Rotation center calibration method and equipment for rotary motion fuzzy imaging system

Abstract

The invention relates to an image processing technology, in particular to a rotation center calibration method and device for a rotation motion fuzzy imaging system, and the method comprises the steps: decoupling the calibration of a rotation center into x-axis calibration and y-axis calibration through employing a geometrical relationship; a rotation center is obtained through calibration and serves as input of a rotation motion deblurring algorithm or other advanced vision tasks; comprising the following steps: y-axis calibration; performing x-axis calibration; y-axis error determination; and determining an x-axis error. The method only needs to calibrate a rotation center once before leaving a factory, and all subsequent rotation motion blurred images can be determined; the method is high in calibration precision, and the single-axis error is less than 1 pixel.

Description

Technical Field

[0001] The invention belongs to the technical field of image processing, and in particular relates to a rotation center calibration method and equipment for a rotational motion blur imaging system. Background Art

[0002] When the camera rotates with the rotating platform, the images acquired by the camera will have rotational motion blur (RMB). For example, on low-cost small satellites, due to the lack of attitude control systems, the satellite will have uncontrolled rotation, and the camera on it will capture images with rotational motion blur. In order to reconstruct textures and details and improve the performance of advanced vision tasks, it is necessary to remove rotational motion blur.

[0003] The rotation center plays a key role in the rotational motion deblurring (RMD) algorithm. Unlike ordinary motion blur, RMB images only satisfy the convolution process along each circle. Therefore, the existing RMD needs to decompose the rotated image into a series of one-dimensional blur sequences along the circle. When the rotation center is inaccurate, all blur sequences will deviate from the convolution process, resulting in ringing artifacts. Therefore, in order to obtain a better RMD restored image, an accurate rotation center is crucial.

[0004] Most of the existing methods for determining the rotation center are based on algorithms. When the rotation center is accurate, the blur degree of the one-dimensional blur sequence is proportional to the radius. Hong et al. in the paper "Fast restoration approach for rotational motion blurred image based on deconvolution along the blurring paths" Optical Engineering, vol. 42, no. 12, pp. 3471–3486. traverse all points in the candidate area and find the point that meets this principle as the rotation center. Isoe et al. in the paper "Blind deconvolution of rotational motion blurred image" in Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications, vol.2012 pp.185–191. proposed a method based on Hough transform. The RMB image is converted into a binary image through the Laplace operator, and the Hough transform is applied to the binary image. The point with the highest score is the rotation center. However, these methods are computationally intensive and have large errors, which limits the performance of the rotational motion deblurring algorithm. Summary of the invention

[0005] The present invention provides a rotation center calibration method and device for a rotational motion blurred imaging system, so as to solve the defects of the prior art that the calculation amount is large and there are large errors, which limit the performance of the rotational motion deblurring algorithm. The rotation center can be obtained by a single calibration, which can be used as the input of the rotational motion deblurring algorithm or other advanced visual tasks.

[0006] The present invention provides a rotation center calibration method for a rotation motion blur imaging system. The calibration of the rotation center is decoupled into x-axis calibration and y-axis calibration by using geometric relationships. The rotation center is obtained by calibration and used as the input of a rotation motion deblurring algorithm or other advanced visual tasks. The method comprises: y-axis calibration; x-axis calibration; y-axis error determination; The x-axis error is determined.

[0007] According to a rotation center calibration method of a rotational motion blur imaging system provided by the present invention, the y-axis calibration includes: 1.1. Randomly select a candidate rotation center and draw a rectangular reference box in the image with this point as the center; 1.2. Select a reference object in your field of view. 1.3. Move the camera until the reference object is tangent to the reference frame in the y-axis direction; 1.4. Rotate the rotating platform 180°. If the rotated reference object is tangent to the reference frame, stop the y-axis calibration. At this time, the y-axis coordinate of the candidate rotation center is the y-axis coordinate of the true rotation center, denoted as yo; otherwise, return to step 1.1.

