A method for evaluating the dynamic range of infrared scene simulator response

Abstract

The present invention provides a method for evaluating the dynamic range of response of an infrared scene simulator, belonging to the technical field of infrared imaging semi-physical simulation dynamic scene simulation. The method comprises the following steps: constructing a test image; imaging the test image using an infrared thermal imager, comparing the effective imaging pixels in the row direction of the infrared thermal imager with the effective pixels in the row direction of the infrared scene simulator, and resetting the grayscale values ​​of the test image rows and columns based on the comparison results; using the test image as an input scene, respectively setting the infrared scene simulator and the infrared thermal imager; collecting and recording the imaging picture projected by the infrared thermal imager on the infrared scene simulator; eliminating abnormal values ​​in each row and column of the image, analyzing the difference between the image and the constructed test image column-wise data, and performing evaluation. The present invention can greatly reduce the workload, and at the same time, the test image can effectively reflect the simulator's resolution performance for different grayscale levels of real complex scenes. The method is highly operable and has good engineering practicality.

Description

Technical Field

[0001] The invention belongs to the technical field of infrared imaging semi-physical simulation dynamic scene simulation, and in particular relates to a method for evaluating the response dynamic range of an infrared scene simulator. Background Art

[0002] Infrared scene simulators are a key technology in infrared imaging hardware-in-the-loop simulation systems. The dynamic range of the scene projected by an infrared scene simulator reflects the simulator's ability to distinguish grayscale levels in the infrared scene, determining the fidelity of its projection of computer-generated images and serving as a core indicator of infrared scene simulators. The quality of the scene projected by the infrared scene simulator directly impacts the accuracy of the hardware-in-the-loop simulation system's testing and evaluation of infrared imaging systems. Traditional methods for evaluating the dynamic range of infrared scene simulator response construct N test images with grayscale levels ranging from 0 to N-1 based on the simulator's dynamic range. An infrared thermal imager then sequentially captures N images projected by the simulator, and the dynamic range of the infrared scene simulator response is evaluated by analyzing these N images. However, this method suffers from drawbacks such as complex operation and large data volumes. Furthermore, this method only projects a single grayscale image at a time, significantly different from the complex scene projected by the simulator. With the advancement of infrared scene simulator technology, the dynamic range of response has increased from 256 to 1024 and even higher. These drawbacks of traditional evaluation methods have become even more pronounced, making them incapable of accurately simulating infrared scenes.

[0003] Therefore, the present invention proposes a method for evaluating the dynamic range of response of an infrared scene simulator. Summary of the Invention

[0004] Technical issues to be solved:

[0005] To overcome the shortcomings of existing technologies, the present invention provides a method for evaluating the dynamic range of an infrared scene simulator's response. By constructing a test image that matches the simulator's dynamic range, the method can rapidly evaluate the dynamic range of the infrared scene simulator in dynamic scenarios. This method significantly reduces workload, while the test image effectively reflects the simulator's ability to resolve different grayscale levels in complex, realistic scenes. Furthermore, the method is highly operational and possesses excellent engineering practicality.

[0006] The technical solution of the present invention is: a method for evaluating the dynamic range of response of an infrared scene simulator, characterized by the following specific steps:

[0007] Constructing an adaptive test image according to the response dynamic range of the infrared scene simulator, wherein the test image is an image with grayscale levels gradually changing in the row direction;

[0008] Use an infrared thermal imager to image the test image, compare the effective pixels of the infrared thermal imager in the row direction with the effective pixels of the infrared scene simulator in the row direction, and reset the grayscale values ​​of the test image rows and columns according to the comparison results;

[0009] Calculate the number of rows corresponding to each gray level in the test image row upwards;

[0010] When the effective imaging pixels of the infrared thermal imager in the row direction are greater than or equal to the effective pixels of the infrared scene simulator in the row direction, the image grayscale value is increased from 0 to the maximum value in the heading direction of the test image, with the number of rows corresponding to each grayscale level in the row direction of the test image as the interval;

[0011] When the effective imaging pixel of the infrared thermal imager in the row direction is smaller than the effective pixel of the infrared scene simulator in the row direction, the grayscale value of the image is changed from 0 in the heading direction of the test image, and the gradient value of the grayscale value in the row direction of the test image is increased to the maximum value.

