Method for generating a reference image and use thereof

Abstract

The invention relates to a method for generating a reference image for a method for imaging a workpiece surface, wherein the reference image is generated by means of a plurality of image recordings of the surface of a reference object which are laterally displaced and / or rotated relative to one another being captured, and a repositioned image recording being generated on the basis of the captured image data and being stored. According to the invention, a masking data recording is generated by means of defining a plurality of evaluation groups, and in each of the evaluation groups one of the individual repositioned image recordings is combined in each case in pairs with a plurality of other individual repositioned image recordings by calculation, and the data recordings obtained from each of the pair combinations by calculation are combined to form a corresponding masking data recording. The masking data recording is applied to the image recordings and the thus modified image recordings are used for generating the reference image.

Description

TECHNICAL FIELD

[0001] The present invention relates to a method for generating a reference image and its use in a method for capturing and imaging the topography of a workpiece surface. BACKGROUND

[0002] In the context of the present specification, the term topography is understood to mean the surface structure of a material, a half-cell or a workpiece. In the following, reference is made to a workpiece for the sake of simplicity. In this case, the workpiece can have a complex design and comprise a plurality of elements.

[0003] The topography of a workpiece can be captured and represented by imaging methods. Various imaging aberrations can occur in the process. One of these is the so-called field curvature. If no correction is made, the occurrence of the field curvature distorts the actual topography conditions on the surface of the object to be measured. In particular in the case of topography differences which manifest themselves very small, i.e. between elevations, depressions and / or flat areas, the occurring field curvature distorts the differences relative to their actual size significantly.

[0004] The occurring field curvature can be reduced or completely eliminated by means of a so-called reference topography. For this purpose, an image recording of the surface of a reference object (reference surface, reference sample) is captured using a recording optical unit. Its image data is subsequently subtracted from the image data of the image recording obtained from the workpiece to be measured using the recording optical unit. In this way, the contributions to the field curvature contained in both the image recording of the reference object and the image recording of the workpiece cancel each other out. In this sense, it is also possible to generate a reference image for reducing the shading (reference shading image; RGB reference shading image). In this case, the data relating to the image noise (background noise; background image) is subtracted from the image of the (white) area (white image).

[0005] In order to minimize the influence of contaminations on the recording optical unit or other fault positions on or at which they occur as far as possible, a plurality of image recordings of the reference object are captured, which in each case are slightly laterally offset from one another. In order to create the reference image for the topography method, the image recordings thus obtained are subsequently combined by calculating the mean value or using the median value pixel by pixel to form the resulting topography, in this case the reference image. As a rule, the data is still filtered in the x and y directions in order to minimize the effects occurring.

[0006] The disadvantage of this procedure is that, in the case of a combination using mean value calculation and in the case of a combination using median value calculation, the image contributions of the occurring contaminations are not eliminated, but rather attenuated (see also Figure 2). The contaminating contributions of the decay can only be eliminated by subsequent strong filtering. However, such strong filtering leads to filter artefacts at the edges of the image field, is considered very cumbersome by users of image representations and acts as an additional virtual field curvature. SUMMARY

[0007] It is an object of the present application to propose an option for improving the reduction of artefacts in a reference image.

[0008] This object is achieved by a method according to the following. A method of generating a reference image for a method of imaging a workpiece surface, wherein the reference image is generated by means of:

[0009] capturing a plurality of image recordings of a surface of a reference object, wherein individual image recordings are captured from recording positions that are laterally displaced and / or rotated relative to one another,

[0010] generating and storing repositioned image recordings on the basis of captured image data of the image recordings, and

[0011] generating the reference image on the basis of the repositioned image recordings,

[0012] the masking data recordings are generated by means of defining a plurality of evaluation groups, and

[0013] in each of the evaluation groups,

[0014] - in each case, one of the individual repositioned image recordings is combined with a plurality of other individual repositioned image recordings in a pairwise manner by means of a calculation, and

[0015] - the data recordings obtained from each of the pairwise combinations by means of the calculation are combined to form a respective masking data recording, wherein structures detected in the data recordings obtained by means of the pairwise combinations are evaluated in their assignment as structures to be masked, and detected structures that exceed a predetermined threshold value of a threshold comparison are classified as structures to be masked,

[0016] and the masking data recordings are applied to the image recordings and the image recordings thus modified are used to generate the reference image.

