus value to be measured, and the Z stimulus value to be measured according to the X / Y / Z calibration stimulus values, the first fitting straight line, the second fitting straight line, and the third fitting straight line includes:

[0028] Substitute the exposure time and the grayscale to be tested into the X stimulus value fitting formula to obtain the X stimulus value;

[0029] Substitute the exposure time and the grayscale to be tested into the Y stimulus value fitting formula to obtain the Y stimulus value;

[0030] Substitute the exposure time and the grayscale to be tested into the Z stimulus value fitting formula to obtain the Z stimulus value.

[0031] The second aspect of the present application discloses a device for calculating a stimulus value, comprising:

[0032] A first photographing unit is used to photograph a first integrating sphere image set, a second integrating sphere image set and a third integrating sphere image set of the X / Y / Z filters at respective exposure time sets using a filter wheel colorimeter;

[0033] A second shooting unit is used to shoot a fourth integrating sphere image set of the Z filter at an exposure time corresponding to the X filter using a filter wheel colorimeter;

[0034] A value taking unit, used for taking grayscale mean values ​​of the first integrating sphere image set, the second integrating sphere image set, the third integrating sphere image set and the fourth integrating sphere image set integrating sphere images;

[0035] A detection unit, used to detect the X / Y / Z calibration stimulus values ​​of the integrating sphere;

[0036] A first fitting unit is used to fit the image grayscale mean of the second integrating sphere image set with the corresponding exposure time set to obtain a first fitting straight line;

[0037] A second fitting unit is used to fit the image grayscale mean value of the third integrating sphere image set with the corresponding exposure time set to obtain a second fitting straight line;

[0038] A third fitting unit is used to fit the image grayscale mean values ​​of the first integrating sphere image set and the fourth integrating sphere image set with the corresponding exposure time to obtain a third fitting straight line;

[0039] The calculation unit is used to calculate the X stimulus value to be measured, the Y stimulus value to be measured and the Z stimulus value to be measured according to the X / Y / Z calibration stimulus value, the first fitting straight line, the second fitting straight line and the third fitting straight line.

[0040] Optionally, before the first shooting unit, the device further includes:

[0041] A first determining unit, used to determine a first light transmittance, a second light transmittance and a third light transmittance of the X / Y / Z filter;

[0042] A second determination unit, used to determine a first human eye stimulation weight, a second human eye stimulation weight, and a third human eye stimulation weight of an X / Y / Z filter;

[0043] The set unit is used to calculate the self-exposure time set of the X / Y / Z filter according to the first transmittance, the second transmittance, the third transmittance, the first human eye stimulation weight, the second human eye stimulation weight and the third human eye stimulation weight.

[0044] Optionally, before the value obtaining unit, the device further includes:

[0045] The denoising unit is used to perform denoising on each image using a median filtering algorithm.

[0046] Optional, denoising unit, including:

[0047] A determination module, used to determine the window size of the median filter;

[0048] A moving module is used to move the window pixel by pixel from left to right and from top to bottom starting from the upper left corner of each integrating sphere image to be processed with a set window size;

[0049] A sorting module is used to sort the grayscale values ​​of all pixels in each window;

[0050] A selection module is used to select the sorted middle value as the new gray value of the center pixel of the window;

[0051] The completion module is used to complete the median filtering denoising process for the entire image.

[0052] Optionally, a computing unit, including:

[0053] Substitute the exposure time and the grayscale to be tested into the X stimulus value fitting formula to obtain the X stimulus value;

[0054] Substitute the exposure time and the grayscale to be tested into the Y stimulus value fitting formula to obtain the Y stimulus value;

[0055] Substitute the exposure time and the grayscale to be tested into the Z stimulus value fitting formula to obtain the Z stimulus value.

[0056] The third aspect of the present application provides a system for calculating a stimulus value, comprising:

[0057] Processor, memory, input-output unit, and bus;

[0058] The processor is connected to the memory, the input and output unit, and the bus;

[0059] The memory stores a program, and the processor calls the program to execute the first aspect and any optional method of the first aspect.