[0008] According to a rotation center calibration method of a rotational motion blur imaging system provided by the present invention, the x-axis calibration includes: 2.1. Randomly select a candidate rotation center and draw a rectangular reference box in the image with this point as the center; 2.2. Select a reference object in your field of view; 2.3. Move the camera until the reference object is tangent to the reference frame in the x-axis direction; 2.4. Rotate the rotating platform 180°. If the rotated reference object is tangent to the reference frame, stop the x-axis calibration. At this time, the x-axis coordinate of the candidate rotation center is the x-axis coordinate of the true rotation center, denoted as xo; otherwise, return to step 2.1.

[0009] According to a rotation center calibration method for a rotational motion blur imaging system provided by the present invention, the y-axis error determination includes: 3.1. Select a reference object in the field of view and adjust the camera to move the reference object to (xo, yo-2), (xo, yo-1), (xo, yo), (xo, yo+1), (xo, yo+2) respectively; 3.2. Rotate the rotating platform one circle at the above five points and take five sets of videos; 3.3. Check the five sets of videos and find the maximum y-axis coordinate point y1 corresponding to the reference object's obvious downward movement in the video; 3.4. Check the five sets of videos and find the minimum y-axis coordinate point y2 corresponding to the reference object's obvious upward movement in the video; 3.5.The y-axis calibration error is max(yo-y2,y1-yo), where max() is the maximum value operation.

[0010] According to a rotation center calibration method for a rotational motion blur imaging system provided by the present invention, the x-axis error determination includes: 4.1. Select a reference object in the field of view and adjust the camera to move the reference object to (xo-2,yo), (xo-1,yo), (xo,yo), (xo+1,yo), (xo+2,yo) respectively; 4.2. Rotate the rotating platform one circle at the above five points and take five sets of videos; 4.3. Check the five sets of videos and find the maximum x-axis coordinate point x1 corresponding to the obvious rightward shift of the reference object in the video; 4.4. Check the five sets of videos and find the minimum x-axis coordinate point x2 corresponding to the reference object's obvious left shift in the video; 4.5. The calibration error of the x-axis is max(xo-x2,x1-xo), where max() is the maximum value operation.

[0011] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a rotation center calibration method for a rotational motion blur imaging system as described in any one of the above is implemented.

[0012] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for calibrating the rotation center of the rotational motion blur imaging system as described in any one of the above is implemented.

[0013] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method for calibrating the rotation center of the rotational motion blur imaging system as described in any one of the above is implemented.

