Method for obtaining a stack of images of a scene, computer program, device, apparatus and vehicle implementing such a method

Abstract

The invention relates to a method (100) for obtaining a stack of images of a scene from a stack of source images (PILs), referred to as source stack, which is acquired with a camera module comprising at least one optical lens and at least one image sensor, and includes at least two source images acquired with different focuses, said method (100) comprising the following steps for at least one source image from said source stack: - correcting (102) geometric aberration(s) in the source image in relation to a reference format by means of a coordinate transformation function, and - storing (108) said corrected image in a stack of images (PILc), referred to as corrected stack, which includes the at least one corrected image instead of the source image. The invention also relates to a computer program and a device implementing such a method.

Description

DESCRIPTION Title: Method for obtaining a stack of images of a scene, computer program, device, apparatus and vehicle implementing such a method.

[0001] The present invention relates to a method for obtaining a stack of images of a scene, and in particular to a stack of images in which at least two images, and in particular all the images, represent the scene with a different focus. It also relates to a computer program and a device implementing such a method. It further relates to an apparatus and a vehicle implementing such a method.

[0002] The field of the invention is the field of obtaining a stack of images of a scene at different focuses. State of the art

[0003] Techniques are known for representing a scene from a stack of images taken at different focusing distances, also called focus, depths of field, different in the present application. For example, the technique called focus bracketing, or focus stacking, "stacking of focus points" in French, is known, which makes it possible to capture a stack of images of a scene, each image being captured at a different depth of field. Then, the scene is represented on a display medium, with a greater depth of field, by exploiting the stack of images.

[0004] However, current techniques, although improving the depth of field of the image of a scene, have drawbacks. When acquiring the stack of images by a camera module comprising an image sensor and an optical lens, the distance between the image sensor and the optical lens is modified to change the focus, in particular for the acquisition of each image. The inventors noticed that this change in focus causes distortions, or shifts, in the images and therefore degrades the representation of the scene on a display medium from the stack of images thus obtained.

[0005] An aim of the present invention is to remedy at least one of the drawbacks of the state of the art.

[0006] Another aim of the invention is to propose a solution making it possible to obtain a stack of images representing the scene at different focuses comprising fewer, or no, geometric aberrations, thus allowing a representation of said scene with fewer distortions or shifts. Statement of the invention

[0007] The invention proposes to achieve at least one of the aforementioned aims by a method of obtaining a stack of images of a scene, from a stack of source images, called source stack, of said scene, said source stack: - comprising at least two source images acquired at different focuses, such that said at least two source images have different areas of sharpness for said scene, and - having been acquired with a camera module comprising at least one optical lens and at least one image sensor; said method comprising the following steps for at least one source image of said source stack: - correction of geometric aberration(s) in said source image, predetermined, by applying, to at least one pixel of said source image, a predetermined coordinate transformation function relative to a reference format, said correction providing a corrected image, and - storing a stack of images, called corrected, comprising said at least one corrected image in place of said source image.

[0008] Thus, the invention proposes to obtain a stack of images, called a corrected stack, in which the geometric aberrations due to a change of focus during the acquisition of the stack of source images are corrected, in at least one image, and in particular all the stack images (except possibly one). As a result, the corrected stack does not present, or presents fewer, geometric aberrations. By using the corrected image stack, it is then possible to produce a representation of the scene on a display medium with little, or no, distortions, or shifts, during said representation, in particular when switching from one of the images in the corrected stack to another, for example to modify the sharp area of ​​the scene displayed on the display medium. In addition, the use of the corrected stack does not require any registration, between them, of the images forming said corrected stack.

[0009] It should be noted that the correction of geometric aberrations does not consist of, or is different from, the registration of images with each other. Indeed, the registration of a first image with respect to a second image applies a coordinate transformation that is uniform, or identical, to all the pixels: for example a translation or a rotation, identical to all the pixels of the image. In a different way, the correction of geometric aberrations is carried out with a coordinate transformation that is different for at least two pixels of the image, and in particular all the pixels of the image.

[0010] By image we mean a digital image, and in particular a raster image.

[0011] According to the invention, the display medium can be any type of display medium.

[0012] For example, the display medium may be a display screen, such as a touch screen, etc.

[0013] For example, the display medium may be a surface onto which an image of the scene is projected, such as, for example, a display surface associated with a projector, etc.

[0014] The display medium may be a display medium fitted to the apparatus implementing the invention, such as: - a display screen fitted to said device, etc. or - a projection surface equipping said device.

