Imaging system and method of image deblurring

Abstract

An imaging system (1) is specified, the imaging system (1) comprising a camera (2) configured to detect a radiation from a scene (9), a self-mixing interferometry (SMI) module (3) configured to obtain an object data from an object (95) within the scene (9), and a processing unit (4) connected to the camera (2) and to the SMI module (3), wherein the processing unit (4) is configured to obtain a deblurred image of the scene (9) based on data from the camera (2) and on the object data from the SMI module (3). Further, a method of image deblurring is specified.

Description

[0001] Description

[0002] IMAGING SYSTEM AND METHOD OF IMAGE DEBLURRING

[0003] The present application relates to an imaging system and to a method of image deblurring .

[0004] In recent years , sophisticated algorithms have been developed to address image deblurring . However, these algorithms require a lot of computational power so that image deblurring is often at the cost of either multiple acquisitions or time delay due to algorithm execution .

[0005] An obj ect to be solved is to provide a way that helps to improve or facilitate image deblurring .

[0006] This obj ect is obtained inter alia by an imaging system and a method according to the independent claims . Further developments and expediencies are the subj ect of the dependent claims .

[0007] An imaging system is speci fied .

[0008] According to at least one embodiment of the imaging system the imaging system comprises a camera configured to detect a radiation from a scene . For example the camera comprises a detector providing spatial resolution .

[0009] For example , the spatial resolution is at least 10 , 000 pixels or at least 100 , 0000 pixels or at least 1 megapixel . For example , the camera is configured to provide a monochromatic or a full color image in the visible spectral range . Alternatively or in addition, the camera may be sensitive in the infrared spectral range , in particular in the near infrared spectral range .

[0010] The camera may further comprise an optics configured to image the scene onto the detector .

[0011] According to at least one embodiment of the imaging system, the imaging system comprises a sel f-mixing interferometry ( SMI ) module configured to obtain an obj ect data from an obj ect within the scene . For example , the obj ect data includes information on a relative position with respect to the imaging device and / or or the velocity of the obj ect .

[0012] For example , a radiation source of the SMI module provides a radiation, wherein radiation reflected of f or scattered at the obj ect and coupled back into the radiation source causes an SMI signal that allows the obj ect data to be determined . In particular, sel f-mixing interference occurs as a portion of the radiation irradiating the obj ect is reflected or scattered back from the obj ect into a cavity ( or resonator ) of the radiation source . The optical interference of this radiation with the original radiation of the radiation source unit leads to a modulation of the laser characteristics . Monitoring at least one laser characteristic may provide information on the obj ect data . For example , the laser characteristic is a laser emission characteristic such as laser output power or a laser operation characteristic such as laser operation voltage or laser operation current .

[0013] For example , the SMI module comprises a vertical cavity surface-emitting laser (VCSEL ) or an array of VCSELs . VCSELs have a low threshold current and thus have a comparably low power consumption . Further, they can have small dimensions and are available at low cost . However, other laser diodes may also be used, such as edge-emitting lasers , for example distributed feedback ( DFB ) lasers or distributed Bragg reflector ( DBR) lasers .

[0014] For example , the SMI module is configured to emit radiation with a peak wavelength in the infrared or near infrared spectral range . For example , the SMI module is configured to emit radiation with a peak wavelength in a range from 800 nm to 1500 nm . Alternatively or in addition, the SMI module may be configured to emit radiation in the visible spectral range .

[0015] For example , the imaging system, in particular the SMI module comprises a sensing unit . In particular, the sensing unit is configured to provide a signal correlated to radiation returning from the obj ect . For example , the radiation is scattered at or reflected of f the obj ect . Thus , the signal of the sensing unit may provide information on the obj ect data such as position and / or velocity .

[0016] For example , the sensing unit is integrated in the radiation source and configured to obtain a sel f-mixing interference signal . For example , the sensing unit comprises a photodiode arranged behind or within the laser cavity in order to measure the output intensity of the laser .

