White light interference three-dimensional shape rapid reconstruction method

Abstract

The invention discloses a white light interference three-dimensional morphology rapid reconstruction method. The method comprises the following steps: S1, continuously collecting N frames of interference images of a detected sample by using a white light interference system; s2, the collected interference images are preprocessed, and preprocessing comprises the steps that S21, interference interval positioning is conducted on all the interference images, and interference images to be reconstructed are obtained; s22, dividing each to-be-reconstructed interference image into a plurality of regions, and performing pixel point number reduction on each region to complete region pixel reconstruction to obtain a corresponding reconstructed image; s3, calculating a focusing metric value of each pixel point in each reconstructed image by using a focusing metric algorithm; and S4, searching zero optical path difference points of all pixel points in all the reconstructed images based on an improved gravity center method so as to recover the three-dimensional morphology of the tested sample. According to the method, the calculated amount and burr noise during three-dimensional shape reconstruction are greatly reduced, the timeliness is improved by nearly five times, and the reconstruction efficiency and accuracy are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of optical measurement, and in particular relates to a method for rapid reconstruction of three-dimensional morphology using white light interference. Background Art

[0002] The processing accuracy of precision manufacturing has developed to the micro-nano level. Since the microscopic morphology of micro-nano components will significantly affect the process performance and service life, high-precision detection has become an indispensable requirement. Early non-optical detection methods belong to contact measurement, which has a limited scope of application and increases the risk of damaging samples. Until the introduction of optical technology, non-contact measurement was realized.

[0003] Among them, focus topography recovery takes advantage of different surface roughness and reflectivity changes, resulting in images with a lot of texture. The depth of each pixel is obtained by calculating the focus metric value for each scan position in the image stack, and finding a single maximum on the acquired focus curve to detect the focus position. However, due to the presence of noise and textureless areas, the focus metric usually has a local maximum, which prevents the accurate positioning of the focus metric peak.

[0004] White light interferometry has good morphology recovery capabilities for smooth surfaces, and the longitudinal resolution can reach a few tenths of a nanometer. However, when solving the interference signal of the rough surface area with a large slope, the calculation result may still have serious deviations. White light interferometry can obtain the depth of each pixel by processing the intensity signal of each scanning position in the image stack. Find the maximum value, that is, the zero optical path difference point, on the acquired intensity modulation curve. There are periodic fluctuations in the focus change signal, and its frequency is similar to the frequency of the white light interference fringes. Based on this point of view, it can be seen that the principles of white light interferometry and focusing morphology recovery and reconstruction are consistent, that is, it is necessary to obtain a Gaussian envelope curve through the image stack of each pixel to find the extreme point.

[0005] Therefore, both focusing topography and white light interferometry are difficult to measure both smooth surfaces and rough surfaces with large slopes. They have a narrow scope of application, great limitations, and low reconstruction accuracy. At the same time, since the above two methods need to traverse each pixel when used alone, they will also cause problems such as large amount of calculation, long time consumption, and poor timeliness. Summary of the invention

[0006] The purpose of the present invention is to solve the above problems and propose a method for rapid reconstruction of three-dimensional morphology by white light interference, which can reduce the amount of calculation and improve the reconstruction efficiency and accuracy.

[0007] To achieve the above object, the technical solution adopted by the present invention is:

[0008] The present invention proposes a method for rapid reconstruction of three-dimensional morphology using white light interference, comprising the following steps:

[0009] S1. Continuously collect N frames of interference images of the sample under test using a white light interferometer system;

[0010] S2. Preprocessing the collected interference image, including:

[0011] S21, performing interference interval positioning on all interference images to obtain interference images to be reconstructed, as follows:

[0012] S211. Obtain the maximum scale factor k max , the formula is as follows:

[0013]

[0014] k max =max{k2,k3,...,k n ,...,k N};

[0015] Where I(n) is the interference light intensity distribution when the number of scanning steps is n, k n is the scale factor when the number of scanning steps is n, n = 2~N, N is the number of scanning steps of the white light interferometer system, that is, the number of frames of the interference image;

