Astronomical telescope under-sampling image processing method, device and equipment and medium

Abstract

The application discloses an undersampling image processing method, device and equipment of an astronomical telescope and a medium, relates to the technical field of optical testing, and comprises the following steps: collecting undersampling images by using the micro-displacement mode and the collection quantity determined based on the target pixel size and the initial pixel size of the undersampling images; determining the size search interval, the search step and the current virtual allocation unit size based on the target pixel size, combining the images by using the Drizzle algorithm and the current virtual allocation unit size to obtain a current reconstructed image; transforming the current reconstructed image to calculate a high-frequency noise power function term and a power spectrum entropy function term and obtain a current function value; if the current virtual allocation unit size is located in the search interval, the current virtual allocation unit size is updated, the step of determining the current reconstructed image is jumped to, and the process is repeated until the current virtual allocation unit size is not located in the search interval; and the reconstructed image with the minimum function value is selected as a target image. In this way, the efficiency of processing images can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of optical testing, in particular to an undersampling image processing method, device and equipment of an astronomical telescope and a medium. BACKGROUND

[0002] At present, a point spread function (PSF) is a core element for evaluating the imaging quality of an astronomical telescope and is also a core basis for modern astrophysics research. The PSF measurement accuracy can not only directly affect the quality of the on-orbit evaluation, on-orbit active optical adjustment and on-orbit assembly of the imaging quality of the astronomical telescope, but also indirectly affect the scientific output of the frontiers such as weak gravitational lensing cosmology and direct imaging of exoplanets. However, the mismatch between the diffraction limit of the optical system and the pixel size of the detector leads to the PSF undersampling problem, resulting in the loss of high-frequency information in the core area of the PSF, spectral aliasing, and further causing the distortion of the PSF shape distribution, the decrease of the full width at half maximum and the measurement accuracy of the ellipticity, and other consequences. With the continuous increase of the aperture of the astronomical telescope and the serious limitation of the manufacturing process of the semiconductor detector, the problem is increasingly serious.

[0003] The existing processing methods for the PSF undersampling problem of the astronomical telescope mainly include the following:

[0004] Linear interpolation algorithm, which is based on a specific mathematical interpolation model and uses the gray scale information of the surrounding integer pixel positions to interpolate and calculate the gray scale information of the sub-pixel positions, wherein the mathematical interpolation model includes a bicubic interpolation model and a spline interpolation model.

[0005] Multi-star point image registration method, which reconstructs a high-resolution star point image by using multiple undersampling star point images with sub-pixel level micro-displacement. The main steps are as follows: first, the telescope captures multiple undersampling star point images, and maintains a sub-pixel level micro-displacement between each image; second, an undersampling image coordinate system is constructed, and the coordinates of the centroids of all undersampling star point images in the undersampling image coordinate system are calculated; third, a high-resolution image coordinate system is constructed, the center position coordinates of the high-resolution image are taken as the registration points of the centroids of all undersampling star point images, and the coordinate conversion relationship between all undersampling images and the high-resolution image is calculated; fourth, the undersampling image pixels are taken as the distribution units in the registration process, and the range of the high-resolution image pixels covered by each undersampling image pixel is calculated; and finally, the gray scale information of each undersampling image pixel is uniformly or according to a specific weight coefficient distributed to the high-resolution image pixels covered thereby, to obtain a reconstructed high-resolution star point image.

[0006] The traditional Drizzle algorithm is a method for reconstructing a high-resolution star point image from multiple undersampled star point images with sub-pixel level micro-displacement, and the main difference between the multi-star point image registration method is that the traditional Drizzle algorithm does not take the undersampled image pixels as the distribution unit of the registration process, but a smaller virtual distribution unit is created to increase the preservation of high-frequency information in the reconstruction process. The size of the virtual distribution unit is set by experience and is usually 0.5 to 0.8 times the size of the undersampled image pixels. The main steps of the traditional Drizzle algorithm are as follows: first, multiple undersampled star point images are taken by a telescope, and each image maintains a sub-pixel level micro-displacement; second, an undersampled image coordinate system is constructed, and the coordinates of the centroids of all undersampled star point images in the undersampled image coordinate system are calculated; third, a high-resolution image coordinate system is constructed, and the high-resolution image center position coordinates are taken as the registration points of the centroids of all undersampled star point images, and the coordinate conversion relationship between all undersampled images and the high-resolution image is calculated; fourth, a virtual distribution unit is constructed, and the range of the high-resolution image pixels covered by each undersampled image pixel is calculated according to the size of the virtual distribution unit; and finally, the gray information of each undersampled image pixel is distributed to the high-resolution image pixels it covers according to a specific weight coefficient, and a reconstructed high-resolution star point image is obtained.

[0007] As can be seen from the above, the existing processing methods for the PSF undersampling problem of astronomical telescopes have the following limitations: linear interpolation algorithm: the essence of this algorithm is mathematical interpolation rather than physical information reconstruction, and it cannot restore the real diffraction limit high-frequency information. Multi-star point image registration method: this method takes the undersampled image pixels as the distribution unit of the registration process, and the distribution unit in the frequency domain is equivalent to a low-pass filter, which actively suppresses the real signal in the higher frequency band during the reconstruction process; the size of the distribution unit of the multi-star point image registration method is equal to the size of the undersampled image pixel, so this method suppresses the real signal higher than the frequency corresponding to the size of the undersampled image pixel, so this method cannot effectively supplement the lost high-frequency information in the undersampled image, and can only improve the measurement accuracy of the low-frequency features of the PSF. Traditional Drizzle algorithm: this method is an improvement of the multi-star point image registration method, and since a virtual distribution unit is used, the size of the virtual distribution unit can be set relatively flexibly, so in theory this method can better supplement the lost high-frequency information in the undersampled image. In theory, the smaller the size of the virtual distribution unit, the better it is for the supplement of high-frequency information; however, high-frequency information preservation and high-frequency aliasing suppression are usually contradictory, and how to find the best balance between the two is the core concern of all reconstruction algorithms. The size of the virtual distribution unit of the traditional Drizzle algorithm is set by experience and is usually 0.5 to 0.8 times the size of the undersampled image pixels, and this assignment method lacks theoretical basis and cannot find the best balance point between high-frequency information preservation and high-frequency aliasing suppression.