[0015] The display medium may be a medium independent of the apparatus implementing the invention, for example a display surface, such as a a painting, a wall, a curtain, etc., receiving images projected by a projector.

[0016] According to the invention, the correction of geometric aberrations in at least one source image is carried out with respect to a reference format.

[0017] In embodiments, the reference format may be a source image in the source stack. That is, one of the source images in the image stack is chosen as the reference image. Geometric aberrations in one, or each, of the other source images in the source stack are corrected with reference to said source image chosen as the reference image, or reference format. In this case, potentially all source images in the source stack may be corrected, except for the source image chosen as the reference format.

[0018] According to embodiments, the reference format may be the format of the image sensor. In other words, the image sensor is chosen as a reference for correcting geometric aberrations in the source images forming the source stack. Geometric aberrations in one, or each, of the source images of the source stack are corrected with reference to the image sensor. In this case, potentially all of the source images forming the source stack can be corrected. This embodiment has the advantage of better correcting the source stack because each of the source images can be corrected. In addition, this embodiment makes it possible to determine the associated coordinate transformation function(s) associated with the camera module and which can be used for all of the source stacks captured by said camera module, for the same scene or for different scenes.

[0019] According to embodiments, for at least one source image, the step of correcting geometric aberration(s) in said source image comprises the following steps carried out for at least one pixel of said source image: - calculation, by the predetermined coordinate transformation function taking as input the position of said pixel in said source image, of a position, called corrected, of said pixel in the reference format, and - resetting of said pixel to said corrected position.

[0020] Thus, geometric aberration correction is performed individually for each point / pixel of the source image. The coordinate transformation applied to one point / pixel may be different from that applied to another point / pixel. In comparison, conventional registration of a first image with respect to a second image generally applies the same transformation to all pixels of the first image.

[0021] According to embodiments, for at least one source image, the transformation function may be a function of the focus of said source image, so that two source images acquired at two different focuses are corrected with different transformation functions.

[0022] Thus, the invention makes it possible to achieve better correction of geometric aberrations in source images acquired at different focuses. Indeed, when source images are acquired with different focuses, the geometric aberrations introduced into said source images, due to the focus, are different. In other words, a first source image acquired at a first focus comprises geometric aberrations which differ from those found in a second image acquired at a second focus, different from the first. Consequently, the coordinate transformation function used to correct the geometric aberrations in the first image with respect to a reference format is different from the coordinate transformation function used to correct the geometric aberrations in the second image.

[0023] For a source stack comprising K source images taken at K different focuses, and in the case where the reference format is one of the source images in the source stack, there can be a total number of (Kl) coordinate transformation functions. In this case, the coordinate transformation functions can be stored in a database by being associated, each, with a focus pair {focus source image used as reference format; focus corrected source image}.

[0024] Alternatively, for a source stack comprising K source images taken at K different focuses, and in the case where the reference format is not one of the source images forming the source stack, for example when the reference format is the image sensor, there may be a total number of K coordinate transformation functions. In this case, the coordinate transformation functions may be stored in a database, each associated with a focus.

[0025] In the correction step, the coordinate transformation function can be read from said database, depending on the focus of the corrected image.

[0026] At least one coordinate transformation function can be of any type, such as a mathematical relation.

[0027] In accordance with embodiments, but not limited to, at least one transformation function may be a pre-trained intelligent model, such as a neural network.

[0028] According to embodiments, but not limited to, at least one transformation function may be a position correspondence matrix. In this case, each location of the correspondence matrix may indicate the corrected position of a pixel / point corresponding to said location in the image to be corrected. In particular, the correspondence matrix may have the same dimensions as the reference format, and in particular the image sensor used for the acquisition of the source stack. In other words, if the reference format comprises (UxV) pixels, at least one coordinate transformation function may be a matrix of size (UxV). In this case, for example, each box (ui,vi) of the matrix may comprise values ​​indicating the position (U2,vz), in the corrected image, of a point / pixel located at said position (ui,vi) in the source image to be corrected.

[0029] To the first order, that is to say for an optical lens not having geometric aberration, at least one transformation function depends directly on the camera - lens distance, more precisely, camera - equivalent optical center of the lens. The transformation function can then be a homothety whose center is the axis perpendicular to the sensor passing through this equivalent optical center, and whose magnification factor is the ratio between this new distance and that of the so-called reference image. This homothety can also be expressed as a field of translation vectors, to the first order radial, centrifugal for a magnification, centripetal for a shrinkage. By equivalent optical center, we mean a point in the lens located on its axis of rotational symmetry, and at a position such that a straight line connecting a point in the scene and its projection on the sensor intercepts this point. We can index the images in the image stack by this distance camera - equivalent optical center of the lens, in order to reduce the basis of the corrections to be memorized.The latter can be represented only by the previously defined center point of the sensor - coming from the axis of symmetry - and the ratio of the projection factor, or an absolute projection factor for each lens setting value in front of the sensor.

