Detection device for a missile

Abstract

The invention relates to a detection device (1) for a missile, in particular a guided missile, comprising an optical device (2) which is designed to image radiation (5, 6) onto a detector plane (3) of a detector unit (4) of the detection device (1), wherein the detector unit (4) has at least two groups of detection regions (10, 11) which are sensitive to different wavelengths and / or wavelength ranges of the radiation (5, 6); the optical device (2) is designed to image radiation (5, 6) with at least two different wavelengths in the same spot size range, in particular with the same spot size, onto the detector plane (3), at least one spot (7, 8) being imaged unsharply onto the detector plane (3); and a control device (9) is designed to use a transformation algorithm, in particular an artificial-intelligence-based transformation algorithm, to transform the at least one spot (7, 8) which is imaged unsharply onto the detector plane (3) and has a first image sharpness into at least one spot with a second image sharpness, the second image sharpness being greater than the first image sharpness.

Description

[0001] IE / HA / ma

[0002] Detection device for a missile

[0003] The invention relates to a detection device for a missile, in particular a guided missile, comprising an optical device configured to image radiation onto a detector plane of a detector device of the detection device, wherein the detector device has at least two groups of detection areas which are configured to be sensitive to different wavelengths and / or wavelength ranges of the radiation.

[0004] Such detection devices for missiles, in which a detector assembly is used to detect radiation of different wavelengths, are generally known from the prior art. For example, such detector assemblies can have detection areas, such as sensitive "pixels," that are arranged alternately in the detector plane, for example in a checkerboard pattern. Such detector assemblies can therefore also be referred to as bispectral checkerboard detectors.

[0005] However, if the wavelength ranges of the radiation to be detected are very far apart, and the same optical device is to be used for imaging the radiation or guiding the radiation into the detector plane, it is not possible to simultaneously focus radiation from different wavelength ranges in the detector plane. This means that at least one type of radiation in a specific wavelength range or at a particular wavelength will be out of focus in the detector plane.

[0006] Furthermore, when using the same or a common optical device, the spot size for radiation of different wavelengths or wavelength ranges is generated differently in the detector plane. Since the detection areas in the detector plane are uniformly distributed, i.e., the sensitive pixels have the same size, this leads to errors or complications during detection, especially when "tracking" a radiation-emitting or reflecting object.

[0007] The invention is based on the objective of providing an improved detection device for a missile.

[0008] The problem is solved by a detection device having the features of claim 1. Advantageous embodiments are the subject of the dependent claims.

[0009] As described, the invention relates to a detection device for a missile, specifically for a guided missile. Such a missile can therefore incorporate the detection device described herein. The following description is therefore also applicable to such a missile.

[0010] The detection device comprises an optical assembly, which includes, for example, at least one optical element, in particular an optical lens and / or a mirror. The optical assembly is generally designed to guide radiation from outside the detection device, particularly in the direction of motion in front of the missile, into the detection device, namely into the detector plane, or to focus it there. Within the detector plane of the detector assembly, the detector assembly has two groups of detection areas, which are sensitive to different wavelengths or wavelength ranges of the radiation.

[0011] This means that radiation of a first wavelength or wavelength range can be detected using detection ranges from a first group of detection ranges, and that radiation of a second wavelength or wavelength range can be detected using detection ranges from a second group of detection ranges. The wavelengths and wavelength ranges are distinct from one another, specifically non-overlapping, so that all wavelengths of the first wavelength range are different from all wavelengths of the second wavelength range. In other words, the different wavelength ranges do not overlap.

[0012] The invention is based on the finding that the optical device is designed to image radiation with at least two different wavelengths with the same spot size range, in particular the same spot sizes, in the detector plane, wherein at least one spot is imaged blurred in the detector plane, and wherein a control device is designed to transform, by means of a transformation algorithm, in particular based on artificial intelligence, the at least one spot imaged blurred in the detector plane, which has a first image sharpness, into at least one second image sharpness which has a greater image sharpness than the first image sharpness.

[0013] The detection device described herein proposes the use of a combination of optical and control elements—that is, a combination of optical design and image processing algorithms—to detect radiation of different wavelengths with the same detector, which has different groups of detection areas. In particular, the detection device can be configured for object detection and / or object tracking. The detection device is designed so that the optical elements guide the radiation of different wavelengths or wavelength ranges into the detector plane, with the different spots in the detector plane lying within the same spot size range, i.e., having nearly identical or identical spot sizes.

