A radiometric calibration and temperature inversion method for a cooled infrared thermal imager

Abstract

This invention provides a radiometric calibration and temperature inversion method for a cooled infrared thermal imager, comprising: constructing a temperature calibration device, acquiring multiple calibration temperature points and their corresponding blackbody radiance to obtain corresponding datasets, acquiring two sets of response image grayscale value datasets to obtain a radiometric calibration model; plotting response curves to simultaneously solve for unknown parameters in the radiometric calibration model to obtain a near-range radiometric calibration model; using the modified radiometric calibration model for back-calculation to obtain the actual radiance of the target; pre-setting the constructed lookup table in the embedded processing unit of the infrared thermal imager to perform online temperature inversion output to obtain the absolute temperature of the measured target, and then outputting the absolute temperature of the measured target to a host computer display module. This invention can significantly reduce the calibration workload, enabling the infrared thermal imager to flexibly adjust the integration time and maintain high-precision temperature measurement in complex scenarios, significantly improving its engineering practicality and environmental adaptability.

Description

Technical Field

[0001] This invention relates to the field of infrared thermometry and thermal imaging technology, and in particular to a method for radiometric calibration and temperature inversion of a cooled infrared thermal imager. Background Technology

[0002] Infrared thermal imagers receive infrared energy radiated from targets and convert it into visualized temperature information, finding wide application in industrial inspection, aerospace, energy and power, and non-destructive testing. Cooled infrared thermal imagers, employing cryogenically cooled detectors, offer advantages such as high sensitivity, low noise, and a wide dynamic range. Furthermore, the cooling mechanism's temperature stabilization effect on the detector and optical system reduces the impact of ambient temperature changes on system performance, making them valuable for high-precision infrared temperature measurement. However, the accuracy of cooled infrared thermal imagers remains highly dependent on the radiation calibration model and temperature inversion method; the applicability of the calibration model and the reliability of the inversion algorithm directly affect the accuracy of the measurement results.

[0003] In existing technologies, infrared thermal imagers are typically calibrated using a surface-source blackbody under laboratory conditions, and the resulting calibration models are mostly based on specific integration times and fixed environmental conditions. In practical applications, to adapt to different temperature measurement scenarios, infrared thermal imagers often need to adjust the integration time according to the target temperature range or radiation intensity. However, changes in integration time alter the detector's response characteristics, making the original calibration model difficult to apply directly. Repeated calibration for different integration times is usually required, increasing the workload and hindering rapid deployment in engineering applications. Furthermore, atmospheric absorption and scattering effects caused by factors such as ambient temperature, humidity, altitude, and target distance further reduce the applicability of the calibration model under different operating environments. Some existing methods improve accuracy by introducing complex atmospheric corrections or recalibration, leading to increased computational burden and poor real-time performance. In addition, existing temperature inversion methods often rely on nonlinear fitting or high-order calculations, requiring high computational power from the lower-level computer, which is insufficient to meet the real-time and engineering practicality requirements of embedded infrared thermal imagers. Summary of the Invention

[0004] To overcome the shortcomings of existing technologies, the purpose of this invention is to provide a radiometric calibration and temperature inversion method for cooled infrared thermal imagers. This method can pre-store the radiometric calibration model inside the infrared thermal imager and calculate the corresponding calibration parameters in real time according to any integration time set by the user, eliminating the need for repeated calibration for specific integration times. This not only significantly reduces the calibration workload but also enables the infrared thermal imager to flexibly adjust the integration time and maintain high-precision temperature measurement in complex scenarios, significantly improving its engineering practicality and environmental adaptability.