[0008] From the above, how to improve the efficiency of image processing in the undersampling image processing process of the astronomical telescope is a problem to be solved at present. SUMMARY

[0009] Therefore, the purpose of the present application is to provide an undersampling image processing method, device and equipment of an astronomical telescope and a medium, which can improve the efficiency of image processing in the undersampling image processing process of the astronomical telescope. The specific scheme is as follows:

[0010] In a first aspect, the present application provides an undersampling image processing method of an astronomical telescope, comprising:

[0011] determining a target pixel size based on a preset requirement, and determining a to-be-collected number and a micro-displacement mode of undersampling images based on the target pixel size and an initial pixel size corresponding to the undersampling images, and then collecting the undersampling images output by the astronomical telescope based on the to-be-collected number and the micro-displacement mode; the target pixel size is smaller than the initial pixel size;

[0012] determining a size search interval, a search step and a current virtual allocation unit size based on the target pixel size, so as to perform splicing on each undersampling image in the size search interval according to the search step and using a Drizzle algorithm based on the current virtual allocation unit size, to obtain a current reconstructed image;

[0013] determining a Fourier transform result corresponding to the current reconstructed image based on the current virtual allocation unit size, so as to determine a high-frequency noise power function term and a power spectrum entropy function term based on the Fourier transform result, and determine a current function value based on the high-frequency noise power function term and the power spectrum entropy function term;

[0014] determining whether the current virtual allocation unit size is located in the size search interval, if yes, updating the current virtual allocation unit size to obtain a new current virtual allocation unit size, and re-jumping to the step of performing splicing on each undersampling image in the size search interval according to the search step and using the Drizzle algorithm based on the current virtual allocation unit size, to obtain a current reconstructed image, until the current virtual allocation unit size is not located in the size search interval, and then setting the current reconstructed image corresponding to the function value with the smallest function value among the current function values as a target image.

[0015] Optionally,

[0016] The target pixel size is determined based on the preset requirement, and the number of to-be-acquired images and the micro-displacement mode of the undersampling images are determined based on the target pixel size and the initial pixel size corresponding to the undersampling images, and then the undersampling images output by the astronomical telescope are acquired based on the number of to-be-acquired images and the micro-displacement mode, comprising:

[0017] A to-be-processed image corresponding to the astronomical telescope is determined, and it is judged whether the image resolution corresponding to the to-be-processed image satisfies a preset image resolution condition, if the image resolution corresponding to the to-be-processed image does not satisfy the preset image resolution condition, the to-be-processed image is set as an undersampling image;

[0018] The target pixel size is determined based on the preset requirement, and the initial pixel size corresponding to the undersampling images is determined, so as to determine the size ratio based on the target pixel size and the initial pixel size, and then the number of to-be-acquired images corresponding to the undersampling images and the micro-displacement mode are determined based on the size ratio;

[0019] A plurality of frames of undersampling images with sub-pixel displacement output by the astronomical telescope are acquired based on the preset dithering mode, the number of to-be-acquired images and the micro-displacement mode.

[0020] Optionally, the size search interval, the search step and the current virtual allocation unit size are determined based on the target pixel size, so as to obtain a current reconstructed image by splicing each undersampling image in the size search interval according to the search step and using the Drizzle algorithm based on the current virtual allocation unit size, comprising:

[0021] The preset lower limit coefficient and the preset upper limit coefficient are determined based on the preset requirement, the size search interval lower limit value is determined based on the target pixel size corresponding to the undersampling images and the preset lower limit coefficient, and the size search interval upper limit value is determined based on the target pixel size corresponding to the undersampling images and the preset upper limit coefficient;

[0022] The size search interval of the resampling grid is determined based on the size search interval lower limit value and the size search interval upper limit value, and the search step and the current virtual allocation unit size corresponding to the resampling grid are determined based on the target pixel size;

[0023] Each undersampling image is processed in sequence in the size search interval according to the search step based on the current virtual allocation unit size by using the Drizzle algorithm, to obtain a current reconstructed image, and the current reconstructed image is processed by using a preset Fourier transform algorithm to obtain a Fourier transform result.

[0024] Optionally, the determining the size search interval, the search step and the current virtual allocation unit size based on the target pixel size comprises:

[0025] determining an arithmetic mean of the size search interval lower limit value and the size search interval upper limit value, and determining the current virtual allocation unit size based on the arithmetic mean and the pixel size of the undersampled image, and then determining the search step based on a preset precision requirement and the initial pixel size corresponding to the undersampled image.

[0026] Optionally, the determining the Fourier transform result corresponding to the current reconstructed image based on the current virtual allocation unit size, to determine the high-frequency noise power function term and the power spectrum entropy function term based on the Fourier transform result, and determining the current function value based on the high-frequency noise power function term and the power spectrum entropy function term comprises:

[0027] performing two-dimensional Fourier transform on the current reconstructed image based on the current virtual allocation unit size to obtain a frequency domain response function corresponding to the current reconstructed image, and determining a power spectrum entropy function and a high-frequency noise power function corresponding to the current reconstructed image based on the frequency domain response function, and then determining a resolvable frequency threshold based on the target pixel size and the initial pixel size;

[0028] determining the high-frequency noise power function term and the power spectrum entropy function term based on the resolvable frequency threshold and using the power spectrum entropy function and the high-frequency noise power function;

[0029] determining a first weight coefficient corresponding to the high-frequency noise power function term and a second weight coefficient corresponding to the power spectrum entropy function term based on a preset requirement, to determine the current function value based on the first weight coefficient, the second weight coefficient, the high-frequency noise power function term and the power spectrum entropy function term.

[0030] Optionally, the determining the current function value based on the high-frequency noise power function term and the power spectrum entropy function term comprises:

[0031] determining a definition improvement degree based on a first power spectrum entropy function term corresponding to the current reconstructed image and a second power spectrum entropy function term corresponding to the undersampled image, and determining a cleanliness improvement degree based on a first high-frequency noise power function term corresponding to the current reconstructed image and a second high-frequency noise power function term corresponding to the undersampled image;

[0032] determining a first weight coefficient corresponding to the sharpness improvement degree, and determining a second weight coefficient based on the cleanliness improvement degree, determining a sharpness score based on the sharpness improvement degree and the first weight coefficient, and determining a cleanliness score based on the cleanliness improvement degree and the second weight coefficient, and then determining a corresponding current function value based on each of the sharpness score and the cleanliness score.