[0060] A fourth aspect of the present application provides a computer-readable storage medium, on which a program is stored. When the program is executed on a computer, the program executes the first aspect and any optional processing method of the first aspect.

[0061] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0062] First, the present application comprehensively considers the image data of multiple filters at different exposure times, and can accurately combine multiple factors such as filter characteristics, exposure time, and grayscale information of the integrating sphere image for calculation. This systematic measurement method overcomes the limitations of traditional measurement technology, reduces the measurement errors caused by not comprehensively considering these factors, and thus improves the accuracy of colorimetric measurement.

[0063] Secondly, by effectively integrating the relationship between different filters and the relationship between different filters and the calibration stimulus values, the demand for high-precision colorimetric measurement can be met. In the context of increasing requirements for colorimetric measurement accuracy in modern industrial production and scientific research, this application can provide more accurate X / Y / Z stimulus values ​​to be measured.

[0064] Finally, the relationship between the grayscale mean value and the exposure time of the image is fully utilized, and the conversion coefficient and weight coefficient are obtained by fitting the grayscale mean value and exposure time of the image under different filters, so that the X, Y, and Z stimulus values ​​can be accurately obtained, and the measurement accuracy is improved. Compared with the simpler data processing of traditional colorimetric measurement, this data processing method can more effectively extract accurate information related to colorimetric measurement from image data, further improving the reliability of the measurement results. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0066] Figure 1 A schematic diagram of an embodiment of the method for calculating the stimulus value of the present application;

[0067] Figure 2 A schematic diagram of an embodiment of a method for calculating a self-exposure time set of an X / Y / Z filter in the present application;

[0068] Figure 3 A schematic diagram of an embodiment of a method for denoising an image according to the present application;

[0069] Figure 4 This is a schematic diagram of another embodiment of the method for performing denoising using a median filtering algorithm in the present application;

[0070] Figure 5 A schematic diagram of another embodiment of a method for calculating an X stimulus value to be measured, a Y stimulus value to be measured, and a Z stimulus value to be measured according to the present application;

[0071] Figure 6 A schematic diagram of an embodiment of a device for calculating stimulus value of the present application;

[0072] Figure 7 A schematic diagram of an embodiment of a system for calculating stimulus values ​​of the present application. DETAILED DESCRIPTION

[0073] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0074] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0075] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0076] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0077] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0078] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0079] Existing measurement technologies lack a systematic method to comprehensively consider the image data of multiple filters at different exposure times. When measuring the chromaticity of the object to be measured, it is difficult to accurately combine multiple factors such as the characteristics of the filter, exposure time, and grayscale information of the integrating sphere image for precise calculation. During the measurement process, there is a lack of effective integration methods for the relationship between different filters and their connection with the calibrated stimulus values. With the growing demand for high-precision chromaticity measurement, existing technologies are difficult to meet the requirements of accurately measuring the X / Y / Z stimulus values ​​to be measured. In addition, traditional chromaticity measurement is relatively simple in data processing and does not fully utilize the relationship between the image grayscale mean and exposure time to improve the accuracy of the measurement.

[0080] Based on this, the present application discloses a stimulation value calculation method, device, system and storage medium for calculating the stimulation values ​​of different filters.

[0081] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the present application. Obviously, the described embodiments are only 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.

[0082] The method of the present application can be applied to a server, a device, a terminal or other devices with logic processing capabilities, and the present application does not limit this. For the convenience of description, the following description is made by taking the execution subject as an example of a terminal.

[0083] See also Figure 1 The present application provides an embodiment of a method for calculating a stimulus value, comprising:

[0084] 101. Using a filter wheel colorimeter to photograph a first integrating sphere image set, a second integrating sphere image set, and a third integrating sphere image set of the X / Y / Z filters at respective exposure time sets;

[0085] The exposure time set of the X / Y / Z filters is determined according to the characteristics of the equipment and the measurement object and based on a preliminary estimate of the reflectivity or transmittance range of the measurement object and the sensitivity range of the colorimeter. Different wavelengths of light of different filters have different characteristics, so the exposure time is also different.

