Method for solving wall emissivity based on infrared thermal image of thermal imager to correct brightness

Abstract

The present application relates to the field of target infrared stealth, especially to a wall emissivity solving method based on infrared thermal image of thermal imager, mainly comprising: step 1, collecting infrared thermal image of non-uniform temperature distribution target; step 2, eliminating temperature difference caused by non-uniform wall temperature; step 3, establishing two groups of "gray value-reference temperature" data relationship sets; step 4, solving the corrected temperature distribution set of wall; step 5, solving the corrected spectral radiation reference brightness and correction error of wall; step 6, further solving the wall surface infrared emissivity from the corrected target spectral radiation reference brightness value. According to the solving principle of infrared radiation brightness, the non-uniform distribution characteristics of target temperature are comprehensively considered, the target reference radiation correction brightness of non-uniform temperature distribution wall is obtained by thermal image correction, and the wall surface infrared emissivity is further solved, so that the solving precision of non-uniform temperature distribution wall emissivity can be improved.

Description

Technical Field

[0001] This invention relates to the field of infrared stealth technology for targets, and in particular to a method for solving the wall emissivity based on brightness correction of infrared thermal images from thermal imagers. Background Technology

[0002] When using the energy comparison method to solve the emissivity of a wall sample, the temperature distribution of the wall sample is not uniform. Therefore, the emissivity is obtained by comparing the measured spectral radiance of the target at a temperature higher than the ambient temperature with the theoretical blackbody reference radiance at the same temperature. The result will be affected by the temperature distribution and the sensor position.

[0003] In summary, to improve the accuracy of spectral emissivity calculation, an effective method is needed to correct the target reference radiance. Summary of the Invention

[0004] In view of this, the present invention discloses a method for solving the wall emissivity based on the brightness correction of the infrared thermal image of a thermal imager, so as to correct the target reference radiance and thus accurately solve the wall emissivity.

[0005] The technical solution provided by this invention is specifically: a method for solving the wall emissivity based on the brightness correction of infrared thermal images from thermal imagers, comprising the following steps:

[0006] Step 1: Use an infrared thermal imager to acquire infrared thermal images of non-uniform temperature wall targets;

[0007] Step 2: Preprocess the acquired infrared thermal image: Eliminate the obvious temperature difference between the two sensor areas on the wall and their respective surrounding walls;

[0008] Step 3: Calculate the average grayscale value of the corresponding boundary region of the two sets of sensors for the wall image obtained in Step 2, and establish two sets of "grayscale value-reference temperature" data relationship sets in combination with the actual temperature collected by the sensors.

[0009] Step 4: Match the preprocessed infrared thermal image with the "grayscale value - reference temperature" data relationship set obtained in Step 3, and solve for the corrected temperature distribution set of the wall surface;

[0010] Step 5: Solve for the wall-corrected spectral radiance reference brightness from the corrected temperature distribution set; calculate the correction error by comparing the wall-corrected spectral radiance reference brightness with the blackbody theoretical spectral radiance brightness.

[0011] Step 6: Further solve for the infrared emissivity of the wall surface using the corrected target spectral radiation reference brightness value.

[0012] Furthermore, the relationship between "grayscale value - reference temperature" in step 3 is shown in the following formula:

[0013]

[0014] In the formula, i = 1, 2, ..., m is the row number of the pixel, j = 1, 2, ..., n is the row number of the pixel, T(i,j) is the correction temperature of the pixel, g(i,j) is the gray value of the pixel, and g s1 g represents the average grayscale value within sensor 1 area. s2 T represents the average grayscale value within the sensor 2 area. s1 T is the reference temperature collected by sensor 1. s2 The reference temperature is collected by sensor 2.

[0015] Furthermore, in step 5, the wall-corrected spectral radiance reference brightness is obtained from the corrected temperature distribution set, calculated using the following formula:

[0016]

[0017] In the formula, n t The number of rounded temperatures corrected for the infrared thermal images of the wall surface, T rk L is the corrected temperature after rounding down to the kth integer. λbb T at wavelength λ rk The theoretical radiance, A, obtained from the blackbody spectral radiation formula at a given temperature. rk P represents the area occupied by the wall at the same corrected temperature. rk The percentage of pixels with the same correction temperature, and n t P rk Since the sum of the values ​​is 1, the above formula can also be written as:

[0018]

[0019] Furthermore, the infrared emissivity of the wall surface in step 6 is calculated using the following formula:

[0020]

[0021] In the formula, L λmr To measure brightness data, L λrvs To correct the reference brightness for the target, L λbg This represents the ambient background spectral radiance.

