Image quality adjustment device and image quality adjustment method

Abstract

The purpose of the present disclosure is to provide an image quality adjustment method capable of clearly distinguishing an upper layer part and a lower layer part in an observation image of a sample in which the upper layer part and the lower layer part are overlapped, even when the contrast of each layer in the image is not clear. An image quality adjustment device according to the present disclosure: receives a first image generated on the basis of an output of a first detector and a second image generated on the basis of an output of a second detector; performs image quality adjustment for bringing the image quality of the first image and the image quality of the second image closer to each other; and removes a lower layer pattern contained in the first image by using the first image having undergone the image quality adjustment and the second image having undergone the image quality adjustment.

Description

Image quality adjustment device and image quality adjustment method

[0001] The present disclosure relates to a technique for adjusting the image quality of an observed image of a sample.

[0002] The recent trend toward miniaturization and layering of semiconductor devices has created a demand for accurate measurement of circuit pattern dimensions, such as line width. In particular, for devices with multilayer structures, such as DRAMs, it is important to measure overlay errors (overlay errors between upper and lower layers) in circuit patterns at high and low positions. A device called a CD-SEM (Critical Dimension-Scanning Electron Microscope) is used for such measurements. A CD-SEM irradiates a fine pattern formed on a wafer with an electron beam, detects the electrons emitted from the circuit pattern with a detector, converts the detected signal into an image, and measures dimensions based on the signal of the circuit pattern in the image.

[0003] CD-SEMs can be equipped with detectors that detect emitted electrons in multiple different energy bands. Images obtained by detecting low-energy emitted electrons generated near the sample surface reflect the surface shape of the sample. On the other hand, images obtained by detecting high-energy emitted electrons that penetrate into the sample and bounce back reflect the shape of the sample in the vertical direction. Technology has been proposed that utilizes the characteristics of low-energy and high-energy emitted electron images and adjusts the image quality of each to enhance signals from the sample surface or deep within.

[0004] The technology described in Patent Document 1 below utilizes a high-energy electron detector capable of detecting high-energy electrons and a low-energy electron detector capable of detecting low-energy electrons. Emitted electrons with an energy of 50 eV or less are called secondary electrons, and a detector for detecting them is a low-energy electron detector. On the other hand, emitted electrons with an energy of 50 eV or more are called reflected electrons (backscattered electrons), and a detector for detecting them is a high-energy electron detector. In Patent Documents 1 and 2, the regions of each layer of a sample having a multilayer structure are separated from the brightness distribution of a reflected electron image, the regions of each layer are associated with regions in the secondary electron image, and the layer to be inspected on the secondary electron image is extracted.

[0005] In the technique described in Patent Document 2 below, a lower layer portion is extracted from a backscattered electron image, and an upper layer portion is extracted from a secondary electron image (see paragraph 0096).

[0006] Japanese Patent No. 5,313,939 (US8,653,456) Japanese Patent Application Laid-Open No. 2021-093336 (US11,276,552)

[0007] In the technology described in Patent Document 1, if the difference in height between the upper and lower layers is small and the contrast between the upper and lower layers in the backscattered electron image is not clear, it may be impossible to distinguish the regions of each layer. Also, if the upper and lower layer patterns overlap, it is difficult to separate the layers.

[0008] Patent Document 2 describes a method for extracting a measurement area present in a lower layer. In this document, the purpose of acquiring an image of the upper layer is to measure an overlay error, and it is not intended to clearly distinguish between the upper and lower layers.

[0009] The present disclosure has been made to solve the above-mentioned problems, and aims to provide an image quality adjustment method that can clearly distinguish between upper and lower layers in an observation image of a sample in which the upper and lower layers overlap, even if the contrast between each layer in the image is not clear.

[0010] The image quality adjustment device of the present disclosure receives a first image generated based on the output of a first detector and a second image generated based on the output of a second detector, performs image quality adjustment to bring the image quality of the first image and the image quality of the second image closer to each other, and uses the first image that has been subjected to the image quality adjustment and the second image that has been subjected to the image quality adjustment to remove an upper layer pattern or an under layer pattern contained in the first image.

[0011] According to the image quality adjustment device of the present disclosure, in an observation image of a sample in which the upper and lower layers overlap, the upper and lower layers can be clearly distinguished even if the contrast between each layer in the image is not clear.

