EP4073478A1 - Verfahren und vorrichtung zur bestimmung von wellenlängenabweichungen von aufnahmen eines multilinsen-kamerasystems - Google Patents
Verfahren und vorrichtung zur bestimmung von wellenlängenabweichungen von aufnahmen eines multilinsen-kamerasystemsInfo
- Publication number
- EP4073478A1 EP4073478A1 EP20842551.2A EP20842551A EP4073478A1 EP 4073478 A1 EP4073478 A1 EP 4073478A1 EP 20842551 A EP20842551 A EP 20842551A EP 4073478 A1 EP4073478 A1 EP 4073478A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- image
- image sensor
- pixels
- images
- camera system
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/28—Investigating the spectrum
- G01J3/2823—Imaging spectrometer
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/02—Details
- G01J3/0205—Optical elements not provided otherwise, e.g. optical manifolds, diffusers, windows
- G01J3/0208—Optical elements not provided otherwise, e.g. optical manifolds, diffusers, windows using focussing or collimating elements, e.g. lenses or mirrors; performing aberration correction
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/02—Details
- G01J3/0278—Control or determination of height or angle information for sensors or receivers
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/28—Investigating the spectrum
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/002—Diagnosis, testing or measuring for television systems or their details for television cameras
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/50—Constructional details
- H04N23/55—Optical parts specially adapted for electronic image sensors; Mounting thereof
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/28—Investigating the spectrum
- G01J3/2823—Imaging spectrometer
- G01J2003/2826—Multispectral imaging, e.g. filter imaging
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/95—Computational photography systems, e.g. light-field imaging systems
- H04N23/957—Light-field or plenoptic cameras or camera modules
Definitions
- the invention relates to a method and a device for determining and in particular the advantageous use of wavelength deviations, in particular for dispersion calibration, of recordings from a multi-lens camera system.
- the multi-lens camera system is preferably a camera system for (hyper) spectral recording of images.
- spectral cameras In many areas of business and science, cameras are used which, in addition to a spatial resolution, have a spectral resolution (spectral cameras) which often goes beyond the visible spectrum (“multispectral cameras”). For example, when measuring the surface of the earth from the air, cameras are often used that not only have normal RGB color resolution, but also deliver a high-resolution spectrum, possibly up to the UV or infrared range. Using these measurements, it is possible, for example, to identify individual planted areas in agricultural areas. This can be used, for example, to determine the state of growth or the health of plants or the distribution of various chemical elements such as chlorophyll or lignin.
- hyperspectral imaging For these measurements, a spectrally high-resolution imaging technique known as “hyperspectral imaging” has proven itself in the last few decades. This hyperspectral imaging allows, for example, a recognition and differentiation of various chemical elements on the basis of the spatially resolved spectrum.
- a lens matrix is arranged in front of an image sensor, which images a motif in the form of many different images (one per lens) on the image sensor.
- Such a camera system is also referred to as a “multi-lens camera system”.
- a filter element for example a mosaic filter or a linearly variable filter, between the lens matrix and the image sensor, each of the images is recorded in a different spectral range.
- a large number of images of the motif are obtained in different spectral ranges ("channels").
- the disadvantage of the prior art is that the recorded images cannot be optimally compared with one another. They still need calibration. Particularly when objects are recorded at different distances from the camera system (e.g. an object in front of a background or two or more objects at different distances), different beam paths when recording through a filter element of the camera system mean that the spectral classification of an object is imprecise.
- the object of the present invention was to overcome the disadvantages of the prior art and to provide a method for determining the wavelength deviations of a multi-lens camera system, in particular for its calibration and / or improvement of the spectral resolution.
- a method according to the invention for determining (and advantageously using) wavelength deviations from recordings of a multi-lens camera system, in particular for dispersion calibration and / or improving the spectral resolution comprises the following steps:
- the spectral sensitivity of a region of the filter element reflects which color (wavelength) which pixel of the image sensor behind the filter element picks up. in the in the ideal case this is light with a single (central) wavelength, in the real case a wavelength distribution with a central wavelength.
- This spectral sensitivity is also referred to here as a “color field” because it comprises a field (area) in which different colors predominate depending on the filter element.
- this color field is usually linearly variable (linear varibal filter) or constant and stepped (mosaic filter).
