CN117934487B - Detection method and device for scanning noise and error, electronic equipment and medium - Google Patents
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Abstract
The invention relates to a detection method, a detection device, electronic equipment and a detection medium for scanning noise and errors, belonging to the technical field of precision detection imaging, wherein the method comprises the following steps: acquiring section data of the whole scanning period of a sample to be tested; envelope analysis is carried out on the section data, and envelope line type and surface morphology information of the section data are determined; carrying out correlation calculation on the envelope line to obtain a correlation curve, and determining a nonlinear sampling error according to the correlation curve; and determining noise points by adopting a preset derivative method according to the envelope line type based on the surface morphology information, and eliminating. The invention solves the technical problems of low feasibility and detection precision of data caused by difficult detection and rejection of noise or nonlinear interference in the scanning interferometry result in the prior art.
Description
Technical Field
The present invention relates to the field of precision detection imaging technologies, and in particular, to a method, an apparatus, an electronic device, and a medium for detecting scanning noise and errors.
Background
Scanning interferometry is a surface height measurement technique widely used for surface topography measurement of stepped microstructures in the optical and integrated circuit fields. Because the critical dimensions of these microstructures are on the order of micrometers or sub-micrometers, by taking advantage of the low coherence of the white light source, an interference pattern will only appear when the path length difference falls within the coherence length, and thus it can achieve accurate measurements on the order of micrometers or sub-micrometers. Due to the fact that measurement personnel do not normalize the measurement process, environmental disturbance, dust of a sample and the like, occasional noise points are unavoidable, the noise points bring larger errors to the calculation of surface roughness and surface morphology, in addition, the piezoelectric displacement device cannot guarantee 100% of linear travel, the influence of the noise can be reduced by median filtering in common filtering means, but the size of a filtering core of the median filtering is different from different samples, and the determination is difficult. And the data of the normal area can be filtered through median filtering, so that the calculated value of the surface roughness of the sample can be reduced, and the accuracy of the white light coherent scanning detection data is destroyed.
Disclosure of Invention
In view of the foregoing, it is necessary to provide a method, an apparatus, an electronic device and a medium for detecting scanning noise and errors, so as to solve the technical problems in the prior art that noise or nonlinear interference in scanning interferometry results is difficult to detect and reject, thereby resulting in low feasibility and detection accuracy of data.
In order to solve the above problems, the present invention provides a method for detecting scanning noise and error, comprising:
acquiring section data of the whole scanning period of a sample to be tested;
envelope analysis is carried out on the section data, and envelope line type and surface morphology information of the section data are determined;
Carrying out correlation calculation on the envelope line to obtain a correlation curve, and determining a nonlinear sampling error according to the correlation curve;
And determining noise points by adopting a preset derivative method according to the envelope line type based on the surface morphology information, and eliminating.
In one possible implementation manner, the performing envelope analysis on the section data to determine envelope type and surface topography information of the section data includes:
Acquiring light intensity change data of the section data pixels, and determining the concentration degree and the total intensity of the light intensity change data;
determining an envelope curve of the light intensity change data by adopting a preset spline interpolation method;
and determining the maximum intensity value of all pixel points based on the envelope curve, and constructing a morphology matrix.
In one possible implementation manner, the calculating the correlation degree of the envelope line to obtain a correlation curve, and determining a nonlinear sampling error according to the correlation curve includes:
carrying out correlation calculation on the envelope line type to obtain a correlation curve;
Determining a coarse error point according to the correlation curve;
And determining nonlinear sampling errors of the sample to be detected based on the coarse error points.
In one possible implementation manner, the determining, based on the surface topography information, a noise point according to the envelope line type by adopting a preset derivative method, and removing the noise point includes:
Obtaining a difference value between the envelope type and a preset envelope type;
Determining noise points according to the differential values;
Conducting derivation processing on the envelope line type, and determining the zero point position of the first derivative of the envelope line type;
And determining a pixel intensity maximum value and a noise point according to the number of the zero positions.
In one possible implementation manner, the determining the maximum pixel intensity value and the noise point according to the number of the zero positions includes:
if the number of the zero positions is 1, determining the zero positions as maximum pixel intensity values;
If the number of the zero positions is a plurality of, judging the relation between the difference value among the zero positions and a preset threshold value interval;
If the difference value among the zero positions is located in a first preset threshold value interval, taking the first zero position as a pixel intensity maximum value and a noise point;
And if the difference value among the plurality of zero positions is in a second preset threshold value interval, taking the second zero position as a pixel intensity maximum value and a noise point.