[0017] Advantageous embodiments are described hereinafter.

[0018] Preferably, the threshold comparison is a comparison of the frequency of the detected structures with a threshold value of the frequency.

[0019] Preferably, the repositioned image recordings are converted into repositioned binary image recordings by means of a calculation rule and form the evaluation groups therefrom.

[0020] Preferably, pixels of the image recordings representing structures to be masked are not included in the further generation of the reference image.

[0021] Preferably, the reference image is used to capture the topography of the surface of the workpiece.

[0022] Preferably, the reference image is used to reduce the existing field curvature.

[0023] The method serves to generate a reference image for a method for imaging a surface of a workpiece. In the process, the reference image is generated by means of capturing a plurality of image recordings of at least one region of a surface of a reference object (reference surface). The individual image recordings are captured from recording positions that are laterally displaced and / or rotated relative to one another. As an example, if there is contamination in the recording optical unit employed, this has an influence on different positions in the images of the variously displaced and / or rotated image recordings. Based on the captured image data of the image recordings, repositioned image recordings are generated and stored. The repositioned image recordings can be converted into binary form. The repositioned image recordings can be converted into repositioned binary image recordings by means of a calculation rule. An evaluation group is then formed therefrom. As an example, the calculation rule can be a threshold comparison. The repositioned image recordings or the repositioned binary image recordings serve as a basis for generating the reference image.

[0024] The method according to the application is characterized in that a masking data record is generated. To this end, a plurality of evaluation groups are defined. In each of the evaluation groups, one of the individual repositioned image recordings is combined with each of the other individual repositioned image recordings or a certain number, in particular in pairs, by means of a calculation. In this case, for example, the image data of the image recordings that correspond to one another are subtracted from one another. If a certain number of further individual repositioned image recordings is used, this can be a certain number of image recordings that are selected at random or a plurality of image recordings that are selected in accordance with a specified criterion. The data record of the evaluation group that is obtained from each of the pair-wise combinations by means of a calculation is generated into a corresponding group result data record, which represents a group result image. In the process, the structures that are detected in the data records that are obtained as a result of the pair-wise combinations by means of a calculation are evaluated in terms of their assignment as structures to be masked. Those detected structures that exceed a predetermined threshold value of a threshold comparison are classified as structures to be masked. These regions are caused in particular by contamination or defects in the recording optical unit and are defined as masked regions of the masking data record.

[0025] As an example, the threshold comparison is a comparison of the frequency of occurrence of the detected structures with a predefined frequency threshold. Those pixels of the image recordings representing structures to be masked are optionally not included in the further generation of the reference image.

[0026] The masking data record is generated from the number of group result images / group result data records (again, all or selected). The masking data group with the masked areas is applied to the image record and the thus modified image record is used to generate the reference image.

[0027] The term recording optical unit is to be interpreted broadly. It not only includes optical elements such as objective, optical lens, mirror, etc., but also technical elements such as detector, etc. Thus, for example, a faulty detector element of a matrix detector (pixel) can be understood as within the meaning of contamination or defect of the recording optical unit.

[0028] The core of the present invention is that the existing imaging aberration (such as contamination reflected in the image data) is not only attenuated, but completely masked and thus eliminated. In contrast to the procedure in the prior art, no contribution of the contaminant remains in the reference image. Furthermore, no complex filtering is required for the purpose of removing such residual contributions. The occurrence of filtering artifacts associated therewith can likewise be significantly reduced or completely avoided by the method according to the invention.