[0086] Install the X-ray filter on the filter wheel of the filter wheel colorimeter, ensuring that it is firmly installed and the optical path is aligned. Set the exposure time of the colorimeter to 10ms, turn on the light source, and the light enters the integrating sphere. After being evenly mixed inside the integrating sphere, it passes through the X-ray filter to reach the detector of the colorimeter. The colorimeter records the light signal at this time and converts it into a digital image signal, which is stored as an image in the first integrating sphere image set. This image represents the light distribution inside the integrating sphere after being filtered by the X-ray filter at the exposure time. Repeat the above operation by changing the exposure time to obtain images at exposure times of 20ms, 30ms, 40ms, and 50ms, respectively, to obtain a complete first integrating sphere image set.

[0087] The steps for acquiring the second integrating sphere image set and the third integrating sphere image set of the Y / Z filter under their respective exposure time sets are the same as those for the X filter, and will not be repeated here.

[0088] 102. Use a filter wheel colorimeter to photograph a fourth integrating sphere image set of the Z filter at an exposure time corresponding to the X filter;

[0089] Determine the exposure time of the X filter to be 10ms, 20ms, 30ms, 40ms and 50ms, and switch the filter wheel to the Z filter. Set the exposure time on the filter wheel colorimeter to 10ms. Turn on the halogen tungsten light source, and the light enters the integrating sphere. After being evenly mixed in the integrating sphere, it passes through the Z filter to reach the detector of the colorimeter. The colorimeter converts the received light signal into a digital image signal and stores it as the first image in the fourth integrating sphere image set. Set the exposure time on the filter wheel colorimeter to 20ms, 30ms, 40ms and 50ms respectively, and repeat the above steps to obtain the fourth integrating sphere image set.

[0090] 103. Taking grayscale mean values ​​of the integrating sphere images of the first integrating sphere image set, the second integrating sphere image set, the third integrating sphere image set, and the fourth integrating sphere image set;

[0091] Use a loop to traverse each image in the first integrating sphere image set. For each image, read the image in grayscale mode. For each grayscale image read, calculate the grayscale mean of the image. Store the grayscale mean of each image in a list, calculate the mean of all elements in the list, and this mean is the grayscale mean of the first integrating sphere image set. The grayscale mean of the integrating sphere images of the second integrating sphere image set, the third integrating sphere image set, and the fourth integrating sphere image set can all be calculated through the above steps, which will not be repeated here.

[0092] 104. Detect the X / Y / Z calibration stimulus value of the integrating sphere;

[0093] Install the integrating sphere on a stable platform to ensure that it is not disturbed by external vibrations. Connect the light source to the entrance port of the integrating sphere and ensure that the optical axis of the light source coincides with the central axis of the integrating sphere to ensure that the light can be evenly distributed in the sphere. Use a standard calibrated light source to calibrate the wavelength and intensity of the spectrometer. Place the standard color plate on the sample port of the integrating sphere, ensuring that the color plate completely covers the sample port and fits tightly to the port surface to avoid light leakage. Use a spectrometer to measure the spectral distribution of the light reflected by the color plate, and the spectrometer will output a series of discrete wavelength values ​​and their corresponding light intensity values. Calculate the X / Y / Z calibration stimulus values ​​of the integrating sphere based on the wavelength values ​​and their corresponding light intensity values.

