Grayscale measurement method and device

Abstract

A measurement method and device. The method includes: collecting the first part of grayscale data of an LED screen when displaying a picture (S102); determining the type of a chip driving the LED screen (S104); and predicting the second part of grayscale data of the LED screen according to the type of the chip and the first part of grayscale data (S106). The method solves the technical problem of low grayscale measurement efficiency caused by the need to measure step by step when measuring grayscale in the related art.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and in particular to a grayscale measurement method and device. Background Art

[0002] With the development of light-emitting diode (LED) display technology, LED display screens are now being applied to various fields due to their advantages of low cost, low power consumption, high visibility, and freedom of assembly. At the same time, with the popularization of LED display screen applications, the market and users have higher and higher requirements for their display quality. Therefore, how to improve the display quality of LED display screens has become a research hotspot in this field.

[0003] Due to the LED pulse width modulation (PWM) driving mechanism and manufacturing process problems, LED display screens have poor linearity, which is the fundamental factor affecting image quality. Therefore, it is necessary to match the luminous intensity of the LED display screen with the grayscale and correct the grayscale to a linear state.

[0004] Grayscale correction depends on the original grayscale brightness data. Currently, grayscale brightness data is collected step by step. In the case of unknown grayscale levels and grayscale characteristics of the screen, multiple measurements are required to obtain all grayscale data. Although this method can directly measure the grayscale brightness displayed by the LED screen, due to the large number of grayscales to be measured and the limitation of the processing speed of the current acquisition equipment, the measurement time of this method is too long, which affects the efficiency of grayscale correction and the user experience. Therefore, there is an urgent need for a grayscale measurement method that can be fast and accurate.

[0005] With regard to the problem that the grayscale measurement efficiency is low because the grayscale measurement in the related art needs to be measured step by step, no effective solution has been proposed yet. Summary of the invention

[0006] The embodiments of the present invention provide a measurement method and device, a non-volatile storage medium and a processor, so as to at least solve the technical problem that the grayscale measurement efficiency is low due to the need to measure the grayscale step by step in the related art.

[0007] According to one aspect of an embodiment of the present invention, a grayscale measurement method is provided, including: collecting a first portion of grayscale data of an LED screen when displaying an image; determining the type of a chip used to drive the LED screen; predicting a second portion of grayscale data of the LED screen based on the type of chip and the first portion of grayscale data; and obtaining the second portion of grayscale data of the LED screen by collecting a small amount of the first portion of grayscale data of the LED screen when displaying an image as measurement data and predicting based on periodic changes in the grayscale data, thereby improving the grayscale measurement efficiency.

[0008] Optionally, predicting the second part of the grayscale data of the LED screen based on the type of chip and the first part of the grayscale data includes: when the chip type of the LED screen is the first type, calculating the first type of period of the first part of the grayscale data; after obtaining the first type of period and removing and merging the first part of the grayscale data, judging whether the first part of the grayscale data after removal and merging shows periodic changes; when the judgment result is yes, predicting the second part of the grayscale data of the LED screen based on the first part of the grayscale data after removal and merging through the first mode; when the judgment result is no, predicting the second part of the grayscale data of the LED screen based on the first part of the grayscale data after removal and merging through the second mode, thereby realizing the prediction of the second part of the grayscale data based on the first part of the grayscale data when the chip is highly effective.

[0009] Optionally, calculating the first type of period of the first part of grayscale data includes: obtaining the first part of grayscale data by measuring multiple grayscale data step by step on the LED screen; obtaining the correlation degree between multiple grayscale data in the first part of grayscale data at different grayscale intervals; and determining the first type of period based on the correlation degree.

[0010] Optionally, the difference in brightness between the grayscale data in the same period of the first type of period is less than a brightness threshold.

[0011] Optionally, determining whether the first part of grayscale data after removal of merging shows periodic changes includes: measuring N first part of grayscale data after removal of merging on the LED screen step by step, and detecting whether the N first part of grayscale data after removal of merging shows periodic changes; if it is detected that there is no periodic change, increasing the grayscale data measured step by step until the first part of grayscale data after removal of merging shows periodic changes, and determining that a second type of cycle exists; when the number of grayscale data measured step by step reaches a preset threshold and at least three cycles do not appear, determining that the N first part of grayscale data after removal of merging do not show periodic changes.

[0012] Optionally, in the second type of period, the brightness of the grayscale data in the same period presents an increasing trend.

[0013] Optionally, predicting the second part of the grayscale data of the LED screen based on the type of chip and the first part of the grayscale data includes: when the chip type of the LED screen is the second type, judging whether the first part of the grayscale data shows periodic changes; when the judgment result is yes, predicting the second part of the grayscale data of the LED screen based on the first part of the grayscale data through the first mode; when the judgment result is no, predicting the second part of the grayscale data of the LED screen based on the first part of the grayscale data through the second mode, thereby realizing the prediction of the second part of the grayscale data based on the first part of the grayscale data when the chip is of low effectiveness.

[0014] Optionally, predicting the second part of the grayscale data of the LED screen based on the type of chip and the first part of the grayscale data includes: when the type of the chip of the LED screen is the third type, predicting the second part of the grayscale data of the LED screen based on the first part of the grayscale data through the following steps: Step 1, measuring several levels of grayscale data of the LED screen step by step until n consecutive grayscale data on a straight line are obtained, and using the slope of the straight line to predict the next grayscale data of the LED screen; if the predicted next grayscale data meets the predicted value, increasing the measurement step of the step-by-step measurement of the LED screen, wherein the unmeasured grayscale data in the middle of the LED screen is calculated using interpolation prediction; Step 2, if the predicted next grayscale data does not meet the predicted value, returning to the previous measurement point, returning to step 1, until all the grayscale data of the LED screen are predicted, thereby realizing the prediction of the second part of the grayscale data based on the first part of the grayscale data when the chip is neither highly effective nor low effective.