[0014] However, this results in at least one of the two spots being imaged blurred in the detector plane. To compensate for this blurring or defocus caused by the chosen optical design, a control unit is used, on which the described transformation algorithm can be executed. The at least one spot that is imaged blurred in the detector plane is transformed or "sharpened" by means of the transformation algorithm. This advantageously makes it possible to image radiation of different wavelength ranges in the detector plane with the same optical device, where the spot sizes are comparable and can therefore be captured with equally sized detection areas. The resulting blurring is corrected by the control unit, i.e., by image processing with the transformation algorithm.In this way, particularly complex optical devices can be dispensed with, as the error resulting from the blurred imaging of at least one of the spots in the detector plane is at least partially reduced or eliminated by the transformation algorithm, in particular based on artificial intelligence. In other words, the present invention proposes that the radiation of the different wavelength ranges, which can differ significantly from one another, for example a combination of a first radiation in the LWIR range ("long wave infrared") and a second radiation in the MWIR range ("mid wave infrared"), be imaged as equally as possible in the detector plane.Since the radiation of the different wavelength ranges passes through the same imaging optics, it is refracted to varying degrees, particularly due to chromatic aberration. Consequently, the diffraction disks described by their respective PSFs (point spread functions) would differ significantly if their areas were minimized simultaneously. However, the optical system of the detection device described herein is designed such that both diffraction disks are imaged to be approximately the same size, and in particular, identical.

[0015] The initial image of the detector system can thus be composed of exactly two different wavelength ranges, with the "images" of the individual wavelength ranges (corresponding to the black and white squares of a chessboard) each being convolved with different PSFs. The sub-images are therefore rendered with varying degrees of sharpness, both with respect to the wavelength ranges and within a wavelength range due to optical distortions, particularly towards the edges. This is especially pronounced with wide-angle optics, as edge light falloff must also be expected.

[0016] Due to the described chessboard entanglement, the initial image from the chessboard detector would not be suitable for direct further processing, especially object detection / acquisition and object tracking. Because of the mathematical complexity of the required conversions, it is proposed here to use data-driven methods, which are collectively referred to as "transformation algorithms".

[0017] In one embodiment of the acquisition device, the transformation algorithm can be trained based on provided ideal images and associated blurred images. The training of the transformation algorithm can, for example, be divided into pre-training and fine-tuning. Ideal images for training can be generated synthetically, for example, using a data processing unit. For fine-tuning, real images acquired using a physical acquisition device can be used.

[0018] To generate the blurred images, a generic PSF can be created for both wavelength ranges, for example, a Gaussian distribution modified by appropriate effects such as aberrations, particularly defocus, astigmatism, chroma, vignetting, optical distortion, and the like. This allows the transformation algorithm to be pre-trained, specifically the artificial intelligence to be trained on potential errors and how to compensate for them. In particular, image pairs can be provided: ideal images and blurred images, such as those produced by the optical system due to blurring in the detector plane.

[0019] During fine-tuning, the described pre-trained model or pre-trained artificial intelligence can be specifically fine-tuned to a real-world acquisition device using real-world measurement data, such as collimator images. The fully trained transformation algorithm can then be loaded into signal processing electronics for inference. For example, the ideal coordinator image might correspond to an image in which the light or radiation originates from only one spatial direction or a very limited solid angle. In the ideal image, for instance, only a single area of ​​the acquisition is illuminated.The output image of the optical device of the real detection device can be used as an input image for the transformation algorithm to be fine-trained, whereby the deviation of the output image of the transformation algorithm to the corresponding ideal collimator image, in which only the corresponding detection area is illuminated, defines the training error for the fine-training.

[0020] The training error is thus specified by the combined deviation of the output images from the ideal output images. The individual deviations can be weighted differently; for example, color image deviations can be weighted with a different constant than intensity image deviations. If color images from both channels are used as output images, the weighting can be set to a constant k = 1. The sum of the training errors can, for example, be calculated using the grayscale values ​​of the acquisition areas of the individual images. In a further development of the acquisition device, the transformation algorithm can include a neural network. As already described in general terms, the transformation algorithm can be based on artificial intelligence or machine learning, or incorporate such mechanisms.Specifically, a neural network can be used to sharpen the output image from the optical device, which is projected onto the detector device in the detector plane.

