High dynamic structured illumination topography measurement method and device based on pixel-by-pixel regulation

Abstract

This invention belongs to the technical field of surface morphology measurement, and discloses a method and apparatus for measuring morphology based on pixel-by-pixel high dynamic structured illumination. The method includes: S1: calibrating the DMD and camera to obtain the grayscale response relationship and coordinate mapping relationship between the DMD and the camera; S2: correcting the phase-shifting fringes generated by the DMD using the grayscale response relationship, coordinate mapping relationship, and optical transfer function; S3: projecting the corrected phase-shifting fringes onto the sample surface and acquiring a phase-shifted structured illumination image by the camera; S4: performing slicing imaging on the phase-shifted structured illumination image to extract the three-dimensional morphology of the sample surface. This application can improve the imaging quality of the camera pixel by pixel, and then obtain the three-dimensional morphology of the sample surface by optical slicing multiple high-quality structured illumination images.

Description

Technical Field

[0001] This invention belongs to the technical field of surface morphology measurement, and more specifically, relates to a method and apparatus for measuring sample surface morphology based on pixel-by-pixel control. Background Technology

[0002] Microstructured surface morphology is a crucial geometric feature of manufactured products and scientific research samples. Its measurement, analysis, and evaluation are essential for ensuring the functional quality characteristics of surfaces. Structured light microscopy, based on the principle of wide-field microscopic imaging, uses structured light to modulate the measured surface or structural information, removing defocus interference and combining it with vertical scanning to obtain an optical tomographic image. Then, peak extraction is performed on the tomographic response curve using peak localization calculations to achieve three-dimensional measurement. This method is non-contact, highly efficient, and highly accurate, and can be applied not only to reflective surfaces but also to the morphology measurement of scattering surfaces.

[0003] However, for samples with significant differences in surface reflectivity, the imaging dynamic range of structured illumination micro-measurement technology is limited. Areas with high surface reflectivity are prone to overexposure, resulting in loss of sample information, while images acquired from low reflectivity areas have low signal-to-noise ratios and poor reconstruction quality. Therefore, these techniques may fail to meet the requirements for precise measurements. Figure 1 As shown in the paper, "A Micro-measurement Method Based on Structured Light Illumination Using Multiple Exposure Technology," for samples with significant differences in surface reflectivity, after projecting a structured light pattern onto the sample surface, at least three sets of images need to be acquired. Each set of images uses a different exposure time, with a recommended exposure ratio of 0.25:0.5:1 to target various reflectivity regions on the sample surface. Then, the multiple sets of structured light images acquired by the camera at different exposure times are fused using a specific algorithm to synthesize a high dynamic range (HMR) image. Finally, an optical slicing method is used to extract a tomographic image from the HMR image. Since the HMR image is composed of structured light patterns fused from different exposure times, it has a high signal-to-noise ratio for different reflectivity regions of the sample surface, thereby improving the quality of the tomographic response signal extracted from the tomographic image. Then, a peak localization algorithm is used to determine the focus state in the tomographic response signal to achieve reconstruction.

[0004] The aforementioned method improves the dynamic range of structured light micro-measurement methods, enhances 3D reconstruction quality, and requires no additional hardware costs. However, this method requires projecting at least three sets of structured light patterns during the measurement process, which is time-consuming and cannot meet the needs of rapid measurement. Furthermore, image fusion introduces additional errors, resulting in limited measurement accuracy. Summary of the Invention

[0005] To address the above-mentioned deficiencies or improvement needs of existing technologies, this invention provides a high dynamic structure illumination morphology measurement method and apparatus based on pixel-by-pixel control. This method can improve the imaging quality of the camera pixel by pixel for samples with complex surface reflectivity, thereby avoiding image overexposure and low signal-to-noise ratio caused by the low dynamic range of the camera. Then, optical slicing is performed on the high-quality image to quickly obtain the three-dimensional morphology of the sample surface.

[0006] To achieve the above objectives, according to one aspect of the present invention, a method for measuring three-dimensional topography based on pixel-by-pixel controlled high dynamic structure illumination is provided, comprising: S1: calibrating the DMD and camera to obtain the grayscale response relationship and coordinate mapping relationship between the DMD and the camera; S2: using the grayscale response relationship, coordinate mapping relationship, and optical transfer function to correct the phase-shifting fringes generated by the DMD; S3: projecting the corrected phase-shifting fringes onto the sample surface and acquiring a phase-shifting structure illumination image by the camera; S4: obtaining a slice image from the phase-shifting structure illumination image, and further extracting the three-dimensional topography of the sample surface.

