Method and apparatus for deformation correction of pushbroom imaging of aerial targets with known size

Abstract

This invention relates to the field of remote sensing image processing technology, and particularly to a method and apparatus for deformation correction of pushbroom imaging of aerial targets with known dimensions. The method includes: establishing a deformation parameter model with the target pushbroom imaging scaling ratio as the core; processing hyperspectral pushbroom imaging data under the premise of known target geometry, extracting the pixel dimensions of the target's circumscribed rectangle along the pushbroom direction, the pixel dimensions perpendicular to the pushbroom direction, and the angle of the target's major axis; calculating the target scaling ratio using a formula based on the model and imaging geometry parameters, and using this as the spatial resampling frequency to resample the target image data, thus completing deformation correction and data reconstruction. This method fully utilizes the known target size, without relying on external motion parameters, achieving rapid correction of pushbroom imaging deformation and effectively improving the accuracy of quantitative applications of hyperspectral data.

Description

Technical Field

[0001] This invention relates to the field of remote sensing image processing technology, and in particular to a method and apparatus for deformation correction of pushbroom imaging of aerial targets of known size. Background Technology

[0002] Satellite infrared hyperspectral imaging technology has advantages such as all-weather operation, wide coverage, and rich spectral information, and has been widely used in Earth observation and target reconnaissance. For cooperative or known targets such as specific types of aircraft, their geometric dimensions (such as length and wingspan) are known prior information.

[0003] When a satellite hyperspectral payload performs pushbroom imaging on such targets, the target will undergo stretching or compression deformation in the pushbroom direction due to a mismatch between the payload's imaging parameters (such as imaging period and instantaneous field of view) and the target's relative motion parameters (especially the relative velocity along the pushbroom direction). This deformation will directly cause the target's radiation characteristics (such as radiation area and intensity) extracted from the image to deviate from the true values, and the greater the deformation, the greater the deviation.

[0004] Currently, although the geometric dimensions of the target are known, there is no publicly available, mature method for quickly and automatically correcting imaging deformation caused by relative motion by fully utilizing this information. Existing techniques typically use uncorrected images directly for analysis or rely on complex motion parameter measurement equipment, which suffers from insufficient accuracy, high cost, and low efficiency. Therefore, there is an urgent need for a simple and efficient method that can directly perform deformation correction using known geometric dimensions. Summary of the Invention

[0005] The purpose of this invention is to provide a method and apparatus for correcting the deformation of airborne targets in pushbroom imaging based on known size. It constructs a pushbroom imaging deformation parameter model of airborne targets in satellite pushbroom imaging mode, and solves the problem of target deformation caused by the mismatch between the satellite hyperspectral payload imaging parameters and the relative motion state parameters of the airborne target under the premise that the target geometry is known.

[0006] To achieve the above objectives, in a first aspect, the present invention provides a method for deformation correction of pushbroom imaging of airborne targets with known dimensions, comprising the following steps: S1. Establish an aerial target pushbroom imaging deformation parameter model, the model including the target pushbroom imaging scaling ratio, used to describe the degree of target spatial deformation caused by pushbroom imaging; S2. Given that the actual geometric dimensions of the aerial target are known, process its hyperspectral pushbroom imaging data and extract the target's imaging geometric parameters; S3. Based on the deformation parameter model and the imaging geometric parameters, determine the target push-broom imaging scaling ratio, and use it as the spatial resampling frequency along the push-broom direction to resample the image data of the target area, thereby completing deformation correction and data reconstruction.

[0007] Optionally, in step S1, the target pushbroom imaging scaling ratio Defined as: in, The field-of-view spatial resolution is defined in the vertical push-broom direction; The equivalent spatial resolution of the target along the push-broom direction.

[0008] Optionally, the spatial resolution of the field of view in the vertical push-broom direction Equivalent spatial resolution of the target along the push-broom direction It can be obtained through the following formula: in, The relative velocity between the satellite payload scanning imaging platform and the target along the push-broom direction. For the payload imaging period, The height difference between the imaging platform and the target. The instantaneous field of view of the imaging payload.