- An area of the image sensor which is used to record an image should have a clearly defined (linearly varying / step-constant) course of the color field.
- the color field thus includes information about the central wavelengths of the light which hits the pixels of the predetermined area of the image sensor through a filter element.
- the color field preferably also includes information about the angular dependency of the central wavelength of the light shining through for the pixels or for groups of pixels. This further improves the accuracy, since the light from objects that are recorded from a closer distance propagates through the filter system at a slightly different angle than light from more distant objects.
- the color field is determined for that area of the filter element through which the light is used to record an image or several images for a predetermined one
- the area of the image sensor is falling.
- the predetermined area is correspondingly large on the image sensor.
- the color field can be determined by means of a direct measurement.
- an image of a motif is recorded and / or provided, which has been recorded by the multispectral multi-lens camera system in a spectral range.
- the color field can also be determined by calculating the behavior of the filter when a wavelength is irradiated with different angles of incidence, taking into account the imaging properties of the optics of the multi-lens camera system assigned to this area of the image sensor.
- the light passes through the filter to different pixels of the image at different angles of incidence.
- the light traverses different routes through the filter element to different pixels of the image sensor.
- this can result in a shift in the filter property. If z is the central wavelength of the filter for light at angle a, a central wavelength z ⁇ Dz can result for light which passes through the filter at angle b.
- This central wavelength is now determined for at least two pixels, preferably for all pixels for a predetermined region of interest (ROI) of the predetermined area of an image sensor.
- ROI region of interest
- a modification function for all pixels can be determined ("support function") assuming a linear course of the central wavelength over the pixels. If the course is not linear, it is preferable to determine central wavelengths for more than two pixels and to determine a modification function from this. A very accurate result can be obtained by looking at the central wavelengths of all pixels in the area.
- the modification function has the advantage that the central wavelengths do not have to be determined for all pixels, but that these can also be specified by the modification function.
- the area of the image sensor and / or corresponding images that have been recorded with the image sensor are then modified with the determined central wavelengths.
- a supplementary data record is generated for the images or for controlling the image recording. Modification and data set generation are mostly synonymous, since in digitized systems a modification can be based on a data set that is read in and used to modify image sensors or data.
- the modification can be an adaptation, in particular a calibration. However, it can also include the addition of image information to an image, for example the addition of additional spectral information or information on the emission characteristics of an object.
- This supplementary information can be available directly in image data, for example, or as an additional data record, ie “outside” an image but linked to it. This data record can then be accessed when viewing the image. If the corresponding data is available and a processing unit “knows” where this data can be found, it is equivalent whether additional data is available in an image file or in a separate data set. The same applies to additional data relating to the image sensor.
- data for modifying the image sensor can also be available in the form of a supplementary data record.
- the recorded image should represent a uniform motif so that each pixel of the image sees the same focus in terms of focus.
- a preferred motif is a uniform surface or the light of a Lambert radiator or a light source that strikes a Lambert scatterer. If only one image is recorded, it is advantageous that the light has approximately the wavelength that corresponds to the spectral channel of the image (narrowband emission is preferred); if several images are recorded, the subject should include the wavelengths of all spectral channels. However, it is also possible here for several images to be recorded sequentially, with the motif or the wavelength being able to change accordingly.
- a recording of (at least) one image of a subject with the multispectral multi-lens camera system in a spectral range is known to the person skilled in the art and is known from the (known) multispectral multi-lens camera system Way made.
- a multi-lens camera system for (multi / hyper) spectral recording of images comprises a flat image sensor, a location-sensitive spectral filter element and an imaging system.
- the imaging system comprises a flat lens matrix with a large number of individual lenses which are arranged such that they generate a large number of raster-shaped first images of a motif in a first area on the image sensor at a first recording time.
- the lenses are e.g. spherical lenses, cylinder lenses, holographic lenses or Fresnel lenses or lens systems (e.g. objectives) made up of several such lenses.
- Flat image sensors are basically known to the person skilled in the art. These are particularly preferably pixel detectors which allow image points (“pixels”) to be recorded electronically.
- Preferred pixel detectors are CCD sensors (CCD: “charge-coupled device”) or CMOS sensors (CMOS: “Complementary metal-oxide-semiconductor”; German “complementary metal-oxide-semiconductor”) ).
