Astronomical image processing method, device, electronic device and computer readable medium

Abstract

The embodiments of the present application provide an astronomical image processing method, device, electronic device and computer-readable medium. The astronomical image processing method of the present application includes: acquiring astronomical acquisition data; for each astronomical observation image, based on the pixel values ​​of each pixel point of the astronomical observation image, determining the pixel median corresponding to the astronomical observation image, and based on the difference between the pixel value of each pixel point of the astronomical observation image and the pixel median corresponding to the astronomical observation image, determining the pixel difference corresponding to each pixel point of the astronomical observation image; based on the pixel difference corresponding to each pixel point of multiple astronomical observation images, generating a pixel data matrix corresponding to the astronomical acquisition data; based on multiple astronomical observation images and the pixel data matrix, generating interference fringe images corresponding to multiple astronomical observation images. The technical solution of the embodiments of the present application effectively improves the processing effect of removing interference fringe processing on astronomical observation images.

Description

Technical Field

[0001] The present application relates to the technical field of image data processing, and in particular to an astronomical image processing method, device, electronic device and computer-readable medium. Background Art

[0002] In the process of astronomical observation, large-aperture optical telescopes are mainly used to collect astronomical images for analyzing celestial bodies or galaxies. Since the infrared band with a wavelength exceeding 600-700nm can effectively penetrate thick dust clouds and provide a more favorable viewing angle, it is crucial for observing celestial bodies and celestial phenomena obscured by dust. The photon absorption rate of the CCD silicon chip of a large-aperture optical telescope decreases rapidly with the increase of wavelength. This will cause low-energy photons to be reflected multiple times on the CCD surface and cause mutual interference, which will cause interference fringes in the captured astronomical images, thereby affecting the observation and analysis of astronomy or galaxies.

[0003] In the prior art, the collected astronomical image sets are generally processed for fringe removal through empirical models or traditional image processing. However, when processing astronomical image sets with large background variations and high noise levels, the current method has a poor effect in removing interference fringes. Therefore, how to better remove interference fringes from astronomical images has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] The embodiments of the present application provide an astronomical image processing method, device, electronic device and computer-readable medium, which effectively improve the processing effect of removing interference fringes from astronomical observation images.

[0005] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0006] According to one aspect of an embodiment of the present application, there is provided an astronomical image processing method, comprising: acquiring astronomical acquisition data, the astronomical acquisition data comprising a plurality of astronomical observation images; for each of the astronomical observation images, determining a pixel median corresponding to the astronomical observation image based on a pixel value of each pixel point of the astronomical observation image, and determining a pixel difference corresponding to each pixel point of the astronomical observation image based on a difference between a pixel value of each pixel point of the astronomical observation image and a pixel median corresponding to the astronomical observation image; generating a pixel data matrix corresponding to the astronomical acquisition data based on the pixel difference corresponding to each pixel point of the plurality of astronomical observation images; generating a plurality of interference fringe images corresponding to the astronomical observation images based on the plurality of astronomical observation images and the pixel data matrix; for each of the astronomical observation images, performing interference fringe removal processing on the astronomical observation image based on the interference fringe image corresponding to the astronomical observation image to obtain a processed astronomical observation image.

[0007] According to one aspect of an embodiment of the present application, an astronomical image processing device is provided, comprising: an acquisition unit, configured to acquire astronomical acquisition data, wherein the astronomical acquisition data comprises a plurality of astronomical observation images; a calculation unit, configured to determine, for each of the astronomical observation images, a pixel median corresponding to the astronomical observation image based on the pixel values ​​of each pixel point of the astronomical observation image, and to determine, based on the difference between the pixel value of each pixel point of the astronomical observation image and the pixel median corresponding to the astronomical observation image, a pixel difference corresponding to each pixel point of the astronomical observation image; a first generation unit, configured to generate a pixel data matrix corresponding to the astronomical acquisition data based on the pixel difference corresponding to each pixel point of the plurality of astronomical observation images; a second generation unit, configured to generate a pixel data matrix corresponding to the astronomical acquisition data based on the pixel difference corresponding to each pixel point of the plurality of astronomical observation images; and an interference fringe processing unit, configured to perform interference fringe removal processing on the astronomical observation image based on the interference fringe image corresponding to the astronomical observation image for each of the astronomical observation images, to obtain a processed astronomical observation image.