[0015] Optionally, the first mode includes: measuring the first grayscale data of each cycle of the LED screen, taking the first grayscale data as a reference point, and predicting the remaining grayscale data according to the periodic law; selecting the last grayscale data in each cycle as a check point for prediction; if the check point prediction is correct, entering the next cycle; if the check point is incorrect, taking the second to last grayscale data as a check point for prediction, until the predicted value of the check point is consistent with the measured value.

[0016] Optionally, the second mode includes: step one, measuring several levels of grayscale data of the LED screen step by step until n continuous grayscale data on a straight line are obtained, and using the slope of the straight line to predict the next grayscale data of the LED screen; if the predicted next grayscale data meets the predicted value, increasing the measurement step of the LED screen step by step, wherein the unmeasured grayscale data in the middle of the LED screen is calculated using interpolation prediction; step two, if the predicted next grayscale data does not meet the predicted value, returning to the previous measurement point, and returning to step one until all grayscale data of the LED screen are predicted.

[0017] According to another aspect of an embodiment of the present invention, a grayscale measurement device is provided, including: an acquisition module, used to acquire a first portion of grayscale data of an LED screen when displaying an image; a type determination module, used to determine the type of a chip used to drive the LED screen; a measurement module, used to predict a second portion of grayscale data of the LED screen based on the type of chip and the first portion of grayscale data; by acquiring a small amount of the first portion of grayscale data of the LED screen when displaying an image as measurement data, a prediction is made based on the periodic changes of the grayscale data to obtain the second portion of grayscale data of the LED screen, thereby improving the grayscale measurement efficiency.

[0018] Optionally, the measurement module includes: a calculation unit, used to calculate a first type of period of the first part of grayscale data when the chip type of the LED screen is the first type; a judgment unit, used to obtain the first type of period and determine whether the first part of grayscale data after removal and merging shows periodic changes after removing and merging the first part of grayscale data; a first measurement unit, used to predict the second part of grayscale data of the LED screen based on the first part of grayscale data after removal and merging through a first mode when the judgment result is yes; and a second measurement unit, used to predict the second part of grayscale data of the LED screen based on the first part of grayscale data after removal and merging through a second mode when the judgment result is no, thereby realizing the prediction of the second part of grayscale data based on the first part of grayscale data when the chip is highly effective.

[0019] Optionally, the calculation unit includes: a step-by-step measurement subunit, used to obtain a first part of grayscale data by measuring multiple grayscale data on the LED screen step by step; an acquisition subunit, used to obtain the degree of correlation between multiple grayscale data in the first part of grayscale data at different grayscale intervals; and a period determination subunit, used to determine the first type of period based on the degree of correlation.

[0020] Optionally, the judgment unit includes: a detection subunit, which is used to measure N first-part grayscale data after merging and removing them for the LED screen step by step, and detect whether the N first-part grayscale data after merging and removing them show periodic changes; a first judgment subunit, which is used to increase the grayscale data measured step by step if it is detected that there is no periodic change, until the first-part grayscale data after merging and removing them show periodic changes, so as to determine that a second type of cycle exists; and a second judgment subunit, which is used to determine that the N first-part grayscale data after merging and removing them do not show periodic changes when the number of grayscale data measured step by step reaches a preset threshold and at least three cycles do not occur.

[0021] Optionally, the measurement module includes: a period judgment unit, used to judge whether the first part of the grayscale data shows periodic changes when the chip type of the LED screen is the second type; a third measurement unit, used to predict the second part of the grayscale data of the LED screen according to the first part of the grayscale data through the first mode when the judgment result is yes; a fourth measurement unit, used to predict the second part of the grayscale data of the LED screen according to the first part of the grayscale data through the second mode when the judgment result is no, thereby realizing the prediction of the second part of the grayscale data based on the first part of the grayscale data when the chip is of low effectiveness.

[0022] Optionally, the measurement module includes: when the chip type of the LED screen is the third type, predicting the second part of the grayscale data of the LED screen based on the first part of the grayscale data through the following steps: a fifth measurement unit, used to execute step one, measuring several levels of grayscale data of the LED screen step by step, until n consecutive grayscale data on a straight line are obtained on a straight line, and using the slope of the straight line to predict the next grayscale data of the LED screen; if the predicted next grayscale data meets the predicted value, increasing the measurement step of the step-by-step measurement of the LED screen, wherein the unmeasured grayscale data in the middle of the LED screen is calculated by interpolation prediction; a sixth measurement unit, used to execute step two, if the predicted next grayscale data does not meet the predicted value, returning to the previous measurement point, returning to the fifth measurement unit to execute step one, until all the grayscale data of the LED screen are predicted, thereby realizing the prediction of the second part of the grayscale data based on the first part of the grayscale data when the chip is neither highly effective nor low effective.

