Image signal-to-noise ratio improving method and device

Abstract

The invention relates to the technical field of image processing, and particularly provides an image signal-to-noise ratio improving method and device, which are characterized in that an overlapping region between adjacent frames is fully utilized by setting proper heading and lateral overlapping rates, and the signal-to-noise ratio of the image is remarkably improved by performing weighted fusion and noise reduction processing on multiple frames of images in the overlapping region. In order to solve the problem that the signal-to-noise ratio is reduced due to shortening of the exposure time, the balance between the image quality and the efficiency can be optimized while the imaging efficiency is ensured by applying a mode of flexibly adjusting the overlapping ratio. The efficient signal-to-noise ratio improving scheme is particularly suitable for high-speed flight platforms such as unmanned aerial vehicles and reconnaissance planes, is widely applied to environment monitoring, disaster assessment and other high-precision wide-area aerial imaging fields, can effectively improve the image quality of an aerial imaging system in a wide-area fine imaging task, and has a wide application prospect.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and specifically provides a method and device for improving the signal-to-noise ratio of an image. Background Art

[0002] With the continuous advancement of aerial imaging technology, wide-area rapid scene observation is finding increasingly widespread applications in areas such as environmental monitoring and disaster relief. In wide-area, high-resolution aerial imaging applications, the flight platform typically flies at a high altitude and high speed (a high speed-to-height ratio). When performing wide-area rapid imaging missions, due to the high flight speed, in order to achieve wide-area imaging coverage, it is often necessary to shorten the exposure time to reduce image blur caused by motion motion. However, an exposure time that is too short results in insufficient light input, thereby reducing the image's signal-to-noise ratio. This problem is particularly prominent under high speed-to-height ratio and low exposure conditions, where image quality is significantly affected. Traditionally, one way to improve image quality is to extend the exposure time, but this increases the risk of motion blur, resulting in loss or distortion of image details. Therefore, how to improve imaging efficiency and reduce exposure time while maintaining image quality has become a pressing challenge in aerial imaging.

[0003] Under high-speed flight conditions, in order to reduce image motion blur caused by aircraft movement during imaging, the camera exposure time needs to be shortened. However, shortening the exposure time will reduce the incident light energy, resulting in a decrease in the signal-to-noise ratio (SNR) of the imaging system. This problem seriously affects image quality and causes information loss, especially in low-light environments. Traditional solutions usually rely on high-sensitivity sensors or post-processing enhancements, but these methods still face physical limitations in high-speed imaging. The present invention proposes a signal-to-noise ratio improvement method based on multi-frame superposition noise reduction, which utilizes the heading overlap rate and lateral overlap rate of the image during aerial imaging, and performs signal fusion on the overlapping areas between adjacent frames to achieve image quality improvement in local areas. This method can effectively reduce the problem of signal-to-noise ratio degradation caused by shortened exposure time while ensuring imaging efficiency. Summary of the Invention

[0004] To solve the above problems, the present invention provides a method and device for improving the image signal-to-noise ratio, which significantly improves the image signal-to-noise ratio by performing weighted fusion and noise reduction processing on multiple frames of images in the overlapping area.

[0005] In a first aspect, an embodiment of the present invention provides a method for improving an image signal-to-noise ratio, comprising: Determine the heading overlap rate and sideways overlap rate of a single-frame image based on the specific parameters of the aviation platform; Determining the registration relationship between adjacent frame images of the single frame image, extracting pixel positions corresponding to overlapping regions of the single frame images, and completing extraction of overlapping regions and image registration; Performing weighted fusion processing on the pixel positions corresponding to the extracted overlapping areas to obtain a fused image; evaluating and optimizing the signal-to-noise ratio of the fused image, and feeding the evaluation result back to the overlap rate adjustment process; Dynamically adjust the overlap rate according to real-time task requirements and environmental changes, and complete dynamic overlap rate adjustment strategy and optimization.