[0009] Optionally, in step S2, the extraction process of the imaging geometric parameters includes: Image segmentation is performed on hyperspectral imaging data to generate a target mask; Analyze the connected regions of the target mask to generate the target bounding rectangle; Extract the pixel size of the circumscribed rectangle along the push-broom direction. and pixel size in the vertical push-broom direction .

[0010] Optionally, the image segmentation method may employ Otsu's method or the Canny edge segmentation method.

[0011] Optionally, in step S2, the angle between the major axis of the target and the horizontal direction is also extracted. .

[0012] Optionally, in step S3, based on the actual length of the target Actual width Pixel size along the push-broom direction Pixel size in the vertical sweep direction and the angle between the target's major axis and the horizontal direction. The target pushbroom imaging scaling ratio is calculated using the following formula. : Optionally, in step S3, resampling is implemented using an interpolation algorithm, which is either nearest neighbor interpolation or linear interpolation.

[0013] Secondly, the present invention also provides a pushbroom imaging deformation correction device based on an aerial target of known size, comprising: The model building module is used to build and store an aerial target pushbroom imaging deformation parameter model, which includes the target pushbroom imaging scaling ratio; The parameter extraction module is used to obtain the actual geometric dimensions of the aerial target and process the hyperspectral pushbroom imaging data to extract the target's imaging geometric parameters; The correction execution module is used to calculate the target pushbroom imaging scaling ratio based on the actual geometric dimensions and imaging geometric parameters, and use this as the spatial resampling frequency along the pushbroom direction to resample and correct the target image data.

[0014] Optionally, in the model building module, the target pushbroom imaging scaling ratio Defined as: in, , , The relative velocity between the satellite payload scanning imaging platform and the target along the push-broom direction. For the payload imaging period, The height difference between the imaging platform and the target. The instantaneous field of view of the imaging payload.

[0015] Optionally, the parameter extraction module is configured as follows: A target mask is generated by segmenting the imaging data, and the mask is analyzed to extract the pixel size of the target's circumscribed rectangle along the push-broom direction. and pixel size in the vertical push-broom direction ; In addition, extract the angle between the major axis of the target and the horizontal direction. .

[0016] The above-described technical solution of the present invention has the following advantages: The present invention provides a deformation correction method for pushbroom imaging of aerial targets with known dimensions. This method transforms the complex motion deformation problem into a model parameter solving problem based on the target's own dimensions and single-frame image features. It eliminates the need for external motion parameters that are difficult to obtain in real time. By combining the aforementioned model with the extracted image features, the specific target pushbroom imaging scaling ratio can be calculated. Using this ratio as a key control parameter, the image data of the target area is resampled along the pushbroom direction, thereby restoring the distorted target shape to its true proportional relationship, completing deformation correction and data reconstruction.

[0017] The present invention provides a pushbroom imaging deformation correction device for airborne targets with known dimensions, comprising a model building module, a parameter extraction module, and a correction execution module. Through the coordinated operation of these three modules, a complete and easy-to-operate system is formed, realizing the aforementioned pushbroom imaging deformation correction method for airborne targets with known dimensions. This significantly lowers the barrier to entry for this method, facilitating its integration into satellite ground processing systems or dedicated analysis software, and promoting the industrial application of the technology. Attached Figure Description

[0018] The accompanying drawings are provided for illustrative purposes only, and the proportions and quantities of the components in the drawings may not be consistent with the actual product.

[0019] Figure 1 This is a schematic diagram of the push-broom imaging deformation effect and target geometric parameters under different relative velocities in an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Figure 1 This invention relates to push-broom imaging deformation effects and target geometric parameters (circumscribed rectangle, angle in the horizontal direction of the image) under different relative velocities in embodiments of the invention. (Illustrative diagram). The present invention provides a method for deformation correction of airborne target pushbroom imaging based on known dimensions. This method first establishes a mathematical model that describes the degree of deformation. The core of this model is the target pushbroom imaging scaling ratio. This parameter acts like a scale, measuring the proportion by which the target is stretched or compressed in the image due to the pushbroom motion. This modeling step fundamentally transforms the blurred visual perception of deformation into a clear, calculable mathematical parameter, providing a quantitative benchmark for the entire correction process.