- CCD sensors CCD: “charge-coupled device”
- CMOS sensors complementary metal-oxide-semiconductor
- German “complementary metal-oxide-semiconductor” German “complementary metal-oxide-semiconductor”
- Silicon-based sensors are particularly preferred, but also InGaAs sensors and sensors based on lead oxide or graphene, especially for wavelength ranges outside the visible range.
- a spectral filter element which is designed in such a way that it transmits different spectral components of incident light at different positions on the surface of the filter element and does not transmit other spectral components is referred to here as a "location-sensitive spectral filter element", whereby it is also referred to as a “location-dependent spectral filter element” could be designated. It is used to filter the images generated by the imaging system on the image sensor according to different (small) spectral ranges.
- the filter element can for example be positioned directly in front of the lens matrix or between the lens matrix and the image sensor. It is also preferred that components of the imaging system are designed as filter elements, in particular the lens matrix. For example, the substrate of the lens matrix can be designed as a filter element.
- a lens matrix within the meaning of the invention comprises a multiplicity of lenses which are arranged in a grid-like manner to one another, that is to say in a regular arrangement, in particular on a carrier.
- the lenses are preferably arranged in regular rows and columns or offset from one another.
- a rectangular or square or a hexagonal arrangement is particularly preferred.
- the lenses can be, for example, spherical lenses or cylindrical lenses, but aspherical lenses are also preferred in some applications.
- (multi- / hyper-) spectral recordings always show similar images of the same subject.
- the filter element records these images with different (light) wavelengths or in different wavelength ranges from the image sensor.
- the images are available as digital images, the image elements of which are referred to as "pixels". These pixels are located at predetermined locations on the image sensor, so that each image has a coordinate system of pixel positions.
- the images are often referred to as "channels". Since the recorded images are typically stored in an image memory, they can also be called up from there for the method. The method can of course also work with “old” images that have been recorded and are now simply read in from a memory for the method and thus made available.
- the central wavelengths or the modification function can be present in an x, y, A space, where x and y are the image coordinates or the corresponding coordinates of the image sensor and A (x, y) the central wavelength assigned to the respective coordinates or the relevant one Modification value.
- a determination unit designed to determine a color field of a region of a filter element of the multi-lens camera system which is assigned to a predetermined region of an image sensor of the multi-lens camera system.
- This determination unit can comprise a computing system (or it can be present as a software module in a computing system), which determines this color field from sensor information and / or calculates it from specified information about the filter and possibly also about the motif to be reproduced (e.g. distance).
- a determination unit designed to determine the central wavelength for at least two pixels of the predetermined area of the image sensor based on the determined color field.
- This determination unit can be implemented by a computing unit (or it can be present as a software module in a computing system), which can evaluate sensor data from the image sensor and use it to determine the central wavelength.
- a processing unit designed to modify the settings of the area of the image sensor and / or images that have been recorded with this image sensor (or the area of the image sensor) and / or to generate a supplementary data set for the images or for controlling the image recording, based on the specific central wavelengths.
- This processing unit can be implemented by a computing unit (or it can be present as a software module in a computing system) that can access the image sensor or its image storage locations or change image data. If this processing unit is only used to modify images or the image sensor, it can also be referred to as a “modification unit”.
- a multi-lens camera system comprises a device according to the invention and / or is designed to carry out a method according to the invention.
- a preferred multi-lens camera system can also be configured analogously to the corresponding description of the method and, in particular, individual features of different exemplary embodiments can also be combined with one another.
- the color field is determined by recording and / or providing an image of a motif by the multispectral multi-lens camera system and / or by calculating the behavior of the filter when irradiated at a wavelength with different angles of incidence, taking into account the imaging properties of the Optics of the multi-lens camera system assigned to this area.
- the color field is therefore based on a measurement or a calculation, both of which can also be combined.
- a modification function (“support function”) is determined for the pixels of the predetermined area of the image sensor based on the determined central wavelengths of at least two pixels.
- This modification function is then used to modify (in particular for adaptation, eg for calibration) the area of the image sensor and / or images that have been recorded with this image sensor (or this area of the image sensor).
- a modification in particular a calibration, can also take place for areas of an image for which there is no color field.
- Other images can also be adapted with this modification function, whereby the color field for these images should be similar.