[0017] For example , the photodiode and the active region of the semiconductor laser are integrated in a common semiconductor body comprising semiconductor layers formed by epitaxial growth . Alternatively, the photodiode may be located behind a back mirror of the laser cavity arranged opposite to a front mirror . Most of the radiation is emitted during operation of the laser source unit through the front mirror .

[0018] Alternatively, the signal of the sensing unit may be determined from a current or voltage input to the respective radiation source . Changes in these laser operation characteristics likewise allow information on the obj ect data to be obtained, as these parameters are af fected by sel fmixing interferometry ef fects as well .

[0019] According to at least one embodiment of the imaging system, the imaging system comprises a processing unit . For example , the processing unit is connected to the camera and to the SMI module . The processing unit may obtain data from the camera and the SMI module is input data . Further, the processing unit may be configured to control at least one component of the imaging system, for example at least one of the camera, the SMI module , a shutter, and an illumination source .

[0020] According to at least one embodiment of the imaging system, the processing unit is configured to obtain an image of the scene based on data from the camera and based on the obj ect data from the SMI module . In other words , the processing unit is configured to obtain an at least partly deblurred image of the scene or to obtain data that allows for a facilitated deblurring . In particular, the additional obj ect data obtained from the SMI module can be used to facilitate image deblurring, for example compared to an imaging system that provides camera data only . In at least one embodiment the imaging system comprises a camera configured to detect a radiation from a scene , a sel fmixing interferometry module configured to obtain an obj ect data from an obj ect within the scene and a processing unit connected to the camera and to the SMI module , wherein the processing unit is configured to obtain an image of the scene based on data from the camera and on the obj ect data from the SMI module .

[0021] By means of the SMI module provided in addition to the camera, the position and / or the velocity of a moving obj ect within the scene can be determined . In particular, the obj ect data can even be used during the image acquisition . Thus , the raw data from the camera can already be in a state which facilitates deblurring . Alternatively or in addition, a deblurring algorithm may be provided with the obj ect data so that the reconstruction of the deblurred image is facilitated .

[0022] Without the additional information on the obj ect data, postcapture deblurring is an ill-posed problem as image blur caused by obj ect motion attenuates high frequency content of the images . The recoverable frequency band quickly becomes narrow for faster obj ect motion as high frequencies are severely attenuated and virtually lost . In particular, obj ects moving at high speed appear signi ficantly blurred when captured with conventional cameras . The blurry appearance is especially ambiguous when the obj ect has a complex shape or texture . In such cases classical methods or even humans are unable to recover the obj ect ' s appearance and motion from the blurred image . Further, a point spread function estimation from a single image is a challenging problem i f only conventionally captured images are available . As the traj ectory and the velocity of the obj ect moving within the scene is typically unknown, conventional deblurring algorithms rely on solving sets of equations in which the solution minimi zes the error between the measurement and the estimation traj ectory applied to the estimated image . Usually this involves the use of heavy algorithms that run on dedicated hardware which consumes a considerable amount of energy and is therefore not suitable for portable devices . By means of the additional obj ect data obtained from the SMI module , in contrast , image deblurring can be signi ficantly facilitated so that the required algorithms can also run on portable devices such as smartphones or tablets .

[0023] According to at least one embodiment of the imaging system, the processing unit is configured to obtain a traj ectory of the obj ect . In particular, the traj ectory of the obj ect and the speed of the obj ect along the traj ectory may be used during the image acquisition . Alternatively or in addition, the data can be stored with the images to facilitate further processing .

[0024] According to at least one embodiment of the imaging system, the processing unit is configured to adapt an acquisition function of the imaging system based on the obj ect data from the SMI module . During an acquisition time , the obj ect data providing information on the velocity of the obj ect may be used to adapt the acquisition function and / or the acquisition time . Thus , the blur can already be mitigated during the image acquisition . The speed and the traj ectory allow the knowledge of the movement spread function so that the image deblurring is no longer an ill-posed problem . This makes the image deblurring faster and easier . In particular, the acquired image , although blurred, may contain more information than a conventional static image . By knowing position and velocity during acquisition, it is for example possible to recover a 3D representation of the moving obj ect .