[0022] Next, the data preparation and feature extraction stage begins. In this stage, the target's geometric dimensions (such as length and wingspan) are utilized, along with hyperspectral pushbroom imaging data containing the target. Advanced image processing algorithms automatically locate and extract the target from the complex scene, and measure its key geometric features in the image, such as contour, orientation, and pixel size in the pushbroom direction and its perpendicular direction. This step links prior world knowledge (physical dimensions) with posterior image observations (pixel size), laying the data foundation for subsequent scale-based correction calculations.

[0023] Then, deformation correction and data reconstruction are performed. By combining the aforementioned model with the extracted image features, the specific target pushbroom imaging scaling ratio can be calculated. Using this ratio as a key control parameter, intelligent resampling of the image data of the target area along the pushbroom direction is performed, thereby restoring the distorted target shape to its true scale, completing deformation correction and data reconstruction.

[0024] In one example, the target pushbroom imaging scaling ratio Defined as the spatial resolution of the field of view in the vertical push-broom direction Equivalent spatial resolution of the target along the push-broom direction The ratio, that is: Field-of-view spatial resolution in the vertical push-broom direction Equivalent spatial resolution of the target along the push-broom direction It can be directly calculated theoretically from the imaging parameters of the satellite platform, specifically obtained through the following formula: In the formula: The relative velocity between the satellite payload scanning imaging platform and the target along the push-broom direction; For the payload imaging period; The height difference between the imaging platform and the target can be obtained through means such as a spaceborne laser rangefinder; if it cannot be obtained, the satellite orbital altitude can be used. The instantaneous field of view of the imaging payload.

[0025] This model links abstract image deformation with specific, measurable imaging system parameters and motion states, providing a solid theoretical basis and quantitative foundation for correction.

[0026] To apply the above model, the geometric features of the target need to be extracted from the hyperspectral image. In one example, firstly, a robust image segmentation algorithm (such as OTSU or Canny edge detection) is used to analyze the data, automatically identifying and separating the target region to generate a target mask. This step effectively eliminates interference from complex backgrounds, ensuring that subsequent parameter measurements are performed on a clean target region, thus improving the signal-to-noise ratio of the data. Next, connected component analysis is performed on the obtained target mask to find the minimum bounding rectangle that completely encloses the target, see [link to relevant documentation]. Figure 1 Record the length of this rectangle in pixels along the sweep direction. Width pixels in the vertical push-broom direction This operation transforms the irregular target shape into a regular, easily measurable geometric representation, directly obtaining the scale information along both directions required for model calculation.

[0027] Furthermore, the target's attitude is crucial for deformation calculation. Therefore, the angle between the target's major axis (e.g., the line connecting the nose and tail of an aircraft) and the horizontal direction of the image is further extracted. See Figure 1 Introducing an angle parameter allows the model to adapt to the general situation of arbitrary target orientation, greatly enhancing the applicability and robustness of the method and avoiding correction failures caused by changes in target attitude.

[0028] Because the relative velocity between the satellite payload scanning imaging platform and the target along the pushbroom direction is directly obtained. and This is usually quite difficult and not accurate enough. Therefore, in one example, it is based on the actual length of the target. Actual width Pixel size along the push-broom direction Pixel size in the vertical sweep direction and included angle The target pushbroom imaging scaling ratio is calculated using the following formula. : In this example, the deformation scaling ratio It can be done without any external motion parameters, solely based on the known dimensions of the target (the actual length of the target). Actual width ) and parameters extracted from single-shot imaging data (pixel size along the pushbroom direction) Pixel size in the vertical sweep direction and included angle The result can be directly calculated. This method enables rapid correction of target hyperspectral imaging deformation using only prior target knowledge and single-broom imaging information, making it highly valuable and efficient in engineering applications.

[0029] Calculate the target pushbroom imaging scaling ratio Then, using these parameters as control parameters, standard algorithms such as nearest neighbor interpolation or linear interpolation are applied to resample the target image region along the push-broom direction. This resampling operation directly and efficiently reverses the geometric deformation during the imaging process, and can recover the true geometric shape and hyperspectral data of the target to a certain extent, providing reliable data support for subsequent target recognition and feature inversion.

[0030] This embodiment also provides a correction device for implementing the above-mentioned pushbroom imaging deformation correction method based on airborne targets of known size. The device comprises three core modules: Model building module: Constructs deformation parameter models either built-in or at runtime, defining the scaling ratio. Its relationship with physical parameters provides a theoretical framework for calculations.