[0007] In a further preferred embodiment, step S2 specifically includes: S21: obtaining the light intensity of each pixel in the phase-shifting fringe; S22: convolving the light intensity of each pixel in the phase-shifting fringe pattern with the optical transfer function to obtain the light intensity of each pixel acquired by the camera; S23: performing coordinate transformation on the light intensity of each pixel acquired by the camera using the coordinate mapping relationship, and then correcting it using the amplitude and grayscale response relationship of the optical transfer function to obtain the corrected phase-shifting fringe.

[0008] In a further preferred embodiment, the light intensity of each pixel in the phase-shifting stripes in step S21 is:

[0009]

[0010] in, Let I be the projected light intensity of the pixel at coordinates (s, t) on the DMD, I0 be the background light intensity, and d be the stripe modulation depth. The fringe phase is represented by n, where n is the phase shift order, n = 0, 1, 2, ..., N-1, and N is the number of phase shift steps.

[0011] The light intensity of each pixel captured by the camera in step S22 is:

[0012]

[0013] in, Let α(u,v) be the light intensity of the pixel at coordinates (u,v) captured by the camera, MTF be the amplitude of the optical transfer function, α(u,v) be the grayscale conversion coefficient in the camera coordinate system, and β(u,v) be the grayscale conversion parameter in the camera coordinate system.

[0014] In a further preferred embodiment, the grayscale conversion coefficients and grayscale conversion parameters in the camera coordinate system are obtained in the following way: the grayscale conversion coefficients and grayscale conversion parameters in the DMD coordinate system are obtained from the grayscale response relationship between the DMD and the camera; the grayscale conversion coefficients and grayscale conversion parameters in the DMD coordinate system are converted into grayscale conversion coefficients and grayscale conversion parameters in the camera coordinate system through coordinate mapping relationship.

[0015] In a further optimized scheme, the grayscale response relationship between the DMD and the camera is as follows:

[0016] I c (u, v) = α(s, t) • I p (s,t)+β(s,t)

[0017] Among them, I c (u, v) represents the light intensity captured by the camera, I p (s,t) represents the illumination intensity of the DMD, α(s,t) represents the grayscale conversion coefficient in the DMD coordinate system, and β(s,t) represents the grayscale conversion parameter in the DMD coordinate system.

[0018] In a further preferred embodiment, the grayscale response relationship between the DMD and the camera is obtained in step S1 as follows: multiple uniform grayscale images with a preset grayscale interval are projected onto the sample; multiple corresponding grayscale images are acquired sequentially using a camera; the light intensity of the grayscale images acquired by the camera and the light intensity of the projected grayscale images are fitted to obtain the grayscale conversion coefficient and grayscale conversion parameter; the grayscale conversion coefficient and grayscale conversion parameter are used to construct a linear relationship between the light intensity acquired by the camera and the light intensity of the DMD illumination, i.e., the grayscale response relationship.

[0019] In a further preferred embodiment, the light intensity of each pixel in the corrected phase-shifted fringes in step S2 for:

[0020]

[0021] Where I0 is the background light intensity and d is the stripe modulation depth. α is the fringe phase, n is the phase shift order, n = 0, 1, 2, ..., N-1, and N is the number of phase shift steps; α(s,t) is the grayscale conversion coefficient in the DMD coordinate system, β(s,t) is the grayscale conversion parameter in the DMD coordinate system, and MTF is the amplitude of the optical transfer function.

[0022] In a further preferred embodiment, step S3 specifically involves: adjusting the distance between the objective lens and the sample according to a preset step distance, projecting multiple corrected phase-shift fringes at each distance, thereby obtaining multiple phase-shift structure illumination images; step S4 specifically involves: performing optical slicing on the multiple phase-shift structure illumination patterns to obtain the three-dimensional morphology of the sample surface.

[0023] The second aspect of this application provides an apparatus for implementing the above-mentioned high dynamic structure illumination topography measurement method based on pixel-by-pixel control, comprising a camera optical path, a DMD optical path, and a light source, wherein: the camera optical path is provided with a sample stage, an objective lens, a piezoelectric ceramic, a beam splitter, a first lens, and a camera in sequence; the DMD optical path is provided with a DMD and a second lens; after the light source illuminates the DMD, it is reflected by the DMD and passes through the second lens into the beam splitter.