[0012] 1 shows the configuration of a pattern measurement system 1000 according to a first embodiment. FIG. 2 is a flowchart explaining the operation of the pattern measurement system 1000. FIG. 3 is a plan view showing the structure of a silicon wafer sample. FIG. 4 is an example of a low-energy electron image converted from the detection signal of the low-energy electron detector 206. FIG. 5 is an example of a high-energy electron image converted from the detection signal of the high-energy electron detector 208. FIG. 6 is a diagram showing a GUI for extracting a measurement area. FIG. 7 is a diagram showing an example of performing masking processing on a low-energy electron image. FIG. 8 is a diagram showing an example of performing masking processing on a low-energy electron image. FIG. 9 is a flowchart explaining the procedure for adjusting the image quality of a low-energy electron image and a high-energy electron image in S303. FIG. 10 shows the appearance of a low-energy electron image after image quality adjustment. FIG. 11 is a diagram showing the appearance of a high-energy electron image after image quality adjustment. FIG. 11 shows an example of a difference image in step S304. FIG. 12 is a diagram showing a GUI for instructing the pattern measurement system 1000 to acquire an electron image with an electron beam having a different acceleration voltage.

[0013] 1 shows the configuration of a pattern measurement system 1000 according to a first embodiment of the present disclosure. The pattern measurement system 1000 is a system that acquires an observation image of a shape pattern of a sample in which an upper layer and a lower layer are overlapped. The pattern measurement system 1000 includes an electron optical unit 200, an image generation unit 211, a calculation unit 212, an input / output unit 213, and a design system 214.

[0014] The electron optical unit 200 includes an electron gun 201, a focusing lens 203, a deflector 204, an ExB deflector 205, an objective lens 207, a detector capable of detecting electrons in a low energy band (hereinafter referred to as a low energy electron detector) 206, an electron detector capable of detecting electrons in a high energy band (hereinafter referred to as a high energy electron detector) 208, and an XY stage 210.

[0015] An electron gun 201 emits an electron beam 202 as charged particles. A focusing lens 203 focuses the electron beam 202 emitted from the electron gun 201. A deflector 204 deflects the focused electron beam 202. An ExB deflector 205 deflects low-energy electrons emitted from a sample 209 and directs them toward a low-energy electron detector 206. An objective lens 207 forms an image of the deflected electron beam 202 on the sample 209.

[0016] The XY stage 210 is configured to transport the sample 209 so that the electron beam 202 can be irradiated onto any position on the sample 209 .

[0017] The low-energy electron detector 206 detects low-energy electrons emitted from the sample 209 irradiated with the electron beam 202. The high-energy electron detector 208 detects high-energy electrons emitted from the sample 209 irradiated with the electron beam 202.

[0018] The low-energy electrons detected by the low-energy electron detector 206 and the high-energy electrons detected by the high-energy electron detector 208 are converted into digital signals by an image generating unit 211 equipped with an A / D converter. The image generating unit 211 generates a low-energy electron detector image (hereinafter referred to as a low-energy electron image) based on the low-energy electron detection signal, and generates a high-energy electron detector image (hereinafter referred to as a high-energy electron image) based on the high-energy electron detection signal.

[0019] The calculation unit 212 includes a processor such as a CPU (Central Processing Unit) that performs calculation processing, and a storage device that stores images. The calculation unit 212 receives the converted digital image, stores it in the storage device, and performs processing such as image processing and pattern matching.

[0020] The input / output unit 213 is composed of an input unit having input means such as a mouse and a keyboard through which the user inputs instructions to the pattern measurement system 1000, and an output unit having a display that displays a screen. The input / output unit 213 provides the user with a GUI (Graphical User Interface) that displays an observed image and a GUI through which the user specifies an extraction region.

[0021] The design system 214 is configured with non-volatile memory to store the extracted images, which are used in pattern matching.

[0022] 2 is a flowchart illustrating the operation of the pattern measurement system 1000. Each step in FIG. 2 will be described below.

[0023] (FIG. 2: Step S301) The calculation unit 212 receives a low-energy electron image converted from the detection signal of the low-energy electron detector 206 and a high-energy electron image converted from the detection signal of the high-energy electron detector 208, and stores them in a storage device for storing images. Examples of a structural diagram and an electron image of the sample will be shown again in FIGS. 3 and 4, which will be described later.