[0022] This invention provides a method for solving wall emissivity based on infrared thermal images from thermal imagers. According to the principle of solving infrared radiation brightness, the corrected brightness value based on the infrared thermal images from thermal imagers is obtained after comprehensively considering the non-uniform distribution characteristics of the target temperature. This method can improve the wall emissivity of non-uniform temperature distribution and is easy to quantify and analyze.

[0023] The method of the present invention can be used to solve the emissivity of walls with non-uniform temperature distribution, and is also applicable to the emissivity of other non-uniform temperature distribution planes.

[0024] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit the disclosure of the present invention. Attached Figure Description

[0025] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a flowchart of a target reference radiance correction method for a non-uniform temperature distribution wall based on an infrared thermal image, provided by an embodiment of the present invention.

[0028] Figure 2 This is an infrared thermal image (color) of a wall surface being heated, captured by an infrared thermal imager according to an embodiment of the present invention.

[0029] Figure 3 This is a preprocessing method for an infrared thermal image (grayscale) of a wall surface at 80℃ provided in an embodiment of the present invention, wherein (a) is the original image and (b) is the image after processing to eliminate differences;

[0030] Figure 4 The temperature distribution of the wall surface at 80°C provided in this embodiment of the invention is a temperature control method, wherein (a) is a geometric distribution and (b) is a histogram distribution.

[0031] Figure 5 This is a comparison of the spectral radiance reference brightness results of the wall surface at 80℃ temperature control provided in the embodiments of the present invention, where (a) is the brightness curve and (b) is the correction error;

[0032] Figure 6 This is a schematic diagram of the brightness and spectral emissivity of the wall surface in the 3-5μm band at 80℃ provided in an embodiment of the present invention;

[0033] Figure 7 This is a schematic diagram of the brightness and spectral emissivity of a wall surface in the 8-14μm band at 80℃ provided in an embodiment of the present invention;

[0034] Figure 8This is a schematic diagram of the brightness and spectral emissivity of a wall surface in the 3-5μm band at a temperature of 100℃ provided in an embodiment of the present invention;

[0035] Figure 9 This is a schematic diagram of the brightness and spectral emissivity of a wall surface in the 8-14μm band at a temperature of 100℃ provided in an embodiment of the present invention;

[0036] Figure 10 This is a schematic diagram of the brightness and spectral emissivity of a wall surface in the 3-5μm band at a temperature control temperature of 120℃, provided in an embodiment of the present invention.

[0037] Figure 11 This is a schematic diagram of the brightness and spectral emissivity of a wall surface in the 8-14μm band at a temperature control temperature of 120℃, provided in an embodiment of the present invention. Detailed Implementation

[0038] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of systems consistent with some aspects of the invention as detailed in the appended claims.

[0039] To improve the accuracy of spectral emissivity calculation in existing technologies, this implementation scheme provides a method for calculating wall emissivity based on brightness correction using infrared thermal images from a thermal imager, such as... Figure 1 As shown, it includes the following steps:

[0040] Step 1: Use an infrared thermal imager to acquire infrared thermal images of non-uniform temperature wall targets;

[0041] Infrared radiation is invisible light. The infrared thermal image generated by an infrared thermal imager is actually a two-dimensional arrangement of the radiation energy received by the imaging unit, which is represented as a two-dimensional array of grayscale values ​​in the entire thermal image data. The grayscale values ​​of the infrared thermal image are scalars that are linearly related to the calculated temperature. Therefore, in the same infrared thermal image, at least two different sets of "grayscale value-reference temperature" correspondences on the wall surface are needed to determine a two-dimensional straight line, achieving a linear mapping of pixel grayscale values ​​to the corrected temperature, thereby obtaining an image of the corrected temperature distribution on the wall surface. This process is called dual-sensor temperature calibration. In this embodiment of the invention, the infrared thermal image generated by the infrared thermal imager is as follows: Figure 2 As shown.