[0033] Optionally, the step of determining whether the current virtual allocation unit size is located in the size search interval, if located, updating the current virtual allocation unit size to obtain a new current virtual allocation unit size, and rejumping to the step of performing the Drizzle algorithm based on the current virtual allocation unit size in the size search interval according to the search step and combining each of the undersampled images to obtain a current reconstructed image, until the current virtual allocation unit size is not located in the size search interval, comprises:

[0034] determining whether the current virtual allocation unit size is located in the interval length corresponding to the size search interval, if the current virtual allocation unit size is located in the interval length corresponding to the size search interval, performing a size increasing operation on the current virtual allocation unit size according to the search step to obtain a new current virtual allocation unit size, and rejumping to the step of performing the Drizzle algorithm based on the current virtual allocation unit size in the size search interval according to the search step and combining each of the undersampled images to obtain a current reconstructed image;

[0035] if the current virtual allocation unit size is not located in the interval length corresponding to the size search interval, jumping to the step of setting the current reconstructed image corresponding to the function value with the minimum value in each of the current function values as the target image.

[0036] In a second aspect, the present application provides an undersampled image processing device of an astronomical telescope, comprising:

[0037] an undersampled image determination module configured to determine a target pixel size based on a preset requirement, determine a to-be-collected number and a micro-displacement mode based on the target pixel size and an initial pixel size corresponding to an undersampled image, and collect the undersampled image output by the astronomical telescope based on the to-be-collected number and the micro-displacement mode; the target pixel size is smaller than the initial pixel size.

[0038] The reconstruction image determination module is configured to determine a size search interval, a search step and a current virtual allocation unit size based on the target pixel size, to stitch each of the undersampling images in the size search interval according to the search step and using a Drizzle algorithm based on the current virtual allocation unit size, and to obtain a current reconstruction image.

[0039] The function value determination module is configured to determine a Fourier transform result corresponding to the current reconstruction image based on the current virtual allocation unit size, to determine a high-frequency noise power function item and a power spectrum entropy function item based on the Fourier transform result, and to determine a current function value based on the high-frequency noise power function item and the power spectrum entropy function item.

[0040] The target image determination module is configured to determine whether the current virtual allocation unit size is located in the size search interval, to update the current virtual allocation unit size to obtain a new current virtual allocation unit size and re-jump to the step of stitching each of the undersampling images in the size search interval according to the search step and using the Drizzle algorithm based on the new current virtual allocation unit size, until the current virtual allocation unit size is not located in the size search interval, and to set a current reconstruction image corresponding to a function value with a minimum value among the current function values as a target image.

[0041] In a third aspect, the present application provides an electronic device, comprising:

[0042] A memory configured to save a computer program;

[0043] A processor configured to execute the computer program to implement the undersampling image processing method of the astronomical telescope.

[0044] In a fourth aspect, the present application provides a computer readable medium configured to save a computer program, wherein the computer program is executed by a processor to implement the undersampling image processing method of the astronomical telescope.

[0045] As can be seen from the above, before the undersampling image processing of the astronomical telescope is performed, the target pixel size needs to be determined based on preset requirements, and the to-be-acquired quantity and micro-displacement mode of the undersampling image are determined based on the target pixel size and the initial pixel size corresponding to the undersampling image, and then the undersampling image output by the astronomical telescope is acquired based on the to-be-acquired quantity and the micro-displacement mode; the target pixel size is smaller than the initial pixel size; the size search interval, the search step and the current virtual allocation unit size are determined based on the target pixel size, so as to perform splicing on each undersampling image in the size search interval according to the search step and by using the Drizzle algorithm based on the current virtual allocation unit size, and a current reconstructed image is obtained; the Fourier transform result corresponding to the current reconstructed image is determined based on the current virtual allocation unit size, so as to determine the high-frequency noise power function term and the power spectrum entropy function term based on the Fourier transform result, and determine the current function value based on the high-frequency noise power function term and the power spectrum entropy function term; it is judged whether the current virtual allocation unit size is located in the size search interval, if yes, the current virtual allocation unit size is updated to obtain a new current virtual allocation unit size, and the step of splicing each undersampling image in the size search interval according to the search step and by using the Drizzle algorithm based on the current virtual allocation unit size to obtain the current reconstructed image is re-jumped until the current virtual allocation unit size is not located in the size search interval, and then the current reconstructed image corresponding to the function value with the minimum function value in each current function value is set as the target image.

[0046] It can be seen that the present application first needs to determine the target pixel size based on the preset demand, and determine the to-be-acquired quantity and micro-displacement mode of the undersampling image based on the target pixel size and the initial pixel size corresponding to the undersampling image, and then acquire the undersampling image output by the astronomical telescope based on the to-be-acquired quantity and the micro-displacement mode; secondly, the size search interval, the search step and the current virtual allocation unit size are determined based on the target pixel size, so as to perform splicing on each undersampling image in the size search interval according to the search step and by using the Drizzle algorithm based on the current virtual allocation unit size, and obtain the current reconstructed image; then, the Fourier transform result corresponding to the current reconstructed image is determined based on the current virtual allocation unit size, so as to determine the high-frequency noise power function item and the power spectrum entropy function item based on the Fourier transform result, and determine the current function value based on the high-frequency noise power function item and the power spectrum entropy function item; finally, it is judged whether the current virtual allocation unit size is located in the size search interval, if yes, the current virtual allocation unit size is updated to obtain a new current virtual allocation unit size, and the step of splicing each undersampling image in the size search interval according to the search step and by using the Drizzle algorithm based on the current virtual allocation unit size is re-jumped to obtain the current reconstructed image, until the current virtual allocation unit size is not located in the size search interval, and then the current reconstructed image corresponding to the function value with the minimum function value in each current function value is set as the target image. In this way, the efficiency of processing the image with undersampling problem is improved in the process of undersampling image processing of the astronomical telescope, and the user experience is improved. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only constitute the embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor based on the provided drawings.