[0025] According to at least one embodiment of the imaging system, the acquisition function comprises a plurality of acquisition time windows . During these time windows , image acquisition occurs whereas there is no , or at least a reduced, image acquisition between subsequent acquisition time windows . In other words , within the entire acquisition time used for recording the image , the acquisition function splits the acquisition time into a plurality of acquisition time windows spaced from one another in time .

[0026] According to at least one embodiment of the imaging system, at least for one time window a distance in time from the directly preceding time window di f fers from a distance in time from the directly following time window . In other words , the duration between the acquisition time windows within one acquisition time is not constant . For example , the distances in time di f fer from one another by at least 10% for at least some of the time windows .

[0027] For example , the acquisition function comprises a randomi zed sequence of acquisition time windows . It has been found that a randomi zed sequence of acquisition time windows may signi ficantly facilitate the image recovery .

[0028] According to at least one embodiment of the imaging system, the imaging system comprises a shutter . For example , the shutter comprises an electro-optical material that changes its transmission properties in response to an applied electrical voltage . Electro-optical shutters may provide particularly fast switching times , in particular compared to mechanical shutters . For example , the acquisition function acts on the shutter . In other words , the acquisition function represents an exposure function that defines the exposure windows during the entire exposure time ( or shutter speed) .

[0029] According to at least one embodiment of the imaging system, the imaging system comprises an illumination source . For example , the illumination source is configured to illuminate the scene to be imaged . For example , the illumination source is a flashlight . For example , the illumination source comprises a plurality of light sources that are controllable independently from one another .

[0030] The illumination source may be configured to emit radiation in the visible spectral range and / or in the infrared spectral range .

[0031] According to at least one embodiment of the imaging system, the illumination source is configured to proj ect an illuminating pattern onto the obj ect . In particular, the illuminating pattern can be provided based on the obj ect data obtained from the SMI module . Thus , an optimum illumination of the obj ect during image acquisition can be obtained .

[0032] According to at least one embodiment of the imaging system, the acquisition function acts on the illumination source . Thus , the time windows during which the image acquisition predominantly occurs may be defined using an appropriate illumination sequence . According to at least one embodiment of the imaging system, the illumination source is configured to adapt its illumination based on the obj ect data from the SMI module . For example , an adaptive flash may be tuned to provide an optimum illumination of the obj ect based on the measured position and / or velocity of the obj ect . Alternatively or in addition, the output power of the illumination source may be varied during the acquisition time .

[0033] According to at least one embodiment of the imaging system, the processing unit is configured to deblur the obj ect in the image based on the obj ect data from the SMI module . For example , a deblurring algorithm using the camera data and the obj ect data as input can be used . However, image deblurring may also be performed by a further processing unit using the output data of the imaging system . For example , the obj ect data may be stored together with the camera data for a subsequent image deblurring using an external processing unit .

[0034] Further, a method of image deblurring is speci fied .

[0035] According to at least one embodiment of the method, the method includes a step of detecting radiation from a scene using a camera .

[0036] According to at least one embodiment of the method, the method includes a step of obtaining obj ect data from an obj ect in the scene using sel f-mixing interferometry .

[0037] According to at least one embodiment of the method, the method includes a step of obtaining a deblurred image based on the obj ect data and the detected radiation . In at least one embodiment , the method of image deblurring comprises the steps of detecting radiation from a scene using a camera, obtaining obj ect data from an obj ect in the scene using sel f-mixing interferometry and obtaining a deblurred image based on the obj ect data and the detected radiation . The listing of the steps does not require the steps to be performed in the speci fied order .

[0038] According to at least one embodiment of the method, the step of detecting radiation from the scene is based on the obj ect data . Thus , the information obtained by means of sel f-mixing interferometry, for example velocity and / or position of the obj ect is used to detect the radiation from the scene in such a way that image deblurring is facilitated .