[0094] 105. Fitting the image grayscale mean of the second integrating sphere image set with the corresponding exposure time set to obtain a first fitting straight line;

[0095] 106. Fitting the image grayscale mean of the third integrating sphere image set with the corresponding exposure time set to obtain a second fitting straight line;

[0096] 107. Fitting the image grayscale mean values ​​of the first integrating sphere image set and the fourth integrating sphere image set with the corresponding exposure times to obtain a third fitting straight line;

[0097] For each image in the first integrating sphere image set, the second integrating sphere image set, and the third integrating sphere image set, the grayscale mean is calculated by the image analysis algorithm. Specifically, the grayscale value of all pixels in the image is summed and then divided by the total number of pixels to obtain the image grayscale mean. The exposure time set is the time of each imaging while obtaining the first integrating sphere image, the second integrating sphere image, and the third integrating sphere image. The image grayscale mean is fitted with the corresponding exposure time set by the least squares method to obtain the fitting straight line that best represents the data trend.

[0098] The first fitting straight line is ;

[0099] The second fitting straight line is ;

[0100] The third fitting straight line is ;

[0101] Where k is the slope and b is the intercept.

[0102] 108. Calculate the X stimulus value to be measured, the Y stimulus value to be measured, and the Z stimulus value to be measured according to the X / Y / Z calibration stimulus value, the first fitting straight line, the second fitting straight line, and the third fitting straight line.

[0103] Before calculating the X, Y, and Z stimulus values ​​to be measured, it is first necessary to obtain accurate X / Y / Z calibration stimulus values. The X / Y / Z calibration stimulus values ​​are obtained by accurately measuring known standard color samples. According to the principle of color science, there is a specific mathematical relationship between the X, Y, and Z stimulus values ​​of the sample to be measured and the X / Y / Z calibration stimulus values, the first fitting straight line, the second fitting straight line, and the third fitting straight line. Specifically, a mathematical model based on the relationship between the color matching function and the measurement data is established. This model links the calibration stimulus values, the fitting straight line, and the grayscale values ​​or spectral radiation values ​​of the image to be measured after a certain conversion, and uses the relationship of the first fitting straight line in combination with the X / Y / Z calibration stimulus values ​​to calculate the X stimulus value to be measured, the Y stimulus value to be measured, and the Z stimulus value to be measured.

[0104] In this embodiment, the present application firstly comprehensively considers the image data of multiple filters at different exposure times, and can accurately combine multiple factors such as filter characteristics, exposure time, and grayscale information of the integrating sphere image for calculation. This systematic measurement method overcomes the limitations of traditional measurement technology, reduces the measurement error caused by not comprehensively considering these factors, and thus improves the accuracy of colorimetric measurement.

[0105] Secondly, by effectively integrating the relationship between different filters and the relationship between different filters and the calibration stimulus values, the demand for high-precision colorimetric measurement can be met. In the context of increasing requirements for colorimetric measurement accuracy in modern industrial production and scientific research, this application can provide more accurate X / Y / Z stimulus values ​​to be measured.

[0106] Finally, the relationship between the grayscale mean value and the exposure time of the image is fully utilized, and the conversion coefficient and weight coefficient are obtained by fitting the grayscale mean value and exposure time of the image under different filters, so that the X, Y, and Z stimulus values ​​can be accurately obtained, and the measurement accuracy is improved. Compared with the simpler data processing of traditional colorimetric measurement, this data processing method can more effectively extract accurate information related to colorimetric measurement from image data, further improving the reliability of the measurement results.

[0107] See also Figure 2 The present application provides an embodiment of a method for calculating a self-exposure time set of an X / Y / Z filter, comprising:

[0108] 201. Determine a first light transmittance, a second light transmittance, and a third light transmittance of an X / Y / Z filter;

[0109] For the X-ray filter, the light emitted by the light source is directly irradiated onto the X-ray filter after passing through the aperture, and then the intensity distribution of the light after passing through the X-ray filter is measured using a spectrometer. Assume that the initial intensity of the light emitted by the light source at a certain wavelength λ is , the light intensity at the same wavelength after passing through the X-ray filter is According to the definition of transmittance, the transmittance of the X-ray filter at wavelength λ can be calculated using the following formula:

[0110]

[0111] According to the same principle, the Y filter and the Z filter have different wavelengths. The transmittance at can also be calculated according to the above operation and the above formula.