[0048] Figure 1 A flow chart of an undersampling image processing method of an astronomical telescope disclosed by the present application;

[0049] Figure 2 A structural schematic diagram of an undersampling image processing device of an astronomical telescope disclosed by the present application;

[0050] Figure 3 A structural diagram of an electronic device disclosed by the present application. DETAILED DESCRIPTION

[0051] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0052] Currently, a point spread function is a core element for evaluating imaging quality of an astronomical telescope and is also a core basis for modern astrophysics research. The PSF measurement accuracy can not only directly affect the quality of frontiers such as on-orbit evaluation of imaging quality of the astronomical telescope, on-orbit active optical adjustment and on-orbit assembly, but also indirectly affect scientific output in frontiers such as weak gravitational lensing cosmology and direct imaging of exoplanets. However, the mismatch between the diffraction limit of the optical system and the pixel size of the detector causes the PSF undersampling problem, resulting in loss of high-frequency information in the core area of the PSF, spectral aliasing, and further causing distortion of the PSF shape distribution, and decline of the measurement accuracy of the full width at half maximum and the ellipticity. With the continuous increase of the aperture of the astronomical telescope and the serious limitation of the manufacturing process of the semiconductor detector, the problem is increasingly serious. Therefore, the present application provides an undersampled image processing method of an astronomical telescope, which can improve the efficiency of image processing in the process of undersampled image processing of the astronomical telescope.

[0053] Referring to Figure 1 The undersampled image processing method of the astronomical telescope disclosed in the embodiments of the present application comprises the following steps:

[0054] In step S11, the target pixel size is determined based on a preset requirement, and the number of to-be-acquired undersampled images and a micro-displacement mode are determined based on the target pixel size and an initial pixel size corresponding to the undersampled images, and then the undersampled images output by the astronomical telescope are acquired based on the number of to-be-acquired and the micro-displacement mode. The target pixel size is smaller than the initial pixel size.

[0055] In the embodiments, the undersampled images output by the astronomical telescope are first determined by Dithering (i.e., dithering processing) and other methods, and then the pixel size of the reconstructed image is determined according to the application requirement , and the pixel size should be smaller than the pixel size corresponding to the undersampled images .

[0056] Specifically, the target pixel size is determined based on the preset requirement, the initial pixel size corresponding to the undersampling image is determined based on the target pixel size and the undersampling image, and then the undersampling image is collected based on the to-be-collected quantity and the micro-displacement mode. The undersampling image output by the astronomical telescope can include: determining a to-be-processed image corresponding to the astronomical telescope, and judging whether the image resolution corresponding to the to-be-processed image meets a preset image resolution condition. If the image resolution corresponding to the to-be-processed image does not meet the preset image resolution condition, the to-be-processed image is set as the undersampling image; the target pixel size is determined based on the preset requirement, and the initial pixel size corresponding to the undersampling image is determined. The size ratio is determined based on the target pixel size and the initial pixel size, and then the to-be-collected quantity and the micro-displacement mode corresponding to the undersampling image are determined based on the size ratio; and the undersampling image output by the astronomical telescope is collected based on the to-be-collected quantity and the micro-displacement mode by using a preset dithering mode.

[0057] In step S12, the size search interval, the search step, and the current virtual allocation unit size are determined based on the target pixel size, and each undersampling image is spliced by using the Drizzle algorithm in the size search interval according to the search step based on the current virtual allocation unit size, to obtain a current reconstructed image.

[0058] In this embodiment, the size search interval corresponding to the virtual allocation unit size needs to be determined by the embodiment of the application, for example, and the search step of the virtual allocation unit size is set, for example, 0.1 Specifically, the size search interval, the search step, and the current virtual allocation unit size are determined based on the target pixel size, and each undersampling image is spliced by using the Drizzle algorithm in the size search interval according to the search step based on the current virtual allocation unit size, to obtain a current reconstructed image, including: determining a preset lower limit coefficient and a preset upper limit coefficient based on a preset requirement, and determining a size search interval lower limit value based on the target pixel size corresponding to the undersampling image and the preset lower limit coefficient, and then determining a size search interval upper limit value based on the target pixel size corresponding to the undersampling image and the preset upper limit coefficient; determining the size search interval of the resampling grid based on the size search interval lower limit value and the size search interval upper limit value, and determining the search step and the current virtual allocation unit size corresponding to the resampling grid based on the target pixel size; each undersampling image is processed in turn by using the Drizzle algorithm and based on the current virtual allocation unit size in the size search interval according to the search step, to obtain a current reconstructed image, and the current reconstructed image is processed by using a preset Fourier transform algorithm to obtain a Fourier transform result.

[0059] Further, the virtual allocation unit size needs to be initially assigned by the embodiment of the application, for example, , and then running a Drizzle algorithm to stitch the undersampled images to obtain the reconstructed image .

[0060] Specifically, determining the size search interval, the search step and the current virtual allocation unit size based on the target pixel size can include: determining the arithmetic mean of the lower limit value and the upper limit value of the size search interval, and determining the current virtual allocation unit size based on the arithmetic mean and the pixel size of the undersampled image, and then determining the search step based on the preset precision requirement and the initial pixel size corresponding to the undersampled image.

[0061] Step S13, determining the Fourier transform result corresponding to the current reconstructed image based on the current virtual allocation unit size, to determine the high-frequency noise power function term and the power spectrum entropy function term based on the Fourier transform result, and to determine the current function value based on the high-frequency noise power function term and the power spectrum entropy function term.

[0062] In this embodiment, the target function is calculated, the virtual allocation unit size assignment is updated, and the above process is repeated, and finally the optimal value of the virtual allocation unit size is output, that is, the value that makes the target function minimum. is the optimal value.

[0063] In addition, after obtaining the current reconstructed image, the Fourier transform result corresponding to the current reconstructed image is determined based on the current virtual allocation unit size, the high-frequency noise power function term and the power spectrum entropy function term are determined based on the Fourier transform result, and the current function value is determined based on the high-frequency noise power function term and the power spectrum entropy function term. Specifically, determining the Fourier transform result corresponding to the current reconstructed image based on the current virtual allocation unit size, determining the high-frequency noise power function term and the power spectrum entropy function term based on the Fourier transform result, and determining the current function value based on the high-frequency noise power function term and the power spectrum entropy function term can include: performing two-dimensional Fourier transform on the current reconstructed image based on the current virtual allocation unit size to obtain a frequency domain response function corresponding to the current reconstructed image, and determining a power spectrum entropy function and a high-frequency noise power function corresponding to the current reconstructed image based on the frequency domain response function, and then determining a resolvable frequency threshold based on the target pixel size and the initial pixel size; determining the high-frequency noise power function term and the power spectrum entropy function term using the power spectrum entropy function and the high-frequency noise power function based on the resolvable frequency threshold; determining a first weight coefficient corresponding to the high-frequency noise power function term and a second weight coefficient corresponding to the power spectrum entropy function term based on the preset requirement, to determine the current function value based on the first weight coefficient, the second weight coefficient, the high-frequency noise power function term and the power spectrum entropy function term.