[0039] According to at least one embodiment of the method, an acquisition function is defined for the step of detecting radiation based on the obj ect data obtained using sel f-mixing interferometry . For example , the acquisition time may be defined based on the detected velocity of the obj ect . For example , the acquisition time can be automatically reduced for a fast-moving obj ect based on further parameters such as the light intensity reaching the camera and the maximum noise , the gain may be reduced to compensate for the light throughput loss due to the reduced acquisition time .

[0040] Alternatively or in addition, acquisition time windows may be appropriately defined based on the obj ect data as described above .

[0041] According to at least one embodiment of the method, the step of obtaining a deblurred image is performed after the step of detecting the radiation using the camera and the step of obtaining the obj ect data using sel f-mixing interferometry . Consequently, compared to a conventional image deblurring technique , a deblurring algorithm may be provided with additional information on the obj ect so that image deblurring is facilitated .

[0042] The method can in particular be performed using an imaging system as described above . Thus , features described in connection with the imaging system may also apply for the method and vice versa .

[0043] Features described above in connection with at least one embodiment of the method or the imaging system can be combined with other features described in connection with at least one embodiment of the method or the imaging system unless they are contradictory .

[0044] In the exemplary embodiments and figures similar or similarly acting constituent parts are provided with the same reference signs . Generally, only the di f ferences with respect to the individual exemplary embodiments are described . Unless speci fied otherwise , the description of a part or feature in one exemplary embodiment applies to a corresponding part or feature in another exemplary embodiment as well .

[0045] In the Figures :

[0046] Figures 1A and IB show an exemplary embodiment of an imaging system in perspective view ( Figure 1A) and in a schematic representation ( Figure IB ) ;

[0047] Figure 2 shows an exemplary embodiment of a method; Figure 3 shows an exemplary embodiment of steps of a method;

[0048] Figures 4A, 4B and 4C show three examples of a traj ectory, a sensor image and an intensity profile wherein the velocity of the moving obj ect increases from Figure 4A to Figure 4C ;

[0049] Figure 5 shows an example of a imaging system workflow;

[0050] Figure 6A illustrates an example of an exposure function, an obj ect position and a sensor image as a function of time ;

[0051] Figure 6B shows Fourier trans forms of the exposure function, obj ect position and sensor image of Figure 6A;

[0052] Figure 7A illustrates an example of a reference exposure function, a reference obj ect position and a reference sensor image as a function of time ;

[0053] Figure 7B shows Fourier trans forms of the reference exposure function, reference obj ect position and reference sensor image of Figure 7A;

[0054] Figure 8A shows an example of a traj ectory exposure , a sensor image and a recovered image ; and

[0055] Figure 8B shows a reference example for a reference traj ectory exposure , a reference sensor image and a reference recovered image .

[0056] The figures are schematic representations wherein the elements illustrated in the figures and their si ze relationships among one another are not necessarily true to scale . Rather, individual elements or layer thicknesses may be represented with an exaggerated si ze for the sake of better representability and / or for the sake of better understanding .

[0057] Figures 1A and IB illustrate an imaging system 1 comprising a camera 2 configured to detect a radiation from a scene 9 . The imaging system further comprises a sel f-mixing interferometry SMI module 3 configured to obtain an obj ect data from an obj ect 95 within the scene 9 .

[0058] The imaging system 1 further comprises a processing unit 4 connected to the camera 2 and to the SMI module 3 . The processing unit 4 is configured to obtain an image of the scene 9 based on data from the camera 2 and on the obj ect data from the SMI module 3 . As illustrated in Figure 1A, the obj ect 95 within the scene 9 is moving during the image acquisition .

[0059] In Figure 1A, four di f ferent positions of the obj ect 95 are illustrated as an example . By means of the SMI module 3 , the position and the velocity of the obj ect 95 with respect to the imaging system 1 can be calculated so that a traj ectory of the obj ect 95 can be obtained during the image acquisition .

[0060] Figure 1A further illustrates that an acquisition function for image recording may comprise a plurality of acquisition time windows 99 during an acquisition time At .