[0006] As a preferred solution, the determining of the heading overlap rate and the side overlap rate of a single-frame image based on specific parameters of the aerial platform includes: According to the specific parameters of the aviation platform, including flight speed v, flight altitude H, camera field of view angle FOV and imaging frame rate f, scientifically determine the heading overlap rate Side overlap ratio , the heading overlap rate The calculation formula is as follows: (1.3) The calculation formula for the ground coverage length L of the single-frame image is: (1.4).

[0007] As a preferred solution, determining the registration relationship between adjacent frame images of the single frame image, extracting the pixel positions corresponding to the overlapping areas of the single frame images, and completing the extraction of the overlapping areas and image registration include: The onboard inertial navigation system INS, global positioning system GPS and / or image matching algorithm of the aviation platform are used to determine the registration relationship between adjacent frame images, extract the pixel positions corresponding to the overlapping areas of the single frame images, and ensure the accuracy of subsequent image fusion.

[0008] As a preferred solution, the step of performing weighted fusion processing on the pixel positions corresponding to the extracted overlapping areas to obtain a fused image includes: Perform weighted fusion on the extracted overlapping areas to obtain the best signal-to-noise ratio improvement effect. Suppose the k-th frame image is at position Pixel grayscale value The corresponding weighting coefficient is , the grayscale value of the fused image is: (1.5) Weighting coefficient w k The calculation method is determined according to the quality or noise level of each frame image: (1.6) in, Represents the variance estimate of the noise in the frame image, which is obtained through image statistics methods such as mean-variance estimation method.

[0009] As a preferred solution, the signal-to-noise ratio of the fused image is evaluated and optimized, and the evaluation result is fed back to the overlap rate adjustment process, including: The fused image is quantitatively evaluated using the regional mean square error method, peak signal-to-noise ratio (PSNR), or a direct signal-to-noise ratio measurement algorithm. The evaluation results are fed back to the overlap rate adjustment process. If the evaluation finds that the signal-to-noise ratio does not meet expectations, the overlap rate is increased and the number of superimposed frames is increased to further improve the signal-to-noise ratio. If the signal-to-noise ratio has met the task requirements, the overlap rate is reduced to improve the coverage efficiency of the platform imaging task.

[0010] As a preferred solution, the method of dynamically adjusting the overlap rate according to real-time task requirements and environmental changes to complete the dynamic overlap rate adjustment strategy and optimization includes: In low-light environments, high-speed flight conditions, or when high-quality imaging is required, the heading overlap rate and lateral overlap rate are increased, the number of multi-frame stacking is increased, the image signal-to-noise ratio is improved, and the image quality loss caused by insufficient exposure is compensated. In mission scenarios with good ambient lighting conditions or time-sensitive tasks, the heading overlap rate and the lateral overlap rate are dynamically reduced to utilize the high-speed advantage of the flight platform to improve imaging efficiency.

[0011] As a preferred solution, the heading overlap rate is set in a range of 30% to 80%, and the lateral overlap rate is set in a range of 20% to 60%.

[0012] As a preferred solution, it also includes: The real image information in the single frame image is recorded as , random noise information is recorded as , then the signal-to-noise ratio of a single frame image is defined as: (1.1) When K frames of images are taken continuously in the same area, the real image information after superposition and fusion is accumulated as follows: ; Since noise is usually random and different frames are independent of each other, the noise intensity after superposition is , the signal-to-noise ratio after multi-frame superposition is expressed as: (1.2) In a second aspect, the present invention further provides an image signal-to-noise ratio improving device, comprising: The first determining unit is used to determine the heading overlap rate and the lateral overlap rate of the single-frame image according to specific parameters of the aviation platform; A second determining unit is used to determine the registration relationship between adjacent frame images of the single frame image, extract the pixel positions corresponding to the overlapping areas of the single frame images, and complete the extraction of the overlapping areas and image registration; A weighted fusion unit, configured to perform weighted fusion processing on the pixel positions corresponding to the extracted overlapping areas to obtain a fused image; An evaluation unit, configured to evaluate and optimize the signal-to-noise ratio of the fused image, and to feed back the evaluation result to the overlap rate adjustment process; The dynamic adjustment unit is used to dynamically adjust the overlap rate according to real-time task requirements and environmental changes, and complete the dynamic overlap rate adjustment strategy and optimization.