[0021] The transformation algorithm can comprise a (deep) neural network with so-called CNN layers. These CNN layers can mimic the function of the human retina and correspond to classical feature images. Such networks can be pre-trained and retrained for the specific task, as described previously. The preprocessing proposed here, similar to the described CNN layers, can be used as a base / input layer for a deep neural network. Alternatively, it can be used for classical image processing, which uses two values ​​per pixel as input, for example, intensity and color temperature. The input layer does not necessarily have to be fully connected, but can be connected only within a limited area, which corresponds, in particular, to the size of the maximum PSF (photospatial field strength).

[0022] The neural network can use the output image on the detector array, specifically in the detector plane of the checkerboard detector, as its input layer. The number of neurons in the network can be equal to the number of pixels, i.e., the detection areas, of the detector array, for example, M rows and N columns. The output layer of the network can output an intensity image and a color image. In contrast to multimedia applications, where color information is often undersampled because the human eye is not as good at spatially locating color information compared to intensity information, it is proposed here to choose the same dimension for both images.

[0023] Based on the previously described pre-training and the optional fine-tuning, the transformation algorithm can be configured to reduce at least one aberration, particularly chroma and / or astigmatism. In addition to optical aberrations, other effects, especially off-axis aberrations, can be considered during fine-tuning, such as distortions and unforeseen effects that may arise, for example, due to manufacturing tolerances of the detector. As previously described, the optical system should be configured to image the spots of the different radiation with approximately the same size in the detector plane.In one embodiment, the optical device can be configured such that it is designed to image radiation of a first wavelength, particularly the longer wavelength, onto the detector plane, and radiation of a second wavelength is adapted to a spot size of the spot of radiation with the first wavelength. In other words, the optical device can be designed primarily for the first wavelength, particularly the longer wavelength or the wider wavelength range, especially LWIR, so that the spot of radiation is imaged approximately sharply onto the detector plane. Subsequently, the radiation of the second wavelength can be imaged onto the detector plane such that the spot size of the resulting spot corresponds to the spot size of the spot of radiation with the first wavelength. It follows that the radiation of the second wavelength must be defocused accordingly so that the spot sizes are equal to each other.are the same.

[0024] As already described, the different wavelengths are distinct wavelengths or wavelength ranges that do not overlap. In one embodiment, the first wavelength can comprise long-wave infrared radiation (LWIR), in particular 8 pm to 15 pm, and / or the second wavelength medium-wave infrared radiation (MWIR), in particular 3 pm to 5 pm. In other words, the optical device can be configured to image long-wave infrared radiation onto the detector plane as the first wavelength and medium-wave infrared radiation onto the detector plane as the second wavelength. The optical device can be designed such that it is suitable for the first wavelength, i.e.,optimized for long-wave infrared radiation, so that radiation with the second wavelength is correspondingly defocused and imaged onto the detector plane, so that the spots of long-wave infrared radiation and the spots of medium-wave infrared radiation are the same with respect to spot diameter or spot size.

[0025] The described control device can be further configured to perform a color transformation of at least two different wavelengths. Advantageously, it is also possible to obtain a single intensity and color image directly, instead of two separate intensity images from the two wavelength ranges. This advantageously allows for the further processing of intensity and temperature characteristics, particularly with pixel-level precision. Pixel-precise intensity conversions from individual color channels to intensity and color signals, specifically using a so-called color transformation known in the visible spectral range, are performed here based on two intensity images in the infrared range, which are not available with pixel-level precision.These are processed here in the sense of a "superpixel" of the checkerboard detector, described below, whose individual gray values ​​are convolved with the respective PSF. Alternatively, the output layer can contain images of both color channels, meaning that no color transformation is performed. The considerations described above regarding the dimensions of the output images apply analogously.

[0026] Furthermore, the detection device can be configured with an optical unit designed to illuminate a group of four detection areas, in particular two detection areas each from the first group and the second group, with the spots. Accordingly, a so-called "superpixel" can be formed, which has two detection areas from the first group and two detection areas from the second group, in particular arranged crosswise. The optical unit can be designed such that the spot size of each of the two spots illuminates four detection areas. For example, the spot diameter can be twice the pixel length or pixel width. This ensures that no gaps occur between the individual superpixels, since several pixels or detection areas are always illuminated by the two spots.