[0042] Step 2: Preprocess the acquired infrared thermal images to eliminate the significant temperature difference between the two sensor areas on the wall and their respective surrounding walls;

[0043] To determine the required "grayscale value - reference temperature" correspondence for dual-sensor temperature calibration, it is necessary to first eliminate the significant differences between the two sensor regions on the wall surface and their respective surrounding walls in the infrared thermal image. This step is called infrared thermal image preprocessing. The sensor regions are filled into the original grayscale image of the wall surface thermal image to complete the infrared thermal image preprocessing, such as... Figure 3 As shown.

[0044] Step 3: Calculate the average grayscale value of the corresponding boundary region of the two sets of sensors for the wall image obtained in Step 3, and establish two sets of "grayscale value-reference temperature" data relationship sets in combination with the actual temperature collected by the sensors.

[0045] The average grayscale value of the corresponding boundary regions of sensor 1 and sensor 2 in the processed image is calculated, and compared with the actual temperatures collected by sensor 1 and sensor 2 to form two sets of "grayscale value - reference temperature" relationships. Based on this grayscale image with a resolution of m×n, the corrected temperature corresponding to the grayscale value of each pixel can be calculated as follows:

[0046]

[0047] In the formula, i = 1, 2, ..., m is the row number of the pixel, j = 1, 2, ..., n is the row number of the pixel, T(i,j) is the correction temperature of the pixel, g(i,j) is the gray value of the pixel, and g s1 g represents the average grayscale value within sensor 1 area. s2 T represents the average grayscale value within the sensor 2 area. s1 T is the reference temperature collected by sensor 1. s2 The reference temperature is collected by sensor 2.

[0048] Now Figure 3 Taking the wall heating experiment data as an example, the resolution of the wall infrared thermal image (grayscale) is 163×270, and the relationship between the two sets of "grayscale value - reference temperature" is shown in Table 1.

[0049] Table 1. Correspondence between temperature calibration of dual sensors on the wall surface at 80℃

[0050]

[0051] Step 4: Combine the infrared thermal image with the obtained "grayscale value - reference temperature" relationship to solve for the corrected temperature distribution on the target surface;

[0052] The average grayscale value g in Table 1 s With reference temperature T s Substituting the numerical values ​​into equation (1), the corrected temperature distribution of the wall at 80℃ is obtained as follows: Figure 4 As shown, the corrected average wall temperature is 79.61℃.

[0053] Step 5: Solve for the wall-corrected spectral radiance reference brightness from the above-mentioned corrected temperature distribution set; calculate the correction error by comparing the wall-corrected spectral radiance reference brightness with the blackbody theoretical spectral radiance brightness.

[0054] Based on the wall surface temperature distribution map, the correction temperature values ​​of each pixel are rounded down to the nearest integer, and the proportion of each correction temperature in the entire wall surface can be obtained as shown in Table 2.

[0055] Assuming the reference emissivity ε is 1, the wall-corrected spectral radiative reference brightness L can be derived from fundamental infrared physics theories. λrvs The calculation model is

[0056]

[0057] In the formula, n t The number of rounded temperatures corrected for the infrared thermal images of the wall surface, T rk L is the corrected temperature after rounding down to the kth integer. λbb T at wavelength λ rk The theoretical radiance, A, obtained from the blackbody spectral radiation formula at a given temperature. rk P represents the area occupied by the wall at the same corrected temperature. rk The percentage of pixels with the same correction temperature, and n t P rk The sum of the values ​​is 1, so the above formula can also be written as

[0058]

[0059] The above formula for blackbody spectral radiation is recorded in "Infrared Physics" published by Tsinghua University Press;

[0060] Substituting the contents of Table 2 into Equation (3), we obtain the temperature-controlled 80℃ wall-corrected spectral radiance reference brightness curve, and compare it with the theoretical spectral radiance of an 80℃ blackbody. Figure 5 As shown, the maximum reference brightness correction range reaches 1.60%.

[0061] Table 2. Percentage of Corrected Temperatures for Wall Thermal Map at 80℃

[0062]

[0063] Table 2. Percentage of Corrected Temperatures for Wall Thermal Map at 80℃

[0064]

[0065] Step 6: Further solve for the infrared emissivity of the wall surface using the corrected target spectral radiation reference brightness value.