[0064] Further, the current function value can be determined based on the high-frequency noise power function term and the power spectrum entropy function term, which can include: determining a definition improvement degree based on a first power spectrum entropy function term corresponding to the current reconstructed image and a second power spectrum entropy function term corresponding to the undersampled image, and determining a cleanliness improvement degree based on a first high-frequency noise power function term corresponding to the current reconstructed image and a second high-frequency noise power function term corresponding to the undersampled image; determining a first weight coefficient corresponding to the definition improvement degree, and determining a second weight coefficient based on the cleanliness improvement degree, to determine a definition score based on the definition improvement degree and the first weight coefficient, and determine a cleanliness score based on the cleanliness improvement degree and the second weight coefficient, and then determine the corresponding current function value based on each definition score and each cleanliness score.

[0065] In step S14, it is determined whether the current virtual allocation unit size is located in the size search interval. If it is located, the current virtual allocation unit size is updated to obtain a new current virtual allocation unit size, and the step of performing the splicing on each undersampled image based on the current virtual allocation unit size in the size search interval according to the search step and using the Drizzle algorithm to obtain a current reconstructed image is re-executed until the current virtual allocation unit size is not located in the size search interval. Then, the current reconstructed image corresponding to the function value with the minimum function value in each current function value is set as the target image.

[0066] In this embodiment, after obtaining the size search interval, the embodiment needs to determine whether the current virtual allocation unit size is located in the size search interval based on the size search interval, and perform corresponding operations based on the determination result.

[0067] It is worth mentioning that the core idea of the adaptive virtual allocation unit design is to establish a target function related to the virtual allocation unit size, so as to find the virtual allocation unit size corresponding to the minimum value of the target function through the adaptive optimization algorithm. In the process of designing the target function, the power spectrum entropy and the high-frequency noise power are used in the embodiment. In a specific implementation, the power spectrum entropy optimization term can promote the energy concentration of the signal frequency band, and the high-frequency noise power optimization term directly suppresses the noise signal exceeding the theoretical maximum resolution frequency of the algorithm. The normalized mathematical expression is as follows:

[0068] ;

[0069] ;

[0070] ;

[0071] wherein, is a comprehensive target function based on the power spectrum entropy and the high-frequency noise power, is a target function item corresponding to a power spectrum entropy, is a target function item corresponding to a high-frequency noise power, and is a weight coefficient, is a virtual allocation unit size to be optimized, is an initial assignment of the virtual allocation unit size, is a two-dimensional Fourier transform result corresponding to a reconstructed image when the virtual allocation unit size is is a power spectrum of the reconstructed image when the virtual allocation unit size is is a theoretical maximum resolvable frequency corresponding to the Drizzle algorithm, wherein the theoretical maximum resolvable frequency is determined by a reconstructed image pixel size and the virtual allocation unit size.

[0072] Specifically, the step of determining whether the current virtual allocation unit size is located in the size search interval, if located, updating the current virtual allocation unit size to obtain a new current virtual allocation unit size, and rejumping to the step of performing the splicing on each undersampling image according to the search step and using the Drizzle algorithm to obtain the current reconstructed image based on the current virtual allocation unit size in the size search interval, until the current virtual allocation unit size is not located in the size search interval, can include: determining whether the current virtual allocation unit size is located in an interval length corresponding to the size search interval, if the current virtual allocation unit size is located in the interval length corresponding to the size search interval, performing a size increasing operation on the current virtual allocation unit size according to the search step to obtain the new current virtual allocation unit size, and rejumping to the step of performing the splicing on each undersampling image according to the search step and using the Drizzle algorithm to obtain the current reconstructed image based on the current virtual allocation unit size in the size search interval; if the current virtual allocation unit size is not located in the interval length corresponding to the size search interval, jumping to the step of setting the current reconstructed image corresponding to the function value with the minimum function value in the current function value as the target image.

[0073] In a specific embodiment, the embodiments of the present application are verified through simulation experiments, and compared with the multi-star point registration method and the traditional Drizzle algorithm, the PSF reconstruction error of the embodiments of the present application is reduced by 27% and 12% respectively, thereby further meeting the accuracy requirement of PSF reconstruction in the current actual production process.

[0074] ​​It can be seen from the above that the application first needs to determine a target pixel size based on preset requirements, and determine a to-be-acquired quantity and a micro-displacement mode of the undersampled images based on the target pixel size and an initial pixel size corresponding to the undersampled images, and then acquire the undersampled images output by the astronomical telescope based on the to-be-acquired quantity and the micro-displacement mode; secondly, a size search interval, a search step and a current virtual allocation unit size are determined based on the target pixel size, so as to perform splicing on each undersampled image in the size search interval according to the search step and by using a Drizzle algorithm based on the current virtual allocation unit size, and obtain a current reconstructed image; then, a Fourier transform result corresponding to the current reconstructed image is determined based on the current virtual allocation unit size, so as to determine a high-frequency noise power function item and a power spectrum entropy function item based on the Fourier transform result, and determine a current function value based on the high-frequency noise power function item and the power spectrum entropy function item; finally, it is judged whether the current virtual allocation unit size is located in the size search interval, if yes, the current virtual allocation unit size is updated to obtain a new current virtual allocation unit size, and the step of performing splicing on each undersampled image in the size search interval according to the search step and by using the Drizzle algorithm based on the current virtual allocation unit size is re-jumped to obtain the current reconstructed image, until the current virtual allocation unit size is not located in the size search interval, and then the current reconstructed image corresponding to the function value with the minimum function value in each current function value is set as a target image. In this way, the efficiency of processing the images with undersampling problems is improved in the process of processing the undersampled images of the astronomical telescope, and the user experience is improved.