[0014] Compared with the prior art, the present invention has the following beneficial effects: (1) Compared with the algorithm-based method, the present invention only needs to calibrate the rotation center once before leaving the factory, and all subsequent rotational motion blurred images can be determined; (2) The calibration method of the present invention has high calibration accuracy, and the single-axis error is less than 1 pixel. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 It is a flow chart of a rotation center calibration method of a rotational motion blur imaging system provided by an embodiment of the present invention; FIG2 (a) is a schematic diagram of a reference object being tangent to a rectangular reference frame in the y-axis direction when the rotation angle is 0° provided by an embodiment of the present invention; FIG2( b ) is a schematic diagram showing that a reference object is tangent to a rectangular reference frame in the y-axis direction when the rotation angle is 180°, provided by an embodiment of the present invention; FIG2( c ) is a schematic diagram showing that the reference object is not tangent to the rectangular reference frame in the y-axis direction when the rotation angle is 180° provided by an embodiment of the present invention; FIG3 (a) is a schematic diagram showing that a reference object is tangent to a rectangular reference frame in the x-axis direction when the rotation angle is 0°, provided by an embodiment of the present invention; FIG3( b ) is a schematic diagram showing that the reference object is tangent to the rectangular reference frame in the x-axis direction when the rotation angle is 180° provided by an embodiment of the present invention; FIG3 (c) is a schematic diagram showing that the reference object is not tangent to the rectangular reference frame in the x-axis direction when the rotation angle is 180° provided by an embodiment of the present invention; FIG4 (a) is a diagram showing the position of a reference object at different rotation angles when the candidate rotation center is (591, 417) provided by an embodiment of the present invention; FIG4 (b) is a diagram showing the position of the reference object at different rotation angles when the candidate rotation center is (591, 418) provided by an embodiment of the present invention; FIG5 (a) is a diagram showing the position of a reference object at different rotation angles when the candidate rotation center is (591, 418) provided by an embodiment of the present invention; FIG5( b ) is a diagram showing the position of the reference object at different rotation angles when the candidate rotation center is (592, 417) provided by an embodiment of the present invention; FIG6 (a) is a rotational motion blurred image captured by a rotational motion blurred image imaging system provided by an embodiment of the present invention; FIG6( b ) is a schematic diagram of ringing artifacts that appear in the result of removing rotational motion blur according to the method proposed by Isoe et al. in FIG6( a ) provided by an embodiment of the present invention; FIG6(c) is a schematic diagram of ringing artifacts that appear in the result of the method proposed by Hong et al. for removing rotational motion blur in FIG6(a) provided by an embodiment of the present invention; FIG6 (d) is a schematic diagram of ringing artifacts in the result of the method of this embodiment provided by an embodiment of the present invention; FIG6 (e) is a clear reference image taken when the rotating platform provided by an embodiment of the present invention is stationary; Figure 7 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Since the camera and the rotating platform are fixed together, once the camera is assembled, the rotation center is fixed. This embodiment uses geometric relationships to decouple the calibration of the rotation center into x-axis calibration and y-axis calibration. As long as the rotation center is calibrated once, it can be used as the input of the rotational motion deblurring algorithm or other advanced visual tasks.

[0019] This embodiment is implemented by the following technical solution, a rotation center calibration method of a rotation motion blur imaging system, comprising the following steps: Step 1, y-axis calibration: Step 1.1, randomly select a candidate rotation center and draw a rectangular reference box in the image with this point as the center; Step 1.2, select a reference object in the field of view; Step 1.3, move the camera until the reference object is tangent to the reference frame in the y-axis direction; Step 1.4, rotate the rotating platform 180°. If the rotated reference object is tangent to the reference frame, stop the y-axis calibration. At this time, the y-axis coordinate of the candidate rotation center is the y-axis coordinate of the true rotation center, recorded as y o ; Otherwise, return to step 1.1; Step 2, x-axis calibration: Step 2.1, randomly select a candidate rotation center and draw a rectangular reference box in the image with this point as the center; Step 2.2, select a reference object in the field of view; Step 2.3, move the camera until the reference object is tangent to the reference frame in the x-axis direction; Step 2.4, rotate the rotating platform 180°. If the rotated reference object is tangent to the reference frame, stop the x-axis calibration. At this time, the x-axis coordinate of the candidate rotation center is the x-axis coordinate of the true rotation center, recorded as x o ; Otherwise, return to step 2.1; Step 3, y-axis error determination: Step 3.1, select a reference object in the field of view, and adjust the camera to move the reference object to (x o ,y o -2)、(x o ,y o -1)、(x o ,y o )、(x o ,y o +1), (x o ,y o +2); Step 3.2, rotate the rotating platform one circle at the above five points to obtain five sets of videos; Step 3.3, check the five sets of videos and find the maximum y-axis coordinate point y1 corresponding to the obvious downward movement of the reference object in the video; Step 3.4, check the five sets of videos and find the minimum y-axis coordinate point y2 corresponding to the reference object's obvious upward movement in the video; Step 3.5, the y-axis calibration error is max(y o -y2,y1-y o ), where max() is the maximum value operation.