[0005] To achieve the above objectives, the present invention provides the following solution: a method for radiometric calibration and temperature inversion of a cooled infrared thermal imager, comprising: A temperature calibration device is built, and multiple calibration temperature points and corresponding blackbody radiance are obtained using the temperature calibration device to obtain a corresponding dataset. Then, based on the corresponding dataset, two sets of response image grayscale value datasets are obtained to obtain a radiometric calibration model. The response curve is plotted on the constructed coordinate system using the grayscale value dataset of the response image, so as to solve the unknown parameters of the radiometric calibration model simultaneously and obtain the near-range radiometric calibration model. The near-range radiometric calibration model is corrected using atmospheric transmittance to obtain a corrected radiometric calibration model. Then, the actual radiance of the target is obtained by back-calculating using the corrected radiometric calibration model. Based on the actual radiance and temperature of the target, an approximate linear equation is constructed to form a lookup table. The lookup table is then pre-placed in the embedded processing unit of the infrared thermal imager to perform online temperature inversion output, thereby obtaining the absolute temperature of the target being measured. Finally, the absolute temperature of the target being measured is output to the host computer display module.

[0006] Optionally, a temperature calibration device is constructed, and multiple calibration temperature points and corresponding blackbody radiance are obtained using the temperature calibration device to obtain a corresponding dataset. Then, based on the corresponding dataset, two sets of response image grayscale value datasets are obtained to obtain a radiometric calibration model, including: The temperature calibration device was built by combining an infrared thermal imager, a controllable surface source blackbody, and a host computer. Using the temperature calibration device, multiple calibration temperature points are selected at equal intervals within the ideal temperature measurement range of the infrared thermal imager to control the blackbody temperature and obtain the calibration temperature points. Using Planck's formula, the blackbody radiance at each calibration temperature point is calculated, forming a correspondence table between the calibration temperature point and the blackbody radiance, thus obtaining the corresponding dataset; Based on the corresponding dataset, multiple frames of infrared images are acquired and processed at two integration times, and two sets of response image grayscale value datasets are output to obtain the radiometric calibration model.

[0007] Optionally, based on the corresponding dataset, multiple frames of infrared images are acquired and processed at two integration times, outputting two sets of response image grayscale value datasets to obtain a radiometric calibration model, including: Two different integration times are selected. Under the two integration times, for each calibration temperature point, each controllable surface source blackbody is sequentially set to the temperature value of the calibration temperature point. It is then determined whether the deviation between the real-time temperature of the controllable surface source blackbody and the set temperature is less than 0.01K and the holding time is greater than 1 minute. If so, it is determined that the temperature of the controllable surface source blackbody is stable, and then continuous acquisition of infrared images is performed. Based on two integration times, the multiple frames of infrared images at each calibration temperature point are averaged to output two sets of response image grayscale value datasets, thus obtaining the radiometric calibration model.

[0008] Optionally, a response curve is plotted on the constructed coordinate system using the grayscale dataset of the response image to simultaneously solve for the unknown parameters of the radiometric calibration model, thereby obtaining a near-range radiometric calibration model, including: A coordinate system is formed by setting each of the calibration temperature points as the horizontal axis and the average gray value as the vertical axis. The response curve under the integral time is plotted on the coordinate system using the gray value dataset of the response image. Based on the response curve, the linear region and the gray value saturation region are identified to obtain the temperature measurement range corresponding to the integral time. At two integration times, corresponding blackbody radiance and grayscale points are selected from the linear region to solve the unknown parameters of the radiometric calibration model simultaneously, thus obtaining the near-range radiometric calibration model.

[0009] Optionally, the near-range radiometric calibration model is corrected using atmospheric transmittance to obtain a corrected radiometric calibration model. Then, the actual radiance of the target is obtained by back-calculating using the corrected radiometric calibration model, including: The atmospheric relative humidity, ambient temperature, and target distance are obtained to obtain environmental parameters. Based on these environmental parameters, atmospheric transmittance is calculated using an atmospheric physical model. The attenuation relationship between the inherent radiance of the target and the radiance at the entrance pupil is obtained. Based on the attenuation relationship, the atmospheric transmittance is used to perform inverse compensation on the radiance at the entrance pupil to correct the near-range radiometric calibration model, thereby obtaining the corrected radiometric calibration model. The target grayscale value obtained by the infrared thermal imager during the measurement process is acquired. Based on the target grayscale value, the actual radiance of the target is obtained by back-calculation using the modified radiometric calibration model.