[0029] For example, the main part of the method according to the invention can be expressed as follows:

[0030] Equation (1)

[0031] with i≠j. The indices i and j are the running indices of the repositioned image records. Here, the term z*denotes the matrix of the image generated thereby. This can be found in Figure 3 a graphical representation of this aspect.

[0032] Subsequently, the image data is determined on the basis of a condition selection. As an example, the latter can be expressed as follows:

[0033] Equation (2)

[0034]

[0035] Naturally, the selection of the 90% quantile is exemplary. Depending on the evaluation method, different percentage values can determine the condition. Thus, the image of the matrix z*is converted into a binary image.

[0036] In the next step, there is a pixel-wise summation of the image data:

[0037] Equation (3)

[0038]

[0039] In order to avoid manipulation of the average value or median value by pixels of the obscured area, in one possible configuration of the method the pixel values of these pixels are considered to be invalid. Although this reduces the number N of pixel values in the obscured area which are available for forming the average value or median value, the pixel values do not contribute to the bias of the bias either. Therefore, pixels in the image recording which have been defined as obscured by the obscured data recording are not included in the further generation of the reference image.

[0040] The reference image generated by means of the method according to the application can be used in particular in a method for capturing the topography of a workpiece surface. In particular, the reference image for reducing the present field curvature can be used in a suitably configured method.

[0041] The reference image or its image data can be optimized by means of this / these optionally subjected to filtering, preferably gentle filtering, respectively.

[0042] In addition, the method can be used for correcting image data in the range of so-called shading or RGB shading.

[0043] Any recording optical unit equipped with a suitable detector can be used to carry out the method according to the application. In particular, the method is suitable for microscopy and material testing.

[0044] The recording optical unit can be connected to a holder and can interact with a motor-driven stage for supporting the sample and / or the reference object.

[0045] As examples, a camera-based system, a laser scanning microscope, a confocal microscope, a wide-field microscope, a white light interferometer and a light sheet microscope can all be used as a microscope. BRIEF DESCRIPTION OF DRAWINGS

[0046] The application is explained below on the basis of exemplary embodiments and the attached drawings. In particular:

[0047] Figure 1 A schematic diagram showing the effect of laterally displacing image recordings relative to one another is shown;

[0048] Figure 2 A schematic diagram showing the generation of a reference image according to the prior art is shown;

[0049] Figure 3 A schematic diagram showing a configuration example of the method according to the application using an example of five evaluation groups is shown;

[0050] Figure 4 A schematic diagram showing the generation of an obscured data recording from a plurality of group result data recordings in one configuration example of the method according to the application is shown; and

[0051] Figure 5 A schematic diagram showing the modification of an image recording is shown. DETAILED DESCRIPTION

[0052] For the purpose of assisting the explanation given below, it should be based on the understanding that Figure 1 the influence of the image recordings a1 to a3 which are laterally displaced relative to one another is to be elucidated. For the purpose of generating a reference image R (cf. Figure 2 ), a plurality of image recordings a1 to a3 of a reference object (top row) are captured, which are recorded from recording positions which are laterally offset and / or rotated relative to one another (rotated recording positions not illustrated). For the purpose of illustrating the offset movement, a small cross has been drawn in each of the image recordings a1 to a5, which marks a fixed position on the surface of the reference object. In addition, a contamination of the recording optical unit has been captured (marked by a star). Since the contamination is fixed relative to the beam path of the recording optical unit, it is always imaged in the same position in the image recordings a1 to a5. It is apparent from the respective positions of the small crosses on the image recordings a1 to a5 that, as a result of the respective modified recording position, the reference object is imaged at different positions depending on the direction and magnitude of the displacement or rotation implemented.