[0016] S212, the maximum scale factor k max When the interference image before the corresponding scanning step appears, it is regarded as redundant data and deleted, and the retained interference image is used as the interference image to be reconstructed to complete the interference interval positioning;

[0017] S22, dividing each interference image to be reconstructed into a plurality of regions, and reducing the number of pixels in each region to complete regional pixel reconstruction, thereby obtaining a corresponding reconstructed image;

[0018] S3, using a focusing metric algorithm to calculate the focusing metric value of each pixel in each reconstructed image;

[0019] S4. Based on the improved centroid method, the zero optical path difference point of each pixel in all reconstructed images is found to restore the three-dimensional morphology of the measured sample. The formula of the improved centroid method is as follows:

[0020] m(n)=[FM(n)-FM(n-1)] 2 ;

[0021]

[0022] Where FM(n) is the focus measurement value of the pixel point (x, y) when the scanning step number is n, m(n) is the square of the difference between the focus measurement values ​​of the pixel point (x, y) in the reconstructed images of two adjacent frames, and h is the height of the sample under test at the pixel point (x, y).

[0023] Preferably, the focus metric algorithm is as follows:

[0024]

[0025] Where FM(x,y) is the focus metric value of the pixel coordinate (x,y) in the evaluation window, G(x,y) is the gradient value of the pixel coordinate (x,y) in the evaluation window, and G x is the lateral gradient value, G y is the longitudinal gradient value, is the average gradient within the evaluation window, Ω is the evaluation window size, x is the horizontal coordinate of the pixel within the evaluation window, and y is the vertical coordinate of the pixel within the evaluation window.

[0026] Preferably, each interference image to be reconstructed is divided into a plurality of regions, and the number of pixels in each region is reduced to complete the regional pixel reconstruction, as follows:

[0027] S221, record the upper left corner of the interference image to be reconstructed as the image origin, and divide the interference image to be reconstructed into a plurality of regions using four adjacent pixels as units;

[0028] S222, reconstruct the regional pixels of each region, and the reconstruction formula is as follows:

[0029] I′(i / 2,j / 2)=(I(i-1,j-1)+I(i,j-1)+I(i-1,j)+I(i,j)) / 4;

[0030] Where I′(i / 2,j / 2) is the gray value of the reconstructed regional pixel, I(i,j) is the gray value of the pixel in the i-th row and j-th column of the interference image to be reconstructed, i, j∈M, and M is the total number of horizontal pixels or the total number of vertical pixels of the interference image to be reconstructed.

[0031] Preferably, the white light interference system comprises a white light source, a first lens, a camera, a second lens, a beam splitter, a piezoelectric ceramic platform and an objective lens, wherein:

[0032] The first lens and the second lens are respectively located on both sides of the beam splitter and their optical axes are perpendicular to each other. The objective lens is installed on the piezoelectric ceramic platform and driven by the piezoelectric ceramic platform to scan the sample to be measured. The light emitted by the white light source is collimated by the first lens and then reflected by the beam splitter. The reflected light passes through the piezoelectric ceramic platform and the objective lens in turn and irradiates the sample to be measured. The light reflected by the sample to be measured then passes through the objective lens and the piezoelectric ceramic platform in turn and is transmitted from the beam splitter. The transmitted light is focused by the second lens onto the camera, and the interference image of the sample to be measured is collected by the camera.

[0033] Preferably, the objective lens is a Mirau interference objective lens.

[0034] Preferably, the piezoelectric ceramic platform is equipped with an objective lens to perform equally spaced nanometer-level scanning on the sample being tested.

[0035] Preferably, the beam splitter is a 45° beam splitting prism.

[0036] Preferably, the camera collects the interference image of the sample under test when there is only one interference fringe in the field of view, and the scanning step length of the objective lens is 100 nm.