[0010] Optionally, based on the actual radiance and temperature of the target, an approximate linear equation is constructed to form a lookup table. This lookup table is then pre-placed in the embedded processing unit of the infrared thermal imager for online temperature inversion output, yielding the absolute temperature of the target. Finally, the absolute temperature of the target is output to the host computer display module, including: For the nonlinear transcendental equation relationship between the actual radiance of the target and the target temperature, the preset full temperature measurement range is discretized into multiple temperature sub-intervals according to the set fixed temperature step size. The theoretical radiance corresponding to the starting and ending temperature points of each temperature sub-interval is calculated using Planck's formula, and an approximate linear equation between the actual radiance of the target and the target temperature is constructed within each temperature sub-interval. The fitting accuracy of the approximate linear equation is verified. Then, a lookup table is constructed for the approximate linear equations corresponding to all the temperature sub-intervals. The lookup table is pre-placed in the embedded processing unit of the infrared thermal imager to perform online temperature inversion output, obtain the absolute temperature of the target being measured, and then output the absolute temperature of the target being measured to the host computer display module.

[0011] This invention discloses the following technical effects by providing a radiometric calibration and temperature inversion method for a cooled infrared thermal imager: 1. High-precision temperature measurement is still possible even with variable integration time: The calibration model explicitly includes the integration time, so users do not need to repeat the calibration when adjusting the integration time according to the scenario.

[0012] 2. Strong cross-environmental applicability: The model incorporates humidity, ambient temperature, and distance calculations and corrections to improve the accuracy of field temperature measurement.

[0013] 3. Improved real-time performance and engineering applicability: Temperature inversion adopts piecewise interpolation lookup table, avoiding the large amount of calculation required for numerical approximation using traditional transcendental equations, making it suitable for embedded thermal imagers.

[0014] 4. Significantly reduced calibration workload: The entire calibration process no longer needs to be repeated frequently for each integration time and each environment.

[0015] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the method flow provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the temperature calibration device provided in an embodiment of the present invention; Figure 3 A line graph of the response grayscale values ​​of blackbody radiation brightness is provided for embodiments of the present invention; Figure 4 This is a schematic diagram of the grayscale values ​​of the acquired image provided in an embodiment of the present invention; Figure 5 The diagram shows the response grayscale values ​​at integration times of 3ms and 4ms provided in this embodiment of the invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] Example 1 like Figure 1 As shown, this invention provides a method for radiometric calibration and temperature inversion of a cooled infrared thermal imager, comprising: Step 1, as follows Figure 2 As shown, a temperature calibration device is constructed, and multiple calibration temperature points and their corresponding blackbody radiance are obtained using this device to generate a corresponding dataset. Based on this dataset, two sets of response image grayscale value datasets are then obtained to derive a radiometric calibration model. Specifically, this includes: 1.1 Combine an infrared thermal imager, a controllable surface source blackbody, and a host computer to complete the construction of a temperature calibration device; 1.2 Using the temperature calibration device, within the ideal temperature measurement range of the infrared thermal imager, multiple calibration temperature points are selected at equal intervals to control the blackbody temperature, thereby obtaining the calibration temperature points; 1.3 Using Planck's formula, calculate the blackbody radiance at each calibration temperature point, form a correspondence table between the calibration temperature points and the blackbody radiance, and obtain the corresponding dataset; 1.4 Based on the corresponding dataset, multiple frames of infrared images are acquired and processed at two integration times, outputting two sets of response image grayscale value datasets to obtain a radiometric calibration model. Specifically, this includes: 1.4.1 Select two different integration times. Under the two integration times, for each calibration temperature point, set each controllable surface source blackbody to the temperature value of the calibration temperature point in sequence, and determine whether the deviation between the real-time temperature of the controllable surface source blackbody and the set temperature is less than 0.01K and the holding time is greater than 1 minute. If so, it is determined that the temperature of the controllable surface source blackbody is stable, and then the infrared image is continuously acquired. 1.4.2 Based on two integration times, the multiple frames of infrared images at each calibration temperature point are averaged to output two sets of response image grayscale value datasets, thus obtaining the radiometric calibration model.