[0012] The reconfigured test image is used as the input scene to set up the infrared scene simulator and the infrared thermal imager respectively;

[0013] Adjust the positions of the infrared thermal imager and infrared scene simulator so that the entrance and exit pupils of the two devices coincide and the optical axes are aligned and parallel. Use the infrared thermal imager synchronization signal to trigger the test image projected by the infrared scene simulator. Capture and record the image of the infrared thermal imager projected by the infrared scene simulator.

[0014] Remove outliers in each row and column of the image, analyze the difference in column data between the image and the constructed test image, and perform evaluation.

[0015] A further technical solution of the present invention is that the effective pixel numbers of the infrared scene simulator are R×C, and the pixel resolution of the constructed test image is R×C.

[0016] A further technical solution of the present invention is that the method for calculating the number of rows corresponding to each gray level in the test image row is to divide the effective pixel R of the infrared scene simulator row by the gray level N of the infrared scene simulator response dynamic range and round down the value obtained, that is, to obtain the number of rows R corresponding to each gray level in the row R. Nfloor .

[0017] A further technical solution of the present invention is that the grayscale values ​​of the test image rows and columns are reset as follows:

[0018] When the infrared thermal imager has an effective imaging pixel R IR ≥R, then in the test image row R direction with R Nfloor To set the image grayscale values ​​to 0 to (N-1) in equal intervals, the (RNfloor ×N+1)~R row image grayscale value is set to N-1;

[0019] When the infrared thermal imager has an effective imaging pixel R IR <R, then in the test image row R direction, R Nfloor Set the image grayscale value to start from 0 for equal intervals and use R IRceil The gradient increases until the maximum value (N-1), and the R direction (N / R IRceil +1)~R rows of image grayscale values ​​are set to N-1.

[0020] A further technical solution of the present invention is that the specific configuration of the infrared scene simulator and the infrared thermal imager is based on the temperature resolution of the infrared scene simulator. And the gray level N of the response dynamic range, set the temperature difference between the low-temperature black body and the high-temperature black body of the infrared scene simulator to be no less than According to the temperature difference range between the low-temperature blackbody and the high-temperature blackbody of the infrared scene simulator, select the integration time gear of the infrared thermal imager, and set the integration time of the infrared scene simulator to be consistent with the integration time of the infrared thermal imager.

[0021] A further technical solution of the present invention is: the method for removing abnormal values ​​in each row and column of the image is to divide the recorded imaging picture into three equal parts in the column direction, randomly select three groups of data of R×10 in the three-divided area, and use the selected three groups of data as the evaluation data set R×30; calculate the row mean array R of the evaluation data set μ ×1 and standard deviation R σ ×1, if the absolute value of the difference between the row data and its mean in the evaluation data set is greater than 3 times the standard deviation, it is replaced with the mean to obtain a new evaluation data set. Repeat the above steps until there is no data with an absolute value greater than 3 times the standard deviation between the row data and its mean in the evaluation data set. The final evaluation data set is obtained by removing the outliers in each row and column of the image, and the row mean array R of the final evaluation data set is calculated. <μ> ×1.

[0022] A further technical solution of the present invention is: the evaluation method is to use the row-wise mean array R <μ> The absolute value of the difference between ×1 and the row value of the test image is divided by the row value of the test image to obtain the deviation rate of the infrared scene simulator in responding to different gray levels. The mean of the response deviation rate of different gray levels can be calculated to complete the response dynamic range evaluation of the infrared scene simulator. The lower the response deviation rate, the better the response dynamic range of the infrared scene simulator.

[0023] An infrared scene simulator response dynamic range evaluation system, characterized by comprising an infrared scene simulator, an infrared thermal imager, and a scene image source generation computer, wherein the infrared scene simulator comprises a signal processing circuit, a drive circuit, a blackbody, a blackbody illumination optical system, and a projection matching optical system, wherein the projection matching optical system is arranged relative to the optical entrance pupil of the infrared thermal imager, with the optical axis centers aligned and parallel;

[0024] The scene image source generating computer converts the test image data constructed according to the response dynamic range of the infrared scene simulator into infrared radiation, which is transmitted to the infrared thermal imager through the projection matching optical system to simulate the infrared scene.