[0037] Preferably, the surface of the sample to be tested is a smooth surface.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] The present application continuously collects several frames of interference images of the measured sample through a white light interferometer system and performs preprocessing, the preprocessing includes interference interval positioning and regional pixel reconstruction to obtain a reconstructed image; then a focusing metric algorithm is used to calculate the focusing metric value of each pixel point in each reconstructed image; based on the improved center of gravity method, the zero optical path difference point of each pixel point in all reconstructed images is found to restore the three-dimensional morphology of the measured sample, so that the amount of calculation and burr noise are greatly reduced, the timeliness is improved by nearly five times, the reconstruction efficiency and accuracy are improved, and the application range is wide. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a flow chart of the method for rapid reconstruction of three-dimensional morphology using white light interference according to the present invention;

[0041] Figure 2 It is a structural schematic diagram of the white light interferometer system of the present invention;

[0042] Figure 3 The original interference image (a) and the reconstructed image (b) of the present invention;

[0043] Figure 4 The reconstructed image (a) and the original interference image (b) of the sample under test of the present invention at the 70th frame;

[0044] Figure 5 The reconstruction result of the measured sample using the focusing morphology recovery method in the prior art;

[0045] Figure 6 This is the reconstruction result of the sample tested by the method of the present invention.

[0046] Explanation of the accompanying drawings: 1. white light source; 2. first lens; 3. camera; 4. second lens; 5. beam splitter; 6. piezoelectric ceramic platform; 7. objective lens; 8. sample to be measured. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0048] It should be noted that, unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art in the technical field of this application. The terms used herein in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application.

[0049] like Figure 1-6 As shown, a method for rapid reconstruction of three-dimensional morphology using white light interference includes the following steps:

[0050] S1. Use the white light interferometry system to continuously collect N frames of interference images of the sample under test.

[0051] In one embodiment, the white light interference system includes a white light source 1, a first lens 2, a camera 3, a second lens 4, a beam splitter 5, a piezoelectric ceramic platform 6 and an objective lens 7, wherein:

[0052] The first lens 2 and the second lens 4 are respectively located on both sides of the beam splitter 5 and their optical axes are perpendicular to each other. The objective lens 7 is installed on the piezoelectric ceramic platform 6 and driven by the piezoelectric ceramic platform 6 to scan the sample to be measured. The light emitted by the white light source 1 is collimated by the first lens 2 and then reflected by the beam splitter 5. The reflected light passes through the piezoelectric ceramic platform 6 and the objective lens 7 in turn and irradiates the sample to be measured. The light reflected by the sample to be measured passes through the objective lens 7 and the piezoelectric ceramic platform 6 in turn and is transmitted from the beam splitter 5. The transmitted light is focused by the second lens 4 onto the camera 3, and the interference image of the sample to be measured is collected by the camera 3.

[0053] like Figure 2 As shown, the white light interferometer system includes a white light source 1, a first lens 2, a camera 3, a second lens 4, a beam splitter 5, a piezoelectric ceramic platform 6 and an objective lens 7, and its measurement principle is:

[0054] The white light source 1 has a wide spectrum characteristic and emits low coherence light. After being collimated by the first lens 2, it is split by the beam splitter 5. The reflected light passes through the piezoelectric ceramic platform 5 and the objective lens 7 in turn to irradiate the sample 8 to be tested. The sample 8 to be tested is placed horizontally, and the objective lens 7 is perpendicular to the sample 8 to be tested. The vertical direction is the depth direction. The piezoelectric ceramic platform 6 can load the objective lens 7 to perform nanometer-level scanning of the sample 8 to be tested at equal intervals along the depth direction. Interference can occur in the objective lens 7. The light beam reflected by the sample 8 to be tested returns from the original light path and is transmitted through the beam splitter 5. It is focused by the second lens 4 onto the camera 3, and the positions where the interference fringes appear and disappear are recorded. The camera 3 is used for continuous acquisition at equal intervals. In this embodiment, the sample 8 to be tested is a smooth silicon wafer. When there is one interference fringe in the field of view, the positions where the interference fringes appear and disappear are recorded. The scanning step length is 100nm, and 117 frames of images are continuously acquired, among which the 70th frame of interference image is as shown in FIG. Figure 4 (b) as shown.

