A method for expanding the depth of field based on sparse scanning in light field microscopy

Abstract

This invention provides a method for expanding the field of view depth based on sparse scanning in light field microscopy, comprising: performing sparse scanning of a sample along the XYZ axes using a microlens array light field imaging system to reduce the overlap rate between adjacent fields of view to a preset value, thereby acquiring multi-field two-dimensional raw light field data; performing pixel rearrangement and deconvolution three-dimensional reconstruction on the two-dimensional raw light field image of each field of view to obtain a reconstructed three-dimensional volume for each field of view; calculating the theoretical overlap region width along the XYZ axes based on the sparse scanning step size, and performing consistency calibration on the overlap region along the XYZ axes of adjacent fields of view; and recursively fusing the calibrated reconstructed three-dimensional volumes along the XYZ axes to obtain a three-dimensional volume image with full field of view and full depth. This invention not only provides a larger imaging depth range but also ensures image clarity at different depth levels, overcoming the inherent depth-of-field limitations of traditional optical systems.

Description

Technical Field

[0001] This invention belongs to the field of three-dimensional imaging technology, specifically relating to a method for expanding the field of view depth based on sparse scanning of an optical field microscope. Background Technology

[0002] With the development of science and technology, three-dimensional imaging technology has been widely used in many fields such as biomedicine, materials science, and archaeology. However, traditional three-dimensional imaging methods (such as confocal microscopy and light sheet microscopy), such as dense Z-axis scanning, face many challenges when processing high-throughput samples or live biological samples. These traditional methods usually require continuous Z-axis scanning of the sample to obtain information at different depths, which is not only time-consuming but also generates a large amount of data, increasing the burden of data processing and storage. In addition, the depth of field of traditional microscopes is limited by the numerical aperture (NA) and depth of focus of the objective lens. While dense scanning can expand the field of view and depth of field, it significantly sacrifices temporal resolution. Therefore, due to the dynamic changes of the sample itself or the limitations of equipment precision, traditional methods often fail to achieve the ideal field of view expansion and depth enhancement effects.

[0003] Therefore, how to achieve more efficient expansion of field of view and depth of field is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] In view of this, the present invention proposes a field of view and depth of field extension method based on sparse scanning of light field microscopy, which achieves more efficient field of view and depth of field extension by fusing sparse three-dimensional scanning and light field three-dimensional reconstruction.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] This invention first discloses a method for expanding the field of view depth based on sparse scanning in light field microscopy, comprising the following steps:

[0007] S1: Use a microlens array light field imaging system to perform sparse scanning of the sample along the XYZ axes, so that the overlap rate between adjacent fields of view is lower than a preset value, and acquire multi-field two-dimensional raw light field data.

[0008] S2: Perform pixel rearrangement and deconvolution 3D reconstruction on the original 2D light field image of each field of view to obtain the reconstructed 3D volume of each field of view;

[0009] S3: Calculate the theoretical overlap region width along the XYZ axes based on the sparse scanning step size, and perform consistency calibration on the overlap region along the XYZ axes of adjacent fields of view.

[0010] S4: Recursively fuse the calibrated reconstructed 3D volume along the XYZ axes to obtain a full-field-of-view, full-depth 3D volume image.

[0011] Preferably, in step S1, by setting the physical size step of sparse three-dimensional scanning, the overlap rate between adjacent fields of view is less than 60%.

[0012] Preferably, step S2 includes the following steps:

[0013] S21: Rearrange the pixels of the original two-dimensional light field image of each field of view to obtain the four-dimensional phase space light field data of each field of view, including the angular coordinates of a single microlens and the spatial coordinates of the microlens array light field imaging system.

[0014] S22: Perform phase space deconvolution on the four-dimensional phase space light field data and the system point spread function (PSF) to obtain the reconstructed three-dimensional volume for each field of view.

[0015] Preferably, step S21 includes the following steps:

[0016] S211: Fix the viewpoint coordinates, obtain the pixel values ​​of the viewpoint coordinates under different spatial coordinates, and form a spatial coordinate sub-image of the viewpoint coordinates.