[0023] Optionally, the first mode includes: a first measuring subunit, which measures the first grayscale data of each cycle of the LED screen, takes the first grayscale data as a reference point, and predicts the remaining grayscale data according to the periodic rule; a selection subunit, which is used to select the last grayscale data in each cycle as a check point for prediction; a jump subunit, which is used to enter the next cycle if the check point prediction is correct; and a second measuring subunit, which is used to predict the second to last grayscale data as a check point if the check point is incorrect, until the predicted value of the check point is consistent with the measured value.

[0024] Optionally, the second mode includes: a third measurement subunit, used to execute step one, measure a number of grayscale data of the LED screen step by step, until n continuous grayscale data on a straight line are obtained, and use the slope of the straight line to predict the next grayscale data of the LED screen; if the predicted next grayscale data meets the predicted value, increase the measurement step of the step-by-step measurement of the LED screen, wherein the unmeasured grayscale data in the middle of the LED screen is calculated using interpolation prediction; a fourth measurement subunit, used to execute step two, if the predicted next grayscale data does not meet the predicted value, return to the previous measurement point, return to the third measurement subunit to execute step one, until all grayscale data of the LED screen are predicted.

[0025] According to another aspect of an embodiment of the present invention, a nonvolatile storage medium is provided, wherein the nonvolatile storage medium includes a stored program, wherein when the program is running, the device where the nonvolatile storage medium is located is controlled to execute the above method.

[0026] According to another aspect of an embodiment of the present invention, a processor is provided, wherein the processor is used to run a program, wherein the above method is executed when the program is run.

[0027] In an embodiment of the present invention, by collecting the first part of grayscale data of the LED screen when displaying the picture; determining the type of chip used to drive the LED screen; and predicting the second part of grayscale data of the LED screen based on the type of chip and the first part of grayscale data, the purpose of exploring various regular characteristics of grayscale data based on a small amount of measurement data of the LED screen is achieved, and on the basis of the regularity, different measurement, prediction, and verification strategies are selected to obtain more grayscale data with a small number of measurements, thereby achieving the technical effect of ensuring data accuracy while improving efficiency, and further solving the technical problem of low grayscale measurement efficiency due to the need to measure grayscale step by step in related technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0029] Figure 1 is a schematic flow chart of a grayscale measurement method according to an embodiment of the present invention;

[0030] Figure 2 is a schematic diagram of a first type of period in a grayscale measurement method according to an embodiment of the present invention;

[0031] Figure 3 is a schematic diagram of a second type of period in a grayscale measurement method according to an embodiment of the present invention;

[0032] Figure 4 is a schematic diagram of a grayscale measurement device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, device, system, product or equipment that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, devices, products or equipment.

[0035] Example 1

[0036] According to an embodiment of the present invention, a method embodiment of a grayscale measurement method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0037] Figure 1 is a flow chart of a grayscale measurement method according to an embodiment of the present invention. Figure 1 As shown, the grayscale measurement method provided in the embodiment of the present application may include the following steps:

[0038] Step S102, collecting the first part of grayscale data when the LED screen displays the picture.

[0039] Among them, different from the related art that requires the LED screen to measure all grayscale data step by step when displaying the picture, resulting in a large amount of calculation and low grayscale measurement efficiency, in the embodiment of the present application, when the LED screen is displaying the picture, part of the measurement data of the LED screen is collected as the first part of the grayscale data, and the remaining grayscale data (that is, the second part of the grayscale data in the embodiment of the present application) is predicted according to the periodic changes of the first part of the grayscale data, as shown in steps S104 and S106.

[0040] Step S104, determining the chip type of the LED screen.

[0041] Among them, the types of chips of the LED screen in the embodiment of the present application include: high effectiveness, low effectiveness, or neither high effectiveness nor low effectiveness.

[0042] It should be noted that if the chip in the embodiment of the present application is highly effective, the chip is recorded as a first-category chip (that is, the type of the chip of the LED screen in the embodiment of the present application is the first type); if the chip is low effective, the chip is recorded as a second-category chip (that is, the type of the chip of the LED screen in the embodiment of the present application is the second type); if the chip is neither highly effective nor low effective, the chip is recorded as a third-category chip (that is, the type of the chip of the LED screen in the embodiment of the present application is the third type).

[0043] Step S106, predicting the second part of the grayscale data of the LED screen according to the type of the chip and the first part of the grayscale data.

[0044] Based on the type of chip of the LED screen determined in step S104, the second part of the grayscale data of the LED screen can be predicted according to each type of chip and the first part of the grayscale data.

[0045] In summary, the grayscale measurement method provided in the embodiments of the present application may include the following three implementation methods.

[0046] Method 1: The type of chip of the LED screen is the first type.

[0047] Optionally, in step S104, predicting the second part of the grayscale data of the LED screen based on the type of chip and the first part of the grayscale data includes: when the chip type of the LED screen is the first type, calculating the first type of period of the first part of the grayscale data; after obtaining the first type of period and removing and merging the first part of the grayscale data, judging whether the first part of the grayscale data after removal and merging shows periodic changes; when the judgment result is yes, predicting the second part of the grayscale data of the LED screen based on the first part of the grayscale data after removal and merging through the first mode; when the judgment result is no, predicting the second part of the grayscale data of the LED screen based on the first part of the grayscale data after removal and merging through the second mode, thereby realizing the prediction of the second part of the grayscale data based on the first part of the grayscale data when the chip is highly effective.

[0048] Optionally, in the grayscale measurement method provided in the embodiment of the present application, CA410 can be selected as the measuring device, and before calculating the first type of cycle T1 of the grayscale data, the level of the chip of the LED screen to be tested is determined. In the embodiment of the present application, the level of the chip of the LED screen to be tested may include: high validity, low validity or other (neither high validity nor low validity).