[0055] In one embodiment, the objective lens 7 is a Mirau interference objective lens, or other commonly used interference objective lenses known to those skilled in the art may also be used.

[0056] In one embodiment, the piezoelectric ceramic platform 6 carries the objective lens 7 to perform equally spaced nanometer-level scanning on the sample being tested.

[0057] In one embodiment, the beam splitter 5 is a 45° beam splitter prism.

[0058] In one embodiment, the camera 3 collects the interference image of the sample under test when there is only one interference fringe in the field of view, and the scanning step length of the objective lens 7 is 100 nm.

[0059] In one embodiment, the surface of the sample to be tested is a smooth surface.

[0060] S2. Preprocessing the collected interference image, including:

[0061] S21, performing interference interval positioning on all interference images to obtain interference images to be reconstructed, as follows:

[0062] S211. Obtain the maximum scale factor k max , the formula is as follows:

[0063]

[0064] k max =max{k2,k3,...,k n ,…,k N};

[0065] Where I(n) is the interference light intensity distribution when the number of scanning steps is n, k nis the scale factor when the number of scanning steps is n, n = 2~N, N is the number of scanning steps of the white light interferometer system, that is, the number of frames of the interference image;

[0066] S212, the maximum scale factor k max When the interference image before the corresponding scanning step appears, it is regarded as redundant data and deleted, and the retained interference image is used as the interference image to be reconstructed to complete the interference interval positioning;

[0067] S22, dividing each interference image to be reconstructed into a plurality of regions, and reducing the number of pixels in each region to complete regional pixel reconstruction, thereby obtaining a corresponding reconstructed image.

[0068] In one embodiment, each interference image to be reconstructed is divided into a plurality of regions, and the number of pixels in each region is reduced to complete regional pixel reconstruction, as follows:

[0069] S221, record the upper left corner of the interference image to be reconstructed as the image origin, and divide the interference image to be reconstructed into a plurality of regions using four adjacent pixels as units;

[0070] S222, reconstruct the regional pixels of each region, and the reconstruction formula is as follows:

[0071] I′(i / 2,j / 2)=(I(i-1,j-1)+I(i,j-1)+I(i-1,j)+I(i,j)) / 4;

[0072] Where I′(i / 2,j / 2) is the gray value of the reconstructed regional pixel, I(i,j) is the gray value of the pixel in the i-th row and j-th column of the interference image to be reconstructed, i, j∈M, and M is the total number of horizontal pixels or the total number of vertical pixels of the interference image to be reconstructed.

[0073] Among them, image preprocessing includes interference interval positioning and regional pixel reconstruction, which can effectively improve timeliness, reduce the amount of calculation, and perform interference interval positioning on the collected continuous interference images. n The maximum scale factor k appears max When , the positioning is completed; in this embodiment, Therefore, the interference images before the 32nd frame can be regarded as redundant data and deleted, and the number of images is reduced from 117 frames to 86 frames. The interference images to be reconstructed in the subsequent steps are 86 frames, and the interference interval positioning takes about 0.137 seconds. Then, the regional pixel reconstruction is performed on the interference image to be reconstructed. Since the calculation of the pixel focus metric value usually requires selecting an area within a certain neighborhood range of the pixel as the evaluation window, and the mean of the focus metric values ​​of all pixels in the evaluation window is used as the evaluation function of the pixel. Assume that the upper left corner of the original interference image I is the image origin, and there are a total of M pixels along the horizontal direction or the vertical direction. Starting from the upper left corner, take the gray value mean of the four adjacent pixels as a unit as a new reconstructed pixel gray value, and the reconstructed image is I′.

[0074] like Figure 3 As shown in , the number of image pixels after regional pixel reconstruction is halved, as Figure 3 The number of pixels of the original interference image recorded as shown in (b) is 500×500, which becomes 250×250 after reconstruction. The reconstruction takes about 0.84 seconds. Figure 3 (a) shown.

[0075] S3. Calculate the focus metric value of each pixel in each reconstructed image using a focus metric algorithm.