[0024] A third aspect of this application provides a high dynamic structure illumination morphology measurement system based on pixel-by-pixel control, comprising: a calibration module for calibrating the DMD and camera to obtain the grayscale response relationship and coordinate mapping relationship between the DMD and the camera; a correction module for correcting the phase-shift fringes generated by the DMD using the grayscale response relationship, coordinate mapping relationship, and optical transfer function; a projection module for projecting the corrected phase-shift fringes onto the sample surface and acquiring the phase-shift structure illumination pattern by the camera; and a modeling module for slicing the phase-shift structure illumination pattern to obtain the sample surface morphology.

[0025] In summary, compared with the prior art, the high dynamic structure illumination morphology measurement method and apparatus based on pixel-by-pixel control provided by the present invention have the following advantages:

[0026] 1. This application addresses a structured illumination measurement system. By utilizing the grayscale response relationship, coordinate mapping relationship, and optical transfer function of the DMD and camera, phase-shifted fringes are corrected. Compared to the original pattern, the corrected fringe pattern projected by the DMD has the optimal illumination intensity, avoiding information loss due to overexposure and low signal-to-noise ratio. This enhances the surface features and details of the sample, improves the imaging dynamic range of the system, and improves the quality of the sample's three-dimensional morphology reconstruction.

[0027] 2. Compared with other high dynamic range structure lighting measurement techniques, the method described in this application does not require the projection of additional auxiliary patterns, which reduces computation time and improves measurement speed.

[0028] 3. The method described in this application can calculate the optimal illumination intensity of the sample during the calibration process, thereby calculating the most suitable stripe pattern to improve the image quality acquired by the camera. It can adaptively improve the reconstruction quality for a variety of samples and has universality. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the conventional surface morphology measurement principle in existing technologies;

[0030] Figure 2 This is a flowchart illustrating the steps of the high dynamic structured illumination three-dimensional topography measurement method based on pixel-by-pixel control in this application;

[0031] Figure 3 This is a schematic diagram of the three-dimensional topography measurement method based on pixel-by-pixel high dynamic structured illumination according to this application;

[0032] Figure 4 The three-dimensional topography is constructed based on the high dynamic structured illumination three-dimensional topography measurement method based on pixel-by-pixel control in this application;

[0033] Figure 5 It is an apparatus for implementing the high dynamic structure illumination three-dimensional topography measurement method based on pixel-by-pixel control as described in this application. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0035] The first aspect of this application provides a method for measuring three-dimensional topography based on pixel-by-pixel controlled high dynamic structured illumination, such as... Figure 2 and Figure 3 As shown, the method includes the following steps S1 to S4.

[0036] S1: Calibrate the DMD and camera to obtain the grayscale response relationship and coordinate mapping relationship between the DMD and the camera.

[0037] Due to the influence of sample reflectivity and energy loss during light transmission, light intensity attenuates as it travels from the Digital Micromirror Device (DMD) to the camera. Ignoring minor changes in ambient stray light and reflectivity during measurement, the relationship between the DMD and the camera's grayscale response is as follows:

[0038] I c (u, v) = α(s, t)·I p (s,t)+β(s,t)

[0039] Among them, I c (u, v) represents the light intensity captured by the camera, I p(s,t) represents the illumination intensity of the DMD, and α(s,t) and β(s,t) are constant coefficients related to camera parameters, ambient stray light, and sample reflectivity. Specifically, α(s,t) is the grayscale conversion coefficient in the DMD coordinate system, and β(s,t) is the grayscale conversion parameter in the DMD coordinate system.

[0040] In step S1, the grayscale response relationship between the DMD and the camera is obtained using the following method:

[0041] S11: Project multiple uniform grayscale images with preset grayscale intervals onto the sample;

[0042] S12: Multiple corresponding grayscale images are acquired sequentially using a camera;

[0043] S13: Fit the light intensity of the grayscale image captured by the camera and the light intensity of the projected grayscale image to obtain the grayscale conversion coefficient and grayscale conversion parameter.

[0044] S14: The grayscale conversion coefficient and grayscale conversion parameters are used to construct a linear relationship between the light intensity acquired by the camera and the light intensity of the illumination by the DMD, that is, the grayscale response relationship.

[0045] The coordinate mapping relationship between the DMD and the camera is obtained using the checkerboard calibration method. This coordinate mapping relationship is as follows:

[0046] P cam (u, v) = T·P DMD (s,t)

[0047] Among them, P cam (u, v) are the camera coordinates, P DMD (s, t) are the DMD coordinates, and T is the coordinate transformation matrix.