[0020] Step 4, x-axis error determination: Step 4.1, select a reference object in the field of view, and adjust the camera to move the reference object to (x o -2,y o )、(x o -1,y o )、(x o ,y o )、(x o +1,y o )、(x o +2,y o ); Step 4.2, rotate the rotating platform one circle at the above five points to obtain five sets of videos; Step 4.3, check the five sets of videos and find the maximum x-axis coordinate point x1 corresponding to the obvious rightward shift of the reference object in the video; Step 4.4, check the five sets of videos and find the minimum x-axis coordinate point x2 corresponding to the reference object's obvious left shift in the video; Step 4.5, the x-axis calibration error is max(x o -x2,x1-x o ), where max() is the maximum value operation.

[0021] Example like Figure 1 FIG. 1 is a flow chart of a rotation center calibration method for a rotational motion blur imaging system according to this embodiment. The specific implementation process is as follows: S1, y-axis calibration: S1.1, randomly select a candidate rotation center and draw a rectangular reference box in the image with the point as the center. As shown in Figure 2(a), the red point is selected as the candidate rotation center, and a blue reference box is drawn in the image with the red point as the center; S1.2, select a reference object in the field of view. As shown in Figure 2(a), select "cloud" as the reference object; S1.3, move the camera until the reference object is tangent to the reference frame in the y-axis direction. As shown in Figure 2(a), move the camera so that the "cloud" is tangent to the blue reference frame. For easy observation, enlarge the tangent point and place it in the yellow box in the upper right corner of the image; S1.4, rotate the rotating platform 180°. If the rotated reference object is tangent to the reference frame, as shown in Figure 2(b), stop the y-axis calibration. At this time, the y-axis coordinate of the candidate rotation center is the y-axis coordinate of the true rotation center, recorded as y o ; Otherwise, the reference object is not tangent to the reference frame, as shown in Figure 2(c), and return to S1.1; S2, x-axis calibration: S2.1, randomly select a candidate rotation center and draw a rectangular reference box in the image with the point as the center. As shown in Figure 3(a), the red point is selected as the candidate rotation center, and a blue reference box is drawn in the image with the red point as the center; S2.2, select a reference object in the field of view. As shown in Figure 3(a), select "cloud" as the reference object; S2.3, move the camera until the reference object is tangent to the reference frame in the x-axis direction. As shown in Figure 3(a), move the camera so that the "cloud" is tangent to the blue reference frame. For easy observation, enlarge the tangent point and place it in the yellow box in the upper right corner of the image; S2.4, rotate the rotating platform 180°. If the rotated reference object is tangent to the reference frame, as shown in Figure 3(b), stop the x-axis calibration. At this time, the x-axis coordinate of the candidate rotation center is the x-axis coordinate of the true rotation center, denoted as x o; Otherwise, the reference object is not tangent to the reference frame, as shown in Figure 3(c), and return to S2.1; S3, y-axis error determination: S3.1, select a reference object in the field of view, adjust the camera to move the reference object to (x o ,y o -2)、(x o ,y o -1)、(x o ,y o )、(x o ,y o +1), (x o ,y o +2). As shown in Figure 4, a black dot in the image is selected as a reference. For easy observation, the area near the black dot is enlarged and placed in the yellow box in the lower right corner of the image; S3.2, rotating the rotating platform for one circle at the above five points to obtain five sets of videos; S3.3, check five groups of videos and find the maximum y-axis coordinate point y1 corresponding to the reference object's obvious downward movement in the video. As shown in FIG4(a), the x-axis coordinate of a rotational motion blur imaging system calibrated by the present invention is o = 591;y o = 417. When the reference object coordinates are (591,415), (591,416), and (591,417), the reference object moves downward. For convenience, only the situation at (591,417) is shown here. As shown in Figure 4(a), eight images with different rotation angles are selected in the video, and the rotation angles are 0°, 45°, 90°, 135°, 180°, 225°, 270°, and 315°, respectively. It can be seen that when the rotation angle is 180°, 225°, and 270°, the reference object moves downward significantly, so y1= 417 is taken.