[0024] (Figure 2: Step S302) The user manually specifies the measurement region to be extracted. On the GUI provided by the input / output unit 213, the user marks the outline of the measurement region on the low-energy electron image or the high-energy electron image and operates a button to extract the measurement region. The calculation unit 212 associates the region surrounded by the outline with an area in the high-energy electron image and an area in the low-energy electron image, and performs a masking process to replace the brightness values ​​of pixels in the corresponding area with 0. The calculation unit 212 saves the masked image in a storage device. In this embodiment, the upper layer region is the measurement region. The GUI for extracting the measurement region and the masking process are shown again in Figures 5 and 6, which will be described later.

[0025] (FIG. 2: step S303) The calculation unit 212 adjusts the contrast of the high-energy electron image before masking processing, using the maximum and minimum brightness values ​​of the low-energy electron image after masking processing as correction parameters. Also, using the maximum and minimum brightness values ​​of the high-energy electron image after masking processing as correction parameters, it adjusts the contrast of the low-energy electron image before masking processing. Through the above processing, the image quality of the low-energy electron image and the image quality of the high-energy electron image can be made closer to each other. The flow for adjusting the image quality of the low-energy electron image and the high-energy electron image, and the state after adjustment, are shown again in FIGS. 7 and 8, which will be described later.

[0026] (FIG. 2: Step S304) The calculation unit 212 acquires a difference image between the image quality adjusted low-energy electron image and the high-energy electron image. This step reduces signals from the lower layers and generates an image that extracts patterns from the upper layers. The difference image will be shown again in FIG. 9, which will be described later.

[0027] (FIG. 2: Step S305) The calculation unit 212 stores the difference image obtained in step S304 in the design system as a template image for pattern matching. The calculation unit 212 can also measure dimensions such as line width for the difference image.

[0028] (FIG. 2: Step S306) The calculation unit 212 performs pattern matching at the measurement position on the low-energy electron image or the high-energy electron image using the template image stored in step S305, and measures the overlay error between the circuit pattern in the upper layer and the circuit pattern in the lower layer. Alternatively, the dimensions and area of ​​the circuit pattern in the upper layer may be measured using an image from which the circuit pattern in the lower layer has been removed.

[0029] 3 is a plan view showing the structure of a silicon wafer sample. Vertical line patterns are formed on the upper layer, horizontal line patterns are formed on the lower layer, and the remaining area is the bottom pattern, i.e., the background.

[0030] 4A is an example of a low-energy electron image converted from the detection signal of the low-energy electron detector 206. In a sample having a multi-layer structure, the upper layer has a brighter brightness and the lower layer has a darker brightness.

[0031] 4B is an example of a high-energy electron image converted from the detection signal of the high-energy electron detector 208. When the height difference between the upper and lower layers is small, the contrast between the upper and lower layers decreases due to the nature of the high-energy electron image reflecting the shape of the sample in the height direction.

[0032] 5 is a diagram showing a GUI for extracting a measurement region. For example, the user uses the mouse of the input / output unit 213 to operate the electron image switching button 215 on the display showing the GUI, and a high-energy electron image capturing button 216 and a low-energy electron image capturing button 217 are dropped down and displayed. In this embodiment, the measurement region to be extracted is the upper layer, so the user clicks the low-energy electron image capturing button 217. This causes a low-energy electron image to be displayed in the image display region 219. The user selects one or more rectangular regions 220 that include the upper layer on the low-energy electron image and clicks the masking region setting button 218. The calculation unit 212 sets the pixels within the selected region as the masking region.

[0033] 6A is a diagram showing an example of performing masking processing on a low-energy electron image. The calculation unit 212 associates the masking region (rectangular region 220) on the GUI shown in FIG. 5 with the low-energy electron image. The brightness values ​​of pixels in the masking region on the low-energy electron image are set to 0, and a new image is generated. FIG. 6A shows the result.

[0034] Figure 6B is a diagram showing an example of performing masking processing on a low-energy electron image. As in Figure 6A, the calculation unit 212 performs masking processing on a high-energy electron image. A masking region (rectangular region 220) is associated with the high-energy electron image. The brightness values ​​of pixels in the masking region on the high-energy electron image are set to 0, and a new image is generated. Figure 6B shows the result.

[0035] 7 is a flowchart illustrating the procedure for adjusting the image quality of the low-energy electron image and the image quality of the high-energy electron image in step S303. Each step in FIG. 7 will be described in detail below.

[0036] (FIG. 7: Step S401) The calculation unit 212 reads the masked low-energy electron image and the masked high-energy electron image.