[0030] At least one coordinate transformation function may be determined beforehand, for example during a calibration phase which is not part of the present invention.

[0031] Alternatively, the method according to the invention may further comprise, prior to the correction step, a phase, called the calibration phase, for determining at least one, in particular each, coordinate transformation function.

[0032] Preferably, but without loss of generality, at least one coordinate transformation function may be specific to the camera module used for capturing the image stack. Thus, said at least one coordinate transformation function is a function of the aberrations specific to the change of focus in said camera module. This makes it possible to carry out a correction of the aberrations specific to said camera module, and therefore more precise.

[0033] Alternatively, or in addition, at least one coordinate transformation function may be design-specific, and / or the architecture of the camera module used for capturing the image stack. In this case, said at least one coordinate transformation function is common to several camera modules having the same design and / or the same architecture. This makes it possible to equip several devices with the same transformation function(s), which is faster to implement because it does not require characterizing each camera module.

[0034] Alternatively, or in addition, at least one coordinate transformation function may be specific to a production batch of the camera module used for capturing the image stack. In this case, said at least one coordinate transformation function is common to several camera modules belonging to the same production batch, which makes it possible to obtain a faster implementation while providing more precision for the correction of aberrations.

[0035] Alternatively, or in addition, at least one coordinate transformation function may not be specific to a camera module.

[0036] The calibration phase can be carried out before or after production of the camera module.

[0037] The calibration phase can be performed before or after acquisition of the source stack.

[0038] The calibration phase can be carried out in the same device that carried out the acquisition of the source stack.

[0039] The calibration phase can be carried out in a device other than the one that carried out the acquisition of the source stack.

[0040] Preferably, but in no way limiting, the calibration phase can be carried out with the camera module used for capturing the source stack so that at least one transformation function is specific to said camera module.

[0041] According to an exemplary embodiment, at least one coordinate transformation function can be determined by simulation, from a digital model of a camera module.

[0042] For example, it is possible to simulate using simulation software, for example of the Zemax ® type, taking as input a digital model of the camera module, the propagation of a light ray in said camera module. This simulation can be repeated: - for different focuses, and in particular the focuses corresponding to those used during the acquisition of the source stack; and / or - for different points in space. It is then possible to identify by simulation the pixel receiving the light ray, for different points in space and for different focuses, which makes it possible to determine the coordinate transformation function(s).

[0043] The simulation can be carried out not with a point light ray, but with a reference pattern, such as a target. This allows the simulation to be carried out for a multitude of points in space, simultaneously, for a given focus.

[0044] According to an exemplary embodiment, at least one coordinate transformation function can be determined, from a stack of images actually acquired.

[0045] According to one embodiment, the calibration phase can be performed with a stack of images. In this case, the calibration phase can comprise the following steps: - acquisition of a stack of images, called a calibration stack, with at least the same focus as those of the images in the source stack, and - deduction from said calibration stack of at least one coordinate transformation function.

[0046] The calibration stack may be a stack of images of a calibration pattern. The calibration pattern may be a calibration scene or a pattern such as a calibration target.

[0047] During the calibration phase, several images are captured, either in real life or by simulation, to constitute a calibration stack, each to one focus among several focuses, such as for example the focuses used during the acquisition of the stack of images of the scene. The calibration pattern being known, it is possible to determine, for each point of the calibration pattern, the pixel to which it corresponds, and this for each of the focuses used. By knowing, for each point of the calibration pattern, the pixel which corresponds to it for each of the focuses, it is then possible to establish the coordinate transformation functions, for example in the form of correspondence matrices, or in the form of mathematical functions.

[0048] Alternatively, the calibration phase can be performed with the source stack, by analyzing the content of the source images forming said source stack.

[0049] In this case, the source stack can be analyzed to detect the different objects in the scene on each source image of the scene. The pixels corresponding to these objects are then determined, for each source image of the scene, which then allows each coordinate transformation function to be deduced.

[0050] According to embodiments, at least one coordinate transformation function can be received from a device other than the one implementing the correction step, in particular when the source stack has been acquired by said other device.