[0076] In one embodiment, the focus metric algorithm is as follows:

[0077]

[0078] Where FM(x,y) is the focus metric value of the pixel coordinate (x,y) in the evaluation window, G(x,y) is the gradient value of the pixel coordinate (x,y) in the evaluation window, and G x is the lateral gradient value, G y is the longitudinal gradient value, is the average gradient within the evaluation window, Ω is the evaluation window size, x is the horizontal coordinate of the pixel within the evaluation window, and y is the vertical coordinate of the pixel within the evaluation window.

[0079] The focus metric algorithm is used to calculate the focus metric value of each pixel point of each frame of the reconstructed image. This embodiment adopts an evaluation window size of 3×3. The focus morphology measurement reconstruction result in the prior art is as follows: Figure 5 As shown, in addition to the influence of dust, both the upper and lower surfaces have a large amount of burr noise and pit defects appear on the surface. It takes about 246.27 seconds to calculate the focus measurement value of the original interference image, and it takes about 50.77 seconds to calculate the focus measurement value of the interference image after image preprocessing.

[0080] S4. Based on the improved centroid method, the zero optical path difference point of each pixel in all reconstructed images is found to restore the three-dimensional morphology of the measured sample. The formula of the improved centroid method is as follows:

[0081] m(n)=[FM(n)-FM(n-1)] 2 ;

[0082]

[0083] Where FM(n) is the focus measurement value of the pixel point (x, y) when the scanning step number is n, m(n) is the square of the difference between the focus measurement values ​​of the pixel point (x, y) in the reconstructed images of two adjacent frames, and h is the height of the sample under test at the pixel point (x, y).

[0084] The center of gravity of the curve, i.e., the zero optical path difference point, is found according to the improved center of gravity method, thereby restoring the three-dimensional shape of the object. In this embodiment, the image after image preprocessing is 86 frames. The reconstruction result according to the method provided by the present invention is as follows Figure 6 As shown, compared with the prior art that only uses the focused morphology recovery algorithm, except for the protrusions caused by dust on the upper surface, the burr noise in other parts is greatly reduced. The original interference image improved centroid method takes about 4.5 seconds, and the image improved centroid method after image preprocessing takes about 0.98 seconds.

[0085] After image preprocessing, composite three-dimensional morphology reconstruction takes a total of about 51.75 seconds. Including the reconstruction time, the method of the present invention takes a total of about 52.727 seconds. The technical solution adopted by the present invention greatly reduces the amount of calculation and the burr noise, and the timeliness is improved by nearly 5 times compared with the existing technical solution.

[0086] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0087] The above-described embodiments only express the more specific and detailed embodiments described in this application, but they cannot be understood as limiting the scope of the patent application. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of this application, which all belong to the protection scope of this application. Therefore, the protection scope of the patent application shall be based on the attached claims.

Claims

1. A method for rapid reconstruction of three-dimensional morphology by white light interferometry, applied to a white light interferometry system, characterized in that: The white light interferometry three-dimensional morphology rapid reconstruction method comprises the following steps: S1. Continuously collect N frames of interference images of the sample under test using a white light interferometer system; S2. Preprocessing the collected interference image, wherein the preprocessing includes: S21, performing interference interval positioning on all interference images to obtain interference images to be reconstructed, as follows: S211. Obtain the maximum scale factor k max , the formula is as follows: k max =max{k2,k3,...,k n ,...,k N }; Where I(n) is the interference light intensity distribution when the number of scanning steps is n, k n is the scale factor when the number of scanning steps is n, n = 2~N, N is the number of scanning steps of the white light interferometer system, that is, the number of frames of the interference image; S212, the maximum scale factor k max When the interference image before the corresponding scanning step appears, it is regarded as redundant data and deleted, and the retained interference image is used as the interference image to be reconstructed to complete the interference interval positioning; S22, dividing each interference image to be reconstructed into a plurality of regions, and reducing the number of pixels in each region to complete regional pixel reconstruction, thereby obtaining a corresponding reconstructed image; S3, using a focusing metric algorithm to calculate the focusing metric value of each pixel in each reconstructed image; S4. Find the zero optical path difference point of each pixel in all reconstructed images based on the improved centroid method to restore the three-dimensional morphology of the measured sample. The formula of the improved centroid method is as follows: m(n)=[FM(n)-FM(n-1)] 2 ; Where FM(n) is the focus measurement value of the pixel point (x, y) when the scanning step number is n, m(n) is the square of the difference between the focus measurement values ​​of the pixel point (x, y) in the reconstructed images of two adjacent frames, and h is the height of the sample under test at the pixel point (x, y).