[0037] (FIG. 7: Step S402) The calculation unit 212 acquires the brightness values ​​of all pixels in the masked low-energy electron image and the masked high-energy electron image, and calculates the minimum and maximum brightness values ​​other than 0. The minimum and maximum brightness values ​​are used as parameters for image quality adjustment.

[0038] (FIG. 7: Step S403) The calculation unit 212 reads the low-energy electron image before masking processing and the high-energy electron image before masking processing, and obtains the brightness value of each pixel.

[0039] (FIG. 7: Step S404) The calculation unit 212 adjusts the contrast of both the low-energy electron image and the high-energy electron image so that the image quality of the two images approaches each other.

[0040] (FIG. 7: Step S404: Image Quality Adjustment of Low-Energy Electron Image) The image quality adjustment of the low-energy electron image uses parameters obtained from the high-energy electron image after masking processing in step S402. For example, the image quality adjustment can be performed using an image quality adjustment formula such as Equation 1.

[0041] Dst_L = (Max_H - Min_H) × Src_L (Formula 1) Dst_L: Brightness value of the low-energy electron image after image quality adjustment Src_L: Brightness value of the low-energy electron image before image quality adjustment Max_H: Maximum brightness value of the high-energy electron image after masking Min_H: Minimum brightness value other than 0 of the high-energy electron image after masking

[0042] (FIG. 7: Step S404: Image Quality Adjustment of High-Energy Electron Image) The image quality adjustment of the high-energy electron image uses the parameters obtained from the low-energy electron image after masking processing in step S402. For example, the image quality adjustment can be performed using an image quality adjustment formula such as (Formula 2).

[0043] Dst_H = (Max_L - Min_L) × Src_H (Equation 2) Dst_H: Brightness value of the high-energy electron image after image quality adjustment Src_H: Brightness value of the high-energy electron image before image quality adjustment Max_L: Maximum brightness value of the low-energy electron image after masking Min_L: Minimum brightness value other than 0 of the low-energy electron image after masking

[0044] Figure 8A shows the appearance of a low-energy electron image after image quality adjustment. Figure 8B shows the appearance of a high-energy electron image after image quality adjustment. The image quality of the lower layer / background region in the low-energy electron image after image quality adjustment is equivalent to the image quality of the lower layer / background region in the high-energy electron image after image quality adjustment. "Equal image quality" here means that the brightness values ​​are approximately the same. According to Equations 1 and 2, the contrast of the high-energy electron image and the contrast of the low-energy electron image can be made the same, except for the masked portion.

[0045] 9 shows an example of the difference image obtained in step S304. The calculation unit 212 obtains the brightness values ​​of all pixels in the low-energy electron image after image quality adjustment and the high-energy electron image after image quality adjustment, and calculates the difference image using the calculation formula shown in Equation 3. In the difference image, the signal in the lower layer is reduced and the signal in the upper layer is emphasized.

[0046] Dst_D = Dst_L - Dst_H Dst_D: Brightness value of the difference image Dst_L: Brightness value of the low-energy electron image after image quality adjustment Dst_H: Brightness value of the high-energy electron image after image quality adjustment

[0047] The calculation unit 212 further uses the minimum and maximum luminance values ​​obtained in step S402 to suppress the luminance value of each pixel to 255 or less through Equation 4, thereby achieving normalization of the image.

[0048] Dst_N = Dst_D / {(Max_L - Min_L) × (Max_H - Min_H)} Dst_N: Brightness value of the difference image after normalization Dst_D: Brightness value of the difference image before normalization Dst_H: Brightness value of the high-energy electron image after image quality adjustment Max_L: Maximum brightness value of the low-energy electron image after masking Min_L: Minimum non-zero brightness value of the low-energy electron image after masking Max_H: Maximum brightness value of the high-energy electron image after masking Min_H: Minimum non-zero brightness value of the high-energy electron image after masking

[0049] Summary of First Embodiment In the pattern measurement system 1000 according to the first embodiment, the calculation unit 212 brings the contrast between the observation image of the upper layer (high-energy electron image) and the observation image of the lower layer (low-energy electron image) closer to each other. The calculation unit 212 generates the observation image of the upper layer using both images with the contrasts brought closer to each other. This makes it possible to separate the lower layer, which is superimposed on the upper layer on the low-energy electron image, from the low-energy electron image.