In one possible implementation, the first preset threshold interval is [ -10,0], and the second preset threshold interval is [0, 10].
In one possible implementation, the preset envelope is a gaussian envelope.
In a second aspect, the present invention further provides a device for detecting scanning noise and error, including:
The acquisition module is used for acquiring section data of the whole scanning period of the sample to be detected;
The envelope processing module is used for carrying out envelope analysis on the section data and determining envelope line type and surface morphology information of the section data;
the nonlinear sampling error determining module is used for carrying out correlation calculation on the envelope line to obtain a correlation curve and determining nonlinear sampling errors according to the correlation curve;
and the noise point determining module is used for determining noise points by adopting a preset derivative method according to the envelope line type based on the surface morphology information and removing the noise points.
In a third aspect, the present invention also provides an electronic device, including: a processor and a memory;
The memory has stored thereon a computer readable program executable by the processor;
The processor, when executing the computer readable program, implements the steps in the method of detecting scanning noise and errors as described above.
In a fourth aspect, the present invention also provides a computer-readable storage medium storing one or more programs executable by one or more processors to implement the steps in the method of detecting scanning noise and errors as described above.
The beneficial effects of the invention are as follows: firstly, cross section data of the whole scanning period of a sample to be tested are obtained, the envelope curve type and the surface morphology information of the cross section data are determined through envelope analysis of the cross section data, then the correlation degree calculation is carried out on the envelope curve type, so that nonlinear scanning errors are determined, finally, noise points are determined through a preset derivative method and removed, artificial image post-processing is avoided, and the test analysis efficiency is greatly improved. From the practical application scene, complex and time-consuming technical means such as high-pass filtering are not used, the complex calculation process of signal conversion is avoided, noise points are removed accurately, and original real data are reserved to the maximum extent.
Drawings
FIG. 1 is a flow chart of a method for detecting scanning noise and error according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a method according to an embodiment of step S102 in FIG. 1;
FIG. 3 is an envelope diagram of collected data in the method for detecting scanning noise and error provided by the invention;
FIG. 4 is a three-dimensional morphology diagram of collected data in the method for detecting scanning noise and errors provided by the invention;
FIG. 5 is a flowchart of a method for detecting scanning noise and error according to an embodiment of the present invention, step S104;
FIG. 6 is a schematic diagram showing correlation of nonlinear error data in the method for detecting scanning noise and error provided by the invention;
FIG. 7 is a schematic diagram of an embodiment of a detection device for scanning noise and error according to the present invention;
FIG. 8 is a schematic diagram of an operating environment of an embodiment of an electronic device provided by the present invention.
Detailed Description
The following detailed description of preferred embodiments of the application is made in connection with the accompanying drawings, which form a part hereof, and together with the description of the embodiments of the application, are used to explain the principles of the application and are not intended to limit the scope of the application.
In one embodiment of the present invention, a method for detecting scanning noise and error is disclosed, please refer to fig. 1, which includes:
s101, acquiring section data of a whole scanning period of a sample to be detected;
S102, carrying out envelope analysis on the section data, and determining envelope type and surface morphology information of the section data;
s103, performing correlation calculation on the envelope line to obtain a correlation curve, and determining a nonlinear sampling error according to the correlation curve;
s104, determining noise points by adopting a preset derivative method according to the envelope line type based on the surface morphology information, and eliminating.
In the embodiment, firstly, the section data of the whole scanning period of the tested sample is obtained, the envelope type and the surface morphology information of the section data are determined by carrying out envelope analysis on the section data, then the correlation degree calculation is carried out on the envelope type, so that the nonlinear scanning error is determined, finally, the noise point is determined by adopting a preset derivative method and is removed, the post-processing of the artificial image is avoided, and the testing and analyzing efficiency is greatly improved. From the practical application scene, complex and time-consuming technical means such as high-pass filtering are not used, the complex calculation process of signal conversion is avoided, noise points are removed accurately, and original real data are reserved to the maximum extent.
In step S101, data is obtained based on white light microscopic interference. In other embodiments, holographic interference, low coherence light source scanning, etc. may be used to obtain the optical signal, which is not limited herein.
In a specific embodiment, the full-period section data of the sample to be tested is obtained by setting equidistant scanning sampling under a certain scanning step h. Preferably, h is generally 1/8 or 1/4 of the center wavelength λ of the light source.
In step S102, envelope analysis is a method for extracting potential features in the signal, and is commonly used for processing waveform data, such as section data, and determining the envelope of the data by performing envelope analysis on the section data to reveal surface topography information. In this embodiment, the section data represents the height data of the sample to be measured.