[0027] Basically, two alternatives are possible. In the first alternative, the centers of superpixels can be considered using a dimension (M-1) x (N - 1). These superpixels, as described, are each formed from two crosswise arranged acquisition areas from different groups. While this allows for maximum resolution, the resulting images correlate with each other because the values ​​of the individual acquisition areas are each incorporated into four superpixels or correspondingly arranged evaluation windows. In the second alternative, non-overlapping superpixels can be considered using a dimension (M / 2) x (N / 2). These are correlated only by the overlap of the PSF (Periodic Field Frame).

[0028] The detection device may further be configured with a control unit designed to evaluate detection areas within a sliding evaluation window, wherein the evaluation window comprises a group of four detection areas, in particular two detection areas each from the first group and the second group. The evaluation window can thus cover or evaluate a previously described "superpixel" in any position. The evaluation window can slide across the detection areas or within the detector plane. This means, in particular, that the evaluation window is not assigned to a fixed grouping of detection areas, but rather that the evaluation window can be positioned over any group of four or a superpixel within the detector plane.

[0029] The sliding evaluation window is particularly useful for object tracking, as there is no signal drop when the spot leaves the evaluation window or the currently illuminated superpixel. Instead, the evaluation window can always be set for the group of four or the superpixel currently illuminated by the two spots. This means that the individual superpixels are not independent of each other; rather, each pixel or detection area can be part of four adjacent superpixels.

[0030] In addition to the described detection device, the invention relates to a missile, in particular a guided missile, which includes a previously described detection device. The missile can, in particular, be configured to detect and track a target signature by means of the described detection device.

[0031] Furthermore, the invention relates to a method for operating a detection device for a missile, in particular a guided missile, comprising an optical device configured to image radiation onto a detector plane of a detector device of the detection device, wherein the detector device has at least two groups of detection areas that are sensitive to different wavelengths and / or wavelength ranges of the radiation, wherein radiation with at least two different wavelengths with the same spot size range, in particular with the same spot sizes, is imaged in the detector plane by means of the optical device, wherein at least one spot is imaged blurred in the detector plane, wherein at least one spot is imaged blurred in the detector plane by means of a control device using a transformation algorithm, in particular based on artificial intelligence, whichA spot exhibiting a first image sharpness is transformed into at least one second spot exhibiting greater image sharpness than the first. The detection device described herein can be used to carry out the described method, or the described method can be carried out in all details using the described detection device.

[0032] All the advantages, details and features described in relation to the detection device are fully transferable to the missile and the procedure, and vice versa.

[0033] The invention is explained below with reference to exemplary embodiments and the figures. The figures are schematic representations and show:

[0034] Fig. 1 shows a schematic representation of a detection device for a missile according to an exemplary embodiment;

[0035] Fig. 2 shows a schematic representation of a detector plane of the detection device of Fig. 1;

[0036] Fig. 3 shows a schematic representation of a detector plane of the detection device of Fig. 1, 2;

[0037] Fig. 4 shows a schematic representation of a detector plane of the detection device of Figs. 1-3; and

[0038] Fig. 5 shows a schematic representation of a detector plane of the detection device of Fig. 1-4.

[0039] Fig. 1 shows a schematic representation of a detection device 1 for a missile (not shown in detail), in particular a guided missile. The missile can detect and / or track target signatures by means of the detection device 1. The detection device 1 includes an optical unit 2 configured to focus radiation onto a detector plane 3 of a detector unit 4 of the detection device 1.

[0040] Specifically, the optical device focuses two different types of radiation 5, 6 onto the detector plane 3 of the detector device 4: first radiation 5 of a first wavelength or from a first wavelength range, in particular long-wave infrared radiation (LWIR), and second radiation 6 of a second wavelength or from a soft wavelength range, in particular mid-wave infrared radiation (MWIR). The different types of radiation 5, 6 are represented by solid lines for first radiation 5 and by dashed lines for second radiation 6.

[0041] It follows that the radiation 5, 6 is imaged differently by the optical device 2 due to its different wavelengths. The optical device 2 can be specifically optimized for the longer wavelength, namely the first radiation 5, so that it can image a spot 7 (see Fig. 2-5) as optimally as possible in the detector plane 3. The radiation 6 of the second wavelength is adjusted, or the optical device 2 is designed, such that a spot 8 of the second radiation 6 corresponds to the same spot size range as the spot 7 of the first radiation 5. This means that, as shown, for example, in Fig. 2-5, the two spots 7, 8 have almost the same spot size or are exactly the same size. The spot size can be understood, for example, as the spot diameter. For the sake of clarity, the two spots 7, 8 are shown slightly differently, although they can also have exactly the same size.