- a modification can also be made with different light paths (e.g. different distances between a motif or object).
- the distance between elements of a motif is taken into account, the color field for pixels of the image sensor preferably being determined as a function of the distance between the areas of the motif shown there and the camera system.
- a parallax determination of recordings also takes place, comprising the steps:
- the modification (which is an adaptation here) comprises a calibration of the area of the image sensor or of the images that have been recorded with this area.
- the above-described measures for modification are therefore preferred here for calibrating the image sensor or images used so that the spectral information per pixel is adjusted accordingly. If the color field is not constant, it is now known which spectral information the pixels of the relevant area reflect.
- the modification function is preferably a calibration function which, for pixels in the area of the image sensor or for images recorded with this area, comprises a calibration value based on the color field with which the relevant pixels are calibrated.
- the modification comprises an improvement of the spectral information of the recordings of the image sensor, at least two pixels being determined in an image whose central wavelengths are known and which belong to an image area for which an approximately identical spectrum is assumed.
- the pixels are therefore at different coordinates of an image and therefore have different central wavelengths here because of the dispersion effects described above, errors in the filter or simply because of the use of a linearly varying filter.
- the pixels all belong to a single object of the motif, whereby the object is assumed to be an area that has approximately the same spectrum (where “approximately” means: in the area of the desired measurement accuracy).
- all these pixels reproduce spectral information as they should prevail at all coordinates of the pixels (due to the almost identical spectrum).
- an object is preferably recognized in the image, as has already been described here at other points.
- the spectral information of the pixels is now combined into total spectral information for at least one of the pixels (preferably for pixel groups or all pixels).
- the modification also includes an improvement in the spectral information of the recordings of the image sensor.
- This method uses the same principle as the method described above: Two pixels that have individual (different) central wavelengths and come from an area that has approximately the same spectrum supplement the overall spectral information. If in the previous procedure there were pixels in the same However, if the image is at different locations on an object, pixels at the same location on an object but in different images are considered below. Both methods can preferably be used in order to further refine the spectral information.
- a multi-lens camera system with a linearly variable filter element is particularly suitable for both methods, in which case the term “different images” can also mean different image regions or different partial images, since the filter element covers one image having a linear course of a central wavelength.
- the preferred further method includes the following additional steps:
- the images can, for example, be recorded at different times with a relative movement of the camera system and the motif, or the motif can be shifted in the area of the image sensor. It is important that the images are not identical, but that at least one object of the motif is depicted in the images at different coordinates and / or from different angles. The latter can already cause different central wavelengths at the same image position due to dispersion effects. Of course, several images can be recorded, with each additional image representing an improvement in the spectrum.
- a change in the viewing angle can also result from tilting the filter element or from a lateral relative displacement of the filter element and lens matrix, since the angle at which the incident light passes through the filter element is important for the viewing angle.
- the term “filter passage angle” could also be used, with “viewing angle”, however, improving comprehensibility.
- pixels in the images that correspond to the same areas of the subject.
- the pixels are therefore in the same places on the subject (but not necessarily on the image). According to the preceding explanations, it is clear that these pixels are typically located at different image coordinates and should be located at the same image coordinates due to different viewing angles and different central wavelengths should have. Of course, some of the pixels can also have identical central wavelengths; this would just not represent any information gain.
- the viewing angle at which the pixels have been imaged is determined from the central wavelength and the intensities of the pixels are determined as a function of the viewing angle.
- the radiation characteristics of the object can also be determined from the viewing angles from which an object (or a pixel) is seen in different spectral regions, that is to say in different regions of the image sensor.
- the intensity of the object (or pixel) is recorded in different channels and plotted against the viewing angle.
- the application is carried out in the form of a bidirectional reflectance distribution function (BRDF). This viewing angle results from the location on the image sensor, for example. It is particularly preferred if the object (pixel) is viewed from two different viewing angles of the camera.
- BRDF bidirectional reflectance distribution function
- the object is usually shown in different spectral channels in the images, in the simplest case it can be assumed that the radiation characteristics are the same for all wavelengths and the (wavelength-dependent) intensity per channel could be normalized with the known spectrum of the object .
- the object in the same channel can be recorded from two or more viewing angles and the intensity of the spectral channels can be normalized from this.