[0008] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the astronomical image processing method as described in the above embodiments.

[0009] According to one aspect of an embodiment of the present application, a computer-readable medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the astronomical image processing method as described in the above embodiment is implemented.

[0010] In the technical solutions provided in some embodiments of the present application, a plurality of astronomical observation images are acquired; for each astronomical observation image, based on the pixel values ​​of each pixel point of the astronomical observation image, a pixel median corresponding to the astronomical observation image is determined, and based on the difference between the pixel values ​​of each pixel point of the astronomical observation image and the pixel median corresponding to the astronomical observation image, a pixel difference corresponding to each pixel point of the astronomical observation image is determined; and based on the pixel difference corresponding to each pixel point of the plurality of astronomical observation images, a pixel data matrix corresponding to the astronomical acquisition data is generated; based on the plurality of astronomical observation images and the pixel data matrix, interference fringe images corresponding to the plurality of astronomical observation images are generated; for the astronomical observation images, based on The astronomical observation image is processed by removing the interference fringe from the interference fringe image corresponding to the astronomical observation image to obtain the processed astronomical observation image. By determining the pixel difference corresponding to each pixel point of the astronomical observation image, the median value of the image itself is subtracted from each astronomical photograph, and the normalization processing of the image is completed. The influence of the differences in brightness information and background information between multiple astronomical observation images on the extraction of interference fringe is effectively reduced, thereby improving the accuracy of extracting interference fringe, and further improving the processing effect of removing the interference fringe from the astronomical observation image, so as to obtain the astronomical observation image with noise removed, the signal-to-noise ratio of the image is improved, and the validity of the astronomical observation data is enhanced.

[0011] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0013] Figure 1 A flow chart of an astronomical image processing method according to an embodiment of the present application is shown.

[0014] Figure 2 A specific flow chart of step S130 of the astronomical image processing method according to one embodiment of the present application is shown;

[0015] Figure 3 A block diagram of an astronomical image processing device according to an embodiment of the present application is shown.

[0016] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0017] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0018] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0019] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0020] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0021] refer to Figure 1 , Figure 1 A flow chart of an astronomical image processing method according to an embodiment of the present application is shown. The astronomical image processing method at least includes steps S110 to S150, which are described in detail as follows.

[0022] Step S110, acquiring astronomical acquisition data, where the astronomical acquisition data includes a plurality of astronomical observation images.

[0023] In one embodiment, the astronomical acquisition data is astronomical observation images acquired by a camera device used for astronomical observation. The camera device may be a device including a charge-coupled device (CCD) silicon chip. The multiple astronomical observation images are astronomical images acquired by the same camera device. They may also be acquired at different survey positions within a time period, or at different positions within different time periods. There is no limitation on this.

[0024] Step S120, for each astronomical observation image, based on the pixel values ​​of each pixel point of the astronomical observation image, determine the pixel median corresponding to the astronomical observation image, and based on the difference between the pixel value of each pixel point of the astronomical observation image and the pixel median corresponding to the astronomical observation image, determine the pixel difference corresponding to each pixel point of the astronomical observation image.

[0025] In order to improve the accuracy of extracting interference fringes, it is necessary to preprocess multiple astronomical observation images. Specifically, for each astronomical observation image, the pixel median corresponding to the astronomical observation image can be determined based on the pixel values ​​of each pixel point of the astronomical observation image. The pixel median corresponding to the astronomical observation image is the pixel value located in the middle position after arranging according to the size of the pixel value in the pixel value data of each pixel point of the astronomical observation image. After obtaining the pixel median corresponding to the astronomical observation image, the pixel difference corresponding to each pixel point of the astronomical observation image can be determined based on the difference between the pixel value of each pixel point of the astronomical observation image and the pixel median corresponding to the astronomical observation image.

[0026] By determining the pixel difference corresponding to each pixel point of the astronomical observation image, the median value of each astronomical image is subtracted from the image itself, completing the image normalization processing, effectively reducing the impact of differences in brightness information and background information between multiple astronomical observation images on interference fringe extraction, and improving the accuracy of interference fringe extraction.