[0075] Correspondingly, referring to Figure 2 The undersampled image processing device is further provided by the application, and the undersampled image processing device comprises:

[0076] The undersampled image determination module 11 is configured to determine a target pixel size based on preset requirements, determine a to-be-acquired quantity and a micro-displacement mode of the undersampled images based on the target pixel size and an initial pixel size corresponding to the undersampled images, and acquire the undersampled images output by the astronomical telescope based on the to-be-acquired quantity and the micro-displacement mode; the target pixel size is smaller than the initial pixel size.

[0077] The reconstructed image determination module 12 is configured to determine a size search interval, a search step and a current virtual allocation unit size based on the target pixel size, perform splicing on each undersampled image in the size search interval according to the search step and by using a Drizzle algorithm based on the current virtual allocation unit size, and obtain a current reconstructed image.

[0078] The function value determination module 13 is configured to determine a Fourier transform result corresponding to the current reconstructed image based on the current virtual allocation unit size, determine a high-frequency noise power function term and a power spectrum entropy function term based on the Fourier transform result, and determine a current function value based on the high-frequency noise power function term and the power spectrum entropy function term.

[0079] The target image determination module 14 is configured to determine whether the current virtual allocation unit size is located in the size search interval, and if so, update the current virtual allocation unit size to obtain a new current virtual allocation unit size, and re-jump to the step of performing the splicing on each undersampled image in the size search interval based on the new current virtual allocation unit size and using the Drizzle algorithm to obtain a current reconstructed image, until the current virtual allocation unit size is not located in the size search interval, and then set the current reconstructed image corresponding to the function value with the minimum value among the current function values as the target image.

[0080] In some embodiments, the undersampled image determination module 11 can specifically include:

[0081] The image determination unit is configured to determine a to-be-processed image corresponding to the astronomical telescope, and determine whether an image resolution corresponding to the to-be-processed image satisfies a preset image resolution condition, and if the image resolution corresponding to the to-be-processed image does not satisfy the preset image resolution condition, set the to-be-processed image as an undersampled image.

[0082] The size ratio determination unit is configured to determine a target pixel size based on a preset requirement, determine an initial pixel size corresponding to the undersampled image, determine a size ratio based on the target pixel size and the initial pixel size, and then determine a to-be-acquired number and a micro-displacement mode corresponding to the undersampled image based on the size ratio.

[0083] The undersampled image acquisition unit is configured to acquire a plurality of frames of undersampled images with sub-pixel displacement output by the astronomical telescope based on the to-be-acquired number and the micro-displacement mode using a preset dithering mode.

[0084] In some embodiments, the reconstructed image determination module 12 can specifically include:

[0085] The coefficient determination unit is configured to determine a preset lower limit coefficient and a preset upper limit coefficient based on a preset requirement, determine a size search interval lower limit value based on the target pixel size corresponding to the undersampled image and the preset lower limit coefficient, and then determine a size search interval upper limit value based on the target pixel size corresponding to the undersampled image and the preset upper limit coefficient.

[0086] The size search interval determining unit is configured to determine a size search interval of a resampling grid based on the size search interval lower limit value and the size search interval upper limit value, and determine a search step corresponding to the resampling grid and a current virtual allocation unit size based on the target pixel size.

[0087] The Fourier transform result determining unit is configured to sequentially process each of the undersampling images in the size search interval according to the search step based on the current virtual allocation unit size by using the Drizzle algorithm, to obtain a current reconstructed image, and process the current reconstructed image by using a preset Fourier transform algorithm to obtain a Fourier transform result.

[0088] In some embodiments, the reconstructed image determining module 12 can specifically include:

[0089] The search step determining unit is configured to determine an arithmetic mean of the size search interval lower limit value and the size search interval upper limit value, and determine a current virtual allocation unit size based on the arithmetic mean and the pixel size of the undersampling image, and then determine a search step based on a preset precision requirement and an initial pixel size corresponding to the undersampling image.

[0090] In some embodiments, the function value determining module 13 can specifically include:

[0091] The frequency domain response function determining unit is configured to perform two-dimensional Fourier transform on the current reconstructed image based on the current virtual allocation unit size to obtain a frequency domain response function corresponding to the current reconstructed image, and determine a power spectrum entropy function and a high-frequency noise power function corresponding to the current reconstructed image based on the frequency domain response function, and then determine a resolvable frequency threshold based on the target pixel size and the initial pixel size.

[0092] The function item determining unit is configured to determine a high-frequency noise power function item and a power spectrum entropy function item based on the power spectrum entropy function and the high-frequency noise power function and based on the resolvable frequency threshold.

[0093] The first function value determining sub-unit is configured to determine a first weight coefficient corresponding to the high-frequency noise power function item and a second weight coefficient corresponding to the power spectrum entropy function item based on a preset requirement, and determine a current function value based on the first weight coefficient, the second weight coefficient, the high-frequency noise power function item and the power spectrum entropy function item.

[0094] In some embodiments, the function value determining module 13 can specifically include:

[0095] an improvement degree determination unit configured to determine a sharpness improvement degree based on a first power spectrum entropy function item corresponding to the current reconstructed image and a second power spectrum entropy function item corresponding to the undersampled image, and determine a cleanness improvement degree based on a first high frequency noise power function item corresponding to the current reconstructed image and a second high frequency noise power function item corresponding to the undersampled image;

[0096] a second function value determination subunit configured to determine a first weight coefficient corresponding to the sharpness improvement degree, and determine a second weight coefficient based on the cleanness improvement degree, to determine a sharpness score based on the sharpness improvement degree and the first weight coefficient, and determine a cleanness score based on the cleanness improvement degree and the second weight coefficient, and then determine a corresponding current function value based on each of the sharpness score and the cleanness score.

[0097] In some embodiments, the target image determination module 14 can specifically include:

[0098] a virtual allocation unit size judgment unit configured to judge whether the current virtual allocation unit size is located in the interval length corresponding to the size search interval, and if the current virtual allocation unit size is located in the interval length corresponding to the size search interval, perform a size increasing operation on the current virtual allocation unit size according to the search step to obtain a new current virtual allocation unit size, and re-jump to the step of splicing each undersampled image according to the search step and using the Drizzle algorithm based on the current virtual allocation unit size in the size search interval to obtain a current reconstructed image;

[0099] a step jumping unit configured to jump to the step of setting the current reconstructed image corresponding to the function value with the minimum function value among the current function values as the target image if the current virtual allocation unit size is not located in the interval length corresponding to the size search interval.