[0021] Step 2: Using the grayscale dataset of the response image, plot the response curve on the constructed coordinate system to simultaneously solve for the unknown parameters of the radiometric calibration model, thereby obtaining the near-range radiometric calibration model; specifically including: 2.1 Set each of the calibration temperature points as the horizontal axis and the average gray value as the vertical axis to form a coordinate system. Use the gray value dataset of the response image to draw the response curve under the integration time on the coordinate system. Then, based on the response curve, identify the linear region and the gray value saturation region to obtain the temperature measurement range corresponding to the integration time. 2.2 At two integration times, select the corresponding blackbody radiance and grayscale value points from the linear region to solve the unknown parameters of the radiometric calibration model simultaneously, and obtain the near-range radiometric calibration model.

[0022] Step 3: Correct the near-range radiometric calibration model using atmospheric transmittance to obtain a corrected radiometric calibration model. Then, use the corrected radiometric calibration model to inversely calculate the actual radiance of the target. Specifically, this includes: 3.1 Obtain atmospheric relative humidity, ambient temperature and target distance to obtain environmental parameters, and calculate atmospheric transmittance using an atmospheric physical model based on the environmental parameters; 3.2 Obtain the attenuation relationship between the inherent radiance of the target and the radiance at the entrance pupil. Based on the attenuation relationship, use the atmospheric transmittance to perform inverse compensation on the radiance at the entrance pupil to correct the near-range radiometric calibration model and obtain the corrected radiometric calibration model. 3.3 Obtain the target grayscale value obtained by the infrared thermal imager during the measurement process. Based on the target grayscale value, use the modified radiometric calibration model to back-calculate and obtain the actual radiance of the target.

[0023] Step 4: Based on the actual radiance and temperature of the target, construct an approximate linear equation to form a lookup table. This lookup table is then pre-placed in the embedded processing unit of the infrared thermal imager for online temperature inversion output, obtaining the absolute temperature of the target. Finally, the absolute temperature of the target is output to the host computer display module. Specifically, this includes: 4.1 For the nonlinear transcendental equation relationship between the actual radiance of the target and the target temperature, the preset full temperature measurement range is discretized into multiple temperature sub-intervals according to the set fixed temperature step size; 4.2 Calculate the theoretical radiance corresponding to the starting and ending temperature points of each temperature sub-interval using Planck's formula, and construct an approximate linear equation between the actual radiance of the target and the target temperature within each temperature sub-interval; 4.3 The fitting accuracy of the approximate linear equation is verified, and then the approximate linear equations corresponding to all the temperature sub-intervals are constructed into a lookup table. The lookup table is pre-placed in the embedded processing unit of the infrared thermal imager to perform online temperature inversion output, obtain the absolute temperature of the target being measured, and then output the absolute temperature of the target being measured to the host computer display module.

[0024] Example 2 I. Obtaining a close-range calibration model through close-range calibration: 1. Calculate the blackbody radiance: Select N equidistant calibration temperature points to control the blackbody temperature, and calculate the blackbody radiance corresponding to each temperature. The radiance corresponding to a target (blackbody) at temperature T within a wavelength. Calculated using Planck's formula: ; in: First radiation constant ; Second radiation constant ; λ1 and λ2 represent the wavelength range (μm) of the radiation received by the detector. The emissivity of the blackbody (default is 0.99). That is, the radiance at a blackbody temperature of T. .

[0025] 2. Acquire and process infrared images: Within the ideal temperature measurement range of the thermal imager, N calibration temperature points are selected at equal intervals of 2K, and the blackbody source is sequentially set to the aforementioned calibration temperature values. Once the blackbody temperature stabilizes (e.g., when the real-time temperature of the blackbody radiation source deviates from the set temperature by less than 0.01K and remains stable for more than 1 minute), the infrared thermal imager continuously acquires 30 infrared images. This process is repeated for all calibration temperature points until all selections are complete. The 30 infrared images acquired at each temperature are averaged to obtain the grayscale value of the thermal imager's response image at that blackbody temperature. The above steps are repeated at a different integration time.