[0042] The detection device 1 also includes a control unit 9 configured to execute a transformation algorithm, specifically one based on artificial intelligence. The transformation algorithm is designed to transform the spot 8, which is imaged blurred in the detector plane 3 and has an initial sharpness, into a spot with a second sharpness that is greater than the first. In other words, the transformation algorithm is used to sharpen the image of the second radiation 6 in the detector plane 3. Alternatively or additionally, it is also possible to sharpen the spot 7 of the first radiation 5 by applying the transformation algorithm.

[0043] The transformation algorithm can operate based on artificial intelligence, for example, machine learning. The transformation algorithm can specifically comprise a neural network. Ideal images, as well as corresponding blurred images, can be provided to train the transformation algorithm. In other words, the transformation algorithm is provided with information on which errors caused by the blurred image must be compensated for by the optical device 2. The transformation algorithm can thus be trained to compensate for or eliminate the defocus or blur, for example, in spot 8. For example, synthetically generated images can be provided to the transformation algorithm during pre-training, allowing the transformation algorithm to be pre-trained on any number of synthetically generated images.

[0044] Subsequently, fine-tuning or adjustment can be performed, in which the images are generated by the acquisition device 1 and can be compared, for example, with ideal images. In particular, it is possible to train the transformation algorithm to recognize the aberrations and effects that occur in the real-world acquisition device 1.

[0045] As illustrated by example in Fig. 2-5, the detector assembly 4 has two groups of detection areas 10, 11 in the detector plane 3, which are arranged alternately in two dimensions in the detector plane 3. The detector assembly 4 can therefore also be understood as a bispectral checkerboard detector. For example, the detection areas 10 (shown hatched) are sensitive to the first radiation 5 and the detection areas 11 (shown in white) are sensitive to the second radiation 6.

[0046] In the illustrated embodiment, the optical device 2 is designed and configured such that the spots 7, 8 of the different radiation 5, 6 are imaged in the detector plane 3 as approximately or exactly the same size, and a higher-order pixel or superpixel is illuminated, which comprises two detection areas 10, 11 of the different groups. In other words, the two spots 7, 8 in the detector plane 3 always illuminate two detection areas 10 of the first group and two detection areas 11 of the second group, which together form a superpixel.

[0047] To evaluate the detector device 4, an evaluation window 12 is considered, which corresponds to a superpixel in terms of size in the detector plane 3. The evaluation window 12 can be evaluated in a sliding manner or formed in a sliding manner by means of spots 7, 8 in the detector plane 3. Figure 3 shows an example of the movement of spots 7, 8 in the detector plane 3, whereby the evaluation window 12 can slide or be moved together with the spots 7, 8. In particular, during object detection or object tracking, the object emitting the radiation 5, 6 or the corresponding spots 7, 8 can therefore be tracked without gaps, so that no drop-off in the signal of the detector device 4 occurs.

[0048] Fig. 4 shows, purely by way of example, a movement from Fig. 2 diagonally in the detector plane 3, or from Fig. 3 downwards in the plane of the drawing along the slit. Since the two spots 7, 8 are of the same size and each illuminates a superpixel, as shown, it is impossible for either spot 7, 8 to fall exclusively on a detection area 10, 11 that is not sensitive to this radiation 5, 6. If, for example, the spot size were smaller than or within the range of the detection areas 10, 11, each spot 7, 8 could lie exclusively on one of the detection areas 10, 11 and therefore could not be continuously detected, as it would not be sensitive to the corresponding wavelength.

[0049] By using the sliding evaluation window 12 shown, which always includes a group of four detection areas 10, 11, namely exactly two detection areas 10 and exactly two detection areas 11, both spots 7, 8 of the different radiation 5, 6 are detected in each area of ​​the detector plane 3.