[0100] Further, the embodiment of the present application further discloses an electronic device, Figure 3 is a structural diagram of an electronic device 20 according to an exemplary embodiment, and the contents in the figure cannot be considered as any limitation on the use range of the present application. The electronic device 20 can specifically include at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25 and a communication bus 26. The memory 22 is used to store a computer program, the computer program is loaded and executed by the processor 21 to realize the related steps in the undersampled image processing method of the astronomical telescope disclosed in any of the preceding embodiments. In addition, the electronic device 20 in the embodiment can be an electronic computer.

[0101] In this embodiment, the power supply 23 is configured to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 is configured to create a data transmission channel between the electronic device 20 and external devices, and the communication protocol followed by the communication interface 24 can be any communication protocol applicable to the technical solution of the present application, which will not be specifically limited herein; the input and output interface 25 is configured to obtain external input data or output data to the outside, and the specific interface type can be selected according to the specific application needs, which will not be specifically limited herein.

[0102] In addition, the memory 22 as a carrier of resource storage can be a read-only memory, a random access memory, a magnetic disk or an optical disk, etc., and the resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage mode can be temporary storage or permanent storage.

[0103] The operating system 221 is configured to manage and control each hardware device on the electronic device 20 and the computer program 222, and can be Windows Server, Netware, Unix, Linux, etc. In addition to the computer program capable of completing the undersampling image processing method of the astronomical telescope executed by the electronic device 20 disclosed in any of the foregoing embodiments, the computer program 222 can further include a computer program capable of completing other specific work.

[0104] Further, the present application also discloses a computer readable medium for storing a computer program; wherein the computer program is executed by a processor to realize the undersampling image processing method of the astronomical telescope disclosed above. For the specific steps of the method, please refer to the corresponding content disclosed in the foregoing embodiments, which will not be described here.

[0105] In the specification, each embodiment is described in a progressive manner, and each embodiment focuses on the difference from other embodiments. For the same or similar parts between the embodiments, please refer to each other. For the device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and please refer to the method part for the relevant part.

[0106] The skilled person can further realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized by electronic hardware, computer software or a combination of both. In order to clearly show the interchangeability of hardware and software, the components and steps of each example have been described in the above description. Whether the functions are realized by hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0107] The steps of a method or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module can reside in RAM, flash memory, ROM, electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. The storage medium can be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the processor. The processor and the storage medium can reside in an ASIC.

[0108] Finally, it should be noted that the terms "first", "second", and the like, herein do not denote any order, quantity, combination, or importance, but rather are used to distinguish one element from another, and do not imply singular or plural. Moreover, the terms "include", "have", and the like, are intended to be inclusive, in that a process, method, article, or apparatus that includes a list of elements is not necessarily limited to those elements, but can include other elements not expressly listed, or even other elements that are inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a", "has... a", "includes... a", or "contains... a", does not, without more constraints, preclude the existence of additional identical elements in the process, method, article, or apparatus that comprises, has, includes, or contains the element. The terms "a" and "an" are defined as one or more unless explicitly indicated to the contrary or understood otherwise by context.

[0109] The above has introduced the technical solutions provided by the present application in detail, and the principles and implementation manners of the present application have been described by applying specific examples; the above example explanations are only for helping to understand the method of the present application and its core idea; meanwhile, for the ordinary skilled in the art, according to the idea of the present application, the specific implementation manners and application scopes will have changes; in conclusion, the content of the present description should not be understood as the limitation of the present application.

Claims

1. An undersampled image processing method for an astronomical telescope, characterized in that, The method comprises the steps of: determining a target pixel size based on preset requirements, determining a to-be-acquired quantity and a micro-displacement mode of the undersampled images based on the target pixel size and an initial pixel size corresponding to the undersampled images, and then acquiring the undersampled images output by the astronomical telescope based on the to-be-acquired quantity and the micro-displacement mode; the target pixel size is smaller than the initial pixel size; determining a size search interval, a search step and a current virtual allocation unit size based on the target pixel size, performing splicing on each undersampled image in the size search interval according to the search step and by using a Drizzle algorithm based on the current virtual allocation unit size, and obtaining a current reconstructed image; determining a Fourier transform result corresponding to the current reconstructed image based on the current virtual allocation unit size, determining a high-frequency noise power function item and a power spectrum entropy function item based on the Fourier transform result, and determining a current function value based on the high-frequency noise power function item and the power spectrum entropy function item; determining whether the current virtual allocation unit size is located in the size search interval, if yes, updating the current virtual allocation unit size to obtain a new current virtual allocation unit size, and re-jumping to the step of performing splicing on each undersampled image in the size search interval according to the search step and by using the Drizzle algorithm based on the current virtual allocation unit size, and obtaining a current reconstructed image, until the current virtual allocation unit size is not located in the size search interval, and then setting the current reconstructed image corresponding to the function value with the smallest function value among the current function values as a target image.

2. The method of processing undersampled images of an astronomical telescope according to claim 1, characterized in that, The method comprises the steps of: determining a target pixel size based on preset requirements, determining a to-be-acquired quantity and a micro-displacement mode of the undersampled images based on the target pixel size and an initial pixel size corresponding to the undersampled images, and then acquiring the undersampled images output by the astronomical telescope based on the to-be-acquired quantity and the micro-displacement mode; determining a to-be-processed image corresponding to the astronomical telescope, and determining whether an image resolution corresponding to the to-be-processed image satisfies a preset image resolution condition, if the image resolution corresponding to the to-be-processed image does not satisfy the preset image resolution condition, setting the to-be-processed image as an undersampled image; determining a target pixel size based on preset requirements, and determining an initial pixel size corresponding to the undersampled images, determining a size ratio based on the target pixel size and the initial pixel size, and then determining a to-be-acquired quantity and a micro-displacement mode corresponding to the undersampled images based on the size ratio; 3. The method of processing undersampled images of an astronomical telescope according to claim 1, characterized in that, acquiring a plurality of frames of undersampled images with sub-pixel displacement output by the astronomical telescope by using a preset dithering mode and based on the to-be-acquired quantity and the micro-displacement mode. The method comprises the steps of: determine a preset lower limit coefficient and a preset upper limit coefficient based on a preset requirement, determine a size search interval lower limit value based on the target pixel size corresponding to the undersampled image and the preset lower limit coefficient, and then determine a size search interval upper limit value based on the target pixel size corresponding to the undersampled image and the preset upper limit coefficient; determine a size search interval of a resampling grid based on the size search interval lower limit value and the size search interval upper limit value, and determine a search step and a current virtual allocation unit size corresponding to the resampling grid based on the target pixel size; perform processing on each of the undersampled images in the size search interval according to the search step based on the current virtual allocation unit size by using a Drizzle algorithm, to obtain a current reconstructed image, and perform processing on the current reconstructed image by using a preset Fourier transform algorithm, to obtain a Fourier transform result.