[0027] In one embodiment, step S120 may specifically include: performing grayscale transformation on the pixel value of each pixel point of the astronomical observation image to obtain the grayscale value of each pixel point of the astronomical observation image; determining the pixel median corresponding to the astronomical observation image based on the grayscale value of each pixel point of the astronomical observation image; determining the pixel difference corresponding to each pixel point of the astronomical observation image based on the difference between the grayscale value of each pixel point of the astronomical observation image and the pixel median corresponding to the astronomical observation image.

[0028] In this embodiment, when determining the pixel difference corresponding to each pixel point of the astronomical observation image based on the pixel value of each pixel point of the astronomical observation image, the pixel value of each pixel point of the astronomical observation image can be firstly transformed into grayscale to obtain the grayscale value of each pixel point of the astronomical observation image. Specifically, the grayscale transformation is to obtain a grayscale value by graying the pixel values ​​of the pixel points of the astronomical observation image under the three color channels of RGB. Specifically, any one of the component method, maximum value method, average value method and weighted average method can be adopted, which is not limited here.

[0029] After obtaining the grayscale value of each pixel of the astronomical observation image, the pixel median corresponding to the astronomical observation image can be determined based on the grayscale value of each pixel of the astronomical observation image. The pixel median corresponding to the astronomical observation image is the grayscale value located in the middle position after arranging the grayscale value data of each pixel of the astronomical observation image according to the size of the grayscale value. Finally, based on the difference between the grayscale value of each pixel of the astronomical observation image and the pixel median corresponding to the astronomical observation image, the pixel difference corresponding to each pixel of the astronomical observation image can be determined.

[0030] In the scheme of this embodiment, the astronomical observation image is grayed out, and the pixel difference corresponding to each pixel of the astronomical observation image is determined based on the grayscale value of each pixel of the astronomical observation image. Compared with the method of directly calculating the pixel difference of the astronomical observation image based on the color image, less data needs to be processed, thereby effectively improving the efficiency of data processing.

[0031] Step S130, generating a pixel data matrix corresponding to the astronomical acquisition data based on the pixel difference corresponding to each pixel point of the plurality of astronomical observation images.

[0032] In one embodiment, after obtaining the pixel difference values ​​corresponding to each pixel point of the plurality of astronomical observation images, the pixel difference values ​​corresponding to each pixel point of the plurality of astronomical observation images may be combined to obtain a pixel data matrix corresponding to the astronomical acquisition data.

[0033] Reference Figure 2 In one embodiment, step S130 may specifically include steps S1310 to S1320, which are described in detail as follows.

[0034] Step S1310, generating pixel vectors corresponding to a plurality of astronomical observation images based on pixel differences corresponding to respective pixel points of a plurality of astronomical observation images.

[0035] Step S1320: combining pixel vectors corresponding to the plurality of astronomical observation images to generate a pixel data matrix corresponding to the astronomical acquisition data.

[0036] As described above, the pixel difference corresponding to each pixel point of each astronomical observation image can be used as an element in the pixel vector to obtain the pixel vector corresponding to the astronomical observation image. The order of the elements in the pixel vector can be arranged according to the position order of the pixel points in the astronomical observation image, or according to other predetermined orders, which are not limited here. It can be understood that the pixel vectors corresponding to multiple astronomical observation images are generated in the same way.

[0037] When combining pixel vectors corresponding to multiple astronomical observation images, the pixel vector corresponding to each astronomical observation image can be used as a column vector or a row vector, and then multiple column vectors or row vectors are combined to obtain a pixel data matrix corresponding to the astronomical acquisition data.

[0038] In one embodiment, step S1310 may specifically include: based on the pixel difference corresponding to each pixel point of the multiple astronomical observation images, respectively generating the first column vectors corresponding to the multiple astronomical observation images; based on the first column vectors corresponding to the multiple astronomical observation images, determining the median of the multiple first column vectors at each same element position, and generating the second column vector based on the median of the multiple first column vectors at each same element position; based on the difference between the first column vector corresponding to the multiple astronomical observation images and the second column vector at each same element position, respectively generating the pixel vectors corresponding to the multiple astronomical observation images.