[0112] In the selected wavelength range The transmittance at each wavelength is measured. The weighted average calculation is performed to obtain the first light transmittance of the X filter. Similarly, the second light transmittance and the third light transmittance corresponding to the Y filter and the Z filter can also be calculated by the above method.

[0113] 202. Determine a first human eye stimulation weight, a second human eye stimulation weight, and a third human eye stimulation weight of an X / Y / Z filter;

[0114] According to the function and application of X / Y / Z filter in the optical system, the wavelength range related to it is determined. According to the corrected human visual sensitivity curve, the human eye stimulation weight at each wavelength is calculated, and the weights at each wavelength calculated are weighted averaged to obtain the first human eye stimulation weight, the second human eye stimulation weight and the third human eye stimulation weight corresponding to the X / Y / Z filter.

[0115] 203. Calculate a self-exposure time set of the X / Y / Z filters according to the first light transmittance, the second light transmittance, the third light transmittance, the first human eye stimulation weight, the second human eye stimulation weight, and the third human eye stimulation weight.

[0116] The time intervals of the X / Y / Z filters in the self-exposure time set are calculated using the following formula:

[0117]

[0118] The filter time interval is the time interval of X, Y, and Z, and the time interval of each value is different.

[0119] The determination of the time interval is related to the optical properties of the filter, such as the filter's absorption and transmission capabilities for light of a specific wavelength. If the filter absorbs light of a certain wavelength more strongly, a relatively short self-exposure time is required, and the time interval will be smaller; if the light of this wavelength range is more critical in the entire optical process, a longer self-exposure time is required, and the time interval will be larger.

[0120] After calculating the time interval corresponding to the X / Y / Z filter, the self-exposure time set of the X / Y / Z filter can be calculated according to the first transmittance, the second transmittance, the third transmittance, the first human eye stimulation weight, the second human eye stimulation weight and the third human eye stimulation weight.

[0121] In this embodiment, according to the characteristics of X / Y / Z filters in different optical applications, their transmittance, their respective human eye stimulation weights and their respective self-exposure time sets are determined respectively, which can better meet the needs of different optical systems for filter performance evaluation.

[0122] See also Figure 3 The present application provides an embodiment of a method for denoising an image, comprising:

[0123] 301. Use the median filter algorithm to perform denoising on each image.

[0124] The median filter algorithm is applicable to various types of images, including grayscale images and color images. For color images, the color image can be decomposed into three channels: red, green, and blue. Each channel is subjected to median filtering, and then the processed channels are merged into a color image. If it is a grayscale image, we start from the upper left corner pixel of the image and perform median filtering on each pixel in order from left to right and from top to bottom.

[0125] In this embodiment, the median filtering algorithm can effectively remove various types of noise, especially salt and pepper noise and impulse noise, improve the quality of the image, and at the same time can better preserve the edge and detail information of the image, so that the image still has a high degree of recognizability after denoising.

[0126] See also Figure 4 The present application provides another embodiment of a method for performing denoising using a median filtering algorithm, comprising:

[0127] 401. Determine a window size for median filtering;

[0128] First, analyze the noise type of the image. When salt and pepper noise is detected in the image, the window size can be determined according to the distribution density of salt and pepper noise points in the image, because the salt and pepper noise is mainly isolated noise points. For Gaussian noise, since the Gaussian noise distribution is relatively uniform and has a certain continuity, the window size can be determined according to the standard deviation of the Gaussian noise.

[0129] 402. For each integrating sphere image to be processed, starting from the upper left corner of the image, the window is moved pixel by pixel in a sequence from left to right and from top to bottom with a set window size;

[0130] The window size is set based on the resolution of the integrating sphere image, the noise level, and the target features to be processed. Moving the window pixel by pixel from the upper left corner of the image in a left-to-right, top-to-bottom order matches the storage order of the image data in the computer memory, which can improve the efficiency of data reading and processing. When processing integrating sphere images, the order from left to right, top to bottom ensures full coverage of the image without missing any pixel area. For integrating sphere images with uniformity and symmetry, the order from left to right, top to bottom helps to evenly process all parts of the image, and can easily use the symmetry of the image for optimization.

