Image processing method

Abstract

In the image processing method according to the present disclosure, a measurement image is acquired which is generated by raster scanning, in which, after scanning the surface of a sample in a first direction by using a probe, the probe is moved in a second direction intersecting the first direction, and scanning in the first direction is repeated. In the image processing method, the measurement image is subjected to filter processing by using a rectangular spatial filter having a first side along the first direction and a second side along the second direction in the measurement image. The second side is longer than the first side.

Description

Image Processing Method

[0001] The present disclosure relates to image processing methods, and more particularly to methods for processing images generated based on measurements of a sample by a scanning probe microscope.

[0002] A scanning probe microscope (SPM) observes the surface of a sample by moving a probe so as to trace the surface. A known measurement mode of an SPM is a scan mode called raster scan. Raster scan is a measurement mode in which a measurement image is acquired by scanning the probe along multiple scanning lines parallel to a first direction on the sample surface.

[0003] Because SPM observes the minute surface structures of samples with high resolution, it is susceptible to environmental influences during scanning, such as noise from the device vibrations that occur during scanning and air vibrations caused by air conditioning and sound.

[0004] Japanese Patent Laid-Open Publication No. 2023-015633 (Patent Document 1) discloses an image processing method for reducing noise in a scanning electron microscope that obtains a scanned image by scanning a sample with an electron probe, by filtering the obtained scanned image using a square spatial filter.

[0005] Japanese Patent Application Laid-Open No. 2023-015633

[0006] In raster scanning, probe measurements are performed continuously along a single main scanning line parallel to the first direction. Therefore, if an event that causes noise occurs, the noise caused by that event may continuously appear in the measurement results along the single main scanning line. On the other hand, probe measurements are not performed continuously along a sub-scanning line in the second direction perpendicular to the main scanning line. Therefore, while the influence of noise may be similarly present in pixels adjacent to a pixel of interest along the first direction that corresponds to a measurement result in which noise appears in the measurement image, it is unlikely that the influence of that noise will be present in pixels adjacent to the pixel of interest along the second direction.

[0007] When a square spatial filter is used, the pixel of interest is converted using a surrounding area including pixels adjacent to the pixel of interest along the first direction. As a result, when noise occurs continuously in the first direction, the influence of the noise appearing in the adjacent pixels may also be reflected in the pixel of interest. Therefore, it may not be appropriate to use a square spatial filter when filtering a measurement image.

[0008] An object of the present disclosure is to further improve measurement accuracy by suppressing the influence of noise that appears continuously in a first direction in a measurement image generated by raster scanning and removing the noise.

[0009] The image processing method disclosed herein is a method for processing an image generated based on measurement of a sample using a scanning probe microscope. The image processing method includes the steps of: acquiring a measurement image generated by raster scanning using the scanning probe microscope, in which a probe is scanned over the surface of the sample in a first direction, and then the probe is moved in a second direction intersecting the first direction and scanned again in the first direction, and filtering the acquired measurement image using a rectangular spatial filter having a first side along the first direction and a second side along the second direction in the measurement image, the second side being longer than the first side.

[0010] According to the present disclosure, by using a rectangular spatial filter in which the second side along a second direction intersecting the first direction is longer than the first side along the first direction, the effect of noise that appears continuously in the first direction can be suppressed and the noise can be removed, thereby further improving measurement accuracy.

[0011] FIG. 1 is a schematic configuration diagram of a scanning probe microscope according to a first embodiment; FIG. 2 is a diagram showing the trajectory of a probe in a raster scan; FIG. 3 is a diagram showing a spatial filter according to the present embodiment and a spatial filter according to a comparative example; FIG. 4 is a flowchart of an image processing method; FIG. 5 is a diagram showing an example of a setting screen for filter processing; FIG. 6 is a diagram showing a converted measurement image obtained when a measurement image is processed using each spatial filter according to a first comparative example and an example; and FIG. 7 is a diagram showing a converted measurement image obtained when a measurement image is processed using each spatial filter according to a second comparative example and an example.

[0012] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are designated by the same reference numerals, and description thereof will not be repeated.

[0013] [Scanning Probe Microscope] Fig. 1 is a schematic diagram of a scanning probe microscope according to embodiment 1. An example of a scanning probe microscope is an atomic force microscope. However, the scanning probe microscope may be another type of scanning probe microscope (for example, a scanning tunneling microscope).