[0026] 3. Obtain the radiation calibration model: The mathematical expression for the calibration model can be represented as: ; in, The grayscale value of the thermal imager's response image. Let be the integration time of the thermal imager, and k be the slope of the linear response of the thermal imager. Let be the pixel response caused by background stray light, and b be the response intercept. For a specific infrared thermal imager... , b will not change. Since G is a set constant, within the temperature measurement range of the thermal imager, G and It is a linear function.

[0027] 4. Calculate the blackbody radiance corresponding to each calibration temperature point. Using the average grayscale value G, acquired and processed by the infrared thermal imager at the corresponding temperature, as the horizontal axis, and using the average grayscale value G as the vertical axis, data points are projected and connected in a two-dimensional coordinate system to plot the radiance-grayscale response characteristic curve (i.e., G-) at that integration time. Line chart), for example Figure 3 As shown, the temperature measurement range of the thermal imager at that integration time can be obtained based on its linear region and saturation region (thermal imager grayscale value saturation). Figure 3 For example, with an integration time of 4ms, the linear region is 305-315K, while the region above 315K is the saturation region, which exceeds the temperature measurement range of the thermal imager.

[0028] 5. Solve the radiation calibration model: Therefore, based on the two set integration times , Blackbody radiance corresponding to two set blackbody temperatures within the linear region. and and the corresponding thermal imager response grayscale value at the integration time G 1. G 2. G 3. Solve the simultaneous equations according to formula 2. ; All the unknowns of the calibration model formula (2) can be obtained. The integration time t determines the temperature measurement range of the camera. The appropriate integration time t can be selected according to different temperature measurement requirements, and recalibration is not required.

[0029] II. Modified Model for Practical Application Environment: In close-range laboratory calibration, since the blackbody radiation source is close to the infrared thermal imager and the optical path is extremely short, atmospheric absorption and scattering in the transmission path can be ignored, and the atmospheric transmittance is approximately considered to be 1.

[0030] However, in actual field measurements, atmospheric corrections must be made based on real-time meteorological conditions. The specific plan is as follows: 1. Based on the atmospheric physics model, consider the relative humidity of the atmosphere. (Dimensionless), ambient temperature (K), atmospheric transmittance at target distance d (km) for: ; in The specific attenuation coefficient (km) for this infrared band -1 For mid-wave infrared (3-5μm), a value of 0.05 can be used, and for long-wave infrared (8-12μm), a value of 0.09 can be used.

[0031] 2. In practical application environments, the inherent radiance of the observed target. Radiance received at the entrance pupil The following attenuation relationship exists: ; 3. At this point, the atmospheric transmittance is calculated in real time. The actual entrance pupil radiance received by the thermal imager Inverse compensation calculations are performed to eliminate the attenuation effect of atmospheric paths, thereby restoring the target's true radiance. To achieve high-precision long-distance temperature measurement: .

[0032] III. Temperature Inversion: Temperature inversion involves two steps: 1. For the observed target, the thermal imager responds to obtain the gray value G, which is obtained from the modified calibration model formula (7): ; The actual radiance of the target can be obtained by reverse calculation. .

[0033] 2. According to formula (1) ; The temperature T of the observed target is obtained by reverse calculation. However, this equation is a transcendental equation and cannot be solved analytically using elementary functions. Traditional methods use numerical approximation, which involves a large amount of computation. Therefore, this invention proposes a new piecewise interpolation method: (1) Regarding radiance The nonlinear transcendental equation relationship between the target temperature T and the preset full temperature measurement range is discretized into N temperature sub-intervals, where the temperature span of each sub-interval is set to 1K; (2) Establish radiance within each of the aforementioned temperature sub-intervals. The approximate linear equation with temperature T is obtained, and the coefficients of the linear equation corresponding to all sub-intervals are constructed into a lookup table; It should be added that: in actual calibration, coarse step sizes such as 2K and 5K can be selected according to the temperature measurement accuracy requirements. When performing temperature inversion, the entire temperature measurement range is discretized with a fine step size of 1K to ensure the accuracy of the inversion.