[0049] Among them, the grayscale level of the chip of the general LED screen does not exceed 16 bits. For the chip with less than 16 bits and high bit effective, its grayscale shows a merged grayscale, such as Figure 2 As shown, Figure 2 It is a schematic diagram of the first type of period in a grayscale measurement method according to an embodiment of the present invention, and the period of grayscale merging caused by insufficient grayscale levels is determined as the first type of period T1. It should be noted that in the embodiment of the present application, by combining with the CA410 fast measurement device, the measurement efficiency can be further improved. The grayscale measurement method provided in the embodiment of the present application is only described by selecting the CA410 fast measurement device as a preferred example to implement the grayscale measurement method provided in the embodiment of the present application, and is not specifically limited.

[0050] Optionally, calculating the first type of period of the first part of grayscale data includes: obtaining the first part of grayscale data by measuring multiple grayscale data on the LED screen step by step; obtaining the correlation degree between multiple grayscale data in the first part of grayscale data at different grayscale intervals; and determining the first type of period based on the correlation degree.

[0051] Optionally, the difference in brightness between the grayscale data in the same period of the first type of period is less than a brightness threshold.

[0052] The brightness threshold of this embodiment may be a threshold used to measure whether the brightness of each grayscale data in the same period of the first type of period is similar or equal.

[0053] Optionally, the first type of cycle for calculating the first portion of grayscale data may be as follows:

[0054] N1 grayscale data are measured step by step on the LED screen to explore and calculate the first type of period T1.

[0055] The first type of period can be calculated by autocorrelation analysis. The autocorrelation function is used to measure the correlation between grayscale data at different grayscale intervals, which can be expressed as a function of the grayscale interval τ:

[0056]

[0057] in:

[0058] X0={dLum1, dLum2,..., dLum nτ},

[0059] X τ ={dLum 1+τ ,dLum 2+τ , ...dLum n+τ ,dLum1,dLum2,...,dLum nτ},

[0060] dLum i =Lum i+1 -Lum i .

[0061] Lum i Can be used to represent the brightness of the i-th grayscale, μ, σ 2 They can be used to represent mathematical expectation and variance, X0 and X τ Have the same mathematical expectation and variance. If the grayscale has a period T, then its autocorrelation function is also a periodic function of period T, and the maximum value can be obtained when τ = T. The period T can be determined by the spacing of the peaks of the autocorrelation graph.

[0062] In addition, if the number of gray levels can be accurately predicted, the step of calculating the first type of period of gray scale data can be omitted.

[0063] Optionally, determining whether the first part of grayscale data after removal of merging shows periodic changes includes: measuring N first part of grayscale data after removal of merging on the LED screen step by step, and detecting whether the N first part of grayscale data after removal of merging shows periodic changes; if it is detected that there is no periodic change, increasing the grayscale data measured step by step until the first part of grayscale data after removal of merging shows periodic changes, and determining that a second type of cycle exists; when the number of grayscale data measured step by step reaches a preset threshold and at least three cycles do not appear, determining that the N first part of grayscale data after removal of merging do not show periodic changes.

[0064] Optionally, in the second type of period, the brightness of the grayscale data in the same period presents an increasing trend.

[0065] Optionally, after removing the first part of the merged grayscale data, some screen grayscale data still show obvious periodicity, such as Figure 3 As shown, Figure 3 is a schematic diagram of a second type of period in a grayscale measurement method according to an embodiment of the present invention, and the period may be referred to as a second type of period T2.

[0066] It should be noted that in the embodiment of the present application, the calculation method of the second-type period T2 is the same as that of the first-type period T1, and both use autocorrelation analysis. It should be noted that if the autocorrelation analysis is directly used to calculate the period of the 16-bit LED screen, it is very likely that the second-type period T2 will be miscalculated as the first-type period T1. Therefore, it is necessary to distinguish that the brightness of each grayscale in the first-type period is almost equal, while the brightness of the second-type period is almost increasing (taking into account the measurement error and rebound phenomenon).

[0067] In order to ensure accurate calculation, in the embodiment of the present application, grayscale data of at least 3 cycles are measured step by step (the autocorrelation diagram has more than 7 equally spaced peaks). Since the approximate value of the second type of period T2 cannot be predicted, N2 grayscale data of the LED screen are first measured step by step. If more than 3 cycles are not detected, the grayscale data measured step by step is increased until more than three cycles appear. For the case where there is no cycle or the grayscale data is very linear, no matter how many grayscales are measured step by step, more than 3 cycles will not appear. When the step-by-step measurement value reaches a certain upper limit (N2_Max) and no three cycles appear, T2=1. In addition, the second type of period is generally 2 n , if not, then T2=1.

[0068] Method 2: When the chip type of the LED screen is the second type.

[0069] Optionally, predicting the second part of the grayscale data of the LED screen based on the type of chip and the first part of the grayscale data includes: when the chip type of the LED screen is the second type, judging whether the first part of the grayscale data shows periodic changes; when the judgment result is yes, predicting the second part of the grayscale data of the LED screen based on the first part of the grayscale data through the first mode; when the judgment result is no, predicting the second part of the grayscale data of the LED screen based on the first part of the grayscale data through the second mode, thereby realizing the prediction of the second part of the grayscale data based on the first part of the grayscale data when the chip is of low effectiveness.