[0013] Compared with the prior art, the present invention can achieve the following beneficial effects: An image signal-to-noise ratio improvement method and device provided in an embodiment of the present invention, by setting appropriate heading and lateral overlap rates, enables full utilization of the overlapping areas between adjacent frames, and significantly improves the image signal-to-noise ratio by performing weighted fusion and noise reduction processing on multiple frames of images in the overlapping area. In response to the problem of decreased signal-to-noise ratio due to shortened exposure time, the present invention proposes a method for flexibly adjusting the overlap rate, which can optimize the balance between image quality and efficiency while ensuring imaging efficiency. By using an efficient signal-to-noise ratio improvement solution, it is particularly suitable for high-speed flying platforms such as drones and reconnaissance aircraft, and is widely used in environmental monitoring, disaster assessment and other high-precision wide-area aerial imaging fields. The implementation of the present invention can effectively improve the image quality of aerial imaging systems in wide-area fine imaging tasks, and has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a flowchart of a method for improving image signal-to-noise ratio according to an embodiment of the present invention; Figure 2 is a schematic diagram of overlapping areas in a method for improving an image signal-to-noise ratio provided by an embodiment of the present invention; Figure 3 4 is a structural block diagram of an image signal-to-noise ratio improvement device provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0015] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the following description, identical modules are denoted by identical reference numerals. In the case of identical reference numerals, their names and functions are also identical. Therefore, their detailed description will not be repeated.

[0016] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and do not constitute a limitation of the present invention.

[0017] Combine Figure 1 As shown, an embodiment of the present invention provides a method for improving the image signal-to-noise ratio, including: S101. Determine the heading overlap rate and the side overlap rate of a single-frame image according to specific parameters of the aviation platform.

[0018] S102: Determine the registration relationship between adjacent frame images of the single frame image, extract pixel positions corresponding to overlapping areas of the single frame images, and complete extraction of overlapping areas and image registration.

[0019] S103 , performing weighted fusion processing on the pixel positions corresponding to the extracted overlapping areas to obtain a fused image.

[0020] S104: Evaluate and optimize the signal-to-noise ratio of the fused image, and feed the evaluation result back to the overlap rate adjustment process.

[0021] S105. Dynamically adjust the overlap rate according to real-time task requirements and environmental changes, and complete the dynamic overlap rate adjustment strategy and optimization.

[0022] Addressing the low signal-to-noise ratio (SNR) problem caused by shortened exposure times during wide-area rapid imaging in existing aerial imaging systems, this invention, unlike traditional SNR enhancement methods, adjusts the relationship between overlap and imaging efficiency to maximize the high-speed characteristics of the flight platform, improving imaging efficiency while significantly improving the image's SNR. This method is particularly suitable for the use of high-speed flight platforms in wide-area rapid scene observation, offering high image quality improvement efficiency and practical application value.

[0023] In some embodiments, in S101, determining the heading overlap rate and the side overlap rate of a single frame image based on specific parameters of the aerial platform includes: According to the specific parameters of the aviation platform, including flight speed v, flight altitude H, camera field of view angle FOV and imaging frame rate f, scientifically determine the heading overlap rate Side overlap ratio , the heading overlap rate The calculation formula is as follows: (1.3) The calculation formula for the ground coverage length L of the single-frame image is: (1.4).

[0024] In some embodiments, the heading overlap rate is set in a range of 30% to 80%, and the lateral overlap rate is set in a range of 20% to 60%. Ordinary technicians in this field can flexibly choose and there is no limitation on this.