[0131] 403. In each window, sort the grayscale values ​​of all pixels in the window;

[0132] Sorting the grayscale values ​​of pixels in each window can further explore the local features of the image. By sorting the grayscale values ​​of pixels in each window, the median can be accurately obtained. In addition, the sorting algorithm is optimized according to the characteristics of the integrating sphere image. Since the integrating sphere image has local uniformity, the pixels in the window can be pre-judged before sorting. If the grayscale values ​​of most pixels in the window are very close, a simplified sorting method is used, such as directly marking them as sorted, without the need for a complete quick sort or heap sort process.

[0133] 404. Select the sorted middle value as the new gray value of the center pixel of the window;

[0134] The value of the pixel in the center of the window is replaced by the sorted median value as the new grayscale value. This can better maintain the original characteristics of the integrating sphere image while removing noise. Since the median value is based on the sorting result of the pixels in the window, it will not excessively change the grayscale value change characteristics that originally exist in the image.

[0135] 405. Complete the median filtering denoising process for the entire image.

[0136] Each pixel in the image is traversed to complete the median filtering denoising process for the entire image.

[0137] In this embodiment, the whole image is subjected to denoising by median filtering, which can effectively remove the noise in the image and improve the clarity and visual effect of the image. While denoising, the edge and detail features of the image can be well maintained to avoid over-smoothing the image, with low computational complexity, and the whole image can be subjected to median filtering denoising quickly, which is suitable for processing images of different sizes and improves the efficiency of image processing.

[0138] See also Figure 5 The present application provides another embodiment of a method for calculating an X stimulus value to be measured, a Y stimulus value to be measured, and a Z stimulus value to be measured, including:

[0139] 501. Substituting the exposure time and the grayscale to be tested into the X stimulus value fitting formula to obtain the X stimulus value;

[0140] The X stimulus value fitting formula is as follows:

[0141]

[0142] in is the slope, is the offset value, is the exposure time under the X-ray filter, It is the calibrated stimulus value of the X-ray filter of the integrating sphere.

[0143] 502. Substitute the exposure time and the grayscale to be tested into the Y stimulus value fitting formula to obtain the Y stimulus value;

[0144] The Y stimulus value fitting formula is as follows:

[0145]

[0146] in is the slope, is the offset value, is the exposure time under the Y filter, is the calibrated stimulus value of the Y filter of the integrating sphere.

[0147] 503. Substitute the exposure time and the grayscale to be tested into the Z stimulus value fitting formula to obtain the Z stimulus value.

[0148] The Z stimulus value fitting formula is as follows:

[0149]

[0150] in is the slope, is the offset value, is the exposure time under the Z filter, is the calibrated stimulus value of the Z filter of the integrating sphere.

[0151] In this embodiment, by accurately substituting the exposure time and grayscale into the fitting formula to calculate the X, Y, and Z stimulus values, the true color characteristics of the image or object can be more accurately reflected, and different exposure times and grayscale conditions can be adapted. Whether it is an image captured with a longer exposure time in a low-light environment or an image captured with a shorter exposure time in a high-light environment, the stimulus value can be accurately calculated, so that high-precision color measurement can be achieved in various complex image capture environments.

[0152] See also Figure 6 The present application provides an embodiment of a stimulus value calculation device, comprising:

[0153] A first determining unit 601 is used to determine a first light transmittance, a second light transmittance and a third light transmittance of an X / Y / Z filter;

[0154] A second determining unit 602 is used to determine a first human eye stimulation weight, a second human eye stimulation weight, and a third human eye stimulation weight of an X / Y / Z filter;

[0155] A collection unit 603 is used to calculate a self-exposure time collection of the X / Y / Z filter according to the first light transmittance, the second light transmittance, the third light transmittance, the first human eye stimulation weight, the second human eye stimulation weight and the third human eye stimulation weight;

