Line illumination super-resolution imaging method and apparatus, medium and computer program product

Abstract

Disclosed in the present invention are a line illumination super-resolution imaging method and apparatus, a medium and a computer program product. The method comprises: scanning a sample in an orthogonal line illumination imaging mode, so as to simultaneously acquire line illumination images in two orthogonal directions; performing pixel mapping on each of the line illumination images, so as to obtain images the spatial resolution of which has been preliminarily enhanced after pixel mapping; performing detection modulation on each of the pixel-mapped images, so as to obtain detection-modulated images; and performing deconvolution-based fusion on the detection-modulated images, so as to obtain a transversely uniform super-resolution tomographic reconstructed image as a final imaging result of the sample. By means of interaction of pixel mapping, detection modulation and deconvolution-based fusion, the present invention solves the technical problems of limited imaging throughput, insufficient tomographic capability and complex reconstruction algorithms in existing structured illumination modulation-based optical super-resolution technologies.

Description

Line illumination super-resolution imaging method, device, medium and computer program product TECHNICAL FIELD

[0001] The present application relates to super-resolution optical imaging technology, in particular to a line illumination super-resolution imaging method, device, medium and computer program product. BACKGROUND

[0002] With the increasing demand for subcellular organelle ultrastructure and interaction, the development of imaging devices and labeling methods has gradually matured, and currently a variety of optical super-resolution imaging technologies have been developed, including single molecule localization microscopy (SMLM), stimulated emission depletion microscopy (STED) and structured illumination microscopy (SIM) and the like. Compared with other optical super-resolution imaging technologies, linear SIM has slightly weaker spatial resolution capability, but it has high-speed imaging, low light bleaching, compatibility with traditional fluorescence detection, covering various wide-field imaging modes, and can be used for long-term observation of physiological activities of living cells, and has been widely used. Although the development of software and hardware has promoted the performance improvement of SIM, there are still some deficiencies in traditional SIM based on wide field.

[0003] In the traditional scanning confocal imaging method (CLSM), the paraxial detection unit deviated from the optical axis by a distance of 2v records the high-frequency information of the object surface deviated from the optical axis by a distance of v. However, due to the misregistration of high-frequency information, CLSM cannot achieve super-resolution.

[0004] Therefore, it is necessary to develop a high-throughput optical super-resolution imaging method and system with strong tomographic ability and uniform spatial resolution in the lateral direction. SUMMARY

[0005] The purpose of the present application is to solve the technical problems of limited imaging throughput, insufficient tomographic ability and complex reconstruction algorithm in the existing optical super-resolution technology based on structured illumination modulation by pixel mapping, detection modulation and deconvolution fusion interaction, and provide a line illumination super-resolution imaging method, device, medium and computer program product.

[0006] According to one aspect of the present application, a line illumination super-resolution imaging method is provided, comprising:

[0007] Scanning the sample in an orthogonal line illumination imaging mode, and simultaneously acquiring line illumination imaging images in two orthogonal directions;

[0008] Pixel mapping is performed on the line illumination imaging images in the two orthogonal directions respectively to obtain pixel-mapped images;

[0009] Detection modulation is performed on the pixel-mapped images in the two orthogonal directions respectively to obtain detection-modulated images;

[0010] The deconvolution fusion of the images after the detection modulation of the two orthogonal directions obtains the reconstructed image as the imaging result of the sample.

[0011] As a further technical solution, when scanning the sample in the orthogonal line illumination imaging mode, the method further comprises: using the orthogonal line illumination to cooperate with the N-row subarray exposure mode of the detector to scan the sample.

[0012] As a further technical solution, after obtaining the line illumination imaging images in the two orthogonal directions, the method further comprises: upsampling the line illumination imaging images in the two orthogonal directions respectively to obtain upsampled images.

[0013] As a further technical solution, after obtaining the upsampled images, the method further comprises: determining an offset vector corresponding to each strip image in the upsampled images according to the position of each detection unit in the N-row subarray of the detector; and performing translation on the strip image according to the offset vector to realize pixel mapping.

[0014] As a further technical solution, after obtaining the image after pixel mapping, the method further comprises: when the number N of subarray rows of the detector is even, adding the N / 2th and (N+1) / 2th images after pixel mapping, multiplying the sum by a specified multiple, and then subtracting the remaining images after pixel mapping to obtain the image after detection modulation.