[0014] 1, scanning probe microscope 1 includes a measuring device 10, a computer 20, a display 30, and an input device 40. Measuring device 10 is configured to be able to communicate with computer 20, and sends measurement results to computer 20. Computer 20 processes the sent measurement results and notifies the user of the calculation results via display 30. Computer 20 accepts inputs such as measurement conditions via input device 40, and controls the entire measuring device 10 in accordance with the accepted measurement conditions.

[0015] [Measuring Apparatus] The measuring apparatus 10 includes a sample stage 112 on which a sample S is placed, a piezoelectric scanner 111 that displaces the sample stage, a cantilever 113 having a probe 114 formed at the tip, a displacement detection mechanism 120 that detects the displacement of the cantilever 113, and a feedback signal generating unit 131.

[0016] The piezo scanner 111 includes a Z scanner 111z that generates displacement in the Z direction based on a command voltage value Vz, and an XY scanner 111xy that generates displacement in the X and Y directions based on command voltage values ​​Vx and Vy.

[0017] The displacement detection mechanism 120 includes a laser diode 115 and a photodetector 119. In the scanning probe microscope 1, when the tip of the probe 114 is brought close to the sample S to observe the surface, the laser light emitted from the laser diode 115 is reflected by the back surface of the cantilever 113, and the reflected light is received by the photodetector 119. When the probe 114 is brought close to the surface of the sample S, the cantilever 113 bends like a leaf spring, and the amount of bending is observed at the light receiving position of the photodetector 119.

[0018] The feedback signal generating unit 131 receives a detection signal from the photodetector 119. The feedback signal generating unit 131 calculates the amount of deflection of the cantilever 113 based on the detection signal. The feedback signal generating unit 131 controls the Z-direction position of the sample so that the atomic force between the probe 114 and the surface of the sample S is always constant. The feedback signal generating unit 131 calculates a command voltage value Vz for displacing the piezo scanner 111 in the Z-axis direction based on the amount of deflection of the cantilever 113, and outputs the command voltage value Vz to the Z scanner 111z.

[0019] The scanning signal generating unit 133 calculates command voltage values ​​Vx and Vy in the X-axis and Y-axis directions so that the sample S moves relative to the probe 114 in the XY plane according to a predetermined scanning pattern, and outputs them to the XY scanner 111xy.

[0020] A signal reflecting the feedback amount in the Z-axis direction (command voltage value Vz to the scanner and deviation signal Sd) is also sent to computer 20 and stored in memory 24. Computer 20 calculates the amount of surface displacement due to the unevenness of sample S from command voltage value Vz based on correlation information that indicates the relationship between command voltage value Vz, which has been stored in advance in memory 24, and the corresponding amount of surface displacement due to the unevenness of sample S.

[0021] [Computer 20] The computer 20 includes a processor 22, a memory 24, and an input / output I / F 26. Each unit in the computer 20 is configured to be able to communicate with each other via a bus.

[0022] The processor 22 is typically an arithmetic processing unit such as a CPU (Central Processing Unit) or an MPU (Micro Processing Unit). The processor 22 controls the operation of the computer 20 by reading and executing programs stored in the memory 24. The programs include a program that, when executed by the processor 22, causes the computer 20 to control the measuring device 10, the display 30, and the input device 40.

[0023] The memory 24 is realized by a storage device such as a read-only memory (ROM), a random access memory (RAM), and a hard disk drive (HDD). The ROM stores the programs executed by the processor 22. The RAM temporarily stores data used by the processor 22 while the programs are running, and functions as a temporary data memory used as a work area. The HDD is a non-volatile storage device. A semiconductor storage device such as a flash memory may be used in addition to or instead of the HDD. The programs and / or data may be stored in an external storage device accessible by the processor 22.

[0024] The input / output I / F 26 is an interface for exchanging various types of data between the processor 22 and external devices connected to the input / output I / F 26. The external devices include a display 30, an input device 40, and the measurement device 10. The display 30 is an example of a notification unit that notifies the user of predetermined information, and displays, for example, an image for accepting input from the input device 40 and the results of calculations by the processor 22. The notification unit may also be other devices such as a speaker or a printer. The input device 40 is typically composed of a touch panel, a keyboard, a mouse, etc. The input device 40 accepts user input operations for the processor 22.