In some embodiments, the performing envelope analysis on the section data to determine extremum features and surface topography information of the section data, referring to fig. 2, includes:
s201, acquiring light intensity change data of the section data pixels, and determining concentration and total intensity of the light intensity change data;
s202, determining an envelope curve of the light intensity change data by adopting a preset spline interpolation method;
s203, determining the maximum intensity value of all pixel points based on the envelope curve, and constructing a morphology matrix.
In this embodiment, light intensity variation data of pixels are extracted, and the concentration and total intensity of the light intensity variation data are obtained; calculating an envelope curve from the light intensity change data by using a spline interpolation method, wherein the envelope curve is a Gaussian curve, and the spline interpolation envelope calculation formula is that
Wherein a i,bi,ci,di is an interpolation coefficient, (x i,yi)(xi+1,yi+1) is light intensity data corresponding to a sampling position in the light intensity data, m i、mi+1 is a second derivative of an interpolation curve g i、gi+1, h=x i+1-xi is an interpolation step length, the obtained envelope curve is shown in fig. 3, there are 1 extreme value and only 1 extreme value of an envelope with a gaussian envelope line, irregular line type appears in dust and sample surface defects, and the envelope of a noise signal tends to be a bimodal envelope.
And determining the maximum intensity of all pixel points, and constructing the morphology moment.
It should be noted that the extreme points provide important information about the surface topography, including raised, recessed locations, height differences, and quality and characteristics of the surface. By analyzing the extreme points, the surface structure, the morphological characteristics and the quality condition of the sample can be more deeply known.
In some embodiments, the calculating the correlation of the envelope curve to obtain a correlation curve, and determining a nonlinear sampling error according to the correlation curve includes:
carrying out correlation calculation on the envelope line type to obtain a correlation curve;
Determining a coarse error point according to the correlation curve;
And determining nonlinear sampling errors of the sample to be detected based on the coarse error points.
In this embodiment, correlation screening is performed on the collected data, and nonlinear sampling errors of the sample to be measured are determined according to correlation linearity: the correlation degree of the same acquisition group is maintained in a change interval, and the jump point and the coarse error are nonlinear sampling errors of the displacement driver of the sample to be detected, wherein the calculation formula of the correlation degree is as follows:
Wherein I i,Ii+2 represents the I-th image and i+2-th image data of the dataset, and n is the number of images of the dataset. The calculated correlation is compared with a pearson correlation coefficient comparison table. For coherent scanning interferometry, the scanning steps correspond to changes in optical path difference, which corresponds to changes in phase, i.e., the scanning steps correspond to changes in phase, which can be expressed as:
Wherein lambda is the center wavelength of the light source, h represents the scanning step, To vary the phase.
Further, referring to the correlation diagram of the nonlinear error data shown in fig. 4, the correlation of the same acquisition group should be maintained within a variation range, where the variation range depends on the instrument noise and the natural vibration of the acquisition instrument, and in general, the variation range is [ -0.05, +0.05].
In some embodiments, the determining noise points according to the envelope pattern by using a preset derivative method based on the surface topography information, and performing rejection, referring to fig. 5, includes:
S501, obtaining a difference value between the envelope type and a preset envelope type;
s502, determining noise points according to the differential value;
S503, conducting derivative processing on the envelope line type, and determining the zero point position of the first derivative of the envelope line type;
s504, determining a pixel intensity maximum value and a noise point according to the number of the zero positions.
In this embodiment, a difference value between a preset envelope type and an actual envelope type in the surface topography information is calculated, and the degree of the phase difference between the actual envelope type and the preset model is determined by the difference value. The position of the noise point is then determined according to the magnitude of the differential value. Noise points typically represent outliers or noise disturbances in the surface topography information. By determining the position of the noise point, the method can help us to remove the adverse effect in the data, so that more accurate morphology information is obtained. And finally, determining noise points and maximum pixel intensity values according to the number of zero positions. If there are fewer zeros, this may represent a smoother envelope, lacking significant intensity maxima. If there are more zeros, this may represent more intensity maxima and noise points. Noise points and maximum pixel intensity values can be identified and removed according to specific conditions.
In some embodiments, the determining the pixel intensity maxima and noise points from the number of zero positions includes:
if the number of the zero positions is 1, determining the zero positions as maximum pixel intensity values;
If the number of the zero positions is a plurality of, judging the relation between the difference value among the zero positions and a preset threshold value interval;
If the difference value among the zero positions is located in a first preset threshold value interval, taking the first zero position as a pixel intensity maximum value and a noise point;
And if the difference value among the plurality of zero positions is in a second preset threshold value interval, taking the second zero position as a pixel intensity maximum value and a noise point.