4. The method of processing undersampled images of an astronomical telescope according to claim 3, characterized in that, The determination of the size search interval, the search step, and the current virtual allocation unit size based on the target pixel size includes: determine an arithmetic mean of the size search interval lower limit value and the size search interval upper limit value, determine a current virtual allocation unit size based on the arithmetic mean and the pixel size of the undersampled image, and then determine a search step based on a preset precision requirement and an initial pixel size corresponding to the undersampled image.

5. The method of processing undersampled images of an astronomical telescope according to claim 1, characterized in that, The determination of the Fourier transform result corresponding to the current reconstructed image based on the current virtual allocation unit size, the determination of a high-frequency noise power function term and a power spectrum entropy function term based on the Fourier transform result, and the determination of a current function value based on the high-frequency noise power function term and the power spectrum entropy function term include: perform two-dimensional Fourier transform on the current reconstructed image based on the current virtual allocation unit size, to obtain a frequency domain response function corresponding to the current reconstructed image, and determine a power spectrum entropy function and a high-frequency noise power function corresponding to the current reconstructed image based on the frequency domain response function, and then determine a resolvable frequency threshold based on the target pixel size and the initial pixel size; determine a high-frequency noise power function term and a power spectrum entropy function term based on the power spectrum entropy function and the high-frequency noise power function and based on the resolvable frequency threshold; determine a first weight coefficient corresponding to the high-frequency noise power function term and a second weight coefficient corresponding to the power spectrum entropy function term based on a preset requirement, and determine a current function value based on the first weight coefficient, the second weight coefficient, the high-frequency noise power function term, and the power spectrum entropy function term.

6. The method of processing undersampled images of an astronomical telescope according to claim 5, characterized in that, The determination of the current function value based on the high-frequency noise power function term and the power spectrum entropy function term includes: determine a definition improvement degree based on a first power spectrum entropy function term corresponding to the current reconstructed image and a second power spectrum entropy function term corresponding to the undersampled image, and determine a cleanliness improvement degree based on a first high-frequency noise power function term corresponding to the current reconstructed image and a second high-frequency noise power function term corresponding to the undersampled image. determine a first weight coefficient corresponding to the sharpness improvement degree, and determine a second weight coefficient based on the cleanliness improvement degree, determine a sharpness score based on the sharpness improvement degree and the first weight coefficient, and determine a cleanliness score based on the cleanliness improvement degree and the second weight coefficient, and then determine a corresponding current function value based on each of the sharpness score and the cleanliness score.

7. The method of processing undersampled images of an astronomical telescope according to any one of claims 1 to 6, characterized in that, The judgment current virtual allocation unit size is located in the size search interval, if it is located, update the current virtual allocation unit size, get new current virtual allocation unit size, and jump to the step of based on the current virtual allocation unit size in the size search interval according to the search step and using Drizzle algorithm to splicing each undersampling image, get current reconstruction image, until the current virtual allocation unit size is not located in the size search interval, including: If the current virtual allocation unit size is located in the interval length corresponding to the size search interval, the size of the current virtual allocation unit size is increased according to the search step, a new current virtual allocation unit size is obtained, and the step of based on the current virtual allocation unit size in the size search interval according to the search step and using Drizzle algorithm to splicing each undersampling image, get current reconstruction image is jumped to again; If the current virtual allocation unit size is not located in the interval length corresponding to the size search interval, jump to the step of setting the current reconstruction image corresponding to the function value with the minimum function value in each current function value as the target image.

8. An undersampled image processing apparatus for an astronomical telescope, characterized in that, Including: The undersampling image determination module is used for determining a target pixel size based on a preset requirement, determining the number of undersampling images to be collected and the micro displacement mode based on the target pixel size and the initial pixel size corresponding to the undersampling image, and then collecting the undersampling image output by the astronomical telescope based on the number of undersampling images to be collected and the micro displacement mode; the target pixel size is smaller than the initial pixel size; The reconstruction image determination module is used for determining a size search interval, a search step and a current virtual allocation unit size based on the target pixel size, and splicing each undersampling image according to the search step and using Drizzle algorithm based on the current virtual allocation unit size in the size search interval, to obtain a current reconstruction image; The function value determination module is used for determining the Fourier transform result corresponding to the current reconstruction image based on the current virtual allocation unit size, determining the high-frequency noise power function term and the power spectrum entropy function term based on the Fourier transform result, and determining the current function value based on the high-frequency noise power function term and the power spectrum entropy function term. The target image determining module is configured to determine whether the current virtual allocation unit size is located in the size search interval, and if so, update the current virtual allocation unit size to obtain a new current virtual allocation unit size, and jump back to the step of performing the Drizzle algorithm on each undersampled image according to the search step and based on the new current virtual allocation unit size to obtain a current reconstructed image until the current virtual allocation unit size is not located in the size search interval, and then set the current reconstructed image corresponding to the function value with the minimum function value among the current function values as the target image.

9. An electronic device, comprising: The method comprises: a memory configured to store a computer program; a processor configured to execute the computer program to implement the undersampled image processing method of the astronomical telescope according to any one of claims 1 to 7.

10. A computer readable medium characterized by a memory configured to store a computer program, wherein the computer program is executed by a processor to implement the undersampled image processing method of the astronomical telescope according to any one of claims 1 to 7.

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