[0025] The computer 20 recreates a three-dimensional image of the sample surface by calculating the amount of displacement at each position in the X-axis and Y-axis directions, and displays this on the screen of the display 30. This three-dimensional image data is stored in the memory 24. The three-dimensional image data includes coordinates indicating positions on the X-Y plane and pixel values ​​corresponding to the sample height at those coordinates. The computer 20 reads out the three-dimensional image data stored in the memory 24 as needed and displays it on the display 30.

[0026] [Raster Scanning] In this embodiment, the measurement apparatus 10 performs raster scanning. Raster scanning is a measurement mode in which a measurement image is acquired by scanning the probe 114 along multiple scanning lines parallel to a first direction on the sample surface. FIG. 2 is a diagram showing the trajectory of the probe in raster scanning. FIG. 2 shows the same X-axis, Y-axis, and Z-axis as FIG. 1. In this embodiment, the sample stage 112 is moved in the X and Y directions by the piezo scanner 111, so that the probe 114 moves relative to the sample S. Note that, for ease of explanation, the following description will be given assuming that the sample S is fixed and the probe 114 is moving.

[0027] As shown in FIG. 2 , the measurement apparatus 10 scans the surface of the sample S with the probe 114 in the X-axis direction (the positive X-axis direction in FIG. 2 ), then moves the probe 114 in the Y-axis direction and scans the probe 114 again in the X-axis direction (the negative X-axis direction in FIG. 2 ). The computer 20 generates a measurement image based on the measurement results obtained by raster scanning, which repeats scanning in the X-axis direction and movement in the Y-axis direction. In the example shown in FIG. 2 , the measurement apparatus 10 scans with the probe 114 such that the scanning direction in the X-axis direction alternates between the positive and negative directions. Note that the measurement apparatus 10 may also perform raster scanning by repeating scanning in the X-axis direction and movement in the X and Y-axes so that the scanning direction in the X-axis direction is always constant (the positive or negative direction).

[0028] In raster scanning, measurements by the probe 114 are performed continuously along the X-axis direction. Therefore, when an event that causes noise occurs, the noise caused by the event may appear continuously in the measurement results in the X-axis direction.

[0029] The computer 20 performs image processing on the generated and acquired measurement image to remove noise.

[0030] [Overview of Image Processing Method] In this embodiment, the computer 20 uses a spatial filter to perform filtering on each region in the measurement image. FIG. 3 is a diagram showing the spatial filter according to this embodiment and a spatial filter according to a comparative example. In FIG. 3, as an example, filtering is performed on a measurement image of 16 pixels (4×4). FIG. 3 shows virtual pixel coordinates (X-Y coordinates) corresponding to the X-axis and Y-axis in FIG. 1. Each pixel value corresponds to the sample height.

[0031] As described above, in a raster scan, measurements by the probe 114 are performed continuously along the X-axis direction, so noise may appear continuously in the measurement results in the X-axis direction. For example, in the example shown in Figure 3, among the pixel data a1 to a16 of the measurement image corresponding to each coordinate (X, Y) on the XY plane, noise appears continuously in pixel data a6 and pixel data a7.

[0032] Conventionally, filtering has been performed using a square spatial filter Fc, such as the 3 × 3 spatial filter Fc in the comparative example. Therefore, as shown in the comparative example, when pixel data a7 is subjected to filtering and conversion as a pixel of interest, the influence of pixel data a6, which is adjacent in the X-axis direction and in which noise appears, is also reflected in the filtering of pixel data a7.

[0033] In this embodiment, the computer 20 performs filtering using a rectangular spatial filter Fe having a first side s1 along the X-axis direction and a second side s2 along the Y-axis direction that is longer than the first side s1. As an example, in Figure 3, the computer 20 performs filtering using a 1 x 3 spatial filter Fe. For example, if pixel data a7 is filtered and converted using the 1 x 3 spatial filter Fe as a pixel of interest, the filtering of pixel data a7 can be performed without the influence of noise that appears in pixel data a6 adjacent in the X-axis direction.