In this embodiment, if the difference between the plurality of zero positions is located in the first preset threshold interval, the first zero position is taken as the maximum pixel intensity value and the noise point, where if the difference between the plurality of zero positions is located in the first preset threshold interval, it is indicated that the difference between the two zero positions is very small, and it is likely that the difference is the characteristic value on the sample surface. In this case the first zero position is taken as the pixel intensity maxima and noise point. If the difference value between the plurality of zero positions is in the second preset threshold value interval, the second zero position is taken as the pixel intensity maximum value and the noise point, wherein if the difference value between the plurality of zero positions is in the second preset threshold value interval, the difference value between the plurality of zero positions is larger, and the difference value is possibly caused by noise interference. Therefore, the second zero point position is taken as the pixel intensity maximum value and the noise point at this time.
In a specific embodiment, if the difference between the zero positions is between the threshold intervals [ -10,0], the zero position with the latter derivative of 0 is taken to replace the maximum value; if the zero position is between the threshold intervals [0, 10], taking the zero position with the previous derivative of 0 as the maximum value. Fig. 6 shows a schematic representation of the three-dimensional topography of the local surface of a circuit board obtained by the method of the present invention.
Based on the above method for detecting scanning noise and error, the present invention further provides a device for detecting scanning noise and error, referring to fig. 7, including: an acquisition module 710, an envelope processing module 720, a nonlinear sampling error determination module 730, and a noise point determination module 740.
An acquisition module 710, configured to acquire cross-section data of a full period of scanning of a sample to be measured;
The envelope processing module 720 is configured to perform envelope analysis on the section data, and determine envelope type and surface morphology information of the section data;
the nonlinear sampling error determining module 730 is configured to perform correlation calculation on the envelope line to obtain a correlation curve, and determine a nonlinear sampling error according to the correlation curve;
the noise point determining module 740 is configured to determine noise points by using a preset derivative method according to the envelope based on the surface topography information, and reject the noise points.
As shown in fig. 8, based on the method for detecting the scanning noise and the error, the invention further provides an electronic device, which can be a computing electronic device such as a mobile terminal, a desktop computer, a notebook computer, a palm computer, a server and the like. The electronic device includes a processor 810, a memory 820, and a display 830. Fig. 8 shows only some of the components of the electronic device, but it should be understood that not all of the illustrated components are required to be implemented and that more or fewer components may be implemented instead.
The memory 820 may be an internal storage unit of the electronic device in some embodiments, such as a hard disk or memory of the electronic device. The memory 820 may also be an external storage electronic device of the electronic device in other embodiments, such as a plug-in hard disk provided on the electronic device, a smart memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD), or the like. Further, the memory 820 may also include both internal storage units and external storage electronic devices. The memory 820 is used for storing application software installed in the electronic device and various data, such as program codes for installing the electronic device. The memory 820 may also be used to temporarily store data that has been output or is to be output. In one embodiment, the memory 820 stores a scan noise and error detection program 840, and the scan noise and error detection program 840 is executable by the processor 810 to implement the scan noise and error detection method according to the embodiments of the present application.
The processor 810 may in some embodiments be a central processing unit (Central Processing Unit, CPU), microprocessor or other data processing chip for executing program code or processing data stored in the memory 820, for example, performing scan noise and error detection methods, etc.
The display 830 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like in some embodiments. Display 830 is used to display information at the detection electronics of the scanning noise and error and to display a visual user interface. The components 810-830 of the electronic device communicate with each other over a system bus.
Those skilled in the art will appreciate that all or part of the flow of the methods of the embodiments described above may be accomplished by way of a computer program to instruct associated hardware, where the program may be stored on a computer readable storage medium. Wherein the computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory, etc.
The present invention is not limited to the above-mentioned embodiments, and any changes or substitutions that can be easily understood by those skilled in the art within the technical scope of the present invention are intended to be included in the scope of the present invention.