[0039] As described above, when generating pixel vectors corresponding to multiple astronomical observation images, for each astronomical observation image, the first column vector corresponding to the astronomical observation image can be generated according to the pixel difference corresponding to each pixel point of the astronomical observation image. The order of elements in the first column vector can be arranged according to the position order of the pixel points in the astronomical observation image, or can be arranged according to other predetermined orders, which are not limited here. Secondly, according to the first column vectors corresponding to the multiple astronomical observation images, the median of the multiple first column vectors at the same element position is determined. The median is the value group of the multiple first column vectors in the same element, which is arranged according to the size of the value group and is located in the middle position, that is, the median of the pixel difference of the multiple astronomical observation images at the same pixel point is calculated. The median of the multiple first column vectors at the same element is used to generate the second column vector. It can be understood that the order of elements in the second column vector is the same as the order of elements in the first column vector. Finally, based on the difference between the first column vector and the second column vector corresponding to the multiple astronomical observation images at the same element position, the pixel vectors corresponding to the multiple astronomical observation images are generated respectively.

[0040] In the scheme of this embodiment, by determining the median of the pixel differences of multiple astronomical observation images at each pixel point, and then normalizing the pixel differences corresponding to each pixel point of the multiple astronomical observation images according to the median, the influence of the differences in brightness information and background information between the multiple astronomical observation images on the interference fringe extraction can be further reduced, thereby improving the accuracy of the interference fringe extraction.

[0041] Step S140, generating interference fringe images corresponding to the plurality of astronomical observation images based on the plurality of astronomical observation images and the pixel data matrix.

[0042] In this embodiment, the interference fringe images corresponding to the plurality of astronomical observation images can be calculated through the pixel data matrix corresponding to the astronomical observation images and the astronomical acquisition data.

[0043] In one embodiment, step S140 may specifically include:

[0044] Perform matrix decomposition processing on the pixel data matrix to obtain a matrix decomposition result, wherein the matrix decomposition result includes a low-rank matrix; perform linear regression calculation on a plurality of astronomical observation images and the low-rank matrix respectively to obtain a transformation scale between the plurality of astronomical observation images and the low-rank matrix; based on the transformation scale between the plurality of astronomical observation images and the low-rank matrix and the low-rank matrix, generate interference fringe images corresponding to the plurality of astronomical observation images respectively.

[0045] As mentioned above, since the components of the interference fringes of the astronomical observation image are distributed widely and smoothly, and the brightness changes in the image are basically small, in order to separate the final interference fringes, it can be represented as a low-rank matrix. However, the celestial body part in the astronomical observation image, such as the bright spot information caused by the celestial body signal and thermal noise information, is unevenly distributed in the CCD imaging of different shooting devices and the number is relatively small, so the celestial body part image of the astronomical observation image can be represented as a sparse matrix. Based on this method, in order to realize the extraction of the interference fringe image, the pixel data matrix corresponding to the astronomical observation image and the astronomical acquisition data can be analyzed according to the principal component pursuit (PCP) algorithm, and then the interference fringe images corresponding to multiple astronomical observation images can be obtained.

[0046] Specifically, the pixel data matrix can be first subjected to matrix decomposition processing to obtain a matrix decomposition result, which includes a low-rank matrix and a sparse matrix; then, linear regression calculations are performed on multiple astronomical observation images and the low-rank matrix respectively to obtain transformation scales between the multiple astronomical observation images and the low-rank matrix. For each astronomical observation image, the interference fringe image corresponding to the astronomical observation image can be obtained based on the product of the transformation scale between the astronomical observation image and the low-rank matrix and the low-rank matrix.

[0047] In one embodiment, the pixel data matrix is ​​subjected to matrix decomposition processing by the following formula to obtain a matrix decomposition result:

[0048] in, is the pixel data matrix, and the matrix decomposition results include the low-rank matrix and sparse matrices , Represents a low-rank matrix Find the nuclear norm, is a sparse matrix To implement sparsity constraints, Represents a low-rank matrix and sparse matrices The weight ratio between Indicated in When the loss function takes the minimum value, the low-rank matrix and sparse matrices The value of .

[0049] In the technical solution of this embodiment, the matrix decomposition process of the pixel data matrix is ​​completed by using the principal component tracking algorithm and numerical optimization technology. Can adjust low-rank matrices and sparse matrices The weighted proportional relationship between them is used to determine the accuracy of the decomposition of the interference fringe image corresponding to the low-rank matrix. The linear regression method is used to dynamically calculate the transformation scale between each astronomical observation image and the clear fringe image, so as to obtain the interference fringe image corresponding to the astronomical observation image, so as to realize the interference fringe removal of the astronomical observation image according to the difference between the astronomical observation image and the interference fringe image, so that the signal-to-noise ratio of the astronomical observation image is maintained at a high level.