[0017] S212: The spatial coordinate sub-images of all viewpoint coordinates are arranged in sequence, together forming the four-dimensional phase space light field data of the two-dimensional original light field image, with a size of [missing information]. u v h w The vertical and horizontal dimensions of the two-dimensional light field map are respectively... u h and v w , h and w These represent the longitudinal and transverse spatial coordinates in the microlens array optical field imaging system, respectively. u and v These represent the longitudinal and transverse angular coordinates of a single microlens, respectively.

[0018] Preferably, step S22 includes the following steps:

[0019] The Richardson-Lucy deconvolution algorithm was used to process the four-dimensional phase space light field data. Phase space deconvolution is performed with the system point spread function (PSF) to obtain the reconstructed 3D volume for each view. :

[0020] ;

[0021] In the formula, z Represents the reconstruction of a three-dimensional body zAxial coordinates k This indicates the number of iterations in the deconvolution algorithm. This represents the convolution operation. for PSF conjugate convolution, h and w These represent the longitudinal and transverse spatial coordinates in the microlens array optical field imaging system, respectively. u and v These represent the longitudinal and transverse angular coordinates of a single microlens, respectively.

[0022] Preferably, step S3 includes the following steps:

[0023] The theoretical overlap region width along the XYZ axes is calculated based on the sparse scan step size, and the overlap region along the XYZ axes of adjacent fields of view is calibrated for consistency with the goal of minimizing the similarity of the overlap region of the reconstructed 3D volume for each pair of adjacent fields of view.

[0024] Preferably, in S3:

[0025] Calculate the pixel steps corresponding to the spatial steps X, Y, and Z of sparse 3D sampling. , , for:

[0026] ;

[0027] ;

[0028] ;

[0029] In the formula, pix This represents the physical size of a sensor pixel in a microlens array light field imaging system. M The optical magnification of the microlens array light field imaging system. dz The Z-axis spacing for three-dimensional tomography;

[0030] The theoretical overlap regions widths along the XYZ axes of sparse 3D scanning are derived as follows:

[0031] ;

[0032] ;

[0033] ;

[0034] In the formula, W The X-axis dimension of the original two-dimensional light field image. H is the Y-axis dimension of the original two-dimensional light field image.

[0035] Preferably, in S3:

[0036] Registration windows are established along the three axes, and the widths of the overlapping regions in the three directions are calibrated to automatically estimate the optimal fusion offset. Specific steps include: reconstructing a 3D volume for each pair of adjacent views (…). A dynamic search window is defined within a specified range of the theoretical overlap area along the XYZ axes, and all offsets within the search window are traversed. d and perform the corresponding offset. d The result after the operation ( The new theory calculates the similarity of overlapping regions and selects the offset with the highest similarity score as the optimal fusion offset.

[0037] Preferably, in S3: the similarity of overlapping regions is calculated using the multiplicative correlation method, or the similarity of overlapping regions is calculated using the structural similarity method.

[0038] Preferably, step S4 includes the following steps:

[0039] The reconstructed 3D volumes calibrated along each row of the X-axis are recursively fused to obtain multiple X-axis 3D volumes.

[0040] Recursively fuse each layer of the already fused X-axis 3D volume along the Y-axis to obtain multiple 2D planar 3D volumes;

[0041] The two-dimensional planar three-dimensional volumes of each layer are recursively fused along the Z-axis to obtain the full field of view and full depth three-dimensional volume image.

[0042] Preferably, in step S4, when the recursive fusion step is performed on the reconstructed 3D volume after adjacent view calibration, the overlapping area after adjacent view calibration is replaced with smooth.

[0043] As can be seen from the above technical solution, compared with the traditional dense Z-axis scanning method, the beneficial effects of the present invention include:

[0044] The method of this invention utilizes light field data acquisition under sparse three-dimensional displacement and combines it with a light field phase space reconstruction algorithm to achieve spatial continuity reconstruction, while overcoming the problem of traditional limited depth of field.

[0045] This invention utilizes a combination of intermittent acquisition and phase space reconstruction technology to achieve full-field-of-view, full-depth 3D volume construction. It not only provides a wider imaging depth range but also ensures image clarity at different depth levels, overcoming the inherent depth-of-field limitations of traditional optical systems. Simultaneously, it significantly reduces the amount of data acquired and improves imaging speed, making it suitable for high-throughput, live biological imaging, and other 3D imaging scenarios with extremely high speed and depth-of-field requirements.