[0061] This will be described in more detail in connection with Figures 6A and 6B . In the exemplary embodiment of Figure IB, the imaging system 1 comprises an SMI module 3 with an SMI matrix 30 comprising a plurality of SMI devices 31 . For example , each of the SMI devices 31 is assigned to an individual partial region of the scene 9 . For example , the number of SMI devices 31 of SMI module 3 is at least one or at least two or at least five and / or at most 100 , 000 or at most 10 , 000 or at most 1 , 000 or at most 100 .

[0062] Each of the SMI devices 31 comprises a radiation source 32 configured to emit coherent radiation . For example , the radiation source 32 is a vertical cavity surface-emitting laser (VCSEL ) . Within the radiation source 32 , the radiation 38 emitted by the radiation source 32 oscillates in a cavity

[0063] 33 . Part of the radiation 38 impinges onto the obj ect 95 and is reflected of f or scattered at the obj ect 95 towards the SMI module 3 . Part of the returning radiation 39 is coupled back into the cavity 33 and interferes there with the original radiation produced by the radiation source 32 .

[0064] These interference ef fects may be detected by a sensing unit

[0065] 34 . For example , the sensing unit is configured to monitor a laser emission characteristic such as the optical output power or a laser operation characteristic such as operation current or operation voltage . The data of the sensing unit 34 may be used to determine the obj ect data with comparably low power consumption and a high repetition rate . Thus , the data from the SMI module may be used to control the image acquisition by the camera 2 .

[0066] As illustrated in Figure IB, the imaging system 1 may comprise a shutter 5 . Based on the obj ect data, the processing unit 4 may act on the shutter 5 to define the acquisition time and / or the acquisition function based on the obj ect data obtained from the SMI module 3 . For example , the shutter 5 may comprise an electro-optical material that changes its transmission in response to an applied electrical voltage or current .

[0067] As illustrated in Figure IB, the imaging system 1 may further comprise an illumination source 6 configured to produce an illumination radiation 60 .

[0068] Based on the obj ect data obtained from the SMI module 3 , the processing unit 4 may control the illumination source 6 appropriately . For example , the acquisition function may act on the illumination source in addition to the shutter 5 or instead of the shutter 5 .

[0069] Alternatively or in addition, the illumination source 6 may be configured to proj ect an illuminating pattern onto the obj ect 95 . For example , the illumination source may be configured as an adaptive flash that can be tuned to provide an optimum illumination based on the obtained obj ect data .

[0070] Thus , the illumination source 6 may adapt its illumination based on the obj ect data from the SMI module 3 .

[0071] Figure 2 shows an exemplary embodiment of a method of image deblurring . In a step 201 , radiation from a scene 9 is detected using a camera 2 . In a step 202 , obj ect data from an obj ect 95 in the scene 9 is obtained using sel f-mixing interferometry .

[0072] In a step 203 , a deblurred image is obtained based on the obj ect data and the detected radiation . The order of the method steps shown does not limit the actual order of the method steps performed. Rather, the image acquisition using the camera in step 201 may be performed based on the object data obtained in method step 202. In particular, an acquisition function may be defined for the image acquisition using the camera 2 based on the object data obtained via self-mixing interferometry.

[0073] Thus, the image recording may be performed such that image deblurring is facilitated. Alternatively or in addition, the object data obtained using self-mixing interferometry may be stored in addition to the camera data so that both the object data and the camera data may be used for a subsequent image deblurring. Consequently, a deblurring algorithm may be provided with additional information on the trajectory of a moving object within the scene.

[0074] Figure 3 illustrates a workflow where a constant exposure is performed during an acquisition time At. Using self-mixing interferometry, an SMI speed 301 is derived for the moving object 95 within the scene 9. Based on the SMI speed 301, the shutter speed 302 may be set. For example, the acquisition time (or shutter speed) At is reduced if an object moving at high speed through the scene 9 is detected. Based on a light intensity 305 and a maximum noise 306, an ISO gain 303 may be set such that an image sensor 304 provides raw data with mitigated blurring effects. Thus, the speed of the moving object may be used to set the ideal acquisition time.