[0015] As a further technical solution, after obtaining the image after pixel mapping, the method further comprises: when the number N of subarray rows of the detector is odd, multiplying the (N+1) / 2th image after pixel mapping by a specified multiple, and then subtracting the remaining images after pixel mapping to obtain the image after detection modulation.

[0016] As a further technical solution, the deconvolution fusion of the two orthogonal direction images after tomographic enhancement is realized in the following manner: O=argmin O ((PSF X *O-I X-LISM ) 2 +(PSF Y *O-I Y-LISM ) 2

[0017] Wherein, argmin represents finding the minimum value of the function expression corresponding to the value of O in the interval where the variable O is allowed to change, PSF X and PSF Y respectively represent the point spread functions corresponding to the line illumination focused in the horizontal x and y directions, I X-LISM and I Y-LISM ​respectively represent the images obtained after pixel mapping and detection modulation of the multi-row detection imaging results corresponding to the line illumination in the transverse x and y directions, and O represents the real structure distribution of the sample on the focal plane.

[0018] According to an aspect of the present application, a line illumination super-resolution imaging device is provided, comprising:

[0019] a sample imaging module, configured to scan a sample in an orthogonal line illumination imaging mode and simultaneously acquire line illumination imaging images in two orthogonal directions;

[0020] a pixel mapping module, configured to perform pixel mapping on the line illumination imaging images in the two orthogonal directions respectively, to obtain pixel-mapped images;

[0021] a detection modulation module, configured to perform detection modulation on the pixel-mapped images in the two orthogonal directions respectively, to obtain detection-modulated images;

[0022] a bidirectional fusion module, configured to perform deconvolution fusion on the detection-modulated images in the two orthogonal directions, to obtain a reconstructed image as an imaging result of the sample.

[0023] According to an aspect of the present application, a computer readable storage medium is provided, which stores a computer program, and the computer program is executed by a processor to implement the steps of the method.

[0024] According to an aspect of the present application, a computer program product is provided, comprising a computer program, and the computer program is executed by a processor to implement the steps of the method.

[0025] Compared with the prior art, the present application has the following beneficial effects:

[0026] The present application combines line illumination imaging with the multi-row parallel working mode of the detector, simultaneously acquires line illumination imaging images of the sample along two orthogonal directions, realizes fast acquisition of the sample image without sacrificing the imaging flux, improves the image spatial resolution and tomography by performing pixel mapping and then detection modulation on the imaging images, enhances the image resolution by performing deconvolution fusion on the detection-modulated images in the two orthogonal directions, and finally achieves the effect of realizing super-resolution high-definition optical imaging based on structure illumination modulation.

[0027] The present application realizes pixel mapping by first upsampling and then vector offsetting the original imaging image, and the offset vector corresponds to the detection position of the original strip image, so that detection modulation can be performed through simple addition and subtraction operations based on the pixel-mapped image, and the proportion of negative values caused by subtraction required for background removal can be suppressed.

[0028] The present application utilizes detection modulation, and through simple operation, the effects of improving the chromatographic capacity, signal-to-noise ratio and spatial resolution are achieved, and relative to the existing chromatographic mode, the calculation complexity is reduced.

[0029] The present application utilizes the deconvolution fusion method to realize the image fusion of detection modulation in two orthogonal directions, and relative to the existing resolution improvement in the direction of line illumination focusing, the deconvolution is utilized to realize the two-direction fusion of the super-resolution chromatographic image obtained based on orthogonal line illumination imaging, and the lateral uniform resolution improvement is realized. BRIEF DESCRIPTION OF DRAWINGS

[0030] Fig. 1 is a flowchart of the super-resolution imaging method of the present application.

[0031] Fig. 2 is a schematic diagram of the optical path structure of the line illumination super-resolution imaging method of the present application.

[0032] Fig. 3 is a flowchart of the super-resolution high-definition image reconstruction of the present application.

[0033] Fig. 4 is a schematic diagram of the spatial resolution comparison of the system LISM based on detection modulation and pixel mapping to realize super-resolution high-definition imaging, the line confocal system LC, and the system ISM based on line confocal pixel mapping in the line illumination focusing direction.