[0050] In one embodiment, step S140 may specifically include: generating interference fringe images corresponding to the plurality of astronomical observation images respectively based on the plurality of astronomical observation images and the pixel data matrix by using the following formula: generating interference fringe images estimated by the plurality of astronomical observation images based on the plurality of astronomical observation images and the pixel data matrix by using the following formula:

[0051] ;

[0052] is the pixel data matrix, It is expressed as calculating the nuclear norm of the interference fringe estimate. Indicates the calculation of the mask for the star image in the astronomical observation image. For the matrix Compute the Frobenius norm, for and The weight between these two terms is is the left singular vector matrix, is the singular value matrix, is the right singular vector matrix, is the transpose of the right singular vector matrix, For the pixel data matrix After singular value decomposition, the singular value matrix is ​​soft-thresholded and then the three matrices are , as well as Reorganization Interference fringe image.

[0053] In the technical solution of this embodiment, since the interference fringes of multiple astronomical observation images can be represented by a linear combination of the same interference fringes, the pixel data matrix can be directly decomposed into singular values ​​according to the multiple astronomical observation images to directly obtain the interference fringe images of each astronomical observation image. Compared with the aforementioned embodiment, more complicated calculations are avoided and the extraction efficiency of the corresponding interference fringe images in the astronomical observation images is improved.

[0054] Step S150 , for each astronomical observation image, performing interference fringe removal processing on the astronomical observation image based on the interference fringe image corresponding to the astronomical observation image to obtain a processed astronomical observation image.

[0055] In one embodiment, for each astronomical observation image, the astronomical observation image is subjected to interference fringe removal processing based on the interference fringe image corresponding to the astronomical observation image, thereby obtaining an astronomical observation image with noise removed. Specifically, it is necessary to perform linear fitting on each astronomical observation image and its corresponding interference fringe image and calculate the regression coefficient, and calculate the product of the regression coefficient and the interference fringe image, and finally obtain the astronomical observation image with noise and interference fringe removed based on the difference between each astronomical observation image and the product. In the above manner, the signal-to-noise ratio of the image can be improved, thereby enhancing the validity of the astronomical observation data.

[0056] In this embodiment, a plurality of astronomical observation images are acquired; for each astronomical observation image, based on the pixel value of each pixel point of the astronomical observation image, a pixel median corresponding to the astronomical observation image is determined, and based on the difference between the pixel value of each pixel point of the astronomical observation image and the pixel median corresponding to the astronomical observation image, a pixel difference corresponding to each pixel point of the astronomical observation image is determined; and based on the pixel difference corresponding to each pixel point of the plurality of astronomical observation images, a pixel data matrix corresponding to the astronomical acquisition data is generated; based on the plurality of astronomical observation images and the pixel data matrix, interference fringe images corresponding to the plurality of astronomical observation images are generated; for the astronomical observation images, based on the astronomical observation images The corresponding interference fringe image is used to perform interference fringe removal processing on the astronomical observation image to obtain the processed astronomical observation image. By determining the pixel difference corresponding to each pixel point of the astronomical observation image, the median value of the image itself is subtracted from each astronomical image, and the image normalization processing is completed. The influence of the differences in brightness information and background information between multiple astronomical observation images on the extraction of interference fringe is effectively reduced, thereby improving the accuracy of interference fringe extraction, and further improving the processing effect of interference fringe removal processing on the astronomical observation image, so as to obtain the astronomical observation image with noise removed, the signal-to-noise ratio of the image is improved, and the validity of the astronomical observation data is enhanced.

[0057] The following describes an apparatus embodiment of the present application, which can be used to execute the astronomical image processing method in the above-mentioned embodiment of the present application. For details not disclosed in the apparatus embodiment of the present application, please refer to the above-mentioned embodiment of the astronomical image processing method of the present application.

[0058] Figure 3 A block diagram of an astronomical image processing device according to an embodiment of the present application is shown.