[0048] S2: The phase-shifted fringes generated by the DMD are corrected using the gray-scale response relationship, coordinate mapping relationship, and optical transfer function.

[0049] For samples with complex surface reflectivity, it is difficult to reconstruct a highly complete sample surface under a single background illumination intensity. To obtain high signal-to-noise ratio, unsaturated, high-quality HDR images, a pixel-by-pixel encoding method is employed. This method adaptively adjusts the illumination intensity based on the reflectivity distribution of the measured surface. A phase-shifting fringe pattern is used as the illumination pattern projected onto the sample.

[0050] Step S2 specifically includes:

[0051] S21: Obtain the light intensity of each pixel in the phase-shifting stripe.

[0052] The light intensity of each pixel in the phase-shifting stripe is:

[0053]

[0054] in, Let I be the projected light intensity of the pixel at coordinates (s, t) on the DMD, I0 be the background light intensity, and d be the stripe modulation depth. Let n be the fringe phase, n be the phase shift order, n = 0, 1, 2, ..., N-1, and N be the number of phase shift steps.

[0055] S22: Convolve the light intensity of each pixel in the phase-shifted fringe pattern with the optical transfer function to obtain the light intensity of each pixel captured by the camera.

[0056]

[0057] Where OTF stands for Optical Transfer Function. The light intensity captured by the camera, This refers to the light intensity projected by the DMD.

[0058] The light intensity of each pixel captured by the camera is:

[0059]

[0060] in, The light intensity of the pixel at coordinates (u, v) captured by the camera has an intensity range of I. c (u)∈[β,α.I o [1+MTF·d)+β], where MTF is the amplitude of the optical transfer function, α(u,v) is the grayscale conversion coefficient in the camera coordinate system, and β(u,v) is the grayscale conversion parameter in the camera coordinate system.

[0061] In a further preferred embodiment, the grayscale conversion coefficient and grayscale conversion parameters in the camera coordinate system are obtained in the following way:

[0062] Step 1: Obtain the grayscale conversion coefficients and grayscale conversion parameters in the DMD coordinate system from the grayscale response relationship between the DMD and the camera;

[0063] Step 2: Convert the grayscale conversion coefficients and grayscale conversion parameters in the DMD coordinate system to grayscale conversion coefficients and grayscale conversion parameters in the camera coordinate system through coordinate mapping relationships.

[0064] S23: The coordinates of the light intensity of each pixel acquired by the camera are transformed using the coordinate mapping relationship, and then the amplitude and grayscale response relationship of the optical transfer function are used to correct the phase shift fringes to obtain the corrected phase shift fringes.

[0065] The light intensity of each pixel in the corrected phase-shifted fringes for:

[0066]

[0067] Where I0 is the background light intensity and d is the stripe modulation depth. Let n be the fringe phase, n be the phase shift order (n = 0, 1, 2, ..., N-1), and N be the number of phase shift steps; α(s, t) be the grayscale conversion coefficient in the DMD coordinate system, β(s, t) be the grayscale conversion parameter in the DMD coordinate system, and MTF be the amplitude of the optical transfer function. The intensity range of the fringe pattern acquired by the camera is [0, I...]. o [1+d] shows that the modulation depth of the acquired stripe pattern is improved, thereby avoiding overexposure and enhancing the signal-to-noise ratio of the pattern.

[0068] S3: The corrected phase-shift fringes are projected onto the sample surface and the phase-shift structure illumination image is acquired by the camera. According to the preset step size, the distance between the objective lens and the sample is adjusted, and multiple corrected phase-shift fringes are projected at each distance to obtain multiple phase-shift structure illumination images.

[0069] S4: Obtain slice imaging from the phase-shift structure illumination images, and further extract the three-dimensional morphology of the sample surface. Optical slicing is performed on the multiple phase-shift structure illumination images to obtain the three-dimensional morphology of the sample surface, such as... Figure 4 As shown.

[0070] A second aspect of this application provides an apparatus for the aforementioned high dynamic structure illumination topography measurement method based on pixel-by-pixel control, such as... Figure 5 As shown, it includes the camera optical path, the DMD optical path, and the light source.

[0071] The camera optical path includes, in sequence, a sample stage, an objective lens, a piezoelectric ceramic, a beam splitter, a first lens, and a camera.

[0072] The DMD optical path includes a DMD and a second lens.

