Method for correcting optical aberrations introduced by an optical lens in an image, apparatus and system implementing such a method.

Abstract

The invention relates to a method (400) for image acquisition with an apparatus comprising a camera module having an optical lens associated with an image sensor, said method comprising at least one iteration of an image acquisition phase by said apparatus comprising the following steps: capturing (404) an image with said camera module; and correcting (412) said captured image according to at least one correction matrix calculated, directly or indirectly, from at least one matrix, called the aberration matrix, determined for said optical lens, and representative of optical aberrations introduced by said optical lens into an image. It also relates to a characterization system and an imaging apparatus implementing such a method. (Shorthand figure: Fig. 4)

Description

Title of the invention: Method for correcting optical aberrations introduced by an optical lens into an image, apparatus and system implementing such a method.

[0001] The present invention relates to a method for correcting optical aberrations introduced by an optical lens in an image captured with said optical lens. It also relates to a system and an apparatus implementing such a method.

[0002] The field of the invention is the field of correcting images captured with an optical lens, with a view to correcting optical aberrations due to said optical lens. State of the art

[0003] Optical lenses are used in various devices, such as cameras, still cameras, smartphones, etc. to image a scene.

[0004] Generally, an optical lens consists of a stack of optical elements, such as optical lenses, separated from each other by an empty space, also called an "air gap" in English, or by a spacer, also called a "spacer" in English. They are generally assembled via a device called a barrel or barrel.

[0005] To produce an image, the optical lens cooperates with a photosensitive sensor, such as a CMOS or CCD sensor. The average plane of the image sensor is called the image plane and the sensor comprises a multitude of pixels. The assembly comprising the optical lens and the image sensor is generally called an “optical module” or “camera module”.

[0006] The trend towards miniaturization of camera modules mounted in electronic devices, such as smartphones, reduces the tolerances on the manufacturing of components and in particular on those of the optical lens and lenses that compose it. Manufacturing defects can thus appear in the form of defects in the image obtained on the image sensor. For example, optical aberrations can result in blurring of images. The brightness of a pixel in an original image is distorted and modifies the brightness of an adjacent pixel in the captured image.

[0007] An aim of the present invention is to remedy at least one of the aforementioned drawbacks.

[0008] Another aim of the invention is to propose a solution allowing correction of optical aberrations introduced by an optical lens in an image captured by said lens. Statement of the invention

[0009] The invention proposes to achieve at least one of the aforementioned aims by an image acquisition method with an apparatus comprising a camera module comprising an optical lens associated with an image sensor, said method comprising at least one iteration of a phase of acquisition of an image by said apparatus comprising the following steps: - capturing an image with said camera module; and - correction of said captured image according to at least one correction matrix calculated, directly or indirectly, from at least one matrix, called aberration matrix, determined for said optical objective, and representative of optical aberrations introduced by said optical objective in an image.

[0010] Thus, the invention proposes to carry out a correction of an image captured with an optical lens within the device comprising said optical lens. Thus, the correction of the image can be adapted to each device individually and can be carried out on the fly at the time the image is taken by the device. The solution proposed by the present invention is therefore more customizable and more scalable.

[0011] To do this, the invention proposes using a correction matrix calculated as a function of at least one aberration matrix previously determined for the optical objective used. The determination of the correction matrix can be carried out directly from the aberration matrix, or indirectly, for example from an aberration kernel matrix or a correction kernel matrix previously calculated, as will be described later.

[0012] By "optical aberration" is meant in particular optical blur or optical distortion. Optical blur generally results in a spreading of a light point. Distortion generally results in a displacement of the optical point.

[0013] The optical elements composing an optical lens are stacked along a stacking direction, also called the Z axis in the following, or the axis of the optical lens. The plane perpendicular to the Z axis, that is to say the plane along which each optical element extends, is called the XY plane in the following.

[0014] By “geometric parameter of an optical interface” is meant, for example, and without loss of generality: - a position of the optical interface within the lens, in the Z axis; - a position of an APEX of the optical interface, in particular in the X- plane Y and / or - a position of an APEX of the optical interface, in particular along the Z axis, - an inclination (TIP and / or TILT) of said optical interface relative to the axis Z, - a decentering of an optical interface, or of an optical element, relative to the Z axis, in the XY plane.