[0059] Reference Figure 3As shown, an astronomical image processing device 300 according to an embodiment of the present application includes: an acquisition unit 310 , a calculation unit 320 , a first generation unit 330 , a second generation unit 340 and an interference fringe processing unit 350 . The acquisition unit 310 is used to acquire astronomical acquisition data, wherein the astronomical acquisition data includes multiple astronomical observation images; the calculation unit 320 is used to determine, for each of the astronomical observation images, the pixel median corresponding to the astronomical observation image based on the pixel value of each pixel point of the astronomical observation image, and determine the pixel difference corresponding to each pixel point of the astronomical observation image based on the difference between the pixel value of each pixel point of the astronomical observation image and the pixel median corresponding to the astronomical observation image; the first generation unit 330 is used to generate a pixel data matrix corresponding to the astronomical acquisition data based on the pixel difference corresponding to each pixel point of the multiple astronomical observation images; the second generation unit 340 is used to generate a pixel data matrix corresponding to the astronomical acquisition data based on the pixel difference corresponding to each pixel point of the multiple astronomical observation images; the interference fringe processing unit 350 is used to perform interference fringe removal processing on the astronomical observation image based on the interference fringe image corresponding to the astronomical observation image for each of the astronomical observation images to obtain the processed astronomical observation image.

[0060] In some embodiments of the present application, based on the aforementioned scheme, the calculation unit 320 is specifically used to perform grayscale transformation on the pixel value of each pixel point of the astronomical observation image to obtain the grayscale value of each pixel point of the astronomical observation image; based on the grayscale value of each pixel point of the astronomical observation image, determine the pixel median corresponding to the astronomical observation image; based on the difference between the grayscale value of each pixel point of the astronomical observation image and the pixel median corresponding to the astronomical observation image, determine the pixel difference corresponding to each pixel point of the astronomical observation image.

[0061] In some embodiments of the present application, based on the aforementioned scheme, the first generating unit 330 is specifically used to generate a plurality of pixel vectors corresponding to the astronomical observation images based on the pixel difference corresponding to each pixel point of the plurality of astronomical observation images; and combine the pixel vectors corresponding to the plurality of astronomical observation images to generate a pixel data matrix corresponding to the astronomical acquisition data.

[0062] In some embodiments of the present application, based on the aforementioned scheme, the first generating unit 330 is specifically used to generate first column vectors corresponding to multiple astronomical observation images respectively based on pixel differences corresponding to each pixel point of the multiple astronomical observation images; based on the first column vectors corresponding to the multiple astronomical observation images, determine the median of the multiple first column vectors at each same element position, and generate a second column vector based on the median of the multiple first column vectors at each same element position; based on the difference between the first column vectors corresponding to the multiple astronomical observation images and the second column vector at each same element position, generate pixel vectors corresponding to the multiple astronomical observation images respectively.

[0063] In some embodiments of the present application, based on the aforementioned scheme, the second generation unit 340 is specifically used to perform matrix decomposition processing on the pixel data matrix to obtain a matrix decomposition result, wherein the matrix decomposition result includes a low-rank matrix; linear regression calculations are performed on the multiple astronomical observation images and the low-rank matrix respectively to obtain transformation scales between the multiple astronomical observation images and the low-rank matrix; based on the transformation scales between the multiple astronomical observation images and the low-rank matrix and the low-rank matrix, interference fringe images corresponding to the multiple astronomical observation images are generated respectively.

[0064] In some embodiments of the present application, the second generating unit 340 is specifically configured to perform matrix decomposition processing on the pixel data matrix by using the following formula to obtain a matrix decomposition result: ;

[0065] in, is the pixel data matrix, and the matrix decomposition result includes a low-rank matrix and sparse matrices , Represents the low-rank matrix Find the nuclear norm, is the sparse matrix To implement sparsity constraints, Represents the low-rank matrix and the sparse matrix The weight ratio between Indicated in When the loss function takes the minimum value, the low-rank matrix and the sparse matrix The value of .

[0066] In some embodiments of the present application, based on the aforementioned solution, the second generating unit 340 is specifically used to generate a plurality of interference fringe images estimated by the astronomical observation images based on the plurality of astronomical observation images and the pixel data matrix by using the following formula:

[0067] ;

[0068] is the pixel data matrix, It is expressed as calculating the nuclear norm of the interference fringe estimate. represents calculating a mask for the star image in the astronomical observation image, For the matrix Compute the Frobenius norm, for and The weight between these two terms is is the left singular vector matrix, is the singular value matrix, is the right singular vector matrix, is the transpose of the right singular vector matrix, For the pixel data matrix After singular value decomposition, the singular value matrix is ​​soft-thresholded and then the three matrices are , as well as Reorganization processing, is the interference fringe image.