[0053] The image data of the image recordings a1 to a5 are then each, in particular, realigned with one another (repositioned) by calculation, and repositioned image recordings A1, A2, A3, A4 and A5 are obtained respectively (bottom row). The small crosses are again imaged in the repositioned image recordings A1 to A5, always in the same position. It is thus possible, for example, to subtract the repositioned image recordings A1 to A5 from one another, for example to determine the background noise (background image) present. In contrast, the contamination (star) is imaged at different positions in the repositioned image recordings A1 to A5. When, for example, the repositioned images A1 and A2 are subtracted from one another, the contamination remains in the result.

[0054] These cases are recorded in Figure 2 , which shows the generation of a reference image R according to the prior art in an exemplary and simplified manner. The repositioned image recordings A1 to A5 show the contamination at five different positions in an exemplary manner. If the repositioned image recordings A1 to A5 are added together and an average value or, alternatively, a median value is formed for each pixel to obtain the reference image R, the contamination contributes to the image content of the reference image R at each of the five positions. Although the contribution of the contamination has been reduced to approximately one fifth of the original intensity in each case as a result of the formation of the average value or median value, it nevertheless appears in the reference image R. These "shadows" can be further reduced using a subsequent filtering step, but there is a risk of filter artefacts occurring. Figures 2 to 5 The summation symbol used in

[0055] should be based on the understanding that Figure 3The configuration of the method according to the application is explained. After capturing the image recordings a1 to a5 and creating the repositioned image recordings A1 to A5, as described above, the repositioned binary images are generated by applying formula 2 (see above). These repositioned binary images are subsequently evaluated in evaluation groups. In the present example five evaluation groups I to V are defined (illustrated in rows i = 1, 2,..., 5). In each of the evaluation groups I to V one of the individual repositioned image recordings is combined in a pairwise manner by calculation (formula 1 ) with each of the other individual repositioned image recordings of the respective evaluation group I, II, III, IV and V, respectively. In this process the image data of the image recordings corresponding to each other are for example subtracted from each other. As an example, in the first evaluation group I the result of the combination of the repositioned binary image A1 with the repositioned binary image A2 (see Figure 2 ) is illustrated at position i = 1, j = 2, the result of the combination of the repositioned binary image A1 with the repositioned binary image A3 by calculation is illustrated at position i = 1, j = 3, etc. In the second evaluation group the repositioned binary image A2 is combined with A1 by calculation (position i = 2, j = 1 ), the repositioned binary image A2 is combined with A3 by calculation (position i = 2, j = 3), etc. Corresponding statements apply to the third to fifth evaluation groups III to V.

[0056] The results of the evaluation groups I to V obtained by the pairwise combination by calculation are optionally averaged (formula (3)) and each result represents a group data record G i A selection criterion (formula (4)) is selected for selecting those detected structures which are detected at least 3 times, for example.

[0057] Formula (4) can be as follows:

[0058]

[0059] wherein NaN represents a pixel without a measured value, i.e. a pixel to be masked.

[0060] The results of the frequency comparison in the group data records Gi of the evaluation groups are illustrated in the M i column.

[0061] The method configuration should be explained on the basis of the first evaluation group I.

[0062] As already mentioned in the introduction, the method according to the application is based on the assumption that the structures to be detected are present in each of the image recordings a1 to a5. Figure 2The recording positions of the image recordings a1 to a5 are changed in such a way that, in the thus generated repositioned image recordings, the contaminated image located in the upper left corner in the first repositioned image recording Al is represented imaged in the upper right corner in the second repositioned image recording A2, imaged in the lower left corner in the third repositioned image recording A3, imaged in the lower right corner in the fourth repositioned image recording A4 and imaged in the center of the image field in the fifth repositioned image recording A5, by way of example.

[0063] As an example, in the case of Figure 3 In the scheme shown, the combination of the image data of the first repositioned binary image recording Al with the second repositioned binary image recording A2 is shown schematically in the second column (j = 2) of the first evaluation group I by calculation. The combination of the image data of the first repositioned binary image recording Al with the third repositioned binary image recording A3 is shown in the third column (j = 3) by calculation, etc.