[0070] In which, when the chip type of the LED screen is the second type, it is determined that the first type period T1 of the grayscale data is 1, that is, the grayscale data changes periodically.

[0071] In the embodiment of the present application, the process of calculating the second type of period is the same in method 1 and method 2, except that, in method 2, no merged grayscale data is required.

[0072] Combining method one and method two, predicting the second part of the grayscale data of the LED screen based on the first part of the grayscale data through the first mode includes: measuring the first grayscale data of each cycle of the LED screen, taking the first grayscale data as the reference point, and predicting the remaining grayscale data according to the periodic law; selecting the last grayscale data in each cycle as the check point for prediction; if the check point is predicted correctly, entering the next cycle; if the check point is predicted incorrectly, the second to last grayscale data is used as the check point for prediction, until the predicted value of the check point is consistent with the measured value.

[0073] Optionally, when the merged grayscale data is removed and there is still an obvious periodic regularity, that is, when T2 is not equal to 1, the first mode can be used for measurement and prediction.

[0074] Measure the first grayscale data of each cycle as the reference point, and predict the remaining grayscale data according to the cycle law. Select the last grayscale data in each cycle as the test point. If the prediction is correct, enter the next cycle. If the prediction is incorrect, check the second to last grayscale data, and so on, until the predicted value matches the measured value.

[0075] From the above, it can be seen that the grayscale measurement method provided in the embodiment of the present application can estimate the measurement grayscale reduction space in different situations: for the case where the first mode is used for measurement and prediction, the space where the measurement grayscale can be reduced is approximately: 1-(1 / T1)*(2 / T2). For the case where the first mode is used for measurement and prediction, 1-(1 / T1)*P, P depends on whether the grayscale is linear, where completely linear < piecewise linear < non-linear.

[0076] Combining method one and method two, wherein predicting the second part of the grayscale data of the LED screen according to the first part of the grayscale data through the second mode includes: step one, measuring several levels of grayscale data of the LED screen step by step until n continuous grayscale data on a straight line are obtained, and using the slope of the straight line to predict the next grayscale data of the LED screen; if the predicted next grayscale data meets the predicted value, increasing the measurement step of the step-by-step measurement of the LED screen, wherein the unmeasured grayscale data in the middle of the LED screen is calculated by interpolation prediction; step two, if the predicted next grayscale data does not meet the predicted value, returning to the previous measurement point, returning to step one, until all the grayscale data of the LED screen are predicted.

[0077] Optionally, for the case where there is no obvious periodic regularity, linearity, or piecewise linearity after grayscale merging due to insufficient grayscale levels is removed, that is, when T2=1, the second mode is used for measurement and prediction.

[0078] Step 1, measure several levels of grayscale data of the LED screen step by step until n consecutive grayscale data on a straight line are found, and use the slope of the straight line to predict the next point of the LED screen. If the predicted next grayscale data meets the predicted value, increase the measurement step of the LED screen step by step (when the step exceeds a certain threshold, appropriately reduce the step), and so on. Interpolation prediction calculation is used for the unmeasured grayscale data in the middle of the LED screen.

[0079] Step 2, if the predicted next grayscale data does not meet the predicted value, return to the previous measurement point and return to Step 1 until all grayscales of the LED screen are predicted.

[0080] Method three: For the case where the chip type of the LED screen is the third type chip.

[0081] Optionally, predicting the second part of the grayscale data of the LED screen based on the type of chip and the first part of the grayscale data includes: when the type of the chip of the LED screen is the third type, predicting the second part of the grayscale data of the LED screen based on the first part of the grayscale data through the following steps: Step 1, measuring several levels of grayscale data of the LED screen step by step until n consecutive grayscale data on a straight line are obtained, and using the slope of the straight line to predict the next grayscale data; if the predicted next grayscale data meets the predicted value, increasing the measurement step of the step-by-step measurement of the LED screen, wherein the unmeasured grayscale data in the middle of the LED screen is calculated using interpolation prediction; Step 2, if the predicted next grayscale data does not meet the predicted value, returning to the previous measurement point, returning to step 1, until all the grayscale data of the LED screen are predicted, thereby realizing the prediction of the second part of the grayscale data based on the first part of the grayscale data when the chip is neither highly effective nor low effective.

[0082] Optionally, for the case where there is no obvious periodic regularity, linearity, or piecewise linearity after grayscale merging due to insufficient grayscale levels is removed, that is, when T2=1, the collected grayscale data can be predicted as follows:

[0083] Step 1, measure several levels of grayscale data step by step until n continuous grayscale data are found on a straight line, and use the slope of the straight line to predict the next grayscale data. If the predicted next grayscale data meets the predicted value, increase the measurement step of the LED screen step by step (when the step exceeds a certain threshold, appropriately reduce the step), and so on. Interpolation prediction calculation is used for the unmeasured grayscale data in the middle of the LED screen.

[0084] Step 2, if the predicted next grayscale data does not meet the predicted value, return to the previous measurement point and return to Step 1 until all grayscales of the LED screen are predicted.

[0085] The grayscale measurement method provided in the embodiment of the present application solves the problem of low efficiency of grayscale measurement based on the regular characteristics of grayscale and combines with CA410 fast measurement equipment, ensures the accuracy of data, and greatly improves the user experience. The grayscale measurement method provided in the embodiment of the present application can explore various regular characteristics of grayscale data based on a small amount of measurement data, and on the basis of the regularity, select different measurement, prediction, and verification strategies to obtain more grayscale data with a small number of measurements, thereby improving efficiency while ensuring data accuracy.