- the motif is shifted on the image sensor after the first image has been taken; this can be done, for example, by that a mirror or a lens matrix of the multi-lens camera system is tilted. A whole series of images can also be recorded, in particular by means of such a tilt. As a result of the shift, identical points or areas of the motif are imaged on different pixels of the image sensor.
- An associated shift in the central wavelength can be used, as described above, to improve the spectral resolution. For example, a first image can be recorded first and then a sequence of several images can be recorded during a shift, in particular in the form of a film, with a lower spatial resolution or with a reduced exposure time in order to improve the spectral resolution of the first image.
- the above-mentioned lateral relative displacement of the filter element and lens matrix can also take place and / or the filter element can be changed, for example by a filter wheel or the filter can be exchanged.
- the filter element comprises a mosaic filter.
- the mosaic of the mosaic filter is preferably arranged in such a way that large wavelength steps are inside, while smaller intervals are outside.
- a colored mosaic in particular a colored glass mosaic, is applied, in particular vapor-deposited, to one side of a substrate, preferably glass.
- the filter element (a mosaic filter or another filter) is applied to the front side of a substrate and the lens matrix (e.g. embossed) is applied to the rear side of the substrate.
- a mosaic filter preferably transmits a different wavelength for each individual lens.
- the filter element comprises a linearly variable filter with filter lines (“graduated filter”), which is preferably rotated at an angle between 1 ° and 45 ° with regard to the alignment of the filter lines with respect to the lens matrix.
- the filter element comprises a filter matrix, particularly preferably a mosaic filter.
- the multi-lens camera system comprises an aperture mask between the lens matrix and the image sensor, with apertures being positioned on the aperture mask corresponding to the lenses of the lens matrix and the aperture mask being positioned so that light from the images of the individual lenses is displayed occurs through apertures of the aperture mask.
- the aperture mask thus has the same pattern as the lens matrix, with apertures being present there instead of the lenses.
- modification methods in particular calibration steps, can also be carried out, which also represent an advantage for recordings with a multi-lens camera system independently of the method according to the invention presented above .
- a preferred calibration method for a multispectral multi-lens camera system is used to identify a region of interest or ROI for short. It consists of the following steps:
- this image preferably having a uniform brightness distribution or such a high brightness that overexposure of the image sensor occurs.
- Overexposure has the advantage that in this case regions become visible in a recorded image that receive less light due to shielding effects (e.g. due to aperture edges). These areas should no longer belong to the ROI, as it is not guaranteed that the image information is optimal here (due to the shielding effects).
- the result is an image in which only the area visible to the ROI is illuminated.
- Performing a Hough transformation By means of this Hough transformation, the angles of the images can be brought into agreement. Selection of that area from the images which has the greatest similarity according to the autocorrelation and / or cross-correlation. This selection preferably includes a separation of the selected area or a limitation of an image section to this selected area. In this context, a corresponding predetermined definition in the reference image or the reference image and an object segmentation of the recorded image preferably take place.
- a preferred calibration method for a multispectral multi-lens camera system is used to correct lens errors. It consists of the following steps:
- a preferred calibration method for a multispectral multi-lens camera system is used to calibrate projection errors. It consists of the following steps:
- Characterizing points are e.g. corners of the target.
- a preferred calibration method for a multispectral multi-lens camera system is used to improve its resolution. It consists of the following steps:
- a plurality of images of low spatial resolution in different spectral ranges and a pan image or a gray-scale image with a higher spatial resolution are preferably recorded.
- the multi-lens camera system can also be additionally calibrated, in particular with a previously described method for calibrating projection errors.
- the parallax of objects in the images is determined beforehand and the parallax is compensated.
- the higher spatial resolution of one image is used to improve the spatial resolution of the image with the higher spectral resolution and / or the higher spectral resolution of the other image is used to improve the spectral resolution of the image with the higher spatial resolution.
- the spatial resolution is increased based on the information in the image with the higher spatial resolution.
- the well-known principle of pan-sharpening is preferably used here. This makes use of the fact that, when looking at the motif, a group of pixels of the image with the higher spatial resolution belongs to a pixel of an image of a spectral channel, for example 10x10 pixels from the pan image.
- a corresponding group of is now preferred from a pixel of a (spectral) image Pixels created (e.g. 10x10 spectral pixels) using the shape of the spectrum from the original spectral pixel but the brightness from the pan image.