[0046] This invention calibrates the width of the overlapping area through dynamic search, compensates for the positioning deviation of the scanning platform, and ensures accurate alignment between adjacent reconstructed 3D volumes. This step greatly improves the consistency and accuracy of multi-view reconstruction.

[0047] This invention supports multiple similarity measurement modes (multiplication / SSIM) to adapt to different sample characteristics (high dynamic range, low contrast). By traversing all possible offsets and selecting the offset with the highest similarity score as the optimal fusion offset, it achieves an automated best-match selection process. This automation not only improves work efficiency but also reduces errors caused by human intervention. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0049] Figure 1 A flowchart of a field-of-view depth-of-field extension method based on sparse scanning of an optical field microscope provided in an embodiment of the present invention;

[0050] Figure 2 This is a schematic diagram of three-dimensional sparse scanning, reconstruction, and fusion provided in an embodiment of the present invention;

[0051] Figure 3 This is a schematic diagram of the two-dimensional scanning step size and interval provided in an embodiment of the present invention;

[0052] Figure 4 This is a schematic diagram of three-dimensional volume fusion reconstruction along the X / Y / Z axes of adjacent fields of view provided in an embodiment of the present invention. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] Light field microscopy is a revolutionary 3D imaging technique. Its core lies in capturing four-dimensional light field information (light position + direction) of a scene in a single exposure, enabling 3D volume reconstruction without physical scanning. A microlens array (MLA) is placed in front of the imaging sensor (such as CMOS / CCD) of a traditional microscope. Each microlens separates light rays from different directions on the sample into different pixel regions on the sensor, forming a series of multi-view sub-images. By recording the position and angle information of the light rays and combining it with back-projection algorithms or deep learning models, the 3D spatial distribution of the sample can be determined.

[0055] The field-of-view depth-of-field extension method based on sparse scanning of light field microscopy provided in this invention allows light field microscopy to directly reconstruct sample structures at different depths using angular information. A single image can cover a three-dimensional volume of hundreds of micrometers, significantly extending the effective depth of field. When the sample size exceeds the field of view of a single frame, only sparse XYZ scanning is required (conventional microscopy requires dense scanning). Combined with three-dimensional registration and fusion algorithms, a large field of view, high depth of field, and high resolution imaging can be achieved.

[0056] like Figure 1 The flowchart shown is a method for extending the field of view depth based on sparse scanning in light field microscopy, which mainly includes the following steps:

[0057] S1: The sample is sparsely scanned along the XYZ axes using a microlens array light field imaging system, so that the overlap rate between adjacent fields of view is lower than a preset value, and multi-field two-dimensional raw light field data is acquired.

[0058] In one embodiment, the sparse 3D scanning acquisition steps in S1 are as follows:

[0059] The sample is fixed on the stage to prevent relative movement between the sample and the stage during the three-dimensional movement of the stage;

[0060] Assume the size of the original two-dimensional light field image is H. W sets the physical size step sizes X, Y, and Z for sparse 3D scanning, ensuring that the overlap rate between adjacent fields of view is less than 60%. In this embodiment, the overlap rate between adjacent fields of view can be 40% to 60%.

[0061] Keeping the sample stationary, sparse displacement is achieved only through focusing on the stage or optical axis, and multi-field two-dimensional raw light field data is acquired through sparse scanning.

[0062] S2: Perform pixel rearrangement and deconvolution 3D reconstruction on the original 2D light field image of each field of view to obtain the reconstructed 3D volume of each field of view.

[0063] In one embodiment, S2 includes the following steps:

[0064] S21: Rearrange the pixels of the original two-dimensional light field image for each field of view to obtain the first... i Four-dimensional phase space light field data for each field of view It characterizes the spatial light intensity distribution under multiple viewpoints, including the viewpoint coordinates of a single microlens and the spatial coordinates of the microlens array light field imaging system;

[0065] S22: Perform phase space deconvolution on the four-dimensional phase space light field data and the system point spread function (PSF) to obtain the reconstructed three-dimensional volume for each field of view.