[0034] The specific process of constructing the lookup table is as follows: Step 1: Discretization of the entire temperature measurement range First, determine the preset full temperature measurement range [T_{min}, T_{max}] of the infrared thermal imager (e.g., 300K-320K). Set a fixed temperature step size (in this embodiment, the step size is set to 1K).

[0035] The entire temperature range is divided into N consecutive temperature sub-intervals based on the step size. The i-th sub-interval is represented as [T_i, T_{i+1}], where i = 1, 2, ..., N.

[0036] For example: the first interval is [300K, 301K], the second interval is [301K, 302K], and so on.

[0037] Step 2: Precise calculation of radiance at interval boundaries: For each temperature sub-interval [T_i, T_{i+1}], the theoretical radiance values ​​corresponding to the starting temperature point T_i and the ending temperature point T_{i+1} of the interval are calculated using the standard Planck blackbody radiation formula (i.e., Formula 1 in the instruction manual), and denoted as L_{b,i} and L_{b,i+1} respectively.

[0038] Step 3: Establish local linear approximation equations Within each tiny temperature sub-range, assuming temperature T is related to radiance... The relationship is linear. The linear equation is constructed as follows: ; Step 4: Fitting accuracy verification To ensure that the accuracy of the linear approximation meets the measurement requirements, the goodness of fit of the linear equation within the sub-interval (e.g., the coefficient of determination R^2) can be calculated. Step 5: Obtain the lookup table, as shown in Table 1 below: Table 1. Radiance Lookup Table

[0039] (3) The lookup table is pre-placed in the embedded processing unit of the thermal imager; (4) During the measurement process, the infrared thermal imager obtains an infrared grayscale image with a grayscale value of G. The radiance value is calculated according to the formula (7) of the atmospheric transmission correction model. The radiance sub-interval where the match is located is retrieved from the lookup table, and the absolute temperature T of the target under test is directly calculated by using the linear equation of the sub-interval. If a thermal imager observes a target and obtains a grayscale value G_i, substituting this value into formula (7) yields the target's radiance as Lb_i. Assuming Lb_i = 1.248, which corresponds to the interval [1.246+, 1.292] in table 3, substituting Lb_i = 1.248 into the equation corresponding to this interval... That is, we get T_i = 300.05K at this time.

[0040] (5) Output the calculated temperature T to the host computer display module.

[0041] Example 3: The equipment used in this example is a mid-wave cooled infrared thermal imager with an infrared band of 3.7-4.8μm.

[0042] (1) Obtaining the close-range calibration model through close-range calibration: 1. Calculate the blackbody radiance: T is selected within the temperature range of 305-319K, and a blackbody calibration temperature point is set every 2K. The corresponding blackbody radiance is calculated according to formula (1). As shown in Table 2 below: Table 2 Blackbody Radiance

[0043] 2. Acquire and process infrared images: by Figure 2 The device is used for radiometric calibration. First, the integration time t of the thermal imager is set to 2ms. In step 1, the blackbody temperature is set for the sampling points, and 30 infrared images are acquired at each temperature. Taking T=305K as an example, the grayscale values ​​of the acquired images are as follows: Figure 4 As shown. Switch the thermal imager to another integration time of 4ms and repeat the above operation.

[0044] The 30 infrared images obtained in each group are averaged to obtain the thermal imager response grayscale value at the current integration time and blackbody setting temperature. See Table 3 below.

[0045] Table 3. Gray values ​​of thermal imager response

[0046] 3. Based on the data in Tables 2 and 3, plot a line graph showing the relationship between the blackbody radiance Lb and the thermal imager's response grayscale value G. Figure 5 Based on the linearity, it can be determined that the thermal imager reaches grayscale saturation after a temperature of 313K with an integration time of 4ms. Other areas remain linear.