[0034] In raster scanning, measurements by the probe 114 are performed continuously along the X-axis direction, but not continuously along the Y-axis direction, so there is a low possibility that the influence of noise appearing in a pixel of interest is present in pixels adjacent to the pixel of interest in the Y-axis direction.

[0035] In this embodiment, the computer 20 performs filtering using a rectangular spatial filter that is long in the Y-axis direction, thereby performing filtering using surrounding pixels that are unlikely to contain the same noise as the pixel of interest, rather than using surrounding pixels that may contain the same noise as the pixel of interest. This makes it possible to reduce the influence of noise that appears continuously in the X-axis direction in the measurement image and remove noise.

[0036] 4 is a flowchart of the image processing method according to this embodiment. In S100, the computer 20 controls the measuring device 10 to perform a raster scan.

[0037] In S102, the computer 20 displays on the display 30 a measurement image generated from the measurement results obtained by raster scanning.

[0038] In S104, it is determined whether the measurement image is affected by specific noise that is continuous in the X-axis direction and discontinuous in the Y-axis direction. For example, the user checks the displayed measurement image and determines whether there is noise that is continuous in the X-axis direction but discontinuous in the Y-axis direction, and inputs the determination result via the input device 40. The computer 20 determines whether there is noise that is continuous in the X-axis direction and discontinuous in the Y-axis direction according to the input determination result.

[0039] If the computer 20 determines that the noise is continuous in the X-axis direction and discontinuous in the Y-axis direction (YES in S104), it performs filtering using a rectangular spatial filter in S106. As the spatial filter, for example, a linear filter such as an averaging filter or a Gaussian filter, or a nonlinear filter such as a median filter or a mode filter can be used.

[0040] When a 1x3 median filter is used, the following filtering process is performed. The case of converting a7 in FIG. 3 will be described as an example. The computer 20 extracts all pixel values ​​included in a 1x3 pixel range centered on the pixel of interest a7. The computer 20 sets the median value of the three extracted pixels (a3, a7, a11) as pixel a7' after conversion of the pixel of interest a7. The same process is performed on all pixels in the measurement image. This results in a filtered measurement image.

[0041] In S110, the computer 20 displays the measurement image after the filtering process, and then the process ends.

[0042] On the other hand, if the computer 20 determines that the noise is continuous in the X-axis direction and that there is no discontinuous noise in the Y-axis direction (NO in S104), the process ends.

[0043] As described above, when there is continuous noise in the X-axis direction and discontinuous noise in the Y-axis direction, filtering is performed using a rectangular spatial filter that is long in the Y-axis direction. This allows filtering appropriate for the type of noise, resulting in more efficient noise removal.

[0044] The computer 20 may present spatial filters available for use in the filtering process to the user via the display 30, and perform the filtering process using a type of spatial filter selected via the input device 40. FIG. 5 illustrates an example of a filtering setting screen. For example, the computer 20 presents available spatial filters to the user by displaying a setting screen 300 on the display 30. The setting screen 300 includes an area 304 presenting selectable spatial filter sizes (e.g., 3×3, 5×5, 7×7, 1×3, 1×5, 1×7, etc.), an area 302 presenting spatial filter types (e.g., averaging filter, Gaussian filter, median filter, mode filter, etc.), and an area 306 indicating the selected setting. The user selects a spatial filter to use from the presented options via the input device 40. The computer 20 performs the filtering process using the selected spatial filter.

[0045] [Examples] Fig. 6 is a diagram showing a transformed measurement image obtained when the measurement image is processed using the spatial filters according to Comparative Example 1 and Example 1. Fig. 7 is a diagram showing a transformed measurement image obtained when the measurement image is processed using the spatial filters according to Comparative Example 2 and Example 2.

[0046] The spatial filter in Example 1 is a 1 × 3 median filter. The spatial filter in Comparative Example 1 is a 3 × 3 median filter. The spatial filter in Example 2 is a 1 × 5 median filter. The spatial filter in Comparative Example 2 is a 5 × 5 median filter. In Comparative Examples 1 and 2 and Examples 1 and 2, an image simulating an image obtained by observing a sample surface with a line and space pattern was used as the measurement image. The horizontal direction of the paper surface in the measurement image corresponds to the X-axis direction in FIG. 3, and the vertical direction of the paper surface corresponds to the Y-axis direction in FIG. 1.