[0025] Beneficial effects

[0026] The beneficial effects of the present invention are as follows: the method of the present invention combines the performance and dynamic range indicators of the infrared scene simulator and the indicators of the infrared thermal imager of the test equipment to construct a grayscale gradient test image that can simulate the infrared scene simulator projecting a real complex scene. Based on the comparison of the imaging effective pixels in the row direction of the infrared thermal imager and the effective pixels in the row direction of the infrared scene simulator, the grayscale values ​​in the row direction of the test image are reset to obtain an image that can react dynamically to the reactor. The processed image is then used as input to collect and record the imaging picture of the infrared thermal imager projecting the infrared scene simulator. After removing the abnormal values ​​in the image, an evaluation is performed to complete the dynamic range evaluation of the response of the infrared scene simulator. This method does not require the construction of a large number of test images, which can greatly reduce the workload. At the same time, the test image can effectively reflect the simulator's resolution performance for different grayscale levels of real complex scenes. The method is highly operable and has good engineering practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a flow chart for implementing the dynamic range evaluation of the infrared scene simulator response.

[0028] Figure 2 The figure shows a comparison between the generated test pattern and the infrared scene simulator projection. As can be seen from the figure, the infrared scene simulator can effectively project the test pattern, but its resolution is reduced at lower grayscale levels within the dynamic range. This method can effectively reflect the infrared scene simulator's resolution performance at different grayscale levels and can quickly and easily evaluate the infrared scene simulator's dynamic range response. DETAILED DESCRIPTION

[0029] The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present invention, but should not be construed as limiting the present invention.

[0030] The traditional infrared scene simulator response dynamic range evaluation method has the disadvantages of complex operation and large amount of data. At the same time, this method only projects a single grayscale image at the same time, which is quite different from the real complex scene projected by the simulator. Especially with the development of infrared scene simulator technology, the response dynamic range has developed from 256 to 1024 or even higher. The shortcomings of the traditional evaluation method are more prominent, and it is impossible to simulate the infrared scene accurately. The present invention provides an infrared scene simulator response dynamic range evaluation method, which has the following specific steps:

[0031] Step 1: constructing an adapted test image according to the response dynamic range of the infrared scene simulator, wherein the test image is an image with grayscale levels gradually changing in the row direction;

[0032] Step 2: Use an infrared thermal imager to image the test image, compare the effective pixels in the row direction of the infrared thermal imager with the effective pixels in the row direction of the infrared scene simulator, and reset the grayscale values ​​of the test image rows and columns based on the comparison results;

[0033] Step 2.1: Calculate the number of rows corresponding to each gray level in the test image row upwards;

[0034] Step 2.2: When the effective pixels of the infrared thermal imager in the row direction are equal to or greater than the effective pixels of the infrared scene simulator in the row direction, increase the grayscale value of the test image from 0 to the maximum value in the heading direction, with the number of rows corresponding to each grayscale level in the row direction of the test image as the interval;

[0035] Step 2.3: When the effective pixel of the infrared thermal imager in the row direction is smaller than the effective pixel of the infrared scene simulator in the row direction, the grayscale value of the test image is set to zero in the heading direction, and the gradient value of the grayscale value in the row direction of the test image is used as the transformation gradient value to the maximum value.

[0036] Step 3: Use the reconfigured test image as the input scene to configure the infrared scene simulator and the infrared thermal imager respectively.

[0037] Step 4: Adjust the positions of the infrared thermal imager and infrared scene simulator so that the entrance and exit pupils of the two devices coincide and the optical axes are aligned and parallel. Use the infrared thermal imager synchronization signal to trigger the test image projected by the infrared scene simulator. Capture and record the image of the infrared thermal imager projected on the infrared scene simulator.

[0038] Step 5: Remove outliers in each row and column of the image, analyze the difference in column data between the image and the constructed test image, and perform evaluation.

[0039] The present invention provides an infrared scene simulator response dynamic range evaluation system, comprising an infrared scene simulator, an infrared thermal imager, and a scene image source generation computer. The infrared scene simulator comprises a signal processing circuit, a drive circuit, a blackbody, a blackbody illumination optical system, and a projection matching optical system. The projection matching optical system is arranged relative to an optical entrance pupil of the infrared thermal imager, with optical axis centers aligned and parallel. The scene image source generation computer converts test image data constructed according to the response dynamic range of the infrared scene simulator into infrared radiation, which is transmitted to the infrared thermal imager through the projection matching optical system to simulate the infrared scene.

[0040] The present invention only needs to construct a test image to complete the response dynamic range assessment. The method is simple and highly operable. The following is a further explanation of the above technical solution with reference to specific examples:

[0041] Reference Figure 1 As shown, this embodiment provides a method for evaluating the dynamic range of response of an infrared scene simulator, and the specific steps are as follows:

[0042] Step 1: Based on the effective pixel R×C of the infrared scene simulator, a test image with a grayscale gradient is constructed. The pixel resolution of the test image is R×C.