[0075] Figures 4A, 4B and 4C illustrate examples of a trajectory 401, a sensor image 402 and a cross-section of an intensity profile 403, wherein the object shown in Figure 4A moves at the lowest speed and the object illustrated in Figure 40 moves at the highest speed. In these examples, the moving object has the shape of a circle in the image plane.

[0076] The figures illustrate that the blur sizes k in the sensor image 402 increase with increasing object speed. Using the SMI module 3, the object speed can be measured in real time so that the image acquisition can be adjusted in real time. This can be done either to optimally mitigate the blur or to recover the image more effectively. For example, for a given exposure time At, the best results are obtained if the pulse sequence length m essentially corresponds to the blur size K.

[0077] Figure 5 illustrates an example of an imaging system workflow where an SMI speed 501 derived from the SMI module 3 is used to define a coded sequence length 502 for the acquisition function which may act on a shutter 503 such that the image with information on the trajectory and the speed 504 may be obtained. Thus, the imaging system may mitigate the blur during acquisition and / or more effectively apply a deblur filter. In particular, the acquisition function may have an optimum sequence length m and the knowledge of the movement spread function makes the deblurring problem easier and faster to solve.

[0078] If the SMI module 3 comprises a plurality of SMI devices 31, for example in an SMI matrix 30, motion can be detected in different partial regions of the scene which allows for the deblur to be localized in the final image process. In a similar manner, this knowledge can also be used to make a 3D reconstruction of the object 95.

[0079] Figure 6A illustrates an example of an exposure function 601. The object 602 is a sinusoidal function in this example. In this example, the exposure function 601 represents a randomized sequence during the exposure time comprising a plurality of acquisition time windows at different distances in time. The resulting sensor image 603 is illustrated on the right-hand side of Figure 6A.

[0080] Figure 6B illustrates the associated Fourier transform functions wherein curve 601f represents the sampling frequency of the exposure function 601, curve 602f represents the sampling frequency of the object position 602 and curve 603f represents the sampling frequency of the sensor image 603. As curve 603f illustrates, the Fourier transform does not have any zero values so that the function is invertible in the convolutional sense.

[0081] Figure 8A illustrates an associated trajectory exposure 801, sensor image 802 and a recovered image 803. Due to the randomized exposure time windows, the star shape of the blurred object can be recognized well in the recovered image 803.

[0082] For comparison, Figure 8B illustrates associated reference trajectory exposure 801r, reference sensor image 802r and reference recovered image 803r. Reference recovered image 803r illustrates that the recovery process is not successful in this reference example. This is because the reference relies on a single exposure time window, as illustrated in Figure 7A (curve 601r) wherein the object position 602r corresponds to the object position 602 of Figure 6A.

[0083] Curve 603r represents the reference sensor image. Similar to Figure 6B, Figure 7B shows the associated Fourier trans form functions 601rf , 602rf and 603rf for the curves of Figure 7A. As the exposure function 601r is a simple rectangular window, its Fourier trans form 601rf has regular zeros at multiples of the frequency 1 / At . During the recovery process , the inverted zeros will diverge . Consequently, the image recovery does not provide reasonable results as reference recovered image 803r of Figure 8B illustrates .

[0084] The examples above illustrate that the additional SMI data may signi ficantly facilitate image deblurring . In particular, based on the obj ect data provided by the SMI module , the image acquisition may be adapted such that blurring ef fects are already mitigated during the image acquisition . Alternatively or in addition, the obj ect data such as the traj ectory and / or the velocity of the obj ect may be used for deblurring algorithms as additional input so that the reliability of the deblurring algorithm may be increased .

[0085] This patent application claims the priority of German patent application 10 2023 135 500 . 7 , the disclosure content of which is hereby incorporated by reference .