[0156] A first photographing unit 604 is used to photograph a first integrating sphere image set, a second integrating sphere image set and a third integrating sphere image set of the X / Y / Z filters at respective exposure time sets using a filter wheel colorimeter;

[0157] The second photographing unit 605 is used to photograph a fourth integrating sphere image set of the Z filter at an exposure time corresponding to the X filter using a filter wheel colorimeter;

[0158] A denoising unit 606, configured to perform denoising on each image using a median filter algorithm;

[0159] Optionally, the denoising unit 606 includes:

[0160] A determination module 6061 is used to determine the window size of the median filter;

[0161] The moving module 6062 is used to move the window pixel by pixel from the upper left corner of each integrating sphere image to be processed in the order from left to right and from top to bottom with a set window size;

[0162] A sorting module 6063 is used to sort the gray values ​​of all pixels in each window;

[0163] A selection module 6064 is used to select the sorted middle value as the new gray value of the center pixel of the window;

[0164] Completion module 6065, used to complete the median filter denoising process on the entire image;

[0165] A value taking unit 607 is used to take grayscale mean values ​​of the first integrating sphere image set, the second integrating sphere image set, the third integrating sphere image set and the fourth integrating sphere image set integrating sphere images;

[0166] A detection unit 608, used to detect the X / Y / Z calibration stimulus value of the integrating sphere;

[0167] A first fitting unit 609 is used to fit the image grayscale mean of the second integrating sphere image set with the corresponding exposure time set to obtain a first fitting straight line;

[0168] A second fitting unit 610 is used to fit the image grayscale mean of the third integrating sphere image set with the corresponding exposure time set to obtain a second fitting straight line;

[0169] A third fitting unit 611 is used to fit the image grayscale mean values ​​of the first integrating sphere image set and the fourth integrating sphere image set with the corresponding exposure time to obtain a third fitting straight line;

[0170] The calculation unit 612 is used to calculate the X stimulus value to be measured, the Y stimulus value to be measured and the Z stimulus value to be measured according to the X / Y / Z calibration stimulus value, the first fitting straight line, the second fitting straight line and the third fitting straight line.

[0171] Optionally, the computing unit 612 includes:

[0172] Substitute the exposure time and the grayscale to be tested into the X stimulus value fitting formula to obtain the Y stimulus value;

[0173] Substitute the exposure time and the grayscale to be tested into the Y stimulus value fitting formula to obtain the Z stimulus value;

[0174] Substitute the exposure time and the grayscale to be tested into the Z stimulus value fitting formula to obtain the X stimulus value.

[0175] See also Figure 7 , the present application provides a system for calculating stimulus value, comprising:

[0176] Processor 701 , memory 702 , input / output unit 703 , and bus 704 .

[0177] The processor 701 is connected to the memory 702 , the input and output unit 703 , and the bus 704 .

[0178] The memory 702 stores a program, and the processor 701 calls the program to execute the following steps: Figure 1 , Figure 2 and Figure 3 , Figure 4 and Figure 5 The method in .

[0179] The present application provides a computer-readable storage medium, on which a program is stored, and when the program is executed on a computer, the program performs the following steps: Figure 1 , Figure 2 and Figure 3 , Figure 4 and Figure 5 The method in .

[0180] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0181] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, 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 integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0182] The units described as separate components may or may not be physically separated, and the components shown 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 solution of this embodiment.

[0183] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0184] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, read-only memory), random access memory (RAM, random access memory), disk or optical disk and other media that can store program code.