[0047] 4. According to Figure 5 As a result, by selecting the unsaturated temperature points (305, 311 K) at integration times of 3 ms and 4 ms, and substituting the corresponding 3 data points into formula (4), we can obtain: ; Solving for k, we get: k = 8087.916; =5662.44; b= -27421.03; thus, the short-range calibration equation can be obtained.

[0048] ; (2) Modified model for practical application environment: Based on the usage environment of this embodiment, the atmospheric relative humidity is: =0.4, ambient temperature =293K, the atmospheric transmittance at a target distance d=0.005km can be calculated using formula (5). =0.9005; The corrected radiometric calibration model of the infrared thermal imager under these environmental conditions can be obtained as follows: ; Embed this model into the camera.

[0049] (3) Temperature inversion: 1. The piecewise interpolation method is now used to obtain... The piecewise interpolation relationship with T is shown in Table 4, taking the lookup table for the 300K to 320K segment as an example, and the lookup table is embedded in the embedded processing unit. Table 4 Lookup Table

[0050] 2. Using a thermal imager with embedded complete radiation calibration and temperature inversion models, a standard blackbody was tested at different integration times. The obtained temperature data and their errors are shown in Table 5 below: Table 5 Error Table

[0051] The results demonstrate the high accuracy of the radiation calibration system and temperature inversion model of this invention, which can quickly correct the calibration model according to temperature measurement requirements and environmental factors, thereby achieving rapid and high-precision temperature measurement.

[0052] Therefore, this invention provides a radiometric calibration and temperature inversion method for a cooled infrared thermal imager, which can pre-store the radiometric calibration model inside the infrared thermal imager and calculate the corresponding calibration parameters in real time according to any integration time set by the user, without the need for repeated calibration for a specific integration time. This not only greatly reduces the calibration workload, but also enables the infrared thermal imager to flexibly adjust the integration time and maintain high-precision temperature measurement in complex scenarios, significantly improving its engineering practicality and environmental adaptability.

[0053] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0054] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for radiometric calibration and temperature inversion of a cooled infrared thermal imager, characterized in that, include: A temperature calibration device is built, and multiple calibration temperature points and corresponding blackbody radiance are obtained using the temperature calibration device to obtain a corresponding dataset. Then, based on the corresponding dataset, two sets of response image grayscale value datasets are obtained to obtain a radiometric calibration model. The response curve is plotted on the constructed coordinate system using the grayscale value dataset of the response image, so as to solve the unknown parameters of the radiometric calibration model simultaneously and obtain the near-range radiometric calibration model. The near-range radiometric calibration model is corrected using atmospheric transmittance to obtain a corrected radiometric calibration model. Then, the actual radiance of the target is obtained by back-calculating using the corrected radiometric calibration model. Based on the actual radiance and temperature of the target, an approximate linear equation is constructed to form a lookup table. The lookup table is then pre-placed in the embedded processing unit of the infrared thermal imager to perform online temperature inversion output, thereby obtaining the absolute temperature of the target being measured. Finally, the absolute temperature of the target being measured is output to the host computer display module.

2. The radiometric calibration and temperature inversion method for a cooled infrared thermal imager according to claim 1, characterized in that, A temperature calibration device is constructed, and multiple calibration temperature points and their corresponding blackbody radiance are obtained using this device to generate a corresponding dataset. Based on this dataset, two sets of response image grayscale value datasets are then obtained to derive a radiative calibration model, including: The temperature calibration device was built by combining an infrared thermal imager, a controllable surface source blackbody, and a host computer. Using the temperature calibration device, multiple calibration temperature points are selected at equal intervals within the ideal temperature measurement range of the infrared thermal imager to control the blackbody temperature and obtain the calibration temperature points. Using Planck's formula, the blackbody radiance at each calibration temperature point is calculated, forming a correspondence table between the calibration temperature point and the blackbody radiance, thus obtaining the corresponding dataset; Based on the corresponding dataset, multiple frames of infrared images are acquired and processed at two integration times, and two sets of response image grayscale value datasets are output to obtain the radiometric calibration model.