[0064] Due to the application of the selection criterion (formula (4)), the positions of the contaminations which were still contained initially but captured only once in each case have been eliminated from the masking data recording M i .

[0065] Thus, in the masking data recording Ml of the first evaluation group I, the contamination imaged in the upper left corner of the image recordings a1 to a5 is recorded. Its specific shape and extent have likewise been determined. The second to fifth evaluation groups II to V are continued using the same principle.

[0066] The individual masking data recordings Ml to M5 can be combined to form the masking data recording M (and also: )( Figure 4 ).

[0067] The masking data recording M or the individual masking data groups Ml to M5 is applied to the image recordings a1 to a5 of the reference object (formula (5)), wherein the intensity value is not contained at the image position NaN corresponding to the position of the contamination (NaN = 0). The image recordings a1 to a5 thus become the modified image recordings a1 mod , a2 mod ,..., a5 mod .

[0068] Formula (5)

[0069]

[0070] The expression denotes the modified image recordings a1 mod , a2 mod ,..., a5 mod .

[0071] Figure 5 The function of the masking data record M is illustrated in exemplary fashion. In Figure 1 The image records a1, a2 to a5, which have been shown in the top row, are modified by applying the masking data record M1. In this process, the contamination in the upper left corner (indicated by the asterisk) is masked. For purposes of illustration, the contamination is still indicated (dashed line). The thus modified image records a1 mod , a2 mod ,..., a5 mod are converted back into the repositioned image records A1 mod to A5 mod and are used to calculate the reference image R (corrected image; contains field curvature but no contamination, equation (6)).

[0072] Equation (6)

[0073]

[0074] The reference image R can then be used for correction purposes, for example in a method for capturing the topography of a workpiece surface. In this process, the NaNs must be taken into account accordingly. As an example, if an average value is to be calculated, for example the sum of all valid elements (pixels) divided by the number of valid elements.

[0075] Reference signs

[0076] a1, a2, a3, a4, a5 image records with lateral offset / rotation

[0077] a1 mod , a2 mod ,..., a5 mod modified image records

[0078] A1, A2,..., A5 repositioned (binary) image records

[0079] A1 mod , A2 mod ,..., A5 mod modified repositioned image records

[0080] M i masking data record (i = 1, n)

[0081] G i group data record (i = 1, n)

[0082] R reference image

[0083] I, II, III, IV, V evaluation groups

Claims

1. A method for generating a reference image for imaging a workpiece surface, in, The reference image is generated by means of the following: Multiple image records are captured of the surface of a reference object, wherein individual image records are captured from recording positions that are laterally displaced and / or rotated relative to each other. Based on the captured image data of the image record, a repositioned image record is generated and stored. The reference image is generated based on the repositioned image record. Its features are, The masking data records were generated by defining multiple evaluation groups, and, In each of the evaluation groups, - In each case, by calculating and combining one of the individually relocated image records with multiple other individually relocated image records in a pairwise manner, and - Data records obtained from each pair of combinations are combined by a computational evaluation group to form corresponding masking data records, wherein the structures detected in the data records obtained by computational pair combinations are evaluated as structures to be masked in their allocation, and Structures detected that exceed a predetermined threshold for comparison are classified as structures to be masked. The occlusion data record is applied to the image record, and the image record is thus modified to generate the reference image.

2. The method according to claim 1, characterized in that, The threshold comparison is a comparison of the frequency of occurrence of the detected structure with a frequency threshold.

3. The method according to claim 1 or 2, characterized in that, The repositioned image records are converted into repositioned binary image records using calculation rules, thereby forming an evaluation group.

4. The method according to claim 1 or 2, characterized in that, The further generation of the reference image does not include pixels representing the structure to be masked.

5. The method according to claim 1 or 2, characterized in that, The reference image is used to capture the surface topography of the workpiece.

6. The method according to claim 1 or 2, characterized in that, The reference image is used to reduce the existing field curvature.

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