[0047] 6 , a comparison is made between measurement image M before conversion, measurement image B after conversion using the spatial filter according to Example 1, and measurement image C after conversion using the spatial filter according to Comparative Example 1. When measurement image M was converted to measurement image B, neither the pitch width nor the positions of the lines and spaces changed. Similarly, when measurement image M was converted to measurement image C, neither the pitch width nor the positions of the lines and spaces changed.

[0048] An area m1 in measurement image M where noise is thought to be present is compared with areas mb1 and mc1 in measurement images B and C corresponding to area m1. Area m1 is an area where noise is not present in the surrounding pixels, but is present in a single pixel. Whether the spatial filter of Example 1 or Comparative Example 1 is used, noise is not present in the surrounding pixels, and noise in a single pixel that exists alone can be removed.

[0049] A comparison is made between area m2 in measurement image M, where noise is thought to be present, and areas mb2 and mc2 in measurement images B and C corresponding to area m2. Area m2 is an area where noise appears continuously in both the X-axis direction and the Y-axis direction. As can be seen from the comparison between area m2 and area mb2, when the spatial filter of Example 1 (a 1 × 3 median filter) is used, noise appearing continuously in the X-axis direction can be removed. On the other hand, even when the spatial filter of Example 1 is used, noise appearing continuously in the Y-axis direction cannot be removed. As can be seen from the comparison between area m2 and area mc2, when the spatial filter of Comparative Example 1 (a 3 × 3 median filter) is used, not only is it not possible to remove any of the noise appearing continuously in the X-axis direction and the Y-axis direction, but the range of influence of the noise is even wider.

[0050] An area m3 in measurement image M where noise is thought to be present is compared with areas mb3 and mc3 in measurement images B and C corresponding to area m3. Area m3 is an area where noise appears at one-pixel intervals in the Y-axis direction. Whether the spatial filter of Example 1 or Comparative Example 1 is used, if noise appears at one-pixel intervals in the Y-axis direction, the effect of the noise can be reduced, but the noise cannot be completely removed.

[0051] 7 , a comparison is made between measurement image M before conversion, measurement image D after conversion using the spatial filter of Example 2, and measurement image E after conversion using the spatial filter of Comparative Example 2. When measurement image M was converted to measurement image D, neither the pitch width nor the positions of the lines and spaces changed. On the other hand, when measurement image M was converted to measurement image E, the pitch width remained unchanged, but the positions of the lines and spaces shifted in the X-axis direction.

[0052] A comparison is made between region m1 in measurement image M and regions md1 and me1 corresponding to region m1 in measurement images D and E. No matter which spatial filter is used, Example 2 or Comparative Example 2, noise does not appear in surrounding pixels, and noise in a single pixel that exists alone can be removed.

[0053] A comparison is made between region m2 in measurement image M and regions md2 and me2 in measurement images D and E corresponding to region m2. As can be seen from the comparison between region m2 and region md2, when the spatial filter of Example 2 (a 1×5 median filter) is used, it is possible to remove both noise that appears continuously in the X-axis direction and the Y-axis direction. As can be seen from the comparison between region m2 and region me2, when the spatial filter of Comparative Example 1 is used, it is not possible to remove noise.

[0054] A comparison is made between area m3 in measurement image M and areas md3 and me3 corresponding to area m3 in measurement images D and E. No matter which spatial filter is used, Example 1 or Comparative Example 1, noise present at one pixel intervals in the Y-axis direction can be removed.

[0055] As described above, by using the rectangular spatial filter according to this embodiment, it is possible to remove noise that exists continuously in the X-axis direction, which could not be removed by a conventional square spatial filter.

[0056] [Modification] In the above embodiment, the length of the short side of the rectangular spatial filter is the same as the length of one side of each pixel that constitutes the measurement image. The length of the short side only needs to be shorter than the length of the long side. For example, the spatial filter may be a 3x5 spatial filter. By making the length of the short side the same as the length of one side of each pixel that constitutes the measurement image, the effect of consecutive noise can be further suppressed and the noise can be removed in the filtering process.