[0025] In some embodiments, in S102, determining the registration relationship between adjacent frame images of the single frame image, extracting pixel positions corresponding to overlapping regions of the single frame images, and completing extraction of overlapping regions and image registration include: The onboard inertial navigation system INS, global positioning system GPS and / or image matching algorithm of the aviation platform are used to determine the registration relationship between adjacent frame images, extract the pixel positions corresponding to the overlapping areas of the single frame images, and ensure the accuracy of subsequent image fusion.

[0026] In some embodiments, in S103, performing weighted fusion processing on the pixel positions corresponding to the extracted overlapping areas to obtain a fused image includes: Perform weighted fusion on the extracted overlapping areas to obtain the best signal-to-noise ratio improvement effect. Suppose the k-th frame image is at position Pixel grayscale value The corresponding weighting coefficient is , the grayscale value of the fused image is: (1.5) Weighting coefficient w k The calculation method is determined according to the quality or noise level of each frame image: (1.6) in, Represents the variance estimate of the noise in the frame image, which is obtained through image statistics methods such as mean-variance estimation method.

[0027] In some embodiments, in S104, evaluating and optimizing the signal-to-noise ratio of the fused image, and feeding back the evaluation result to the overlap rate adjustment process, includes: In order to solve the problem of insufficient image signal-to-noise ratio caused by shortened exposure time as described in the background of the present invention, the regional mean square error method, peak signal-to-noise ratio PSNR or signal-to-noise ratio direct measurement algorithm are used to quantitatively evaluate the fused image, and the evaluation results are fed back to the overlap rate adjustment process. If the evaluation finds that the signal-to-noise ratio does not meet the expectations, the overlap rate can be appropriately increased and the number of superimposed frames can be increased to further improve the signal-to-noise ratio; if the signal-to-noise ratio has met the task requirements, it means that this method has successfully taken into account the imaging efficiency while ensuring the imaging quality, and the overlap rate can be appropriately reduced to improve the coverage efficiency of the platform imaging task.

[0028] In some embodiments, in S105, dynamically adjusting the overlap ratio according to real-time task requirements and environmental changes to complete the dynamic overlap ratio adjustment strategy and optimization includes: In low-light environments, high-speed flight conditions, or when high-quality imaging is required, appropriately increase the heading and lateral overlap rates to effectively increase the number of multi-frame stacks, significantly improve the image signal-to-noise ratio, and compensate for the loss of imaging quality caused by underexposure. In mission scenarios with good ambient lighting conditions or time-sensitive tasks, the heading and lateral overlap rates can be dynamically reduced to fully utilize the high-speed advantage of the flight platform and effectively improve imaging efficiency.

[0029] Combine Figure 2 As shown, the signal-to-noise ratio of the wide-area aerial imaging system is effectively improved by the stacking and fusion technology of multiple frames of images. In some embodiments, the method further includes: The real image information in the single frame image is recorded as , random noise information is recorded as , then the signal-to-noise ratio of a single frame image is defined as: (1.1) When K frames of images are taken continuously in the same area, the real image information after superposition and fusion is accumulated as follows: ; Since noise is usually random and different frames are independent of each other, the noise intensity after superposition is , the signal-to-noise ratio after multi-frame superposition is expressed as: (1.2) The above formula clearly shows that the multi-frame image superposition processing can increase the signal-to-noise ratio exponentially. The theoretical improvement factor is proportional to the square root of the number of superimposed frames, effectively solving the problem of insufficient signal-to-noise ratio of single-frame images.

[0030] A method for improving the image signal-to-noise ratio provided in an embodiment of the present invention makes full use of the overlapping area between adjacent frames by setting appropriate heading and lateral overlap rates, and significantly improves the signal-to-noise ratio of the image by performing weighted fusion and noise reduction processing on multiple frames of images in the overlapping area. In response to the problem of decreased signal-to-noise ratio due to shortened exposure time, the present invention proposes a method for flexibly adjusting the overlap rate, which can optimize the balance between image quality and efficiency while ensuring imaging efficiency. By using an efficient signal-to-noise ratio improvement solution, it is particularly suitable for high-speed flying platforms such as drones and reconnaissance aircraft, and is widely used in environmental monitoring, disaster assessment and other high-precision wide-area aerial imaging fields. The implementation of the present invention can effectively improve the image quality of aerial imaging systems in wide-area fine imaging tasks, and has broad application prospects.