[0050] Fig. 5 shows, by way of a dashed line, an example of the achievable resolution with the detector device 4, or the detection areas 10, 11 grouped into superpixels, and the evaluation window 12 described above. It is evident that the individual superpixels are not independent of each other, since the individual detection areas 10, 11 are part of adjacent superpixels. For example, if a specific detection area 10, 11 is considered, it is, with the exception of a boundary region in the detector plane 3, part of four adjacent superpixels. The resolution is thus given, in terms of the number of rows M and columns N of the detection areas 10, 11 in the detector plane 3, as (M-1)x(N-1).

[0051] The advantages, details, and features described in relation to the individual embodiments can be combined, interchanged, and transferred to one another as desired. The method described herein can be carried out in all its details using the described detection device 1. The detection device 1 is thus designed to carry out the described method. Reference numerals

[0052] 1 Detection device

[0053] 2 Optical device

[0054] 3 Detector level

[0055] 4 Detector device

[0056] 5, 6 radiation

[0057] 7, 8 Spot

[0058] 9 Control unit

[0059] 10, 11 Recording area

[0060] 12 evaluation windows

Claims

Patent claims 1. Detection device (1) for a missile, in particular a guided missile, comprising an optical device (2) configured to image radiation (5, 6) onto a detector plane (3) of a detector device (4) of the detection device (1), wherein the detector device (4) has at least two groups of detection areas (10, 11) which are sensitive to different wavelengths and / or wavelength ranges of the radiation (5, 6), characterized in that the optical device (2) is configured to image radiation (5, 6) with at least two different wavelengths with the same spot size range, in particular with the same spot sizes, in the detector plane (3), wherein at least one spot (7, 8) is imaged blurred in the detector plane (3), wherein a control device (9) is configured to use a transformation algorithm, in particular based on artificial intelligence,to transform the at least one spot (7, 8) that is blurred in the detector plane (3) and has a first image sharpness into at least one second image sharpness that has a greater image sharpness than the first image sharpness.

2. Detection device (1) according to claim 1, characterized in that the transformation algorithm is trained based on provided ideal images and associated blurred images.

3. Detection device (1) according to claim 1 or 2, characterized in that the transformation algorithm comprises a neural network.

4. Detection device (1) according to one of the preceding claims, characterized in that the transformation algorithm is configured to reduce at least one aberration, in particular chroma and / or astigmatism.

5. Detection device (1) according to one of the preceding claims, characterized in that the optical device (2) is designed such that an image is projected onto the detector plane (3) for radiation (5, 6) of a first wavelength, in particular the longer wavelength, and radiation (6) of a second wavelength is adapted to a spot size of the spot (7, 8) of the radiation (5, 6) with the first wavelength.

6. Detection device (1) according to one of the preceding claims, characterized in that the first wavelength comprises long-wave infrared radiation, in particular 8pm - 15pm, and / or the second wavelength comprises medium-wave infrared radiation, in particular 3pm - 5pm.

7. Detection device (1) according to one of the preceding claims, characterized in that the control device (9) is configured to perform a color transformation of the at least two different wavelengths.

8. Detection device (1) according to one of the preceding claims, characterized in that the optical device (2) is configured to illuminate a group of four detection areas (10, 11), in particular two detection areas (10, 11) of the first group and the second group, with the spots (7, 8).

9. Detection device (1) according to one of the preceding claims, characterized in that the control device (9) is designed to evaluate the detection areas (10, 11) in a sliding evaluation window (12), wherein the evaluation window (12) comprises a group of four detection areas (10, 11), in particular two detection areas (10, 11) each of the first group and the second group.

10. Missile, in particular guided missile, comprising a detection device (1) according to one of the preceding claims.

11. Method for operating a detection device (1) for a missile, in particular a guided missile, comprising an optical device (2) configured to image radiation (5, 6) onto a detector plane (3) of a detector device (4) of the detection device (1), wherein the detector device (4) has at least two groups of detection areas (10, 11) having which are sensitive to different wavelengths and / or wavelength ranges of the radiation (5, 6), characterized in that by means of the optical device (2) radiation (5, 6) with at least two different wavelengths with the same spot size range, in particular with the same spot sizes, in the The detector plane (3) is imaged, wherein at least one spot (7, 8) is imaged blurred in the detector plane (3), wherein by means of a control device (9) using a transformation algorithm, in particular based on artificial intelligence, the at least one spot (7, 8) imaged blurred in the detector plane (3) and having a first image sharpness is transformed into at least one second image sharpness having a greater image sharpness than the first image sharpness.

Images