[0073] After the light source shines on the DMD, it is reflected by the DMD and passes through the second lens into the beam splitter.

[0074] as follows Figure 5 As shown, it consists of a DMD (LightCrafter 6500), a camera (acA1920-155um, Basler), a piezoelectric ceramic (P-721, Physik Instrumente), an LED light source (center wavelength 518nm), a microscope objective (10×, 0.3 numerical aperture, Nikon Inc.), and related lenses and mounting brackets.

[0075] First, coordinate mapping calibration is performed during system calibration. A pre-generated checkerboard pattern is input into the DMD. At this point, a plane mirror is placed under the microscope objective and adjusted to a clear position. The camera captures a clear checkerboard pattern. Then, using a corner detection algorithm, the coordinate positions of each corner point on the checkerboard are obtained. Based on the coordinate positions P in the input checkerboard image... DMD = [s, t] and coordinates P in the acquired image cam =[u,v] T The location, given the following linear projection transformation:

[0076] η·P cam =H·P DMD

[0077] Where η≠0 is the scaling factor, H is the mapping matrix, and P cam and P DMD These are the homogeneous coordinates of the corner points in the input chessboard image and the acquired image, respectively. Since the projective matrix H is unique for a given input parameter, the above transformation can be further simplified to:

[0078] P cam (u, v) = T·P DMD (s,t)

[0079] Where T represents the transformation matrix from DMD to camera coordinate system. The transformation matrix can be obtained by substituting the camera image corner coordinates obtained by the corner detection algorithm above and the preset checkerboard corner coordinates into the above formula.

[0080] Next, grayscale mapping calibration is performed during system calibration. The sample to be tested is placed under the objective lens and adjusted to a clear position. Twenty-five uniform grayscale images are generated using a computer, each with a grayscale value of 10*x (x = 1, 2, ..., 25). These 25 uniform grayscale images are sequentially input into the DMD, projected onto the sample surface, and captured by a camera. The α and β parameters at each point on the sample surface are calculated using the grayscale response calibration algorithm mentioned above.

[0081] Next, an adaptive lighting stripe pattern is generated. Based on coordinate mapping calibration, grayscale response calibration, and the modified structured lighting stripe generation algorithm, the lighting pattern is adjusted pixel by pixel to generate 5 modified stripe lighting patterns (this invention uses a 5-step phase shift method, so 5 stripe patterns need to be generated).

[0082] Finally, three-dimensional reconstruction was performed: the piezoelectric ceramic step size was set to 50 nm, with a total displacement of 20 μm. At each scanning position, five corrected illumination images were sequentially projected onto the sample surface and acquired by the camera. After image acquisition, the tomographic response was calculated from the acquired images according to the optical slicing algorithm. Then, Gaussian fitting was used to fit the tomographic response curves at each point, and the peak positions were extracted to reconstruct the sample morphology.

[0083] This application further provides a high dynamic structure illumination topography measurement system based on pixel-by-pixel control, comprising:

[0084] Calibration module: used to calibrate the DMD and camera to obtain the grayscale response relationship and coordinate mapping relationship between the DMD and the camera;

[0085] Correction module: used to correct the phase-shifted fringes generated by the DMD using the gray-scale response relationship, coordinate mapping relationship, and optical transfer function;

[0086] Projection module: used to project the corrected phase-shift fringes onto the sample surface and acquire the phase-shift structure illumination image by a camera;

[0087] Modeling module: used to extract the surface morphology of the sample by slicing the phase-shifted structure illumination image.

[0088] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A high dynamic structured illumination topography measurement method based on pixel-by-pixel regulation, characterized in that, include: S1: Calibrate the DMD and camera to obtain the grayscale response relationship and coordinate mapping relationship between the DMD and the camera; S2: The phase-shifted fringes generated by the DMD are corrected using the gray-scale response relationship, coordinate mapping relationship, and optical transfer function. S3: The corrected phase-shift fringes are projected onto the sample surface and the phase-shift structure illumination image is acquired by a camera; S4: The three-dimensional morphology of the sample surface is obtained by slicing the phase-shifted structure illumination image; In step S1, the grayscale response relationship between the DMD and the camera is obtained using the following method: Multiple uniform grayscale images with preset grayscale intervals are projected onto the sample; Multiple corresponding grayscale images are acquired sequentially using a camera; The grayscale conversion coefficient and grayscale conversion parameters are obtained by fitting the light intensity of the grayscale image captured by the camera and the light intensity of the projected grayscale image. The grayscale conversion coefficient and grayscale conversion parameters are used to construct a linear relationship between the light intensity acquired by the camera and the light intensity of the illumination by the DMD, which is also known as the grayscale response relationship.