[0034] Fig. 5 is a schematic diagram of the imaging results of the orthogonal line illumination super-resolution high-definition high-speed optical imaging method of the present application on three distances within the diffraction limit range, the diameter of the fluorescent microbead is 100nm, and the center emission wavelength is 515nm. DETAILED DESCRIPTION

[0035] In view of the problems of weak chromatographic capacity and complex reconstruction algorithm in the existing structure illumination modulation method for realizing super-resolution optical imaging, the present application provides a line illumination super-resolution imaging method, which quickly obtains the original sample image through orthogonal line illumination imaging, processes the original sample image through pixel mapping, detection modulation and multi-image fusion, realizes super-resolution optical imaging with strong chromatographic capacity, simple reconstruction algorithm and fast imaging speed, and solves the technical problems of insufficient imaging flux, insufficient chromatographic capacity and complex reconstruction algorithm in the optical super-resolution technology based on structure illumination modulation.

[0036] It should be noted that the present application utilizes the orthogonal line illumination method to obtain the original sample image, and under the premise of not additionally increasing the scanning time, the sample images in two orthogonal directions can be obtained at the same time, the imaging flux is improved, and the problem of limited imaging flux is solved.

[0037] The technical solutions of the present application will be clearly and completely described below with reference to the drawings in the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0038] The present application provides a line illumination super-resolution imaging method, as shown in FIG. 1, which comprises the following steps:

[0039] Step 1: scanning the sample in the orthogonal line illumination imaging mode, and simultaneously acquiring two direction orthogonal line illumination imaging images.

[0040] Here, the orthogonal line illumination imaging method is used to simultaneously acquire two direction orthogonal line illumination imaging results, which realizes the transverse uniform super-resolution reconstruction results without sacrificing the imaging flux, changing the focusing direction of the line illumination and reducing the imaging speed.

[0041] The schematic diagram of the whole optical imaging structure is shown in FIG. 2, in which 1 is an imaging objective, 2 is a displacement table for scanning after fixing the sample, 3 is orthogonal line illumination formed by the focal plane of the imaging objective, 4 is a device (such as a beam splitter) for separating the signals excited by the two line illuminations, 5 is a detector conjugated with the line spot focused along the Y direction, and 6 is a detector conjugated with the line spot focused along the X direction.

[0042] In actual application, the orthogonal line illumination is used to realize the signal excitation of the sample, the two detectors conjugated with the two line spots are used to collect the signals, and the diagonal line scanning is used to simultaneously acquire the line illumination imaging results in two directions.

[0043] Specifically, the implementation method of the orthogonal line illumination imaging comprises the following steps:

[0044] Step 1: two orthogonal line beams with the same focusing plane are used to simultaneously irradiate the sample, and the relative motion of the orthogonal line beams and the sample in the diagonal line direction of the orthogonal line beams is controlled to acquire two strip images of the orthogonal line beams;

[0045] Step 2: the pixels in the two strip images are translated and positioned to obtain two positioned images as two direction orthogonal line illumination imaging images.

[0046] It is noted that the orthogonal line illumination imaging method simultaneously obtains the line illumination imaging results in two directions perpendicular to each other by diagonal line scanning, and realizes the improvement of the spatial sampling rate to This makes it unnecessary to add a 4f module for secondary amplification in the detection light path, and simplifies the complexity of the optical path.

[0047] Step 2, pixel mapping is performed on the line illumination imaging images in two orthogonal directions respectively to obtain pixel-mapped images.

[0048] After obtaining the original sample image, upsampling by a specified multiple is performed.

[0049] Specifically, since the high-frequency signal obtained by the paraxial detection unit has a 1 / 2 times spatial misalignment, the collected original image needs to be first upsampled by 2 times, and the numerical interpolation method used can be a classical interpolation method such as the cubic algorithm.

[0050] It should be noted that the N rows of detection units need to cover at least the width of the line illumination, and increasing the value of N will result in a decrease in the acquisition speed of the detector (hardware limitation), therefore, N is selected to be the minimum number of detection rows allowed by the detector that can cover the width of the line illumination, and here, N = 8 is taken as an example for illustrative purposes, without limiting the specific working mode of the detector of the present application.