[0051] In this case, preferably, said at least one transformation function may be specific to the camera module of said other device.

[0052] Alternatively, the correction step can be implemented in the device used for source stack acquisition.

[0053] According to embodiments, the method according to the invention may not include a step of acquiring the source stack.

[0054] According to embodiments, the method according to the invention may further comprise a step of acquiring the source stack. The source stack may be acquired by any method, and in particular by focus bracketing.

[0055] According to another aspect of the invention, there is provided a computer program comprising executable instructions which, when executed by a computing device, implement all the steps of the method according to the invention.

[0056] The computer program can be in any computer language, such as machine language, C, C++, JAVA, Python, etc.

[0057] According to another aspect of the invention, a device is proposed comprising means configured to implement all the steps of the method according to the invention.

[0058] The device according to the invention can be, or be integrated into, any type of device such as a smartphone, a tablet, a computer, a calculator, a processor, a computer chip, programmed to implement the method according to the invention, for example by executing the computer program according to the invention.

[0059] According to another aspect of the invention, there is provided an apparatus comprising: - at least one camera module comprising an optical lens and an image sensor, and - at least one computing unit; configured to implement all the steps of the method according to the invention.

[0060] The apparatus according to the invention may comprise at least one means for displaying an image which may be any type of display means.

[0061] For example, the display means may be a display screen, such as a touch screen, etc.

[0062] For example, the display means may be a projector projecting images onto a display surface.

[0063] In particular, the device may be a user device such as a smartphone, tablet, etc.

[0064] In particular, the device may be a computer-type user device.

[0065] In particular, the device may be a television.

[0066] In particular, the device may be a virtual reality or augmented reality headset.

[0067] In particular, the device may be a medical imaging device.

[0068] In particular, the device may be an endoscope, an ultrasound device, etc.

[0069] Of course, the invention is not limited to the devices just given.

[0070] According to another aspect of the present invention, there is provided a vehicle comprising: - at least one camera module comprising an optical lens and an image sensor, and - at least one computing unit; configured to implement the method according to the invention.

[0071] The vehicle may include at least one means for displaying an image which may be any type of display means.

[0072] For example, the display means may be a display screen, such as a touch screen, etc.

[0073] For example, the display means may be a projector projecting images onto a display surface.

[0074] According to embodiments, the vehicle may be a land vehicle, such as a car, autonomous or not.

[0075] According to embodiments, the vehicle may be a flying vehicle, such as a drone, an airplane, a helicopter, autonomous or not.

[0076] According to embodiments, the vehicle may be a maritime vehicle, such as a boat or a submarine, autonomous or not. Description of figures and embodiments

[0077] Other advantages and characteristics will appear on examining the detailed description of non-limiting embodiments, and the attached drawings in which: - FIGURES 1-3 are schematic representations of non-limiting exemplary embodiments of a method according to the invention; - FIGURE 4 is a schematic representation of a non-limiting exemplary embodiment of a device according to the invention; - FIGURES 5a-5c are schematic representations of non-limiting exemplary embodiments of an apparatus according to the invention; and - FIGURE 6 is a schematic representation of a non-limiting exemplary embodiment of a vehicle according to the invention.

[0078] It is understood that the embodiments which will be described below are in no way limiting. In particular, it is possible to imagine variants of the invention comprising only a selection of characteristics described below isolated from the other characteristics described, if this selection of characteristics is sufficient to confer a technical advantage or to differentiate the invention compared to the state of the prior art. This selection includes at least one preferably functional characteristic without structural details, or with only part of the structural details if it is this part which is only sufficient to confer a technical advantage or to differentiate the invention compared to the state of the prior art.

[0079] In particular, all the variants and embodiments described can be combined with each other if there is no technical obstacle to this combination.

[0080] In the figures and in the rest of the description, the elements common to several figures retain the same reference.

[0081] FIGURE 1 is a schematic representation of a non-limiting exemplary embodiment of a method according to the present invention.

[0082] The method 100 of FIGURE 1 can be used to obtain a stack of images of a scene comprising images acquired at different focuses, comprising no, or very few, geometric aberrations due to the use of different focuses during the acquisition of said images.

[0083] The method 100 takes as input a stack of source images of the scene, called a source stack, and denoted PILs. This PILs source stack can be captured by the apparatus implementing the method 100 or another apparatus. The PILs source stack comprises several images of the scene, at least two of which, and in particular all of them, are captured with different focuses so that each of said images has a different sharpness zone for the scene. In other words, the scene is represented on each of the images with a different sharpness zone.