[0015] In the present application, by "buried optical interface" of an optical lens, we mean an interface within the optical lens which is visible, or accessible, only via at least one other optical interface of the lens. The at least one other optical interface through which the buried interface is visible may be an optical interface of the same optical element, or an optical interface of an optical element other than the buried interface.

[0016] By "pixel" we mean an elementary pattern of an image comprising for example R, G, B color values, or brightness and chrominance, therefore an element which forms a 'point' of an image.

[0017] In this document, a region of the image sensor centered on the coordinates (Xi,Yi), in the plane (X,Y), may be denoted by R(X;,Yi), or R;.

[0018] In this document, MA denotes the aberration matrix for the entire optical lens. MA;, or MA;(Xi,Yi) denotes the aberration matrix for the region R; of the lens. The aberration matrix MA can be obtained by concatenating or adding the aberration matrices MA; for all regions of the image sensor.

[0019] The, or each, correction matrix is ​​designated by the letters MC.

[0020] The image sensor can be any type of photosensitive sensor, such as a CMOS sensor or a CCD sensor, etc.

[0021] According to particularly advantageous embodiments, the phase of acquiring an image may comprise a step of determining a distance, noted DOC, between the optical objective and the image sensor, the at least one correction matrix being a function of said distance DOC.

[0022] Indeed, the method according to the invention makes it possible to take into account the optical aberrations introduced by the optical lens in an image, when the distance between the optical lens and the image plane, i.e. the plane of the image sensor, is changing, and to correct these aberrations with correction matrices determined as a function of this distance DOC. Indeed, the inventors have noticed that, for a given lens, the optical aberrations introduced by said lens can vary as a function of the distance between said lens and the image plane.

[0023] The image plane may be the plane of the image sensor.

[0024] Thus, for each distance DOCj, with j>2, an aberration matrix MAj corresponding to the entire image sensor can be determined. Alternatively, for each distance DOCj, several aberration matrices MAy, can be determined, for each region of the image sensor. The aberration matrix MAj, or each aberration matrix MAy, can then be used to directly or indirectly deduce a correction matrix MCj for the entire sensor, or correction matrices MCy for each region R; of the image sensor.

[0025] The, each, distance DOC can for example be measured by a distance sensor, such as an optical sensor, a magnetic sensor, a capacitive sensor, etc.

[0026] The, each, DOC distance can for example be calculated from information provided by a focus adjustment mechanism modifying, or controlling, the distance between the optical lens and the image sensor.

[0027] According to particularly advantageous embodiments, the phase of acquiring an image may comprise a step of determining a distance, DOS, between the optical objective and the scene, the at least one correction matrix being a function of said distance DOS.

[0028] Thus, the method according to the invention makes it possible to take into account the optical aberrations introduced by the optical lens in an image, when the distance between the optical lens and the imaged scene is changing. Indeed, the inventors have noticed that, for a given lens, the optical aberrations introduced by said optical lens can vary depending on the distance between said lens and the scene, or each part of the scene.

[0029] Thus, for each distance DOSk, with k>2, an aberration matrix MAk corresponding to the entire image sensor can be determined. Alternatively, for each distance DOSk, several aberration matrices MAik, can be determined, for each region of the image sensor. The aberration matrix MAk, or each aberration matrix MAik, can then be used to directly or indirectly deduce a correction matrix MCk for the entire sensor, or correction matrices MCik for each region R; of the image sensor.

[0030] The, or each, DOS distance can for example be measured by a LIDAR, a time-of-flight camera, an ultrasonic sensor, a textured image analysis, etc.

[0031] A single DOS distance can be measured for the optical lens. Alternatively, DOS distances can be measured for different regions R; of the optical sensor, for the same given scene. Indeed, an imaged scene can comprise several objects located at different DOS distances. In this case, a DOSik distance is determined for each region R; of the sensor, and the correction matrix is ​​selected individually for each region R; according to the DOSik distance measured for this region R; of the sensor.