[0086] In an embodiment of the present invention, by collecting the first part of grayscale data of the LED screen when displaying the picture; determining the type of chip used to drive the LED screen; and predicting the second part of grayscale data of the LED screen based on the type of chip and the first part of grayscale data, the purpose of exploring various regular characteristics of grayscale data based on a small amount of measurement data is achieved, and on the basis of the regularity, different measurement, prediction, and verification strategies are selected to obtain more grayscale data with a small number of measurements, thereby achieving the technical effect of improving efficiency while ensuring data accuracy, and further solving the technical problem of low grayscale measurement efficiency due to the need to measure grayscale step by step in the related technology.

[0087] Example 2

[0088] According to another aspect of the embodiment of the present invention, a grayscale measurement device is further provided. It should be noted that the grayscale measurement device of this embodiment can be used to execute the grayscale measurement method of the embodiment of the present invention.

[0089] Figure 4 is a schematic diagram of a grayscale measurement device according to an embodiment of the present invention. Figure 4 As shown, the grayscale measurement device provided in the embodiment of the present application may include: a collection module 42 , a type determination module 44 and a measurement module 46 .

[0090] The acquisition module 42 is used to acquire the first part of grayscale data when the LED screen displays the picture;

[0091] A type determination module 44, used to determine the type of chip used to drive the LED screen;

[0092] The measuring module 46 is used to predict the second part of the grayscale data of the LED screen according to the type of the chip and the first part of the grayscale data;

[0093] By collecting a small amount of the first part of grayscale data when the LED screen is displaying the picture as measurement data, prediction is made based on the periodic changes of the grayscale data to obtain the second part of grayscale data of the LED screen, thereby improving the grayscale measurement efficiency.

[0094] Optionally, the measurement module 46 includes: a calculation unit, which is used to calculate the first type of period of the first part of the grayscale data when the chip type of the LED screen is the first type; a judgment unit, which is used to obtain the first type of period and determine whether the first part of the grayscale data after removing and merging shows periodic changes; a first measurement unit, which is used to predict the second part of the grayscale data of the LED screen according to the first part of the grayscale data after removing and merging through the first mode when the judgment result is yes; and a second measurement unit, which is used to predict the second part of the grayscale data of the LED screen according to the first part of the grayscale data after removing and merging through the second mode when the judgment result is no, thereby realizing the prediction of the second part of the grayscale data based on the first part of the grayscale data when the chip is highly effective.

[0095] Optionally, the calculation unit includes: a step-by-step measurement subunit, used to obtain a first part of grayscale data by measuring multiple grayscale data on the LED screen step by step; an acquisition subunit, used to obtain the degree of correlation between multiple grayscale data in the first part of grayscale data at different grayscale intervals; and a period determination subunit, used to determine the first type of period based on the degree of correlation.

[0096] Optionally, the judgment unit includes: a detection subunit, which is used to measure N first-part grayscale data after merging and removing them for the LED screen step by step, and detect whether the N first-part grayscale data after merging and removing them show periodic changes; a first judgment subunit, which is used to increase the grayscale data measured step by step if it is detected that there is no periodic change, until the first-part grayscale data after merging and removing them show periodic changes, so as to determine that a second type of cycle exists; and a second judgment subunit, which is used to determine that the N first-part grayscale data after merging and removing them do not show periodic changes when the number of grayscale data measured step by step reaches a preset threshold and at least three cycles do not occur.

[0097] Optionally, the measurement module 46 includes: a period judgment unit, used to judge whether the first part of the grayscale data shows periodic changes when the chip type of the LED screen is the second type; a third measurement unit, used to predict the second part of the grayscale data of the LED screen according to the first part of the grayscale data through the first mode when the judgment result is yes; a fourth measurement unit, used to predict the second part of the grayscale data of the LED screen according to the first part of the grayscale data through the second mode when the judgment result is no, thereby realizing the prediction of the second part of the grayscale data based on the first part of the grayscale data when the chip is of low effectiveness.

[0098] Optionally, the measurement module 46 is used to predict the second part of the grayscale data of the LED screen based on the first part of the grayscale data when the type of the chip of the LED screen is the third type, including: a fifth measurement unit, used to execute step one, measure several levels of grayscale data step by step, until n consecutive grayscale data are obtained on a straight line, and use the slope of the straight line to predict the next grayscale data; if it meets the predicted value, increase the measurement step, wherein the intermediate unmeasured grayscale data is calculated using interpolation prediction; a sixth measurement unit, used to execute step two, if it does not meet the predicted value, return to the previous measurement point, return to the fifth measurement unit to execute step one, until all the grayscale data are predicted, thereby realizing the prediction of the second part of the grayscale data based on the first part of the grayscale data when the chip is neither highly effective nor low effective.

[0099] Optionally, in the first mode, the first measuring subunit measures the first grayscale data of each cycle of the LED screen, takes the first grayscale data as a reference point, and predicts the remaining grayscale data according to the periodic rule; the selection subunit is used to select the last grayscale data in each cycle as a check point for prediction; the jump subunit is used to enter the next cycle if the check point prediction is correct; the second measuring subunit is used to predict the second to last grayscale data as a check point if the check point is incorrect, until the predicted value of the check point is consistent with the measured value.