[0031] The parameter extraction module is used to obtain the actual geometric dimensions of the aerial target and process the hyperspectral pushbroom imaging data to extract the target's imaging geometric parameters.

[0032] Calibration Execution Module: This module receives data from the parameter extraction module and calculates the target pushbroom imaging scaling ratio. It drives the resampler to correct the input hyperspectral image data and finally outputs the deformation-corrected result.

[0033] Through the collaborative work of these three modules, a fully functional and easy-to-use system is formed, which greatly reduces the barrier to entry for this method and makes it easy to integrate into satellite ground processing systems or dedicated analysis software, thus promoting the industrial application of the technology.

[0034] Any aspects of this invention not described in detail are common knowledge or prior art in the field.

[0035] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that not every embodiment contains only one independent technical solution, and in the absence of conflict between solutions, the various technical features mentioned in each embodiment can be combined in any way to form other implementation methods that can be understood by those skilled in the art.

[0036] Furthermore, without departing from the scope of the present invention, modifications to the technical solutions described in the foregoing embodiments, or equivalent substitutions of some of the technical features, shall not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for deformation correction in pushbroom imaging of aerial targets with known dimensions, characterized in that, Includes the following steps: S1. Establish an aerial target pushbroom imaging deformation parameter model, the model including the target pushbroom imaging scaling ratio, used to describe the degree of target spatial deformation caused by pushbroom imaging; S2. Given that the actual geometric dimensions of the aerial target are known, process its hyperspectral pushbroom imaging data and extract the target's imaging geometric parameters; S3. Based on the deformation parameter model and the imaging geometric parameters, determine the target push-broom imaging scaling ratio, and use it as the spatial resampling frequency along the push-broom direction to resample the image data of the target area, thereby completing deformation correction and data reconstruction. The target pushbroom imaging scaling ratio Defined as: Field-of-view spatial resolution in the vertical push-broom direction Equivalent spatial resolution of the target along the push-broom direction It can be obtained through the following formula: in, The field-of-view spatial resolution is defined in the vertical push-broom direction; The equivalent spatial resolution of the target along the push-broom direction; The relative velocity between the satellite payload scanning imaging platform and the target along the push-broom direction. For the payload imaging period, The height difference between the imaging platform and the target. The instantaneous field of view of the imaging payload; The extraction process of the imaging geometric parameters includes: Image segmentation is performed on hyperspectral imaging data to generate a target mask; Analyze the connected regions of the target mask to generate the target bounding rectangle; Extract the pixel size of the circumscribed rectangle along the push-broom direction. and pixel size in the vertical push-broom direction ; Extract the angle between the major axis of the target and the horizontal direction. ; Based on the actual length of the target Actual width Pixel size along the push-broom direction Pixel size in the vertical sweep direction and the angle between the target's major axis and the horizontal direction. The target pushbroom imaging scaling ratio is calculated using the following formula. : Resampling is implemented using an interpolation algorithm, which can be either nearest neighbor interpolation or linear interpolation.

2. The method according to claim 1, characterized in that, The image segmentation method described uses either the Otsu method or the Canny edge segmentation method.

3. A device for correcting the deformation of pushbroom imaging of an airborne target with known size, used to implement the airborne target pushbroom imaging deformation correction method as described in claim 1, characterized in that, include: The model building module is used to build and store an aerial target pushbroom imaging deformation parameter model, which includes the target pushbroom imaging scaling ratio; The parameter extraction module is used to obtain the actual geometric dimensions of the aerial target and process the hyperspectral pushbroom imaging data to extract the target's imaging geometric parameters; The correction execution module is used to calculate the target pushbroom imaging scaling ratio based on the actual geometric dimensions and imaging geometric parameters, and use this as the spatial resampling frequency along the pushbroom direction to resample and correct the target image data.

4. The apparatus according to claim 3, characterized in that, The parameter extraction module is configured as follows: A target mask is generated by segmenting the imaging data, and the mask is analyzed to extract the pixel size of the target's circumscribed rectangle along the push-broom direction. and pixel size in the vertical push-broom direction ; In addition, extract the angle between the major axis of the target and the horizontal direction. .

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