[0022] S3.4, check five sets of videos and find the minimum y-axis coordinate point y2 corresponding to the reference object's obvious upward movement in the video. When the reference object coordinates are (591,418) and (591,419), the reference object moves upward. For convenience, only the situation at (591,418) is shown here. As shown in Figure 4(b), 8 images at different rotation angles are selected in the video, and the rotation angles are 0°, 45°, 90°, 135°, 180°, 225°, 270°, and 315° respectively. It can be seen that when the rotation angles are 135°, 180°, and 225°, the reference object moves upward significantly, so y2= 418 is taken.

[0023] S3.5, the y-axis calibration error is max(y o -y2, y1-y o), where max() is a maximum value operation. In this embodiment, the y-axis calibration error is max(417-417,418-417) = 1.

[0024] S4, x-axis error determination: S4.1, select a reference object in the field of view, adjust the camera to move the reference object to (x o -2,y o )、(x o -1,y o )、(x o ,y o )、(x o +1,y o )、(x o +2,y o ). As shown in Figure 5, a black dot in the image is selected as a reference. For easy observation, the area near the black dot is enlarged and placed in the yellow box in the lower right corner of the image; S4.2, rotating the rotating platform for one circle at the above five points to obtain five sets of videos; S4.3, check five sets of videos and find the maximum x-axis coordinate point x1 corresponding to the reference object's obvious rightward shift in the video. When the reference object coordinates are (589, 417) and (590, 417), the reference object shifts to the right. For convenience, only the situation at (590, 417) is shown here. As shown in Figure 5(a), 8 images at different rotation angles are selected in the video, and the rotation angles are 0°, 45°, 90°, 135°, 180°, 225°, 270°, and 315° respectively. It can be seen that when the rotation angle is 180° and 225°, the reference object moves down significantly, so x1= 590 is taken.

[0025] S4.4, check five sets of videos and find the minimum x-axis coordinate point x2 corresponding to the reference object's obvious left shift in the video. When the reference object coordinates are (592,417) and (593,417), the reference object appears to be shifted to the left. For convenience, only the situation at (592,417) is shown here. As shown in Figure 5(b), 8 images at different rotation angles are selected in the video, and the rotation angles are 0°, 45°, 90°, 135°, 180°, 225°, 270°, and 315° respectively. It can be seen that when the rotation angle is 180° and 225°, the reference object obviously moves downward, so x2= 592 is taken.

[0026] S4.5, the x-axis calibration error is max(x o -x2,x1-x o ), where max() is a maximum value operation. In this embodiment, the y-axis calibration error is max(591-590,592-591) = 1.

[0027] An important purpose of determining the precise rotation center is to improve the performance of the existing rotational motion deblurring algorithm. In this embodiment, a rotational motion blurred image is captured by a rotational motion blurred image imaging system, as shown in FIG6(a), where the rotation speed of the rotating platform is 3 rpm. A clear reference image is captured when the rotating platform is stationary, as shown in FIG6(e). This embodiment uses the method proposed by Isoe et al. in the paper "Blind deconvolution of rotational motion blurred image" in Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications, vol. 2012 pp. 185–191. to calculate the rotation center as (442, 616). This embodiment uses the method proposed by Hong et al. in the paper "Fast restoration approach for rotational motion blurred image based on deconvolution along the blurring paths" Optical Engineering, vol. 42, no. 12, pp. 3471–3486. to calculate the rotation center as (425, 593). These estimated rotation centers are used as inputs to the rotational motion deblurring algorithm proposed by Qin et al. to remove rotational motion blur from Figure 6(a). The results of Isoe et al. are shown in Figure 6(b), where obvious ringing artifacts appear, especially at the location marked by the red circle; the results of Hong et al. are shown in Figure 6(c), where obvious ringing artifacts also appear, especially at the location marked by the red circle; the results of this embodiment are shown in Figure 6(d), where the ringing artifacts are minimal, especially at the location marked by the red circle.