3. The radiometric calibration and temperature inversion method for a cooled infrared thermal imager according to claim 2, characterized in that, Based on the corresponding dataset, multiple frames of infrared images are acquired and processed over two integration times, outputting two sets of response image grayscale value datasets to obtain a radiometric calibration model, including: Two different integration times are selected. Under the two integration times, for each calibration temperature point, each controllable surface source blackbody is sequentially set to the temperature value of the calibration temperature point. It is then determined whether the deviation between the real-time temperature of the controllable surface source blackbody and the set temperature is less than 0.01K and the holding time is greater than 1 minute. If so, it is determined that the temperature of the controllable surface source blackbody is stable, and then continuous acquisition of infrared images is performed. Based on two integration times, the multiple frames of infrared images at each calibration temperature point are averaged to output two sets of response image grayscale value datasets, thus obtaining the radiometric calibration model.

4. The radiometric calibration and temperature inversion method for a cooled infrared thermal imager according to claim 3, characterized in that, Using the grayscale dataset of the response images, a response curve is plotted on the constructed coordinate system to simultaneously solve for the unknown parameters of the radiometric calibration model, resulting in a near-range radiometric calibration model, including: A coordinate system is formed by setting each of the calibration temperature points as the horizontal axis and the average gray value as the vertical axis. The response curve under the integral time is plotted on the coordinate system using the gray value dataset of the response image. Based on the response curve, the linear region and the gray value saturation region are identified to obtain the temperature measurement range corresponding to the integral time. At two integration times, corresponding blackbody radiance and grayscale points are selected from the linear region to solve the unknown parameters of the radiometric calibration model simultaneously, thus obtaining the near-range radiometric calibration model.

5. The radiometric calibration and temperature inversion method for a cooled infrared thermal imager according to claim 4, characterized in that, The near-range radiometric calibration model is corrected using atmospheric transmittance to obtain a corrected radiometric calibration model. Then, the actual radiance of the target is obtained by back-calculating using this corrected radiometric calibration model, including: The atmospheric relative humidity, ambient temperature, and target distance are obtained to obtain environmental parameters. Based on these environmental parameters, atmospheric transmittance is calculated using an atmospheric physical model. The attenuation relationship between the inherent radiance of the target and the radiance at the entrance pupil is obtained. Based on the attenuation relationship, the atmospheric transmittance is used to perform inverse compensation on the radiance at the entrance pupil to correct the near-range radiometric calibration model, thereby obtaining the corrected radiometric calibration model. The target grayscale value obtained by the infrared thermal imager during the measurement process is acquired. Based on the target grayscale value, the actual radiance of the target is obtained by back-calculation using the modified radiometric calibration model.

6. The radiometric calibration and temperature inversion method for a cooled infrared thermal imager according to claim 5, characterized in that, Based on the actual radiance and temperature of the target, an approximate linear equation is constructed to form a lookup table. This lookup table is pre-installed in the embedded processing unit of the infrared thermal imager for online temperature inversion output, obtaining the absolute temperature of the target. The absolute temperature of the target is then output to the host computer display module, including: For the nonlinear transcendental equation relationship between the actual radiance of the target and the target temperature, the preset full temperature measurement range is discretized into multiple temperature sub-intervals according to the set fixed temperature step size. The theoretical radiance corresponding to the starting and ending temperature points of each temperature sub-interval is calculated using Planck's formula, and an approximate linear equation between the actual radiance of the target and the target temperature is constructed within each temperature sub-interval. The fitting accuracy of the approximate linear equation is verified. Then, a lookup table is constructed for the approximate linear equations corresponding to all the temperature sub-intervals. The lookup table is pre-placed in the embedded processing unit of the infrared thermal imager to perform online temperature inversion output, obtain the absolute temperature of the target being measured, and then output the absolute temperature of the target being measured to the host computer display module.

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