[0051] Taking the case where the detector works in the 8-row subarray exposure mode (Sub-Array), during line scanning, the imaging results obtained by sequentially splicing multiple frames of exposure are obtained, and 8 strip images are obtained, and the 8 strip images are upsampled:

[0052] wherein, represents the i-th row of the strip image corresponding to the detection array in the line illumination imaging result, and contains m x n pixels; represents The image after 2 times upsampling contains (2m) x (2n) pixels.

[0053] Subsequently, according to the position of the detection unit, the offset vector corresponding to the i-th strip image in the line illumination imaging result is set as:

[0054] According to the corresponding offset vector, the strip image is translated to realize pixel mapping:

[0055] wherein, (x, y) is the coordinate of the horizontal X and Y axes.

[0056] Step 3, detection modulation is performed on the pixel-mapped images in two orthogonal directions respectively to obtain detection-modulated images.

[0057] Specifically, the natural Gaussian modulation of the line illumination is used, and based on the subtraction method, the enhancement of tomography and the further improvement of spatial resolution are realized; and by using the addition method, the signal-to-noise ratio is enhanced.

[0058] where I LISM is the high-definition super-resolution reconstructed image.

[0059] The core idea is that the detection unit of the axis, that is, the two rows of detection units that are best conjugated with the line illumination, contains information in the corresponding detection results, which is composed of high-amplitude in-focus low-frequency information and out-of-focus background information; the detection unit of the paraxial contains information in the corresponding detection results, which is composed of low-amplitude in-focus high-frequency information and out-of-focus background information. Since the amplitude of the out-of-focus background information does not change significantly in the detection results corresponding to the on-axis or paraxial detection unit, it can be directly removed by subtraction to achieve optical tomography. At the same time, the high-frequency information mapped back to the correct position and the low-frequency information at that position are added to enhance the signal-to-noise ratio of the image. Here, the detection results of the two outermost rows are removed because the hardware design of the current detection device limits the image quality of the imaging results of the two rows of detection units, and the high-frequency information recorded is submerged in the out-of-focus background and noise.

[0060] Step 4: Fuse the deconvolved images of the two orthogonal directions to obtain a transversely uniform reconstructed image as the imaging result of the sample.

[0061] Regarding the fusion of the two-direction imaging results, a multi-image fusion method based on deconvolution is adopted: O = argmin O ((PSF X *O-I X-LISM ) 2 +(PSF Y *O-I Y-LISM ) 2 ). (5)

[0062] where argmin represents finding the minimum value of the function expression corresponding to the value of O within the interval allowed to change, PSF X and PSF Y represent the point spread functions corresponding to the line illumination focused in the transverse x and y directions, respectively, I X-LISM and I X-LISM represent the super-resolution high-definition reconstructed results obtained after pixel mapping and background removal of the multi-row detection imaging results corresponding to the line illumination focused in the transverse x and y directions, respectively, and O represents the true structure distribution of the sample on the focal plane. I cLISM is the estimated value of O after several iterations, and the general number of iterations is 3. The deconvolution method is selected for two-direction fusion to further improve the resolution and reduce the gap between the actual resolution and the theoretical resolution caused by factors such as aberration during imaging.

[0063] In one embodiment, as shown in Fig. 3, the original sample images go through two times upsampling, pixel mapping, LiMo processing and bidirectional image fusion in sequence to get the reconstructed super-resolution high-definition image, and the specific steps include:

[0064] Collecting original sample images I X-Raw and I Y-Raw in X / Y two orthogonal directions by using orthogonal line illumination imaging system

[0065] Upsampling the collected original sample images to get I X-Raw2 and I Y-Raw2 ;

[0066] Pixel mapping the upsampled images according to the set displacement vector to get I X-ISM and I Y-ISM ;

[0067] LiMo processing the pixel mapped images according to plus-minus geometric operation to get I X-LISM and I Y-LISM ;

[0068] Deconvolution image fusion of the two LiMo processed images to get the transverse uniform reconstructed result I cLISM .

[0069] It should be understood that although each step in the flowchart involved in each embodiment as described above is displayed in sequence according to the arrow indication, these steps are not necessarily executed in sequence according to the arrow indication. Unless explicitly stated herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other sequences. Moreover, at least part of the steps in the flowchart involved in each embodiment as described above can include multiple steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence of these steps or stages is not necessarily sequential, but can be executed in rotation or alternation with at least part of other steps or steps or stages in other steps.