2. The white light interferometry three-dimensional morphology rapid reconstruction method according to claim 1, characterized in that: The focus metric algorithm is formulated as follows: Where FM(x,y) is the focus metric value of the pixel coordinate (x,y) in the evaluation window, G(x,y) is the gradient value of the pixel coordinate (x,y) in the evaluation window, and G x is the lateral gradient value, G y is the longitudinal gradient value, is the average gradient within the evaluation window, Ω is the evaluation window size, x is the horizontal coordinate of the pixel within the evaluation window, and y is the vertical coordinate of the pixel within the evaluation window.

3. The white light interferometry three-dimensional morphology rapid reconstruction method according to claim 1, characterized in that: The interference images to be reconstructed are divided into a plurality of regions, and the number of pixels in each region is reduced to complete the regional pixel reconstruction, as follows: S221, record the upper left corner of the interference image to be reconstructed as the image origin, and divide the interference image to be reconstructed into a plurality of regions using four adjacent pixels as units; S222, reconstructing the regional pixels of each region, the reconstruction formula is as follows: I'(i / 2,j / 2)=(I(i-1,j-1)+I(i,j-1)+I(i-1,j)+I(i,j)) / 4; Where I'(i / 2,j / 2) is the gray value of the reconstructed regional pixel, I(i,j) is the gray value of the pixel in the i-th row and j-th column of the interference image to be reconstructed, i, j∈M, and M is the total number of horizontal pixels or the total number of vertical pixels of the interference image to be reconstructed.

4. The white light interferometry three-dimensional morphology rapid reconstruction method according to claim 1, characterized in that: The white light interference system comprises a white light source (1), a first lens (2), a camera (3), a second lens (4), a beam splitter (5), a piezoelectric ceramic platform (6) and an objective lens (7), wherein: The first lens (2) and the second lens (4) are respectively located on both sides of the beam splitter (5) and their optical axes are perpendicular to each other. The objective lens (7) is mounted on the piezoelectric ceramic platform (6) and driven by the piezoelectric ceramic platform (6) to scan the sample to be measured. The light emitted by the white light source (1) is collimated by the first lens (2) and then reflected by the beam splitter (5). The reflected light passes through the piezoelectric ceramic platform (6) and the objective lens (7) in sequence and irradiates the sample to be measured. The light reflected by the sample to be measured then passes through the objective lens (7) and the piezoelectric ceramic platform (6) in sequence and then transmits from the beam splitter (5). The transmitted light is focused by the second lens (4) onto the camera (3), and an interference image of the sample to be measured is collected by the camera (3).

5. The white light interferometry three-dimensional morphology rapid reconstruction method according to claim 4, characterized in that: The objective lens (7) is a Mirau interference objective lens.

6. The white light interferometry three-dimensional morphology rapid reconstruction method according to claim 4, characterized in that: The piezoelectric ceramic platform (6) drives the objective lens (7) to perform nanometer-level scanning at equal intervals on the sample to be measured.

7. The white light interferometry three-dimensional morphology rapid reconstruction method according to claim 4, characterized in that: The beam splitter (5) is a 45° beam splitting prism.

8. The white light interferometry three-dimensional morphology rapid reconstruction method according to claim 4, characterized in that: The camera (3) collects an interference image of the sample under test when there is one interference fringe in the field of view, and the scanning step length of the objective lens (7) is 100 nm.

9. The method for rapid reconstruction of three-dimensional morphology using white light interference according to any one of claims 1 to 8, characterized in that: The surface of the sample to be tested is a smooth surface.

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