2. The high dynamic structure illumination morphology measurement method according to claim 1, characterized in that, Step S2 specifically includes: S21: Obtain the light intensity of each pixel in the phase-shifting stripe; S22: Convolve the light intensity of each pixel in the phase-shifted fringe pattern with the optical transfer function to obtain the light intensity of each pixel captured by the camera; S23: The coordinates of the light intensity of each pixel acquired by the camera are transformed using the coordinate mapping relationship, and then the amplitude and grayscale response relationship of the optical transfer function are used to correct the phase shift fringes to obtain the corrected phase shift fringes.

3. The high dynamic structure illumination morphology measurement method according to claim 2, characterized in that, The light intensity of each pixel in the phase-shifting stripes described in step S21 is: in, Let be the projected light intensity of the pixel at coordinates (s,t) on the DMD. I 0 represents the background light intensity. d For stripe modulation depth, For stripe phase, n The phase shift order, N is the number of phase shift steps; The light intensity of each pixel captured by the camera in step S22 is: in, The coordinates collected by the camera are ( u , v The light intensity of the pixel at position ( ), where MTF is the amplitude of the optical transfer function. This refers to the grayscale conversion factor in the camera coordinate system. These are the grayscale conversion parameters in the camera coordinate system.

4. The high dynamic structure illumination morphology measurement method according to claim 3, characterized in that, The grayscale conversion coefficients and grayscale conversion parameters in the camera coordinate system are obtained in the following way: The grayscale conversion coefficients and grayscale conversion parameters in the DMD coordinate system are obtained from the grayscale response relationship between the DMD and the camera. The grayscale conversion coefficients and grayscale conversion parameters in the DMD coordinate system are converted into grayscale conversion coefficients and grayscale conversion parameters in the camera coordinate system through coordinate mapping.

5. The high dynamic structure illumination morphology measurement method according to claim 1 or 4, characterized in that, The relationship between DMD and camera grayscale response is as follows: in, To collect light intensity for the camera. For DMD illumination intensity, This refers to the grayscale conversion factor in the DMD coordinate system. These are the grayscale conversion parameters in the DMD coordinate system.

6. The high dynamic structure illumination morphology measurement method according to claim 1, characterized in that, The light intensity of each pixel in the corrected phase-shifted fringes in step S2 for: in, I 0 represents the background light intensity. d For stripe modulation depth, For stripe phase, n The phase shift order, N is the number of phase shift steps; This refers to the grayscale conversion factor in the DMD coordinate system. These are the grayscale conversion parameters in the DMD coordinate system. This represents the amplitude of the optical transfer function.

7. The high dynamic structure illumination morphology measurement method according to claim 1, characterized in that, Step S3 is as follows: According to the preset step distance, the distance between the objective lens and the sample is adjusted, and multiple corrected phase-shift fringes are projected at each distance to obtain multiple phase-shift structure illumination images. Step S4 is as follows: The three-dimensional morphology of the sample surface is obtained by slicing and extracting the multiple phase-shifting structured illumination patterns.

8. An apparatus for implementing the high dynamic range structure illumination topography measurement method based on pixel-by-pixel control as described in any one of claims 1 to 7, characterized in that, This includes the camera optical path, the DMD optical path, and the light source, among which: The camera optical path includes, in sequence, a sample stage, an objective lens, a piezoelectric ceramic, a beam splitter, a first lens, and a camera. The DMD optical path includes a DMD and a second lens. After the light source shines on the DMD, it is reflected by the DMD and passes through the second lens into the beam splitter.

9. A high dynamic structure illumination topography measurement system based on pixel-by-pixel control, characterized in that, The method for implementing the high dynamic structure illumination topography measurement method based on pixel-by-pixel control as described in any one of claims 1 to 7 includes: Calibration module: Used to calibrate the DMD and camera to obtain the grayscale response relationship and coordinate mapping relationship between the DMD and the camera; Correction module: used to correct the phase-shifted fringes generated by the DMD using the gray-scale response relationship, coordinate mapping relationship, and optical transfer function; Projection module: used to project the corrected phase-shift fringes onto the sample surface and acquire the phase-shift structure illumination image by a camera; Modeling module: used to extract the surface morphology of the sample by slicing the phase-shifted structure illumination image.

Images