[0100] Optionally, in the second mode, the third measurement subunit is used to execute step one, measure a number of grayscale data of the LED screen step by step, until n continuous grayscale data on a straight line are obtained, and use the slope of the straight line to predict the next grayscale data of the LED screen; if the predicted next grayscale data meets the predicted value, the measurement step of the step-by-step measurement of the LED screen is increased, wherein the unmeasured grayscale data in the middle of the LED screen is calculated using interpolation prediction; the fourth measurement subunit is used to execute step two, if the predicted next grayscale data does not meet the predicted value, return to the previous measurement point, return to the third measurement subunit to execute step one, until all grayscale data of the LED screen are predicted.

[0101] Example 3

[0102] According to another aspect of an embodiment of the present invention, a non-volatile storage medium is provided, wherein the non-volatile storage medium includes a stored program, wherein when the program is running, the device where the non-volatile storage medium is located is controlled to execute the method in the above-mentioned embodiment 1.

[0103] Example 4

[0104] According to another aspect of the embodiments of the present invention, a processor is provided, wherein the processor is used to run a program, wherein the method in the above-mentioned embodiment 1 is executed when the program is run.

[0105] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0106] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0107] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, 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 through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0108] 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 units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0109] In addition, each functional unit in each embodiment of the present invention 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.

[0110] 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 invention, in essence, or the part that contributes to the relevant technology or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of 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 device described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0111] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A grayscale measurement method, characterized in that: include: Collect the first part of grayscale data of the LED screen when it displays the picture; Determine the type of chip used to drive the LED screen; Predicting the second part of the grayscale data of the LED screen according to the type of the chip and the regular characteristics of the first part of the grayscale data; Wherein, the prediction of the second part of the grayscale data of the LED screen according to the type of the chip and the regular characteristics of the first part of the grayscale data includes: when the type of the chip of the LED screen is the first type, calculating the first type of period of the first part of the grayscale data; after obtaining the first type of period and removing and merging the first part of the grayscale data, judging whether the first part of the grayscale data after removal and merging presents a periodic change; when the judgment result is yes, predicting the second part of the grayscale data of the LED screen according to the first part of the grayscale data after removal and merging through the first mode; when the judgment result is no, predicting the second part of the grayscale data of the LED screen according to the first part of the grayscale data after removal and merging through the second mode; The first mode includes: measuring the first grayscale data of each cycle of the LED screen, taking the first grayscale data as a reference point, and predicting the remaining grayscale data according to the cycle law; selecting the last grayscale data in each cycle as a check point for prediction; if the prediction of the check point is correct, entering the next cycle; if the prediction of the check point is incorrect, taking the second to last grayscale data as the check point for prediction, until the predicted value of the check point is consistent with the measured value; The second mode includes: step 1, measuring a number of grayscale data of the LED screen step by step until n continuous grayscale data on a straight line are obtained, and using the slope of the straight line to predict the next grayscale data of the LED screen; if the predicted next grayscale data meets the predicted value, increasing the measurement step of the LED screen step by step, wherein the unmeasured grayscale data in the middle of the LED screen is calculated by interpolation prediction; step 2, if the predicted next grayscale data does not meet the predicted value, returning to the previous measurement point, and returning to step 1, until all grayscale data of the LED screen are predicted; Among them, the chip type of the LED screen is the first type used to indicate that the chip is high-bit valid, the chip type of the LED screen is the second type used to indicate that the chip is low-bit valid, and the chip type of the LED screen is the third type used to indicate that the chip is neither high-bit valid nor low-bit valid.

2. The method according to claim 1, characterized in that The first type of cycle for calculating the first part of grayscale data includes: Measuring a plurality of grayscale data of the LED screen step by step to obtain the first part of grayscale data; Acquire the correlation degree between the plurality of grayscale data in the first part of grayscale data at different grayscale intervals; The first type of period is determined according to the correlation degree.

3. The method according to claim 1, characterized in that The difference in brightness between the grayscale data in the same period of the first type of period is less than the brightness threshold.

4. The method according to claim 1, characterized in that The step of determining whether the first portion of grayscale data after removal and merging presents a periodic change comprises: Measuring the first part of grayscale data after removing N pieces of the first part of the grayscale data step by step on the LED screen, and detecting whether the first part of the grayscale data after removing N pieces of the first part of the grayscale data after the first part of the grayscale data presents a periodic change; If it is detected that there is no periodic change, grayscale data measured step by step are added until the first part of grayscale data after merging is removed and the periodic change is detected, and it is determined that there is a second type of period; When the number of grayscale data measured step by step reaches a preset threshold and at least three cycles do not appear, it is determined that the first part of grayscale data after the N pieces of grayscale data are removed and merged does not show a periodic change.

5. The method according to claim 4, characterized in that In the second type of period, the brightness of the grayscale data in the same period increases gradually.

6. The method according to claim 1, characterized in that The predicting of the second part of the grayscale data of the LED screen according to the type of the chip and the regular characteristics of the first part of the grayscale data includes: When the chip type of the LED screen is the second type, determining whether the first part of grayscale data changes periodically; If the judgment result is yes, predicting the second part of the grayscale data of the LED screen according to the first part of the grayscale data through the first mode; When the judgment result is no, the second part of the grayscale data of the LED screen is predicted according to the first part of the grayscale data through the second mode.