[0086] The invention described herein is not restricted by the description given with reference to the exemplary embodiments . Rather, the invention encompasses any novel feature and any combination of features , including in particular any combination of features in the claims , even i f this feature or this combination is not itsel f explicitly indicated in the claims or exemplary embodiments . References

[0087] 1 imaging system

[0088] 2 camera

[0089] 3 SMI module

[0090] 30 SMI matrix

[0091] 31 SMI device

[0092] 32 radiation source

[0093] 33 cavity

[0094] 34 sensing unit

[0095] 38 radiation

[0096] 39 returning radiation

[0097] 4 processing unit

[0098] 5 shutter

[0099] 6 illumination source

[0100] 60 illumination radiation

[0101] 9 scene

[0102] 95 obj ect

[0103] 99 time window

[0104] 201 method step

[0105] 202 method step

[0106] 203 method step

[0107] 301 SMI speed

[0108] 302 shutter speed

[0109] 303 ISO gain

[0110] 304 image sensor

[0111] 305 light intensity

[0112] 306 maximum noise

[0113] 401 traj ectory

[0114] 402 sensor image

[0115] 403 cross-section of intensity

[0116] 501 SMI speed

[0117] 502 coded sequence length shutter image , traj ectory, speed exposure function obj ect position sensor image f sampling frequency of exposure function f sampling frequency of obj ect position f sampling frequency of sensor image r reference exposure function r reference obj ect position r reference sensor image fr reference sampling frequency of exposure functionfr reference sampling frequency of obj ect positionfr reference sampling frequency of sensor image traj ectory exposure sensor image recovered image r reference traj ectory exposure r reference sensor image r reference recovered image

Claims

Claims1. An imaging system (1) comprising: a camera (2) configured to detect a radiation from a scene ( 9 ) ; a self-mixing interferometry (SMI) module (3) configured to obtain an object data from an object (95) within the scene ( 9 ) ; and a processing unit (4) connected to the camera (2) and to the SMI module (3) ; wherein the processing unit (4) is configured to obtain an image of the scene (9) based on data from the camera (2) and on the object data from the SMI module (3) .

2. The imaging system according to claim 1, wherein the processing unit (4) is configured to obtain a trajectory of the object.

3. The imaging system according to claim 1 or 2, wherein the processing unit (4) is configured to adapt an acquisition function of the imaging system based on the object data from the SMI module.

4. The imaging system according to claim 3, wherein the acquisition function comprises a plurality of acquisition time windows, wherein at least for one time window a distance in time from the directly preceding time window differs from a distance in time from the directly following time window.

5. The imaging system according to claim 3 or 4, wherein the imaging system comprises a shutter and the acquisition function acts on the shutter.

6. The imaging system according to any one of the preceding claims , wherein the imaging system (1) comprises an illumination source ( 6 ) .

7. The imaging system according to claim 6, wherein the illumination source is configured to project an illuminating pattern onto the object (95) .

8. The imaging system according to claim 6 or 7 when referring back to claim 3, wherein the acquisition function acts on the illumination source ( 6 ) .

9. The imaging system according to any one of claims 6 to 8, wherein the illumination source (6) is configured to adapt its illumination based on the object data from the SMI module (3) .

10. The imaging system according to any one of the preceding claims , wherein the processing unit (4) is configured to deblur the object in the image based on the object data from the SMI module (3) .

11. The imaging system according to any one of the preceding claims , wherein the SMI module (3) comprises an SMI matrix (30) with a plurality of SMI devices (31) , wherein the SMI devices are associated to different partial regions of the scene.

12. A method of image deblurring, comprising the steps of: a) detecting radiation from a scene (9) using a camera (2) ;b) obtaining object data from an object (95) in the scene(9) using self-mixing interferometry; c) obtaining a deblurred image based on the object data and the detected radiation.

13. The method according to claim 12, wherein step a) is performed based on the object data.

14. The method according to claim 12 or 13, wherein an acquisition function is defined for step a) based on the object data obtained in step b) .

15. The method according to any one of claims 12 to 14, wherein step c) is performed after step a) and step b) .

16. The method according to any one of claims 12 to 15, wherein the method is performed using an imaging system according to any one of claims 1 to 11.

Images