[0057] In the above embodiment, the X-axis direction is the main scanning direction, and the Y-axis direction perpendicular to the X-axis direction is the sub-scanning direction. Note that the sub-scanning direction may be any direction that intersects the main scanning direction, and is not limited to a direction perpendicular to the X-axis direction.

[0058] [Aspects] It will be understood by those skilled in the art that the above-described embodiments are specific examples of the following aspects.

[0059] (Item 1) An image processing method according to one aspect is a method for processing an image generated based on measurement of a sample using a scanning probe microscope. The image processing method includes the steps of: acquiring a measurement image generated by raster scanning, in which the scanning probe microscope scans the surface of the sample in a first direction with a probe, then moves the probe in a second direction intersecting the first direction, and scans the surface in the first direction again, and performing filtering on the acquired measurement image using a rectangular spatial filter having a first side along the first direction and a second side along the second direction in the measurement image. The second side may be longer than the first side.

[0060] According to the image processing method described in paragraph 1, by using a rectangular spatial filter in which the second side along a second direction intersecting the first direction is longer than the first side along the first direction, the influence of noise that appears continuously in the first direction can be suppressed and the noise can be removed, thereby further improving measurement accuracy.

[0061] (Section 2) The image processing method described in Section 1 further includes a step of determining whether or not a specific region that is continuously affected by noise in a first direction but not continuously affected by noise in a second direction is present in the acquired measurement image. The step of performing filtering using a spatial filter may be executed when it is determined that a specific region is present in the acquired measurement image.

[0062] According to the image processing method described in paragraph 2, when a specific region is present, a step of performing filtering using a rectangular spatial filter is executed, so that filtering appropriate for the type of noise is performed, enabling noise to be removed more efficiently.

[0063] (Item 3) In the image processing method described in item 1 or 2, the spatial filter may be an averaging filter, a Gaussian filter, a median filter, or a mode filter.

[0064] (4) In the image processing method according to any one of the first to third paragraphs, the length of the first side may be the same as the length of one side of each pixel constituting the measurement image.

[0065] According to the image processing method described in paragraph 4, the influence of noise that appears continuously can be further suppressed in the filtering process, and the noise can be removed.

[0066] (5) A program according to one aspect may be a program that causes a computer to execute the image processing method according to any one of the first to fourth aspects.

[0067] (6) A recording medium according to one aspect may be a computer-readable recording medium on which the program according to 5 is recorded.

[0068] The embodiments disclosed herein are intended to be combined as appropriate within the scope of any technical inconsistency. The embodiments disclosed herein should be considered to be illustrative and not restrictive in all respects. The scope of the present invention is defined by the claims, not by the description of the above-mentioned embodiments, and is intended to include all modifications within the meaning and scope of the claims.

[0069] 1 Scanning probe microscope, 10 Measuring device, 20 Computer, 22 Processor, 24 Memory, 26 Input / output I / F, 30 Display, 40 Input device, 111 Piezo scanner, 112 Sample stage, 113 Cantilever, 114 Probe, 115 Laser diode, 119 Photodetector, 120 Displacement detection mechanism, 131 Feedback signal generating unit, 133 Scanning signal generating unit, 300 Setting screen, 302, 304, 306 Area, Fc, Fe Spatial filter, S Sample.

Claims

1. A method for processing an image generated based on measurement of a sample with a scanning probe microscope, comprising the steps of: acquiring a measurement image generated by raster scanning in the scanning probe microscope, in which a probe is scanned in a first direction over the surface of the sample, and then the probe is moved in a second direction intersecting the first direction and scanning in the first direction again, and repeating this process; and performing filtering on the acquired measurement image using a rectangular spatial filter having a first side along the first direction and a second side along the second direction in the measurement image, wherein the second side is longer than the first side.

2. The image processing method of claim 1, further comprising a step of determining whether or not there is a specific area within the acquired measurement image that is continuously affected by noise in the first direction but not affected by continuous noise in the second direction, and the step of performing filtering using the spatial filter is executed when it is determined that the specific area is present within the acquired measurement image.

3. The image processing method according to claim 1 or 2, wherein the spatial filter is an averaging filter, a Gaussian filter, a median filter, or a mode filter.

4. An image processing method according to claim 1 or 2, wherein the length of the first side is the same as the length of one side of each pixel constituting the measurement image.