[0050] Second Embodiment In the first embodiment, the low-energy electron image and the high-energy electron image are detected by detectors for detecting emitted electrons in two different energy bands. In a second embodiment of the present disclosure, the sample is irradiated with electron beams having different acceleration voltages, thereby acquiring the low-energy electron image and the high-energy electron image using only one detector. The other configurations are the same as those of the first embodiment.

[0051] FIG. 10 is a diagram showing a GUI for instructing the pattern measurement system 1000 to acquire electron images using electron beams with different acceleration voltages. The user inputs a voltage value into the acceleration voltage input box 221 on a GUI such as that shown in FIG. 10 provided by the input / output unit 213. When the image capture button 222 is clicked, the electron gun 201 emits the electron beam 202 at the input voltage value. The image display area 225 displays the acquired observation image. The higher the voltage, the more high-energy electrons the detector detects. When the user clicks the high-energy electron image save button 223, the observation image at that time is stored as a high-energy electron image in the storage device of the calculation unit 212. Similarly, when the user clicks the low-energy electron image save button 224, the observation image at that time is stored as a low-energy electron image in the storage device of the calculation unit 212.

[0052] <Regarding Modifications of the Present Disclosure> The present disclosure is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present disclosure, and it is not necessary to include all of the configurations described. Furthermore, a part of one embodiment can be replaced with a configuration of another embodiment. Furthermore, a configuration of another embodiment can be added to a configuration of one embodiment. Furthermore, a part of the configuration of each embodiment can be added to, deleted from, or substituted for a part of the configuration of another embodiment.

[0053] In the above embodiment, the lower-layer pattern of the patterns contained in the low-energy image is removed, thereby leaving only the upper-layer pattern. Alternatively, the upper-layer pattern of the patterns contained in the low-energy image may be removed, thereby leaving only the lower-layer pattern. For example, by irradiating a beam with an energy even lower than the low-energy beam in the above embodiment, an electron image can be obtained in which only the upper-layer pattern remains. Then, by obtaining a difference image between the two electron images, only the lower-layer pattern can be left.

[0054] In the above embodiments, the image generation unit 211 and the calculation unit 212 can be configured by hardware such as a circuit device that implements these functions, or can be configured by a calculation device such as a CPU (Central Processing Unit) that executes software that implements these functions.

[0055] 200: electron optical unit, 201: electron gun, 202: electron beam, 203: focusing lens, 204: deflector, 205: ExB deflector 205, 206: low energy electron detector, 207: objective lens, 208: high energy electron detector, 209: sample, 210: XY stage, 211: image generation unit, 212: calculation unit, 213: input / output unit, 214: design system, 215: electron image switching button, 216: high energy electron image capturing button, 217: low energy electron image capturing button, 218: masking area setting button, 219: image display area, 1000: pattern measurement system.

Claims

1. An image quality adjustment device that adjusts the image quality of an observation image of a sample arranged in overlapping layers, comprising a processor that adjusts the image quality of the observation image, wherein the processor receives as the observation image a first image generated based on the output of a first detector that detects electrons emitted from the sample, and the processor receives as the observation image a second image generated based on the output of a second detector different from the first detector that detects electrons emitted from the sample, and the processor performs image quality adjustment to bring the image quality of the first image and the image quality of the second image closer to each other, and the processor uses the first image that has been subjected to the image quality adjustment and the second image that has been subjected to the image quality adjustment to remove from the first image, of a pattern in a first layer of the sample contained in the first image, and a pattern in a second layer of the sample below the first layer contained in the first image, the pattern in the first layer or the pattern in the second layer.

2. The image quality adjustment device according to claim 1, characterized in that the first detector is configured to detect electrons emitted from the sample by irradiating the sample with a charged particle beam having a first energy, the second detector is configured to detect electrons emitted from the sample by irradiating the sample with a charged particle beam having a second energy greater than the first energy, and the processor removes from the first image a portion of the first image that is generated based on the output of the second detector by removing a pattern in the second layer from the first image.

3. The image quality adjustment device described in claim 1, characterized in that the first detector is configured to detect electrons emitted from the sample by irradiating the sample with a charged particle beam having a first energy, the second detector is configured to detect electrons emitted from the sample by irradiating the sample with a charged particle beam having a second energy greater than the first energy, and the processor removes from the first image a portion of the first image that is generated based on the output of the first detector by removing a pattern in the first layer from the first image.