[0084] The method 100 comprises a step 102 of correcting geometric aberrations for at least one, in particular several, or even all, of the source images forming the PILs source stack, with respect to a reference format and using at least one predetermined coordinate transformation function.

[0085] The reference format can be a source image that is part of the PILs source stack.

[0086] Alternatively, the reference format can be the format of the image sensor used for the acquisition of the source stack. In the following, without loss of generality, we consider the reference format and the format of the image sensor.

[0087] Step 102 is performed individually for at least one, and in particular each, source image.

[0088] For the given source image as input, step 102 comprises the following steps performed for at least one, and in particular each, pixel / point of said source image individually.

[0089] In a step 104 the position of said point / pixel is given as input to a predetermined coordinate transformation function. This coordinate transformation function gives as output a corrected position of this point / pixel.

[0090] In a step 106, the pixel / point whose corrected position was identified in step 104 is added to said corrected position in a corrected source image, also called corrected image.

[0091] By performing steps 104 and 106 for several, and in particular all, points / pixels of the source image, a corrected source image is constructed for said source image. The corrected image represents the scene and does not include, or very few, geometric aberrations due to the focus used to capture the source image.

[0092] Steps 104 and 106 can be performed for each point / pixel of the source image, in turn or in parallel.

[0093] In step 108 the corrected image is stored.

[0094] By performing step 102 for several, or even each, of the source images of the PIL source stack S, in turn or in parallel, a stack of corrected images, called the corrected stack, noted PIL C , is obtained for the scene.

[0095] The corrected PIL stack C may only include corrected images. In particular, the PIL corrected stack C can include a corrected image for each source image in the PIL source stack S .

[0096] Alternatively, the corrected PIL stack C may include corrected images and at least one uncorrected source image.

[0097] The corrected PIL stack C can be stored instead of the PILs source stack. In this case, the corrected PIL stack C is obtained by replacing the source image with the corrected image obtained in step 102 for said source image.

[0098] Alternatively, the corrected PIL stack C can be stored in addition to the PILs source. In this case, the corrected PIL stack Cis built in parallel with the PIL source stack S by gradually adding the corrected images obtained in step 102. If at least one source image is not corrected, a copy of it can be added to the corrected stack PIL C .

[0099] The, or each, data transformation function used in step 104 may be any mathematical relationship. In the following, and without loss of generality, it is considered that the, or each, coordinate transformation function is a position correspondence matrix.

[0100] In addition, in embodiments, for each source image, the coordinate transformation function used to correct said source image depends on the focus used for the acquisition of said source image. Indeed, the geomatic aberrations introduced into an image depend on the focus used for the acquisition of said image. Thus, these aberrations may differ from one image to another when these images are acquired at different focuses.

[0101] In the example of FIGURE 1, the at least one coordinate transformation function is not calculated. Indeed, the at least one transformation function may have been previously calculated. Alternatively, the at least one transformation function may have been provided with the PILs image stack.

[0102] FIGURE 2 is a schematic representation of another non-limiting exemplary embodiment of a method according to the present invention.

[0103] The method 200 of FIGURE 2 can be used to obtain a stack of images of a scene comprising images acquired at different focuses, comprising no, or very few, geometric aberrations due to a change of focus during the acquisition of said images.

[0104] The method 200 of FIGURE 2 includes all of the steps of the method 100 of FIGURE 1.

[0105] The method 200 further comprises a phase 202, called the calibration phase, for calculating at least one coordinate transformation function.

[0106] The calibration phase 202 can be carried out by simulation from a digital model of a camera module. Alternatively, the calibration phase 202 can be carried out from images taken by a real camera module.

[0107] Preferably, the calibration phase 202 can be carried out with the camera module used for the acquisition of the PIL source stack SAlternatively, the calibration phase 202 can be carried out with a camera module other than that used for the acquisition of the PIL source stack. S . In this case, the other camera module can be a camera module with the same design as the camera module used for the acquisition of the PIL source stack S , and / or a camera module produced in the same manufacturing batch as the camera module used for the acquisition of the PILs source stack.

[0108] The calibration phase 202 can be carried out with the source stack PILs or a stack of images from another scene, or even a stack of images from a reference scene.

[0109] In the example described in FIGURE 2, it is considered, without loss of generality, that the calibration phase 202 is carried out, before the acquisition of the PILs source stack, with a reference scene. The reference scene can be any type of scene. Preferably, the reference scene is a test pattern having a known pattern, and arranged at a known distance.