[0069] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown.

[0070] It should be noted that Figure 4 The computer system 400 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0071] like Figure 4 As shown, the computer system 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage part 408 to the random access memory (RAM) 403, such as executing the method described in the above embodiment. In the RAM 403, various programs and data required for system operation are also stored. The CPU 401, the ROM 402 and the RAM 403 are connected to each other through the bus 404. The input / output (I / O) interface 405 is also connected to the bus 404.

[0072] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed so that a computer program read therefrom is installed into the storage section 408 as needed.

[0073] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer readable medium, which includes a computer program carried on a computer readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 409, and / or installed from a removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, various functions defined in the system of the present application are executed.

[0074] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier, which carries a computer-readable computer program. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0075] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0076] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0077] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method described in the above embodiment.

[0078] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0079] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software, or by combining software with necessary hardware. Therefore, the technical solution according to the implementation method of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation method of the present application.

[0080] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0081] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for processing astronomical images, characterized in that: include: Acquiring astronomical acquisition data, wherein the astronomical acquisition data includes a plurality of astronomical observation images; For each of the astronomical observation images, based on the pixel values ​​of each pixel point of the astronomical observation image, determine the pixel median value corresponding to the astronomical observation image, and based on the difference between the pixel value of each pixel point of the astronomical observation image and the pixel median value corresponding to the astronomical observation image, determine the pixel difference value corresponding to each pixel point of the astronomical observation image; Generate a pixel data matrix corresponding to the astronomical acquisition data based on the pixel difference corresponding to each pixel point of the plurality of astronomical observation images; Based on the plurality of astronomical observation images and the pixel data matrix, generating a plurality of interference fringe images corresponding to the astronomical observation images; For each of the astronomical observation images, performing interference fringe removal processing on the astronomical observation image based on the interference fringe image corresponding to the astronomical observation image to obtain a processed astronomical observation image; The step of generating interference fringe images corresponding to a plurality of the astronomical observation images based on the plurality of the astronomical observation images and the pixel data matrix comprises: Based on the plurality of astronomical observation images and the pixel data matrix, interference fringe images corresponding to the plurality of astronomical observation images are generated by the following formula: ； is the pixel data matrix, It is expressed as calculating the nuclear norm of the interference fringe estimate. represents calculating a mask for the star image in the astronomical observation image, For the matrix Compute the Frobenius norm, for and The weight between these two terms is To perform singular value matrix decomposition on the matrix, is the left singular vector matrix, is the singular value matrix, is the right singular vector matrix, is the transpose of the right singular vector matrix, Represents the pixel data matrix Perform singular value decomposition, After performing soft thresholding on the singular value matrix, the three matrices , as well as Reorganization processing, is the interference fringe image.

2. The astronomical image processing method according to claim 1, characterized in that: The determining, based on the pixel value of each pixel point of the astronomical observation image, the pixel median corresponding to the astronomical observation image, and determining, based on the difference between the pixel value of each pixel point of the astronomical observation image and the pixel median corresponding to the astronomical observation image, the pixel difference corresponding to each pixel point of the astronomical observation image, comprises: Performing grayscale transformation on the pixel value of each pixel point of the astronomical observation image to obtain the grayscale value of each pixel point of the astronomical observation image; Determine a pixel median value corresponding to the astronomical observation image based on the grayscale value of each pixel point of the astronomical observation image; Based on the difference between the grayscale value of each pixel point of the astronomical observation image and the median value of the pixel corresponding to the astronomical observation image, the pixel difference corresponding to each pixel point of the astronomical observation image is determined.

3. The astronomical image processing method according to claim 1, characterized in that: The step of generating a pixel data matrix corresponding to the astronomical acquisition data based on the pixel difference corresponding to each pixel point of the plurality of astronomical observation images comprises: Generate a plurality of pixel vectors corresponding to the astronomical observation images based on pixel differences corresponding to respective pixel points of the plurality of astronomical observation images; The pixel vectors corresponding to the plurality of astronomical observation images are combined to generate a pixel data matrix corresponding to the astronomical acquisition data.