[0066] In this embodiment, S21 includes the following steps:

[0067] S211: Fix the viewpoint coordinates, obtain the pixel values ​​of the viewpoint coordinates under different spatial coordinates, and form a spatial coordinate sub-image of the viewpoint coordinates.

[0068] S212: The spatial coordinate sub-images of all viewpoint coordinates are arranged in sequence, together forming the four-dimensional phase space light field data of the two-dimensional original light field image, with a size of [missing information]. u v h w ;

[0069] ;

[0070] ;

[0071] Among them, the vertical and horizontal dimensions of the two-dimensional light field map are respectively u h and v w , h and w These represent the longitudinal and transverse spatial coordinates in the microlens array optical field imaging system, respectively. u and v These represent the longitudinal and transverse angular coordinates of a single microlens, respectively.

[0072] In this embodiment, S22 includes the following steps:

[0073] The Richardson-Lucy deconvolution algorithm was used to process the four-dimensional phase space light field data. Phase space deconvolution is performed with the system point spread function (PSF) to obtain the reconstructed 3D volume for each view. :

[0074] ;

[0075] In the formula, z Represents the reconstruction of a three-dimensional body z Axial coordinates k This indicates the number of iterations in the deconvolution algorithm. This represents the convolution operation. for PSF conjugate convolution, h and w These represent the longitudinal and transverse spatial coordinates in the microlens array optical field imaging system, respectively. u and v These represent the longitudinal and transverse angular coordinates of a single microlens, respectively.

[0076] S3: Calculate the theoretical overlap region width along the XYZ axes based on the sparse scanning step size, and perform consistency calibration on the overlap region along the XYZ axes of adjacent fields of view.

[0077] In one embodiment, S3 includes the following steps:

[0078] The theoretical overlap region width along the XYZ axes is calculated based on the sparse scan step size, and the overlap region along the XYZ axes of adjacent fields of view is calibrated for consistency with the goal of minimizing the similarity of the overlap region of the reconstructed 3D volume for each pair of adjacent fields of view.

[0079] In this embodiment, the pixel steps corresponding to the spatial steps X, Y, and Z of the sparse 3D sampling are calculated. , , for:

[0080] ;

[0081] ;

[0082] ;

[0083] In the formula, pix This represents the physical size of a sensor pixel in a microlens array light field imaging system. M The optical magnification of the microlens array light field imaging system. dz The Z-axis spacing for three-dimensional tomography;

[0084] The theoretical overlap regions widths along the XYZ axes of sparse 3D scanning are derived as follows:

[0085] ;

[0086] ;

[0087] ;

[0088] In the formula,W The X-axis dimension of the original two-dimensional light field image. H is the Y-axis dimension of the original two-dimensional light field image.

[0089] like Figure 2 As shown, the gray area is XYZ(2 1 2) Sparse scan locations, with dashed lines representing the reconstructed 3D volume. For example... Figure 3 As shown, the theoretical overlap region width is illustrated.

[0090] In one embodiment, S3:

[0091] Registration windows are established along the three axes, and the widths of the overlapping regions in the three directions are calibrated to automatically estimate the optimal fusion offset. Specific steps include: reconstructing a 3D volume for each pair of adjacent views (…). A dynamic search window is defined within a specified range of the theoretical overlap area along the XYZ axes, and all offsets within the search window are traversed. d and perform the corresponding offset. d The result after the operation ( The new theory calculates the similarity of overlapping regions and selects the offset with the highest similarity score as the optimal fusion offset.

[0092] The offset range of the dynamic search window is determined by the theoretical overlap region width:

[0093] .

[0094] For example, if Qverlap If the value is 50, then d The value range is [-5, 5], traversing d =[-5,-4,-3,-2,-1,0,1,2,3,4,5]

[0095] In this embodiment, the multiplicative correlation method can be used to calculate the similarity of overlapping regions, taking the calibration of overlapping regions along the X-axis as an example:

[0096] .

[0097] The structural similarity method can also be used to calculate the similarity of overlapping regions. Taking the calibration of overlapping regions along the X-axis as an example:

[0098] .