[0043] Step 2: Use an infrared thermal imager to image the test image and compare the effective pixels of the infrared thermal imager in the row direction with the effective pixels of the infrared scene simulator in the row direction;

[0044] The infrared scene simulator responds to the grayscale level of the dynamic range N. Calculate R / N and round it down to get the number of rows R corresponding to each grayscale level above row R. Nfloor ;

[0045] If the infrared thermal imager has an effective imaging pixel R IR ≥R, then the test image row R is R Nfloor To set the image grayscale values ​​to 0 to (N-1) in equal intervals, the (R Nfloor ×N+1)~R row image grayscale value is set to N-1;

[0046] If R IR <R, calculate R / R IR And round up to get the gradient R of the gray value of the test image row direction IRceil , then in the test image row R to R Nfloor Set the image grayscale value to start from 0 for equal intervals and use R IRceil The gradient increases until the maximum value (N-1), and the R direction (N / R IRceil +1)~R row image grayscale values ​​are set to N-1;

[0047] Step 3: The infrared scene simulator uses the test image as the input scene and calculates the temperature resolution of the infrared scene simulator. And the gray level N of the response dynamic range, set the temperature difference between the low-temperature black body and the high-temperature black body of the infrared scene simulator to be no less than According to the temperature difference range between the low-temperature blackbody and the high-temperature blackbody of the infrared scene simulator, select the integration time gear of the infrared thermal imager, and set the integration time of the infrared scene simulator to be consistent with the integration time of the infrared thermal imager;

[0048] Step 4: Adjust the positions of the infrared thermal imager and infrared scene simulator so that the entrance and exit pupils of the two devices coincide and the optical axes are aligned and parallel. Use the infrared thermal imager synchronization signal to trigger the infrared scene simulator to project the test image. Capture and record the image of the infrared thermal imager projecting the infrared scene simulator.

[0049] Step 5: Divide the recorded image into three equal parts in the column direction, randomly select three groups of data of R×10 in the three-divided area, and use the three selected groups of data as the evaluation data set R×30; calculate the row mean array R of the evaluation data set μ ×1 and standard deviation R σ ×1, if the absolute value of the difference between the row data and its mean in the evaluation data set is greater than 3 times the standard deviation, it is replaced with the mean to obtain a new evaluation data set. Repeat the above steps until there is no data with an absolute value greater than 3 times the standard deviation between the row data and its mean in the evaluation data set. The final evaluation data set is obtained by removing the outliers in each row and column of the image, and the row mean array R of the final evaluation data set is calculated. <μ> ×1;

[0050] Calculate the mean array R of each row and column of three sets of data μ ×1 and standard deviation R σ ×1, remove the outliers whose absolute difference between the data in each row and column and the mean is greater than 3 times the standard deviation, and repeat the above steps until a set of mean arrays R of each row and column without abnormal data is obtained <μ> ×1; analyze and compare the row mean array R <μ> The absolute value of the difference between ×1 and the row value of the test image is divided by the row value of the test image to obtain the deviation rate of the infrared scene simulator in responding to different gray levels, and the mean of the response deviation rate of different gray levels is calculated to complete the response dynamic range evaluation of the infrared scene simulator. The lower the response deviation rate, the better the response dynamic range of the infrared scene simulator, and the response dynamic range evaluation of the infrared scene simulator can be completed.

[0051] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention without departing from the principles and purpose of the present invention.

Claims

1. A method for evaluating the dynamic range of response of an infrared scene simulator, characterized in that The specific steps are as follows: Constructing an adaptive test image according to the response dynamic range of the infrared scene simulator, wherein the test image is an image with grayscale levels gradually changing in the row direction; Use an infrared thermal imager to image the test image, compare the effective pixels of the infrared thermal imager in the row direction with the effective pixels of the infrared scene simulator in the row direction, and reset the grayscale values ​​of the test image rows and columns according to the comparison results; Calculate the number of rows corresponding to each gray level in the test image row upwards; When the effective imaging pixels of the infrared thermal imager in the row direction are greater than or equal to the effective pixels of the infrared scene simulator in the row direction, the grayscale value of the image is increased from 0 to the maximum value in the row direction of the test image, with the number of rows corresponding to each grayscale level in the row direction of the test image as the interval; When the effective imaging pixel of the infrared thermal imager in the row direction is smaller than the effective pixel of the infrared scene simulator in the row direction, the grayscale value of the image is changed from 0 in the row direction of the test image, and the gradient value of the grayscale value in the row direction of the test image is used as the interval; The reconfigured test image is used as the input scene to set up the infrared scene simulator and the infrared thermal imager respectively; Adjust the positions of the infrared thermal imager and infrared scene simulator so that the entrance and exit pupils of the two devices coincide and the optical axes are aligned and parallel. Use the infrared thermal imager synchronization signal to trigger the test image projected by the infrared scene simulator. Capture and record the image of the infrared thermal imager projected by the infrared scene simulator. Remove outliers in each row and column of the image, analyze the difference in column data between the image and the constructed test image, and perform evaluation.