4. The astronomical image processing method according to claim 3, characterized in that: The step of generating a plurality of pixel vectors corresponding to the astronomical observation images based on the pixel difference corresponding to each pixel point of the plurality of astronomical observation images comprises: Based on the pixel difference corresponding to each pixel point of the plurality of astronomical observation images, respectively generate first column vectors corresponding to the plurality of astronomical observation images; Based on the first column vectors corresponding to the plurality of astronomical observation images, determining the median of the plurality of the first column vectors at the respective same element positions, and generating the second column vector based on the median of the plurality of the first column vectors at the respective same element positions; Based on the difference between the first column vector corresponding to the plurality of astronomical observation images and the second column vector at each same element position, the pixel vectors corresponding to the plurality of astronomical observation images are generated respectively.

5. The astronomical image processing method according to claim 1, characterized in that: The step of generating interference fringe images corresponding to a plurality of the astronomical observation images based on the plurality of the astronomical observation images and the pixel data matrix comprises: Performing matrix decomposition processing on the pixel data matrix to obtain a matrix decomposition result, wherein the matrix decomposition result includes a low-rank matrix; Performing linear regression calculations on the plurality of astronomical observation images and the low-rank matrix respectively to obtain transformation scales between the plurality of astronomical observation images and the low-rank matrix; Based on the transformation scales between the plurality of astronomical observation images and the low-rank matrix and the low-rank matrix, respectively generating interference fringe images corresponding to the plurality of astronomical observation images; performing matrix decomposition processing on the pixel data matrix to obtain a matrix decomposition result, comprises: The pixel data matrix is ​​subjected to matrix decomposition processing by the following formula to obtain a matrix decomposition result: ; in, is the pixel data matrix, and the matrix decomposition result includes a low-rank matrix and sparse matrices , Represents the low-rank matrix Find the nuclear norm, is the sparse matrix To implement sparsity constraints, Represents the low-rank matrix and the sparse matrix The weight ratio between Indicated in When the loss function takes the minimum value, the low-rank matrix and the sparse matrix The value of .

6. An astronomical image processing device, characterized in that: include: An acquisition unit, used to acquire astronomical acquisition data, wherein the astronomical acquisition data includes a plurality of astronomical observation images; a calculation unit, configured to determine, for each of the astronomical observation images, a pixel median corresponding to the astronomical observation image based on a pixel value of each pixel point of the astronomical observation image, and determine a pixel difference corresponding to each pixel point of the astronomical observation image based on a difference between a pixel value of each pixel point of the astronomical observation image and a pixel median corresponding to the astronomical observation image; A first generating unit, configured to generate a pixel data matrix corresponding to the astronomical acquisition data based on a pixel difference corresponding to each pixel point of a plurality of the astronomical observation images; A second generating unit, configured to generate a pixel data matrix corresponding to the astronomical acquisition data based on pixel differences corresponding to respective pixel points of a plurality of the astronomical observation images; an interference fringe processing unit, configured to perform interference fringe removal processing on each of the astronomical observation images based on the interference fringe image corresponding to the astronomical observation image, so as to obtain a processed astronomical observation image; The step of generating interference fringe images corresponding to a plurality of the astronomical observation images based on the plurality of the astronomical observation images and the pixel data matrix comprises: Based on the plurality of astronomical observation images and the pixel data matrix, interference fringe images corresponding to the plurality of astronomical observation images are generated by the following formula: ； is the pixel data matrix, It is expressed as calculating the nuclear norm of the interference fringe estimate. represents calculating a mask for the star image in the astronomical observation image, For the matrix Compute the Frobenius norm, for and The weight between these two terms is To perform singular value matrix decomposition on the matrix, is the left singular vector matrix, is the singular value matrix, is the right singular vector matrix, is the transpose of the right singular vector matrix, Represents the pixel data matrix Perform singular value decomposition, After performing soft thresholding on the singular value matrix, the three matrices , as well as Reorganization processing, is the interference fringe image.

7. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the astronomical image processing method according to any one of claims 1 to 5.

8. A computer readable medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the astronomical image processing method according to any one of claims 1 to 5 is implemented.

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