[0099] Traverse all offsets within the search window d Select the offset with the highest similarity score. d’ As the optimal fusion offset:

[0100] The total offset during the search traversal is updated using the following operation:

[0101] .

[0102] Similarly, the optimal fusion offset in the three-axis directions is obtained. , , ;

[0103] S4: Recursively fuse the calibrated reconstructed 3D volume along the XYZ axes to obtain a full-field-of-view, full-depth 3D volume image.

[0104] In one embodiment, S4 includes the following steps:

[0105] X-axis fusion: Recursively fuse the reconstructed 3D volumes along each row of the X-axis to obtain multiple X-axis 3D volumes; the initial left-side reconstructed 3D volume... Reconstructing the three-dimensional volume on the adjacent right side Perform a smooth fusion, and use the fusion result as the left side of the reconstructed 3D volume for the next fusion round. Then, take the reconstructed 3D volume on the right and merge it until the entire row is merged, resulting in multiple X-axis 3D volumes;

[0106] ;

[0107] Y-axis fusion: Recursively fuse each layer of fused X-axis 3D volume along the Y-axis to obtain multiple 2D planar 3D volumes;

[0108] Z-axis fusion: Recursively fuse the two-dimensional planar three-dimensional volumes of each layer along the Z-axis to obtain a three-dimensional volume image with full field of view and full depth.

[0109] It should be noted that the fusion order of the XYZ axes provided in the embodiments is not limited to the fusion order of the XYZ axes. The fusion of the reconstructed three-dimensional volume can be performed on any axis first to obtain the final three-dimensional volume image with full field of view and full depth.

[0110] In this embodiment, the fusion process can adopt a smooth fusion method, and the specific steps include: using a transition curve based on the sigmoid function in the overlapping area to achieve a smooth and gradual fusion.

[0111] ;

[0112] In the formula, p These are pixel coordinates, with values ​​ranging from the width of the corresponding overlapping region. This embodiment uses sigmoid-based smooth blending to eliminate blending seams. Compared to traditional linear blending methods, this approach more naturally transitions the boundaries between adjacent reconstructed 3D volumes, eliminating obvious blending seams and improving the overall visual effect of the final 3D model. For example... Figure 4 As shown, the overlapping areas of adjacent blocks are multiplied by two opposite sigmoid functions as coefficients, and the sums are used to replace the original overlapping areas to achieve smooth fusion.

[0113] In this embodiment, when the recursive fusion step is performed on the reconstructed 3D volume after adjacent field-of-view calibration, the overlapping region after adjacent field-of-view calibration is replaced with "smooth". Taking the overlapping region along the X-axis as an example:

[0114] .

[0115] The overlapping areas along the Y and Z axes are also replaced with "smooth".

[0116] The above provides a detailed description of the field-of-view depth-of-field extension method based on sparse scanning of light field microscope provided by the present invention. Specific examples are used in this embodiment to illustrate the principle and implementation of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation and application scope based on the idea of ​​the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

[0117] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined in these embodiments may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for expanding the depth of field based on sparse scanning in light field microscopy, characterized in that, Includes the following steps: S1: Use a microlens array light field imaging system to perform sparse scanning of the sample along the XYZ axes, so that the overlap rate between adjacent fields of view is lower than a preset value, and acquire multi-field two-dimensional raw light field data. S2: Perform pixel rearrangement and deconvolution 3D reconstruction on the original 2D light field image of each field of view to obtain the reconstructed 3D volume of each field of view; S3: Calculate the theoretical overlap region width along the XYZ axes based on the sparse scanning step size, and perform consistency calibration on the overlap region along the XYZ axes of adjacent fields of view. Calculate the pixel steps corresponding to the spatial steps X, Y, and Z of sparse 3D sampling. , , for: ； ； ； In the formula, pix This represents the physical size of a sensor pixel in a microlens array light field imaging system. M The optical magnification of the microlens array light field imaging system. dz The Z-axis spacing for three-dimensional tomography; The theoretical overlap regions widths along the XYZ axes of sparse 3D scanning are derived as follows: ； In the formula, W The X-axis dimension of the original two-dimensional light field image. H The Y-axis dimension of the original two-dimensional light field image; Registration windows are established in the three axes, and the width of the overlapping area in the three directions is calibrated to automatically estimate the optimal fusion offset; the specific steps include: reconstructing a 3D volume for each pair of adjacent views ( A dynamic search window is defined within a specified range of the theoretical overlap area along the XYZ axes, and all offsets within the search window are traversed. d and perform the corresponding offset. d The result after the operation ( The new theory calculates the similarity of overlapping regions and selects the offset with the highest similarity score as the optimal fusion offset. S4: Recursively fuse the calibrated reconstructed 3D volume along the XYZ axes to obtain a full-field-of-view, full-depth 3D volume image.