[0110] Furthermore, it is considered that the calibration phase 202 is carried out with the same camera module as that used for the acquisition of the PILs source stack, or another camera module having the same design and being part of the same manufacturing batch as that used for the acquisition of the PILs source stack. [YES] The calibration phase 202 comprises a step 204 of acquiring a stack of images, called the calibration stack, and noted PILcai. Preferably, the calibration stack PILcai comprises images taken with at least the same focus as those of the images of the source stack PILs. For example, the calibration stack PILcai can be acquired by a focus bracketing technique.

[0112] Then, a step 206 calculates a coordinate transformation function between each image of the PILcai calibration stack and the reference format. The reference format can be an image of the calibration stack. Preferably, and without loss of generality, in the following, the reference format is considered to be the format of the image sensor.

[0113] To do this, for each image in the PI LCAL calibration stack, each point of the target is identified on the image. By knowing the position of each point of the target on the image sensor, it is then possible to determine the coordinate transformation function giving for each position of the image, the corresponding position in the reference format, namely on the sensor.

[0114] In a step 208, the coordinate transformation function associated with each image of the PI LCAL calibration stack, and therefore with the focus used for the acquisition of said image, is stored in association with said focus. Thus, this coordinate transformation function can be used to perform a coordinate transformation between an image taken at said focus in order to correct the geometric aberrations due to said focus.

[0115] Thus, if the PI LCAL calibration stack comprises K images, step 206 provides K coordinate transformation functions. If the PI LCAL calibration stack comprises a high number of focuses, and potentially all possible focuses with the camera module, then it is possible to determine all the transformation functions that could potentially be needed to correct geometric aberrations in the images captured with said camera module.

[0116] In a step 208, each coordinate transformation function is stored in association with the corresponding focus.

[0117] As indicated above, the coordinate transformation functions obtained during the calibration phase 202 can be used for one or more source stacks, and for the same scene, or different scenes.

[0118] FIGURE 3 is a schematic representation of another non-limiting exemplary embodiment of a method according to the present invention.

[0119] The method 300 of FIGURE 3 may be used to obtain an image stack of a scene comprising images acquired at different focuses, not containing, or very little, geometric aberrations due to a change of focus during the acquisition of said images.

[0120] The method 300 of FIGURE 3 includes all of the steps of the method 200 of FIGURE 2.

[0121] The method 300 further comprises a step 302 of acquiring the stack of source images PILs comprising images acquired at different focuses so that said images comprise different areas of sharpness. Preferably, each source image of the source stack PILs is acquired at a different focus from the other images of the source stack PILs.

[0122] The PILs image stack can be acquired using any known technique, for example by focus bracketing.

[0123] According to a non-limiting exemplary embodiment not shown in the FIGURES, the method according to the invention can comprise all the steps of the method 300, but the step 302 of acquiring the source stack PILs can be carried out before the calibration phase 202.

[0124] According to a non-limiting exemplary embodiment not shown in the FIGURES, the method according to the invention can comprise all the steps of the method 300, with the exception of the calibration phase 200.

[0001] FIGURE 4 is a schematic representation of a non-limiting exemplary embodiment of a device according to the present invention.

[0002] The device 400 of FIGURE 4 comprises a module 402 implementing the step of correcting geometric aberrations.

[0003] The module 402 comprises a module 404 carrying out an identification of the corrected position of a point / pixel in a source image. This module 404 takes as input a position of the point / pixel in the source image and returns a corrected position of said point / pixel in a corrected image, using a coordinate transformation function. This module 404 is in particular configured / programmed to carry out step 104 of the methods 100, 200 and 300.

[0004] The module 402 comprises a module 406 carrying out a construction of a corrected image. This module 406 is in particular configured / programmed to carry out step 106 of the methods 100, 200 and 300.

[0005] The module 402 comprises a module 408 carrying out a storage of each corrected image in a corrected stack. This module 408 is in particular configured / programmed to carry out step 108 of the methods 100, 200 and 300.

[0006] The device 400 may further comprise an optional calibration module 410 for determining the coordinate transformation functions. This module 410 is in particular configured / programmed to carry out phase 202 of the methods 200 and 300.

[0007] The device 400 may further comprise an optional module 412 for acquiring a stack of images of a scene, by cooperating with a camera module comprising an image sensor and an optical lens. This module 412 is in particular configured / programmed to carry out step 302 of the method 300. The optional module 412 may for example be a photo application.

[0008] At least one of the modules of the device 400 may be a module independent of the others.