[0070] Fig. 4 is a comparison of spatial resolution of the line confocal system LC, the system ISM based on line confocal pixel mapping, the system LiMo based on probe modulation to realize tomographic enhancement and resolution enhancement, and the system LISM based on probe modulation and pixel mapping to realize super-resolution high-definition imaging in the direction of line illumination focusing, in which the full width at half maximum of the corresponding point spread function is marked, and the spatial resolution of each imaging system is quantitatively represented. As can be seen from the figure, the spatial resolution of LISM is 1.7 times that of LC. In addition, it is noted that in LiMo, due to the subtraction, there are negative values, and after restoring the correct position of the detection results of each detection unit, LISM can suppress the proportion of negative values. The sum of the negative values and the positive values is calculated, and the ratio is calculated. In LiMo, the ratio of the sum of the negative values to the sum of the positive values is 53.34%, while in LISM, the ratio of the sum of the negative values to the sum of the positive values is 14.37%, which helps to preserve weak signals. PSF(j)<0 PSF(j) / ∑ PSF(j)>0 PSF(j) as 53.34%, while in LISM, the ratio of the sum of the negative values to the sum of the positive values is 14.37%, which helps to preserve weak signals. PSF(j)<0 PSF(j) / ∑ PSF(j)>0 PSF(j) as 53.34%, while in LISM, the ratio of the sum of the negative values to the sum of the positive values is 14.37%, which helps to preserve weak signals.

[0071] Fig. 5 is a result image of the orthogonal line illumination super-resolution high-definition high-speed optical imaging method for imaging three fluorescent microbeads with a diameter of 100 nm and a center emission wavelength of 515 nm within the diffraction limit range. The imaging objective used is a 60x / NA 1.1 water lens. As can be seen from the figure, the three microbeads that cannot be clearly distinguished in the line confocal imaging results X-LC and Y-LC are more difficult to see the boundaries in X-LISM, more obvious to see the boundaries in Y-LISM, and clear and uniform resolution is obtained in cLISM. It is noted that under the same image dynamic range, X-LISM, Y-LISM and cLISM show obvious contrast on the background compared with X-LC and Y-LC, which shows that the geometric operation combined with the line illumination modulation method suppresses the background, thereby improving the image contrast.

[0072] Based on the same technical concept as the method of the present application, the present application also provides a line illumination super-resolution imaging device, comprising:

[0073] a sample imaging module for scanning a sample in an orthogonal line illumination imaging manner and simultaneously acquiring line illumination imaging images in two orthogonal directions;

[0074] a pixel mapping module for respectively performing pixel mapping on the line illumination imaging images in the two orthogonal directions to obtain pixel-mapped images;

[0075] a probe modulation module for respectively performing probe modulation on the pixel-mapped images in the two orthogonal directions to obtain probe-modulated images;

[0076] The bidirectional fusion module is used for deconvolution fusion of images modulated by detection in two orthogonal directions to obtain a reconstructed image as an imaging result of the sample.

[0077] It should be noted that the implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, and therefore the specific limitations in the implementation of the foregoing modules can be referred to the limitations of the super-resolution imaging method in the above, which will not be described here.

[0078] Based on the same technical concept as the method of the present application, the present application also provides a computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the steps of the method.

[0079] Based on the same technical concept as the method of the present application, the present application also provides a computer program product comprising a computer program, the computer program being executed by a processor to implement the steps of the method.

[0080] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0081] The present application is described with reference to flowcharts and / or block diagrams of the method, device (system), and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce the functions specified in one or more flows in the flowcharts and / or one or more blocks in the block diagrams.

[0082] These computer program instructions can also be stored in a computer-readable memory that can direct the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product comprising instruction means, which implements the functions specified in one or more flows in the flowcharts and / or one or more blocks in the block diagrams.

[0083] These computer program instructions can also be loaded into a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks and / or blocks in the block diagram.

[0084] In summary, the present application has the following advantages:

[0085] a) The present application realizes ISM in line illumination imaging, that is, realizing ISM in line illumination imaging with pixel mapping and multi-line parallel detection of the detector, without calculation in the frequency domain, and through simple and fast pixel mapping method, the correct position of high frequency information can be recovered, and the spatial resolution and signal-to-noise ratio of the focusing direction are improved.