4. The image quality adjustment device described in claim 1, characterized in that the processor receives an area specification that specifies an area to be extracted on the observed image on the first image or the second image, the processor performs a masking process that removes the area specified by the area specification on the first image and the second image, respectively, and the processor performs the image quality adjustment using the first image that has been subjected to the masking process and the second image that has been subjected to the masking process.

5. The image quality adjustment device according to claim 4, characterized in that the processor uses the first image that has been subjected to the masking process to perform the image quality adjustment on the second image that has not been subjected to the masking process, and the processor uses the second image that has been subjected to the masking process to perform the image quality adjustment on the first image that has not been subjected to the masking process.

6. The image quality adjustment device described in claim 5, characterized in that the processor performs the image quality adjustment on the second image by using the first image that has been subjected to the masking process to correct the contrast of the second image that has not been subjected to the masking process so that it approaches the contrast of the first image that has been subjected to the masking process, and the processor performs the image quality adjustment on the first image by using the second image that has been subjected to the masking process to correct the contrast of the first image that has not been subjected to the masking process so that it approaches the contrast of the second image that has been subjected to the masking process.

7. The image quality adjustment device described in claim 5, characterized in that the processor performs the image quality adjustment on the second image by correcting the luminance value of the second image that has not been subjected to the masking process using the maximum luminance value of the first image that has been subjected to the masking process and the minimum luminance value of the first image that has been subjected to the masking process so that the luminance value of the second image that has not been subjected to the masking process approaches the luminance value of the first image that has not been subjected to the masking process, and the processor performs the image quality adjustment on the first image by correcting the luminance value of the first image that has not been subjected to the masking process using the maximum luminance value of the second image that has been subjected to the masking process and the minimum luminance value of the second image that has been subjected to the masking process so that the luminance value of the first image that has not been subjected to the masking process approaches the luminance value of the second image that has not been subjected to the masking process.

8. The image quality adjustment device according to claim 5, wherein the image quality adjustment adjusts the image quality of the portion other than the portion subjected to the masking process.

9. The image quality adjustment device according to claim 4, wherein said processor performs said masking process by making the brightness values ​​of pixels in the area specified by said area specification equal to or less than a threshold value.

10. The image quality adjustment device of claim 1, characterized in that the processor removes the pattern in the first layer or the pattern in the second layer from the first image by generating a difference image between the first image after the image quality adjustment and the second image after the image quality adjustment.

11. The image quality adjustment device of claim 7, characterized in that the processor removes the pattern in the first layer or the pattern in the second layer from the first image by generating a difference image between the first image after the image quality adjustment and the second image after the image quality adjustment, and the processor normalizes the brightness value of the difference image using the maximum brightness value of the first image after the masking process, the minimum brightness value of the first image after the masking process, the maximum brightness value of the second image after the masking process, and the minimum brightness value of the second image after the masking process.

12. The image quality adjustment device according to claim 1, characterized in that the processor performs at least one of the following using the first image from which the pattern in the first layer or the pattern in the second layer has been removed: measure the overlay error between the first layer and the second layer; measure the dimensions of the pattern included in the first image; and measure the area of ​​the pattern included in the first image.

13. The image quality adjustment device according to claim 1, characterized in that the image quality adjustment device is configured as a charged particle beam device that obtains the observation image by irradiating the sample with a charged particle beam.

14. The image quality adjustment device according to claim 13, characterized in that the image quality adjustment device comprises a detector that detects electrons emitted from the sample when the sample is irradiated with a charged particle beam, the processor receives a voltage specification that specifies an acceleration voltage of the charged particle beam, the processor generates the first image using the result detected by the detector when the acceleration voltage is a first voltage, and the processor generates the second image using the result detected by the detector when the acceleration voltage is a second voltage.

15. An image quality adjustment method for adjusting the image quality of an observation image of a sample arranged in overlapping layers, comprising the steps of: receiving, as the observation image, a first image generated based on the output of a first detector that detects electrons emitted from the sample; receiving, as the observation image, a second image generated based on the output of a second detector different from the first detector that detects electrons emitted from the sample; performing image quality adjustment to bring the image quality of the first image and the image quality of the second image closer to each other; and using the first image after the image quality adjustment and the second image after the image quality adjustment, removing from the first image, of a pattern in the first layer of the sample contained in the first image, or a pattern in the second layer of the sample below the first layer contained in the first image, the pattern in the first layer or the pattern in the second layer.

Images