[0031] Combine Figure 3As shown, accordingly, an embodiment of the present invention further provides an image signal-to-noise ratio improving device, comprising: The first determining unit 301 is configured to determine the heading overlap rate and the lateral overlap rate of a single frame image according to specific parameters of the aerial platform; The second determining unit 302 is configured to determine the registration relationship between adjacent frames of the single-frame image, extract pixel positions corresponding to overlapping regions of the single-frame image, and complete extraction of overlapping regions and image registration; A weighted fusion unit 303 is configured to perform weighted fusion processing on the pixel positions corresponding to the extracted overlapping areas to obtain a fused image; An evaluation unit 304 is configured to evaluate and optimize the signal-to-noise ratio of the fused image, and to feed back the evaluation result to the overlap rate adjustment process; The dynamic adjustment unit 305 is used to dynamically adjust the overlap rate according to real-time task requirements and environmental changes, and implement dynamic overlap rate adjustment strategy and optimization.

[0032] An image signal-to-noise ratio enhancement device provided in an embodiment of the present invention makes full use of the overlapping area between adjacent frames by setting appropriate heading and lateral overlap rates, and significantly improves the signal-to-noise ratio of the image by performing weighted fusion and noise reduction processing on multiple frames of images in the overlapping area. In response to the problem of decreased signal-to-noise ratio due to shortened exposure time, the present invention proposes a method of flexibly adjusting the overlap rate, which can optimize the balance between image quality and efficiency while ensuring imaging efficiency. By using an efficient signal-to-noise ratio enhancement scheme, it is particularly suitable for high-speed flying platforms such as drones and reconnaissance aircraft, and is widely used in environmental monitoring, disaster assessment and other high-precision wide-area aerial imaging fields. The implementation of the present invention can effectively improve the image quality of aerial imaging systems in wide-area fine imaging tasks, and has broad application prospects.

[0033] Although the embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

[0034] The above specific embodiments of the present invention do not constitute a limitation on the scope of protection of the present invention. Any other corresponding changes and modifications made based on the technical concept of the present invention should be included in the scope of protection of the claims of the present invention.

Claims

1. A method for improving the signal-to-noise ratio of an image, characterized in that: include: Determine the heading overlap rate and sideways overlap rate of a single-frame image based on the specific parameters of the aviation platform; Determining the registration relationship between adjacent frame images of the single frame image, extracting pixel positions corresponding to overlapping regions of the single frame images, and completing extraction of overlapping regions and image registration; Performing weighted fusion processing on the pixel positions corresponding to the extracted overlapping areas to obtain a fused image; evaluating and optimizing the signal-to-noise ratio of the fused image, and feeding the evaluation result back to the overlap rate adjustment process; Dynamically adjust the overlap rate according to real-time task requirements and environmental changes, and complete dynamic overlap rate adjustment strategy and optimization.

2. The image signal-to-noise ratio improvement method according to claim 1, wherein: Determining the heading overlap rate and the side overlap rate of a single-frame image based on specific parameters of the aerial platform includes: According to the specific parameters of the aviation platform, including flight speed v, flight altitude H, camera field of view angle FOV and imaging frame rate f, scientifically determine the heading overlap rate Side overlap ratio , the heading overlap rate The calculation formula is as follows: (1.3) The calculation formula for the ground coverage length L of the single-frame image is: (1.4)。 3. The image signal-to-noise ratio improvement method according to claim 2, wherein: Determining the registration relationship between adjacent frame images of the single frame image, extracting pixel positions corresponding to overlapping areas of the single frame image, and completing extraction of overlapping areas and image registration, includes: The onboard inertial navigation system INS, global positioning system GPS and / or image matching algorithm of the aviation platform are used to determine the registration relationship between adjacent frame images, extract the pixel positions corresponding to the overlapping areas of the single frame images, and ensure the accuracy of subsequent image fusion.