- the spectral resolution of the image can be improved with the higher spatial resolution. If, as stated above, there is a first image with a higher spatial resolution and a lower spectral resolution (however, there must be more than three channels) and a second image with a lower spatial resolution and a higher spectral resolution, this is possible.
- the spectral resolution of the first image is improved so that (almost) a spectral resolution of the second image is achieved by interpolating the missing spectral channels for the first image from the information in the second image. This is preferably done in that a pixel of the second image is assigned to a coherent pixel group of the first image and the spectral information of the pixel of the second image is assigned to this pixel group.
- each block of ZxZ pixels of the first image is assigned to a pixel of the second image at the corresponding image position (taking the blocks into account).
- the result can, however, be improved by object recognition taking place within the first image (or in the pixel groups). This is based on the assumption that the spectra within an object are approximately the same.
- the object recognition can still be improved with information from the second image, in that parts of objects with different spectra are separated from one another and treated as independent objects. There can then be, for example, different adjoining areas in the first image that are separated from one another by edges.
- areas of different objects are treated differently by assigning different spectra to them.
- the spectral information of the second image is used for this one object for one object and the spectral information of the second image for this other object is used for the other object.
- the same procedure is followed for each additional part of the object. Since in this case the spectral information of the corresponding The corresponding pixels in the second image could be a convolution of different object spectra, the spectra of neighboring pixels in the second image, which contain information on the relevant objects, can be used here.
- an additional object recognition can take place in the second image, to which the objects of the first image correspond and corresponding spectral information is assigned to these objects from the information in the second image.
- the color channels are not homogeneous in each case (i.e. the central wavelength for the pixels in a channel (image) follows a course across the image plane), this information can also serve to improve the spectrum.
- the assumption is again made that the spectrum is homogeneous within an object, at least with regard to two neighboring points within the object.
- the spectrum of two neighboring pixels will differ slightly when recording a homogeneous motif.
- One pixel “sees” the motif with the wavelength w, the second with the wavelength w ⁇ ⁇ w. If it is found in an image that the two pixels represent an object (assumed to be homogeneous), this object can be assigned not only the wavelength w, but also the wavelength w ⁇ ⁇ w and the spectrum of the object can be refined in this regard.
- the location information of a resulting image could be (part -) Pan-Sharpening can be brought to 500x500, and the spectrum using "Spectral Sharpening" to 500, the result would be a spatial resolution of 500x500 pixels with a spectral resolution of 500 channels.
- the following method can be combined very easily with the one described above, but in its basic form does not necessarily require two images. More precise spectral information can also be determined from a single image.
- the spectra of at least the directly neighboring pixels are preferably added to each spectrum of a pixel. As already mentioned, these neighboring spectra contain different wavelength information (different support points due to different central wavelengths). Although this simple method increases the resolution of the spectra, it can lead to errors in the transition areas between different objects of a motif.
- the result can also be improved here by object recognition taking place within the image.
- object segmentation can again be carried out in which parts of objects with different spectra are separated from one another and treated as independent objects. For example, there can then be different adjoining areas in the image, which are separated from one another by edges.
- the spectra of pixels within an object in particular the pixels from the center of the object, are now combined with one another. This union can consist of the fact that the spectra of respectively neighboring pixels are combined or also the spectra of all pixels. The first gives an acceptable improvement even with slightly inhomogeneous objects, the second a very high resolution with homogeneous objects. Both alternatives can be combined with each other by dividing an object into concentric areas and combining the spectra of the pixels of these areas.
- Preferred further calibration methods for a multispectral multi-lens camera system are known methods for calibrating the dark current and / or calibrations for white balance and / or a radiometric calibration and / or a calibration within the scope of Photo Response Non Uniformity ("PRNU") ⁇
- FIG. 1 shows a multi-lens camera system according to the prior art.
- FIG. 2 shows a scene of a recording.
- FIG. 3 shows from above a scene of a recording and a multi-lens camera system with an exemplary embodiment of a device according to the invention.
- FIG. 4 shows an example of a dispersion effect.
- FIG. 5 shows an example of the central wavelength and the modification function.
- FIG. 6 shows an example of spectral enhancement for a recorded image.
- FIG. 7 shows a further example for spectral improvement for two recorded images.