Claims (8)
1. The method for detecting the scanning noise and the error is characterized by comprising the following steps:
acquiring section data of the whole scanning period of a sample to be tested;
envelope analysis is carried out on the section data, and envelope line type and surface morphology information of the section data are determined;
Carrying out correlation calculation on the envelope line to obtain a correlation curve, and determining a nonlinear sampling error according to the correlation curve;
Determining noise points by adopting a preset derivative method according to the envelope line type based on the surface morphology information; the method comprises the steps of obtaining a differential value between the envelope type and a preset envelope type; determining noise points according to the differential values; conducting derivation processing on the envelope line type, and determining the zero point position of the first derivative of the envelope line type; determining a maximum pixel intensity value and a noise point according to the number of the zero positions; if the number of the zero positions is 1, determining the zero positions as maximum pixel intensity values; if the number of the zero positions is a plurality of, judging the relation between the difference value among the zero positions and a preset threshold value interval; if the difference value among the zero positions is located in a first preset threshold value interval, taking the first zero position as a pixel intensity maximum value and a noise point; and if the difference value among the plurality of zero positions is in a second preset threshold value interval, taking the second zero position as a pixel intensity maximum value and a noise point.
2. The method for detecting scanning noise and error according to claim 1, wherein said performing envelope analysis on said section data to determine envelope type and surface topography information of said section data comprises:
Acquiring light intensity change data of the section data pixels, and determining the concentration degree and the total intensity of the light intensity change data;
determining an envelope curve of the light intensity change data by adopting a preset spline interpolation method;
and determining the maximum intensity value of all pixel points based on the envelope curve, and constructing a morphology matrix.
3. The method for detecting scanning noise and error according to claim 1, wherein said performing a correlation calculation on the envelope curve to obtain a correlation curve, and determining a nonlinear sampling error according to the correlation curve comprises:
carrying out correlation calculation on the envelope line type to obtain a correlation curve;
Determining a coarse error point according to the correlation curve;
And determining nonlinear sampling errors of the sample to be detected based on the coarse error points.
4. The method of claim 1, wherein the first predetermined threshold interval is [ -10,0], and the second predetermined threshold interval is [0, 10].
5. The method for detecting scanning noise and error according to claim 1, wherein the predetermined envelope is a gaussian envelope.
6. A scanning noise and error detection apparatus, comprising:
The acquisition module is used for acquiring section data of the whole scanning period of the sample to be detected;
The envelope processing module is used for carrying out envelope analysis on the section data and determining envelope line type and surface morphology information of the section data;
the nonlinear sampling error determining module is used for carrying out correlation calculation on the envelope line to obtain a correlation curve and determining nonlinear sampling errors according to the correlation curve;
The noise point determining module is used for determining noise points by adopting a preset derivative method according to the envelope line type based on the surface morphology information; the method comprises the steps of obtaining a differential value between the envelope type and a preset envelope type; determining noise points according to the differential values; conducting derivation processing on the envelope line type, and determining the zero point position of the first derivative of the envelope line type; determining a maximum pixel intensity value and a noise point according to the number of the zero positions; if the number of the zero positions is 1, determining the zero positions as maximum pixel intensity values; if the number of the zero positions is a plurality of, judging the relation between the difference value among the zero positions and a preset threshold value interval; if the difference value among the zero positions is located in a first preset threshold value interval, taking the first zero position as a pixel intensity maximum value and a noise point; and if the difference value among the plurality of zero positions is in a second preset threshold value interval, taking the second zero position as a pixel intensity maximum value and a noise point.
7. An electronic device, comprising: a processor and a memory;
The memory has stored thereon a computer readable program executable by the processor;
The processor, when executing the computer readable program, implements the steps of the method for detecting scanning noise and errors according to any one of claims 1-5.
8. A computer-readable storage medium storing one or more programs executable by one or more processors to perform the steps in the method of detecting scanning noise and error of any of claims 1-5.
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| US7596495B2 (en) * | 2004-03-30 | 2009-09-29 | Yamaha Corporation | Current noise spectrum estimation method and apparatus with correlation between previous noise and current noise signal |
| CN111399039A (en) * | 2019-01-02 | 2020-07-10 | 无锡海斯凯尔医学技术有限公司 | Slope parameter extraction method, device and storage medium |
| WO2023130661A1 (en) * | 2022-01-07 | 2023-07-13 | 乐普（北京）医疗器械股份有限公司 | Method and apparatus for processing two-dimensional spectral doppler echocardiographic image |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7596495B2 (en) * | 2004-03-30 | 2009-09-29 | Yamaha Corporation | Current noise spectrum estimation method and apparatus with correlation between previous noise and current noise signal |
| CN111399039A (en) * | 2019-01-02 | 2020-07-10 | 无锡海斯凯尔医学技术有限公司 | Slope parameter extraction method, device and storage medium |
| WO2023130661A1 (en) * | 2022-01-07 | 2023-07-13 | 乐普（北京）医疗器械股份有限公司 | Method and apparatus for processing two-dimensional spectral doppler echocardiographic image |
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