4. The image signal-to-noise ratio improvement method according to claim 3, wherein: The step of performing weighted fusion processing on the pixel positions corresponding to the extracted overlapping areas to obtain a fused image includes: Perform weighted fusion on the extracted overlapping areas to obtain the best signal-to-noise ratio improvement effect. Suppose the k-th frame image is at position Pixel grayscale value The corresponding weighting coefficient is , the grayscale value of the fused image is: (1.5) Weighting coefficient w k The calculation method is determined according to the quality or noise level of each frame image: (1.6) in, Represents the variance estimate of the noise in the frame image, which is obtained through image statistics methods such as mean-variance estimation method.

5. The method for improving the image signal-to-noise ratio according to claim 4, wherein: The signal-to-noise ratio of the fused image is evaluated and optimized, and the evaluation result is fed back to the overlap rate adjustment process, including: The fused image is quantitatively evaluated using the regional mean square error method, peak signal-to-noise ratio (PSNR), or a direct signal-to-noise ratio measurement algorithm. The evaluation results are fed back to the overlap rate adjustment process. If the evaluation finds that the signal-to-noise ratio does not meet expectations, the overlap rate is increased and the number of superimposed frames is increased to further improve the signal-to-noise ratio. If the signal-to-noise ratio has met the task requirements, the overlap rate is reduced to improve the coverage efficiency of the platform imaging task.

6. The method for improving the image signal-to-noise ratio according to claim 5, wherein: The method of dynamically adjusting the overlap rate according to real-time task requirements and environmental changes to complete the dynamic overlap rate adjustment strategy and optimization includes: In low-light environments, high-speed flight conditions, or when high-quality imaging is required, the heading overlap rate and lateral overlap rate are increased, the number of multi-frame stacking is increased, the image signal-to-noise ratio is improved, and the image quality loss caused by insufficient exposure is compensated. In mission scenarios with good ambient lighting conditions or time-sensitive tasks, the heading overlap rate and the lateral overlap rate are dynamically reduced to utilize the high-speed advantage of the flight platform to improve imaging efficiency.

7. The image signal-to-noise ratio improvement method according to claim 1, wherein: The setting range of the heading overlap rate is 30% to 80%, and the setting range of the lateral overlap rate is 20% to 60%.

8. The method for improving the image signal-to-noise ratio according to claim 1, wherein: Also includes: The real image information in the single frame image is recorded as , random noise information is recorded as , then the signal-to-noise ratio of a single frame image is defined as: (1.1) When K frames of images are taken continuously in the same area, the real image information after superposition and fusion is accumulated as follows: ; Since noise is usually random and different frames are independent of each other, the noise intensity after superposition is , the signal-to-noise ratio after multi-frame superposition is expressed as: (1.2)。 9. An image signal-to-noise ratio improvement device, characterized in that: include: The first determining unit is used to determine the heading overlap rate and the lateral overlap rate of the single-frame image according to specific parameters of the aviation platform; A second determining unit is used to determine the registration relationship between adjacent frame images of the single frame image, extract the pixel positions corresponding to the overlapping areas of the single frame images, and complete the extraction of the overlapping areas and image registration; A weighted fusion unit, configured to perform weighted fusion processing on the pixel positions corresponding to the extracted overlapping areas to obtain a fused image; An evaluation unit, configured to evaluate and optimize the signal-to-noise ratio of the fused image, and to feed back the evaluation result to the overlap rate adjustment process; The dynamic adjustment unit is used to dynamically adjust the overlap rate according to real-time task requirements and environmental changes, and complete the dynamic overlap rate adjustment strategy and optimization.

Images