7. The method according to claim 1, characterized in that The predicting of the second part of the grayscale data of the LED screen according to the type of the chip and the regular characteristics of the first part of the grayscale data includes: In the case where the type of the chip of the LED screen is the third type, the second part of the grayscale data of the LED screen is predicted according to the first part of the grayscale data through the following steps: Step 1, measuring a number of grayscale data of the LED screen step by step until n continuous grayscale data on a straight line are obtained, and the slope of the straight line is used to predict the next grayscale data of the LED screen; if the predicted next grayscale data meets the predicted value, increasing the measurement step length of the LED screen step by step, wherein the unmeasured grayscale data in the middle of the LED screen is calculated by interpolation prediction; Step 2: If the predicted next grayscale data does not meet the predicted value, return to the previous measurement point and return to step 1 until all grayscale data of the LED screen are predicted.

8. A grayscale measurement device, characterized in that: include: The acquisition module is used to acquire the first part of the grayscale data of the LED screen when displaying the picture; A type determination module, used to determine the type of chip used to drive the LED screen; A measuring module, used for predicting the second part of the grayscale data of the LED screen according to the type of the chip and the regular characteristics of the first part of the grayscale data; Wherein, the measurement module includes: a calculation unit, used for calculating the first type of period of the first part of grayscale data when the type of the chip of the LED screen is the first type; a judgment unit, used for obtaining the first type of period and after removing and merging the first part of grayscale data, judging whether the first part of grayscale data after removal and merging presents periodic changes; a first measurement unit, used for predicting the second part of grayscale data of the LED screen according to the first part of grayscale data after removal and merging through a first mode when the judgment result is yes; a second measurement unit, used for predicting the second part of grayscale data of the LED screen according to the first part of grayscale data after removal and merging through a second mode when the judgment result is no; The first mode includes: a first measuring subunit, used to measure the first grayscale data of each cycle of the LED screen, taking the first grayscale data as a reference point, and predicting the remaining grayscale data according to the cycle law; a selecting subunit, used to select the last grayscale data in each cycle as a check point for prediction; a jumping subunit, used to enter the next cycle if the check point is predicted correctly; a second measuring subunit, used to take the second to last grayscale data as the check point for prediction if the check point is predicted incorrectly, until the predicted value of the check point is consistent with the measured value; The second mode includes: a third measuring subunit, which is used to execute step one, measure a number of grayscale data of the LED screen step by step, until n continuous grayscale data on a straight line are obtained, and use the slope of the straight line to predict the next grayscale data of the LED screen; if the predicted next grayscale data meets the predicted value, increase the measurement step of the step-by-step measurement of the LED screen, wherein the unmeasured grayscale data in the middle of the LED screen is calculated by interpolation prediction; a fourth measuring subunit, which is used to execute step two, if the predicted next grayscale data does not meet the predicted value, return to the previous measurement point, return to the third measuring subunit to execute step one, until all grayscale data of the LED screen are predicted; Among them, the chip type of the LED screen is the first type used to indicate that the chip is high-bit valid, the chip type of the LED screen is the second type used to indicate that the chip is low-bit valid, and the chip type of the LED screen is the third type used to indicate that the chip is neither high-bit valid nor low-bit valid.

9. The device according to claim 8, characterized in that The computing unit comprises: A step-by-step measurement subunit, configured to obtain the first part of grayscale data by measuring a plurality of grayscale data step-by-step on the LED screen; An acquiring subunit, used for acquiring the correlation degree between the plurality of grayscale data in the first part of grayscale data at different grayscale intervals; The period determination subunit is used to determine the first type of period according to the correlation degree.

10. The device according to claim 8, characterized in that The judging unit comprises: A detection subunit, used for measuring the N first grayscale data after removing the merger step by step on the LED screen, and detecting whether the N first grayscale data after removing the merger presents a periodic change; A first judgment subunit is used for, if it is detected that there is no periodic change, adding grayscale data measured step by step until the first part of grayscale data after merging is removed and the periodic change is detected, and determining that there is a second type of period; The second judgment subunit is used to determine that the first part of grayscale data after N removal and merging does not show periodic change when the number of grayscale data measured step by step reaches a preset threshold and at least three cycles do not appear.

11. The device according to claim 8, characterized in that The measuring module comprises: a period determination unit, configured to determine whether the first part of grayscale data changes periodically when the type of the chip of the LED screen is the second type; A third measuring unit is configured to predict the second part of the grayscale data of the LED screen according to the first part of the grayscale data through a first mode when the judgment result is yes; The fourth measuring unit is used to predict the second part of the grayscale data of the LED screen according to the first part of the grayscale data through the second mode when the judgment result is no.

12. The device according to claim 8, characterized in that The measuring module is used to predict the second part of the grayscale data of the LED screen according to the first part of the grayscale data when the type of the chip of the LED screen is the third type, including: The fifth measuring unit is used to execute step 1, measure a plurality of grayscale data of the LED screen step by step, until n continuous grayscale data on a straight line are obtained, and use the slope of the straight line to predict the next grayscale data of the LED screen; if the predicted next grayscale data meets the predicted value, increase the measurement step length of the step-by-step measurement of the LED screen, wherein the unmeasured grayscale data in the middle of the LED screen is calculated by interpolation prediction; The sixth measuring unit is used to execute step 2. If the predicted next grayscale data does not meet the predicted value, it returns to the previous measurement point and returns to the fifth measuring unit to execute step 1 until all grayscale data of the LED screen are predicted.

13. A non-volatile storage medium, wherein: The non-volatile storage medium includes a stored program, wherein when the program is executed, the device where the non-volatile storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

14. A processor, wherein: The processor is used to run a program, wherein the program executes the method according to any one of claims 1 to 7 when run by the processor.

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