2. The method for evaluating the dynamic range of response of an infrared scene simulator according to claim 1, wherein: The infrared scene simulator has effective row and column pixels of R×C, and the pixel resolution of the constructed test image is R×C.

3. The method for evaluating the response dynamic range of an infrared scene simulator according to claim 2, wherein: The method for calculating the number of rows corresponding to each gray level in the test image row is to divide the effective pixel R of the infrared scene simulator row by the gray level N of the infrared scene simulator response dynamic range and round down the value obtained, that is, to obtain the number of rows R corresponding to each gray level in the row R. Nfloor .

4. The method for evaluating the response dynamic range of an infrared scene simulator according to claim 3, wherein: The operation of resetting the grayscale values ​​of the test image rows and columns is as follows: When the infrared thermal imager has an effective imaging pixel R IR ≥R, then in the test image row R direction with R Nfloor To set the image grayscale values ​​to 0 to (N-1) in equal intervals, the (R Nfloor ×N+1)~R row image grayscale value is set to N-1; When the infrared thermal imager has an effective imaging pixel R IR <R, then in the test image row R direction, R Nfloor Set the image grayscale value to start from 0 for equal intervals and use R IRceil The gradient increases until the maximum value (N-1), and the R direction (N / R IRceil +1)~R rows of image grayscale values ​​are set to N-1.

5. The method for evaluating the response dynamic range of an infrared scene simulator according to claim 4, wherein: The specific configuration of the infrared scene simulator and the infrared thermal imager is as follows: And the gray level N of the response dynamic range, set the temperature difference between the low-temperature black body and the high-temperature black body of the infrared scene simulator to be no less than According to the temperature difference range between the low-temperature blackbody and the high-temperature blackbody of the infrared scene simulator, select the integration time gear of the infrared thermal imager, and set the integration time of the infrared scene simulator to be consistent with the integration time of the infrared thermal imager.

6. The method for evaluating the response dynamic range of an infrared scene simulator according to claim 5, wherein: The method for removing abnormal values ​​in each row and column of the image is to divide the recorded imaging picture into three equal parts in the column direction, randomly select three groups of data of R×10 in the three-divided area, and use the selected three groups of data as the evaluation data set R×30; calculate the row mean array R of the evaluation data set μ ×1 and standard deviation R σ ×1, if the absolute value of the difference between the row data and its mean in the evaluation data set is greater than 3 times the standard deviation, it is replaced with the mean to obtain a new evaluation data set. Repeat the above steps until there is no data with an absolute value greater than 3 times the standard deviation between the row data and its mean in the evaluation data set. The final evaluation data set is obtained by removing the outliers in each row and column of the image, and the row mean array R of the final evaluation data set is calculated. <μ> ×1.

7. The method for evaluating the response dynamic range of an infrared scene simulator according to claim 6, wherein: The evaluation method is to use the row-wise mean array R <μ> The absolute value of the difference between ×1 and the row value of the test image is divided by the row value of the test image to obtain the deviation rate of the infrared scene simulator in responding to different gray levels, and the average of the deviation rate of the response to different gray levels is calculated to complete the evaluation of the response dynamic range of the infrared scene simulator. The lower the response deviation rate, the better the response dynamic range of the infrared scene simulator.

8. An infrared scene simulator response dynamic range evaluation system, used to implement the infrared scene simulator response dynamic range evaluation method according to any one of claims 1 to 7; characterized in that: The infrared scene simulator comprises an infrared thermal imager and a scene image source generating computer. The infrared scene simulator comprises a signal processing circuit, a driving circuit, a blackbody, a blackbody illumination optical system and a projection matching optical system. The projection matching optical system is arranged relative to the optical entrance pupil of the infrared thermal imager, and the optical axis centers are aligned and parallel. The scene image source generating computer converts the test image data constructed according to the response dynamic range of the infrared scene simulator into infrared radiation, which is transmitted to the infrared thermal imager through the projection matching optical system to simulate the infrared scene.

Images