Claims

1. A method for calculating a stimulus value, characterized in that: include: Using a filter wheel colorimeter to capture a first integrating sphere image set, a second integrating sphere image set, and a third integrating sphere image set of the X / Y / Z filters at respective exposure time sets; Using a filter wheel colorimeter to photograph a fourth integrating sphere image set of the Z filter at an exposure time corresponding to the X filter; Taking grayscale mean values ​​of the first integrating sphere image set, the second integrating sphere image set, the third integrating sphere image set, and the fourth integrating sphere image set integrating sphere images; Detect the X / Y / Z calibration stimulus value of the integrating sphere; Fitting the image grayscale mean of the second integrating sphere image set with the corresponding exposure time set to obtain a first fitting straight line; Fitting the image grayscale mean of the third integrating sphere image set with the corresponding exposure time set to obtain a second fitting straight line; Fitting the image grayscale means of the first integrating sphere image set and the fourth integrating sphere image set with the corresponding exposure time to obtain a third fitting straight line; The X stimulus value to be measured, the Y stimulus value to be measured and the Z stimulus value to be measured are calculated according to the X / Y / Z calibration stimulus values, the first fitting straight line, the second fitting straight line and the third fitting straight line.

2. The method for calculating the stimulus value according to claim 1, characterized in that: Before using the filter wheel colorimeter to capture the first integrating sphere image set, the second integrating sphere image set, and the third integrating sphere image set of the X / Y / Z filters at the respective exposure time sets, the stimulus value calculation method further includes: Determining a first light transmittance, a second light transmittance, and a third light transmittance of the X / Y / Z filter; Determine the first eye stimulation weight, the second eye stimulation weight and the third eye stimulation weight of the X / Y / Z filter; Respective exposure time sets of X / Y / Z filters are calculated according to the first transmittance, the second transmittance, the third transmittance, the first human eye stimulation weight, the second human eye stimulation weight, and the third human eye stimulation weight.

3. The method for calculating the stimulus value according to claim 1, characterized in that: Before taking grayscale mean values ​​of the first integrating sphere image set, the second integrating sphere image set, the third integrating sphere image set, and the fourth integrating sphere image set integrating sphere images, the method further includes: Each image is denoised using the median filter algorithm.

4. The method for calculating the stimulus value according to claim 3, characterized in that: The denoising process of each image using a median filtering algorithm includes: Determine the window size of the median filter; For each integrating sphere image to be processed, start from the upper left corner of the image with the set window size and move the window pixel by pixel in the order from left to right and from top to bottom; In each window, sort the grayscale values ​​of all pixels in the window; Select the sorted middle value as the new grayscale value of the center pixel of the window; Complete the median filtering denoising process for the entire image.

5. A stimulus value calculation device, characterized in that: include: A first photographing unit is used to photograph a first integrating sphere image set, a second integrating sphere image set and a third integrating sphere image set of the X / Y / Z filters at respective exposure time sets using a filter wheel colorimeter; A second shooting unit is used to shoot a fourth integrating sphere image set of the Z filter at an exposure time corresponding to the X filter using a filter wheel colorimeter; a value taking unit, configured to take grayscale mean values ​​of the first integrating sphere image set, the second integrating sphere image set, the third integrating sphere image set, and the fourth integrating sphere image set integrating sphere images; A detection unit, used to detect the X / Y / Z calibration stimulus values ​​of the integrating sphere; A first fitting unit is used to fit the image grayscale mean of the second integrating sphere image set with the corresponding exposure time set to obtain a first fitting straight line; A second fitting unit is used to fit the image grayscale mean of the third integrating sphere image set with the corresponding exposure time set to obtain a second fitting straight line; A third fitting unit is used to fit the image grayscale mean values ​​of the first integrating sphere image set and the fourth integrating sphere image set with the corresponding exposure time to obtain a third fitting straight line; A calculation unit is used to calculate the X stimulus value to be measured, the Y stimulus value to be measured and the Z stimulus value to be measured according to the X / Y / Z calibration stimulus value, the first fitting straight line, the second fitting straight line and the third fitting straight line.

6. A stimulus value calculation system, characterized in that: include: Processor, memory, input-output unit, and bus; The processor is connected to the memory, the input and output unit, and the bus; The memory stores a program, and the processor calls the program to execute the stimulation value calculation method according to any one of claims 1 to 4. 7 . A computer-readable storage medium having a program stored thereon, wherein when the program is executed on a computer, the method for calculating a stimulus value according to claim 1 is executed.

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