- FIG. 8 shows an exemplary block diagram for the method according to the invention.
- FIG 1 shows schematically a multi-lens camera system 1 for hyperspectral recording of images according to the prior art in a perspective view.
- the multi-lens camera system 1 comprises a planar image sensor 3 and a planar lens matrix 2 made of uniform individual lenses 2a, which is arranged in such a way that a large number of first images AS arranged in a grid form from a motif M (see, for example, only the small first images AS in FIG 5) generated on the image sensor 3.
- a motif M see, for example, only the small first images AS in FIG 5
- an aperture mask 5 is arranged between the image sensor 3 and the lens matrix 2.
- Each aperture 5a of the aperture mask 5 is assigned to an individual lens 2a and arranged exactly behind it.
- a filter element 4 is arranged between the aperture mask 5 and the image sensor 3.
- this filter element 4 can also be arranged in front of the lens matrix (see e.g. FIG. 8).
- the filter element 4 is a linearly variable filter which is slightly rotated with respect to the image sensor. Each figure thus has its center at a different wavelength range of the filter element.
- Each first image AS thus supplies different spectral information on the image sensor, and the entirety of the first images AS is used to create an image with spectral information.
- FIG. 2 shows a scene of a recording of a motif M.
- This motif includes a house, which here serves as background H and a tree as object O in the foreground.
- This motif is recorded by a multi-lens camera system 1.
- FIG. 3 shows the motif M from FIG. 2 from above.
- the multi-lens camera system 1 here comprises an exemplary embodiment of a device 6 according to the invention. This device comprises a data interface 7, a determination unit 8, a determination unit 9 and a processing unit 10.
- the data interface 7 is designed to receive the images that have been recorded by the multi-lens camera system 1. For example, it can access the image sensor directly, communicate with a storage unit or with a network.
- the determination unit 8 is designed to determine a color field F of a region of a filter element 4 of the multi-lens camera system 1, which is assigned to a predetermined region of an image sensor 3 of the multi-lens camera system 1.
- the determination unit 9 is designed to determine the central wavelength Z for at least two pixels P1, P2 of the predetermined area of the image sensor 3 based on the determined color field F 1.
- the processing unit 10 is designed to modify the settings of the area of the image sensor 3 and / or images B that have been recorded with this image sensor 3. The modification is carried out based on the determined central wavelengths Z. As an alternative or in addition, the processing unit is designed to generate a supplementary data record for the images or to control the image recording.
- FIG. 4 shows an example of a dispersion effect.
- Two light beams (arrows) with an extended spectrum pass through a filter element 6 at different angles and therefore cover a different distance in the filter element 6. This can lead to a shift in the central wavelength Z.
- the filter element 6 can transmit different wavelengths at different locations, which also leads to different central wavelengths (even if the light beams were parallel).
- FIG. 5 shows an example for the central wavelength Z (left) and for the modification function, which here is an adaptation function A (right).
- a narrow spectrum with a central wavelength Z results after it has passed through.
- FIG. 6 shows an example of spectral enhancement for a recorded image B.
- the entire crown of the tree which here represents the object O
- each pixel P1, P2 which represents the crown of the tree
- the pixels P1, P2 are at different locations, they also have different central wavelengths Z (see e.g. the distribution on the right from FIG. 5). This means that the intensity of the two pixels P1, P2 reproduces information from a respective different part of an overall spectrum.
- the central wavelength Z of both pixels P1, P2 can therefore be assigned to each pixel P1, P2.
- FIG. 7 shows a further example for spectral improvement for two recorded images.
- the principle is very similar to FIG. 8 with the difference that the two pixels are at different coordinates of two different images, but at the same object coordinate of the tree (object O).
- each pixel P1, P2 represents a value of the same spectrum.
- the pixels P1, P2 are located in different areas of the image sensor 3, they also have different central wavelengths Z (see e.g. the distribution on the right from FIG. 5). This means that the intensity of the two pixels P1, P2 reproduces information from a respectively different part of an overall spectrum.
- the central wavelength Z of both pixels P1, P2 can therefore be assigned to each pixel P1, P2.
- FIG. 8 shows an exemplary block diagram for the method according to the invention for parallax determination of recordings from a multi-lens camera system 1.