2. The method for expanding the depth of field based on sparse scanning in a light field microscope according to claim 1, characterized in that, In S1, by setting the physical size step size of sparse three-dimensional scanning, the overlap rate between adjacent fields of view is less than 60%.

3. The method for expanding the depth of field based on sparse scanning in a light field microscope according to claim 1, characterized in that, S2 includes the following steps: S21: Rearrange the pixels of the original two-dimensional light field image of each field of view to obtain the four-dimensional phase space light field data of each field of view, including the angular coordinates of a single microlens and the spatial coordinates of the microlens array light field imaging system. S22: Perform phase space deconvolution on the four-dimensional phase space light field data and the system point spread function (PSF) to obtain the reconstructed three-dimensional volume for each field of view.

4. The method for expanding the depth of field based on sparse scanning in a light field microscope according to claim 3, characterized in that, S21 includes the following steps: S211: Fix the viewpoint coordinates, obtain the pixel values ​​of the viewpoint coordinates under different spatial coordinates, and form a spatial coordinate sub-image of the viewpoint coordinates. S212: The spatial coordinate sub-images of all viewpoint coordinates are arranged in sequence, together forming the four-dimensional phase space light field data of the two-dimensional original light field image, with a size of [missing information]. u v h w The vertical and horizontal dimensions of the two-dimensional light field map are respectively... u h and v w , h and w These represent the longitudinal and transverse spatial coordinates in the microlens array optical field imaging system, respectively. u and v These represent the longitudinal and transverse angular coordinates of a single microlens, respectively.

5. The method for expanding the depth of field based on sparse scanning in a light field microscope according to claim 3, characterized in that, S22 includes the following steps: The Richardson-Lucy deconvolution algorithm was used to process the four-dimensional phase space light field data. Phase space deconvolution is performed with the system point spread function (PSF) to obtain the reconstructed 3D volume for each view. : ； In the formula, z Represents the reconstruction of a three-dimensional body z Axial coordinates k This indicates the number of iterations in the deconvolution algorithm. This represents the convolution operation. for PSF conjugate convolution, h and w These represent the longitudinal and transverse spatial coordinates in the microlens array optical field imaging system, respectively. u and v These represent the longitudinal and transverse angular coordinates of a single microlens, respectively.

6. The method for expanding the depth of field based on sparse scanning in a light field microscope according to claim 1, characterized in that, S3 includes the following steps: The theoretical overlap region width along the XYZ axes is calculated based on the sparse scan step size, and the overlap region along the XYZ axes of adjacent fields of view is calibrated for consistency with the goal of minimizing the similarity of the overlap region of the reconstructed 3D volume for each pair of adjacent fields of view.

7. The method for expanding the depth of field based on sparse scanning in a light field microscope according to claim 1, characterized in that, In S3: the similarity of overlapping regions is calculated using the multiplicative correlation method or the structural similarity method.

8. The method for expanding the depth of field based on sparse scanning in a light field microscope according to claim 1, characterized in that, S4 includes the following steps: The reconstructed 3D volumes calibrated along each row of the X-axis are recursively fused to obtain multiple X-axis 3D volumes. Recursively fuse each layer of the already fused X-axis 3D volume along the Y-axis to obtain multiple 2D planar 3D volumes; The two-dimensional planar three-dimensional volumes of each layer are recursively fused along the Z-axis to obtain the full field of view and full depth three-dimensional volume image.

Images