[0086] b) The present application realizes tomographic enhancement, signal-to-noise ratio improvement and further resolution enhancement through simple addition and subtraction operation by using detection modulation.

[0087] c) The pixel mapping of the present application can inhibit the proportion of negative values caused by subtraction in the detection modulation process for removing the background.

[0088] d) The present application adopts orthogonal line illumination imaging method to simultaneously acquire two orthogonal line illumination imaging results, so as to recover a transversely uniform super-resolution image after single scanning, and in the realization of the transversely uniform super-resolution reconstruction result, the focusing direction of the line illumination does not need to be changed for multiple imaging, and the imaging speed is not reduced.

[0089] Although the embodiments of the present application have been shown and described, it is to be understood that for the purpose of the present application, the changes, modifications, equivalents, substitutions and variations of the embodiments can be made by those skilled in the art without departing from the spirit and principles of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A method of line illumination super-resolution imaging, characterized in that, The method comprises the following steps: scanning the sample in a cross-line illumination imaging mode, and acquiring two cross-line illumination imaging images in two directions; performing pixel mapping on the two cross-line illumination imaging images in two directions respectively to obtain pixel-mapped images; performing detection modulation on the two pixel-mapped images in two directions respectively to obtain detection-modulated images; performing deconvolution fusion on the two detection-modulated images in two directions to obtain a reconstructed image as the imaging result of the sample.

2. The method of claim 1, wherein, When the sample is scanned in the cross-line illumination imaging mode, the method further comprises the following step:

3. The method of claim 2, wherein, acquiring two cross-line illumination imaging images in two directions, and performing upsampling on the two cross-line illumination imaging images in two directions respectively to obtain upsampling images.

4. The method of claim 3, wherein the method further comprises: After the upsampling images are obtained, the method further comprises the following steps:

5. The method of claim 4, wherein, determining an offset vector corresponding to each strip image in the upsampling images according to the position of each detection unit in the N-row subarray of the detector; and performing translation on the strip images according to the offset vector to realize pixel mapping.

6. The method of claim 4, wherein the method further comprises: After the pixel-mapped images are obtained, the method further comprises the following steps:

7. The method of claim 1, wherein the method is a line illumination super resolution imaging method. The fusion of the deconvoluted images of the two orthogonal directions of the probe-modulated images is implemented in the following way: O = argmin O ((PSF X *O-I X-LISM ) 2 +(PSF Y *O-I Y-LISM ) 2 ) where argmin denotes the value of O that minimizes the function expression in the interval where O is allowed to vary, PSF X and PSF Y respectively represent the point spread functions corresponding to line illumination focused in the lateral x and y directions, I X-LISM and I X-LISM respectively represent the images obtained after pixel mapping and detection modulation of the multi-line detection imaging results corresponding to line illumination focused in the lateral x and y directions, and O represents the real structure distribution of the sample on the focal plane.

8. A line illumination super-resolution imaging device, characterized by, when the number N of subarray rows of the detector is even, adding the N / 2th and (N+1) / 2th pixel-mapped images, multiplying the sum by a specified multiple, and then subtracting the remaining pixel-mapped images to obtain the detection-modulated images. After the pixel-mapped images are obtained, the method further comprises the following steps: when the number N of subarray rows of the detector is odd, multiplying the (N+1) / 2th pixel-mapped image by a specified multiple, and then subtracting the remaining pixel-mapped images to obtain the detection-modulated images. The method comprises the following steps: a sample imaging module is configured to scan a sample in a cross-line illumination imaging mode, and acquire two cross-line illumination imaging images in two directions; 9. A computer-readable storage medium having stored thereon a computer program, characterized in that, a pixel mapping module is configured to perform pixel mapping on the two cross-line illumination imaging images in two directions respectively to obtain pixel-mapped images; 10. A computer program product comprising a computer program, characterized in that, a detection modulation module is configured to perform detection modulation on the two pixel-mapped images in two directions respectively to obtain detection-modulated images; a bidirectional fusion module is configured to perform deconvolution fusion on the two detection-modulated images in two directions to obtain a reconstructed image as the imaging result of the sample. The computer program is executed by a processor to implement the steps of the method of any one of claims 1 to 7. The computer program is executed by a processor to implement the steps of the method of any one of claims 1 to 7.

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