- a color field F is determined for an area of a filter element 4 of the multi-lens camera system 1, which is assigned to a predetermined area of an image sensor 3 of the multi-lens camera system 1.
- the central wavelength Z is determined for at least two pixels (P1, P2) of the predetermined area of the image sensor 3 based on the determined color field F.
- step III there is a modification of the area of the image sensor 3 and / or of images B, B1 that have been recorded with this image sensor 3, and / or generation of a supplementary data record for the images or for controlling the image recording, based on the determined central wavelengths Z.
- step lilac there is a calibration (as an example of a modification) of the area of the image sensor 3 or of the images B that have been recorded with this area (see also FIG. 6 in this regard).
- step IIIb the spectral information of the recordings of the image sensor 3 is improved, with at least two pixels P1, P2 being determined in a number of images B, B1, whose central wavelengths Z are known and which belong to an image area for which the same spectrum is assumed and the spectral information of the pixels P1, P2 is combined to form a total spectral information for at least one of the pixels P1, P2 (see also FIG. 7 in this regard).
- Such an improvement in the spectral information can represent a modification of an image or be in the form of a supplementary data set.
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Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102019133516.7A DE102019133516B4 (de) | 2019-12-09 | 2019-12-09 | Verfahren und Vorrichtung zur Bestimmung von Wellenlängenabweichungen von Aufnahmen eines Multilinsen-Kamerasystems |
| PCT/DE2020/101034 WO2021115532A1 (de) | 2019-12-09 | 2020-12-07 | Verfahren und vorrichtung zur bestimmung von wellenlängenabweichungen von aufnahmen eines multilinsen-kamerasystems |
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| Publication Number | Publication Date |
|---|---|
| EP4073478A1 true EP4073478A1 (de) | 2022-10-19 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP20842551.2A Pending EP4073478A1 (de) | 2019-12-09 | 2020-12-07 | Verfahren und vorrichtung zur bestimmung von wellenlängenabweichungen von aufnahmen eines multilinsen-kamerasystems |
Country Status (4)
| Country | Link |
|---|---|
| EP (1) | EP4073478A1 (de) |
| CN (1) | CN114930136B (de) |
| DE (1) | DE102019133516B4 (de) |
| WO (1) | WO2021115532A1 (de) |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| SE0402576D0 (sv) * | 2004-10-25 | 2004-10-25 | Forskarpatent I Uppsala Ab | Multispectral and hyperspectral imaging |
| DE102010041569B4 (de) * | 2010-09-28 | 2017-04-06 | Leica Geosystems Ag | Digitales Kamerasystem, Farbfilterelement für digitales Kamerasystem, Verfahren zur Bestimmung von Abweichungen zwischen den Kameras eines digitalen Kamerasystems sowie Bildverarbeitungseinheit für digitales Kamerasystem |
| US8665440B1 (en) * | 2011-02-10 | 2014-03-04 | Physical Optics Corporation | Pseudo-apposition eye spectral imaging system |
| GB2488519A (en) * | 2011-02-16 | 2012-09-05 | St Microelectronics Res & Dev | Multi-channel image sensor incorporating lenslet array and overlapping fields of view. |
| IN2014CN03038A (de) | 2011-11-04 | 2015-07-03 | Imec | |
| US9395516B2 (en) | 2012-05-28 | 2016-07-19 | Nikon Corporation | Imaging device |
| CA2987404C (en) * | 2015-05-29 | 2024-09-10 | Rebellion Photonics, Inc. | HYDROGEN SULFIDE IMAGING SYSTEM |
-
2019
- 2019-12-09 DE DE102019133516.7A patent/DE102019133516B4/de active Active
-
2020
- 2020-12-07 EP EP20842551.2A patent/EP4073478A1/de active Pending
- 2020-12-07 WO PCT/DE2020/101034 patent/WO2021115532A1/de not_active Ceased
- 2020-12-07 CN CN202080092968.5A patent/CN114930136B/zh active Active
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| Publication number | Publication date |
|---|---|
| CN114930136B (zh) | 2025-11-11 |
| DE102019133516A1 (de) | 2021-06-10 |
| DE102019133516B4 (de) | 2021-07-15 |
| CN114930136A (zh) | 2022-08-19 |
| WO2021115532A1 (de) | 2021-06-17 |
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