[0028] Figure 7 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 7 As shown, the electronic device may include: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus. The processor may call the logic instructions in the memory to execute the rotation center calibration method of the rotation motion blur imaging system.

[0029] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program code.

[0030] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the rotation center calibration method of the rotational motion blur imaging system provided by the above-mentioned methods.

[0031] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the rotation center calibration method of the rotational motion blur imaging system provided by the above-mentioned methods.

[0032] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0033] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0034] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for calibrating the rotation center of a rotational motion blur imaging system, characterized in that: Using geometric relationships, the calibration of the rotation center is decoupled into x-axis calibration and y-axis calibration. The rotation center is calibrated and used as the input of the rotational motion deblurring algorithm or other advanced vision tasks. This includes: y-axis calibration; x-axis calibration; y-axis error determination; The x-axis error is determined.

2. The rotation center calibration method of the rotational motion blur imaging system according to claim 1, characterized in that: The y-axis calibration include: 1.

1. Randomly select a candidate rotation center and draw a rectangular reference box in the image with this point as the center; 1.

2. Select a reference object in your field of view. 1.

3. Move the camera until the reference object is tangent to the reference frame in the y-axis direction; 1.

4. Rotate the rotating platform 180°. If the rotated reference object is tangent to the reference frame, stop the y-axis calibration. At this time, the y-axis coordinate of the candidate rotation center is the y-axis coordinate of the true rotation center, denoted as yo; otherwise, return to step 1.

1.

3. The rotation center calibration method of the rotational motion blur imaging system according to claim 1, characterized in that: The x-axis calibration include: 2.

1. Randomly select a candidate rotation center and draw a rectangular reference box in the image with this point as the center; 2.

2. Select a reference object in your field of view; 2.

3. Move the camera until the reference object is tangent to the reference frame in the x-axis direction; 2.

4. Rotate the rotating platform 180°. If the rotated reference object is tangent to the reference frame, stop the x-axis calibration. At this time, the x-axis coordinate of the candidate rotation center is the x-axis coordinate of the true rotation center, denoted as xo; otherwise, return to step 2.

1.

4. The rotation center calibration method of the rotational motion blur imaging system according to claim 1, characterized in that: The y-axis error is determined include: 3.

1. Select a reference object in the field of view and adjust the camera to move the reference object to (xo, yo-2), (xo, yo-1), (xo, yo), (xo, yo+1), (xo, yo+2) respectively; 3.

2. Rotate the rotating platform one circle at the above five points and take five sets of videos; 3.

3. Check the five sets of videos and find the maximum y-axis coordinate point y1 corresponding to the reference object's obvious downward movement in the video; 3.

4. Check the five sets of videos and find the minimum y-axis coordinate point y2 corresponding to the reference object's obvious upward movement in the video; 3.5.The y-axis calibration error is max(yo-y2,y1-yo), where max() is the maximum value operation.

5. The rotation center calibration method of the rotational motion blur imaging system according to claim 1, characterized in that: The x-axis error is determined include: 4.

1. Select a reference object in the field of view and adjust the camera to move the reference object to (xo-2,yo), (xo-1,yo), (xo,yo), (xo+1,yo), (xo+2,yo) respectively; 4.

2. Rotate the rotating platform one circle at the above five points and take five sets of videos; 4.

3. Check the five sets of videos and find the maximum x-axis coordinate point x1 corresponding to the obvious rightward shift of the reference object in the video; 4.

4. Check the five sets of videos and find the minimum x-axis coordinate point x2 corresponding to the reference object's obvious left shift in the video; 4.

5. The calibration error of the x-axis is max(xo-x2,x1-xo), where max() is the maximum value operation.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the rotation center calibration method of the rotational motion blur imaging system as described in any one of claims 1 to 5 is implemented.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for calibrating the rotation center of a rotational motion blur imaging system as described in any one of claims 1 to 5 is implemented.

8. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for calibrating the rotation center of a rotational motion blur imaging system as described in any one of claims 1 to 5 is implemented.

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