[0009] At least two modules of the device 400 can be integrated within the same module.

[0010] At least one of the modules of the device 400 may be a hardware module.

[0011] At least one of the modules of the device 400 may be a software module, such as a computer program.

[0012] At least one of the modules of the device 400 may be a combination of at least one software module, such as a computer program, and at least one hardware module.

[0013] In particular, at least one of the modules of the device 400 can be integrated into an electronic chip, or even into an application installed in a user device.

[0014] The device 400 may further comprise, optionally, at least one display means 420, such as a display screen, touch or no, or a means of projecting an image onto a medium, to display an image of the scene.

[0015] Such a display means may be integrated into the device.

[0016] Such a display means is optional because the device may not include such a means. For example, the device 400 may be integrated into an apparatus that already has a display means and cooperate with said display means to display the image of the scene.

[0017] According to yet another alternative, the device 400 can be connected to an external display means, or to an external device having a display means or itself connected to a display means.

[0018] In the example shown, and without loss of generality, the display means may be an electronic display screen.

[0019] Optionally, the device 400 may further comprise at least one image acquisition means 430, such as a camera, or a camera module, comprising an optical lens and an image sensor, for acquiring an image or a stack of images of the scene.

[0020] Such an image acquisition means 430 may be integrated into the device, for example on a front face or on a rear face, or both.

[0021] According to yet another alternative, the device 400 can be connected to an external image acquisition means, or to an external device having an image acquisition means or itself connected to an image acquisition means.

[0022] The device 400 may further comprise, optionally, at least one sensor 450 for detecting: - the position of a pointer, - the contact position of a part of the user's body such as a hand or finger, or - the position aimed at by a part of the user's body such as a hand, a finger, an eye, eyes or the user's face.

[0023] The sensor 450 can be any type of sensor such as a camera, a lidar, a detection surface for example of the capacitive type, etc.

[0024] In the example shown in FIGURE 4, and without loss of generality, the sensor 450 may be in the form of a detection surface, of the capacitive type, integrated into the display means 420.

[0025] Such a sensor 450 is optional because the device may not include such a sensor. For example, the device 400 may be integrated into an apparatus that already has a sensor.

[0026] FIGURE 5a is a schematic representation of a non-limiting exemplary embodiment of an apparatus according to the present invention.

[0027] The apparatus 510 of FIGURE 5a comprises means configured to implement the invention, and in particular any one of the methods 100, 200 and 300.

[0028] The apparatus 510 of FIGURE 5a may comprise a device according to the invention, and in particular the device 400 of FIGURE 4.

[0029] In the example shown in FIGURE 5a, the device 510 is a smartphone, or a tablet, comprising the device 400 of FIGURE 4. In particular, the device 510 comprises a display screen 420 equipped with a detection surface 450, for example capacitive, and at least one camera module 430.

[0030] FIGURE 5b is a schematic representation of another non-limiting exemplary embodiment of an apparatus according to the present invention.

[0031] The apparatus 520 of FIGURE 5b comprises means configured to implement the invention, and in particular any one of the methods 100, 200 and 300.

[0032] The apparatus 520 of FIGURE 5b may comprise a device according to the invention, and in particular the device 400 of FIGURE 4, without the camera 430.

[0033] In the example shown in FIGURE 5b, the device 520 is a virtual reality, VR, headset, or an augmented reality headset, comprising the device 400 of FIGURE 4. In particular, the headset 520 comprises a display screen 420, a sensor (not visible in FIGURE 5b) to detect the position aimed by an eye, or eyes, of the user on said display screen 420.

[0034] The headset 520 may comprise at least one camera for capturing images of the scene in which it is located to display them on the screen 420, optionally after enriching said images, for example in the context of an augmented reality application.

[0035] FIGURE 5c is a schematic representation of a non-limiting exemplary embodiment of an apparatus according to the present invention.

[0036] The apparatus 530 of FIGURE 5c comprises means configured to implement the invention, and in particular any one of the methods 100, 200, and 300.

[0037] The apparatus 530 of FIGURE 5c may comprise a device according to the invention, and in particular the device 400 of FIGURE 4.

[0038] In the example shown in FIGURE 5c, the apparatus is a medical imaging apparatus, such as an endoscope, an ultrasound apparatus, etc. comprising the device 400 of FIGURE 4. In particular, the medical imaging apparatus 530 comprises a display screen 420 equipped with a detection surface 450, for example capacitive. The medical imaging apparatus 530 further comprises an imaging means formed by a distal objective connected to an imaging module (not shown).