[0066] Since the temperature-controlled wall sample has reached thermal equilibrium with its surroundings, the wall radiance collected by the radiometer includes background radiance at the same temperature as the environment. In macroscopic observation, the radiant energy affected by the wall's emissivity is only the portion emitted from the wall that exceeds the ambient temperature.

[0067] L λm (λ)-L λbg (λ)=ε λ (λ)·(L λbb (λ)-L λbg (λ)) (4)

[0068] Among them, L λm It is the spectral radiance of the wall measured by the radiometer, L λbg It is the background spectral radiance at the experimental ambient temperature, ε λ It is the spectral emissivity of the wall surface.

[0069] The wall-exit radiance measured by the radiometer is processed by a radiance regression network to obtain a wall-exit radiance regression curve. The regression radiance data L obtained from the measurement is then used as the basis for the curve. λmr and the target reference brightness L based on infrared thermal image correction λrvs Calculating the spectral emissivity of the wall sample requires excluding the overlap brightness of the wall sample and the environment at the experimental temperature; that is, the wall spectral emissivity ε... λ Calculation formula

[0070]

[0071] and the average emissivity ε of the inner wall surface in a certain band m Calculation formula

[0072]

[0073] In the formula, L λmr To measure brightness data, L λrvs To correct the reference brightness for the target, L λbg λ1 represents the ambient background spectral radiance, and λ2 represents the wavelength range.

[0074] Based on the experimentally obtained wall spectral radiance and infrared thermogram, the obtained regression radiance data L λmr Target Correction Reference Brightness L λrvs and ambient background spectral radiance L λbg Substituting into equation (5), the spectral radiance and emissivity of the wall sample at the three temperatures are calculated as follows: Figure 6-11 As shown;

[0075] Table 3 shows the energy comparison emissivity results of the sample wall with a reference wall emissivity of 0.48 after correction using this method.

[0076] Table 3. Calculation results of emissivity of wall sample 1

[0077]

[0078] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these changes and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for solving the wall emissivity based on brightness correction using infrared thermal images from a thermal imager, characterized in that, Includes the following steps: Step 1: Use an infrared thermal imager to acquire infrared thermal images of non-uniform temperature wall targets; Step 2: Preprocess the acquired infrared thermal image: Eliminate the obvious temperature difference between the two sensor areas on the wall and their respective surrounding walls; Step 3: Calculate the average grayscale value of the corresponding boundary region of the two sets of sensors for the wall image obtained in Step 2, and combine it with the actual temperature collected by the sensors to establish two sets of "grayscale value-reference temperature" data relationship sets; Step 4: Match the preprocessed infrared thermal image with the "grayscale value - reference temperature" data relationship set obtained in Step 3, and solve for the corrected temperature distribution set of the wall surface; Step 5: Solve for the wall-corrected spectral radiance reference brightness from the corrected temperature distribution set; calculate the correction error by comparing the wall-corrected spectral radiance reference brightness with the blackbody theoretical spectral radiance brightness. Step 6: Further solve for the wall infrared emissivity using the corrected target spectral radiance reference brightness value; The relationship between "grayscale value - reference temperature" in step 3 is shown in the following formula: (1) In the formula, i = 1, 2, ..., m is the row number of the pixel, j = 1, 2, ..., n is the column number of the pixel, T(i, j) is the corrected temperature of the pixel, g(i, j) is the gray value of the pixel, and g s1 g represents the average grayscale value within sensor 1 area. s2 T represents the average grayscale value within the sensor 2 area. s1 T is the reference temperature collected by sensor 1. s2 The reference temperature is collected by sensor 2; In step 5, the wall-corrected spectral radiance reference brightness is obtained from the corrected temperature distribution set, and is solved according to the following formula: (2) In the formula, n t The number of rounded temperatures corrected for the infrared thermal images of the wall surface, T rk L is the corrected temperature after rounding down to the kth integer. λbb T at wavelength λ rk The theoretical radiance, A, obtained from the blackbody spectral radiation formula at a given temperature. rk P represents the area occupied by the wall at the same corrected temperature. rk The percentage of pixels with the same correction temperature, and n t P rk Since the sum of the values ​​is 1, the above formula can also be written as: (3) The infrared emissivity of the wall surface in step 6 is calculated using the following formula: (4) In the formula, L λmr To measure brightness data, L λrvs To correct the reference brightness for the target, L λbg This represents the ambient background spectral radiance.

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