[0039] FIGURE 6 is a schematic representation of a non-limiting exemplary embodiment of a vehicle according to the present invention.

[0040] The vehicle 600 of FIGURE 6 comprises means configured to implement the invention, and in particular any one of the methods 100, 200 and 300.

[0041] The vehicle 600 of FIGURE 6 may comprise a device according to the invention, and in particular the device 400 of FIGURE 4.

[0042] In the example shown in FIGURE 6, the vehicle 600 is a land vehicle, in particular a car, comprising the device 400 of FIGURE 4. In particular, the vehicle 600 comprises a display screen 420 equipped with a detection surface 450, for example capacitive, arranged in the passenger compartment of the vehicle 600. The vehicle 600 further comprises at least one camera 418, for example arranged on the windshield of the vehicle 600.

[0125] Of course, the invention is not limited to the examples which have just been described.

Claims

CLAIMS 1. Method (100;200;300) for obtaining a stack of images of a scene, from a stack of source images (PIL S ), called source stack, of said scene, said source stack (PIL S ) : - comprising at least two source images acquired at different focuses, such that each of said at least two source images has different areas of sharpness for said scene, and - having been acquired with a camera module comprising at least one optical lens and at least one image sensor; said method (100;200;300) comprising the following steps for at least one source image of said source stack: - correction (102) of geometric aberration(s) in said source image, predetermined, by applying, to at least one pixel of said source image, a predetermined coordinate transformation function relative to a reference format, said correction providing a corrected image, and - storing (108) said corrected image in an image stack (PILc), called corrected stack, comprising said at least one corrected image in place of said source image.

2. Method (100;200;300) according to the preceding claim, characterized in that the reference format is: - the format of a source image from the source stack, or - the format of the image sensor of the camera module.

3. Method (100; 200; 300) according to the preceding claim, characterized in that, for at least one source image, the step (102) of correcting geometric aberration(s) in said source image comprises the following steps carried out for at least one pixel of said source image: - calculation (104), by the predetermined coordinate transformation function taking as input the position of said pixel in said source image, of a position, called corrected, of said pixel in the reference format, and - resetting (106) said pixel to said corrected position.

4. Method (100; 200; 300) according to any one of the preceding claims, characterized in that, for at least one source image, the transformation function is a function of the focus of said source image, so that two source images acquired at two different focuses are corrected with different transformation functions.

5. Method (100; 200; 300) according to any one of the preceding claims, characterized in that at least one transformation function is a position correspondence matrix.

6. Method (200; 300) according to any one of the preceding claims, characterized in that it further comprises, prior to the correction step (102), a phase (202), called the calibration phase, for determining at least one coordinate transformation function.

7. Method (200; 300) according to any one of the preceding claims, characterized in that the calibration phase (202) is carried out with the same camera module as that used for the acquisition of the source stack (PIL S ) so that at least one transformation function is specific to said camera module.

8. Method (200; 300) according to any one of claims 6 or 7, characterized in that the calibration phase (202) comprises the following steps: - acquisition (204) of an image stack (PILcai), called a calibration stack, with at least the same focuses as those of the source images of the source stack (PIL S ), And - deduction (206) from said calibration stack (PILcai) of at least one coordinate transformation function.

9. Method (100; 200; 300) according to any one of claims 1 to 5, characterized in that at least one coordinate transformation function is received from a device other than that implementing the correction step. (102), and in particular when the source stack (PILs) has been acquired by said other device.

10. Method (300) according to any one of the preceding claims, characterized in that it further comprises a step (302) of acquiring the source stack (PILs).

11. Computer program comprising executable instructions which, when executed by a computing device, implement all the steps of the method (100;200;300) according to any one of the preceding claims.

12. Processing device (400) comprising means configured to implement all the steps of the method (100; 200; 300) according to any one of claims 1 to 10.

13. Apparatus (510;520;530) comprising: - at least one camera module (430) comprising an optical lens and an image sensor, and - at least one calculation unit (400); configured to implement all the steps of the method (100; 200; 300) according to any one of claims 1 to 10.

14. Apparatus (510; 520; 530) according to the preceding claim, characterized in that it is: - a smartphone (510), - a tablet - a computer, - a television, - a virtual reality or augmented reality headset (520), or - a medical imaging device (530).

15. Vehicle (600) comprising: - at least one camera module (430) comprising an optical lens and an image sensor, and - at least one calculation unit (400); configured to implement all the steps of the method (100; 200; 300) according to any one of claims 1 to 10.

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