[0032] According to embodiments, an image can be corrected according to several correction matrices, each selected according to: - a region R; of the image sensor, - the distance DOCj between the image sensor and the lens, and - the distance DOSk between the optical objective and the scene in said region R;. This correction matrix can be noted MCijk.

[0033] This involves determining, for each region R; of the sensor, several aberration matrices MAijk each corresponding to a distance DOCj, and to a distance DOSk in said region R;, with: i=l,...,I ​​and I>2, j=l,.„,I and J>2 k=l,...,I ​​and K>2

[0034] For example, taking ten (10) regions of the image sensor, 3 distances DOCj, and 5 distances DOSk for each region of the image sensor, then 15 aberration matrices can be determined for each region of the image sensor, and in total 150 aberration matrices for the image sensor.

[0035] In the following, for the region R; of the sensor, the distance DOCj and the distance DOSk: - MAijk is the aberration matrix, and - MCijk is the correction matrix. Of course, when the DOC distance and / or the DOS distance are not variable, then the notations MAijk and MCijk do not necessarily imply that these distances are variable.

[0036] According to embodiments, the method according to the invention may comprise a step of calculating the at least one correction matrix outside the imaging device. In this case, the correction matrix may in certain cases be stored in said imaging device.

[0037] Alternatively, the method according to the invention may comprise a step of calculating at least one correction matrix within said device.

[0038] In this case, the calculation of the correction matrix used for image correction is carried out by a calculation unit of the imaging device.

[0039] According to embodiments, the step of calculating the at least one correction matrix can be carried out during the acquisition phase so that said at least one correction matrix is ​​calculated on the fly for each captured image.

[0040] Thus, for each image acquisition, the at least one correction matrix is ​​calculated taking into account the conditions under which the image is acquired, so that the correction of the image is personalized for each image. The correction of the image is therefore more precise. In addition, in this embodiment, it is possible to calculate only the correction matrices used for the correction of the acquired image. For example, it is possible to calculate only the correction matrices for the DOC distance, and / or the DOS distance(s) determined for this image.

[0041] According to one embodiment, the step of calculating the at least one correction matrix can be carried out prior to the acquisition phase so that said calculation step is common to several iterations of the image acquisition phase.

[0042] In this case, the correction of the image can be carried out more quickly because it is not necessary to calculate on the fly the at least one correction matrix. In this embodiment, all the correction matrices corresponding to the configurations, and in particular to the DOC and DOS distances likely to be used for the images to be corrected, can be calculated and stored within the device in a database. Then, at each iteration of the acquisition phase, the at least one correction matrix corresponding to the image acquisition configuration during this acquisition phase can be selected, in particular as a function of the DOC distance and / or the at least one DOS distance, to carry out the correction of the image acquired during said acquisition phase.

[0043] At least one correction matrix can be calculated from at least one aberration matrix.

[0044] In particular, each correction matrix can be calculated from an aberration matrix. For example, the correction matrix MCÿk can be calculated from the aberration matrix MAÿk.

[0045] At least one correction matrix can be calculated by inverting the corresponding aberration matrix, which can be done for example by calculations in the spatial frequency domain.

[0046] According to exemplary embodiments, at least one correction matrix can be obtained by the relation: [ ^[Gp] 1 where Go is a function representing the function form Lijk~ [TF^MA^ j of point dispersion to be obtained after correction. It can be a function approaching a Dirac function in 2 dimensions, that is to say worth 1 at the center, and almost 0 around. By noting MTOBSÿk, the matrix of a test light beam as observed for the measurement of an aberration matrix, and MT its native form as it is in reality during its emission, the correction matrix MCÿk can be calculated as follows: f ^f[g0} . 1 In a simplified form, it is possible to lJk~ [ TF{MTOBSlJk} J assume that TF(G0) = 1, the constant function that returns 1 with zero phase at all frequencies, which is written: MCijk = TF-1 (......|with: lJh [ TF{MTOBSijk} ] - TF the Fourier transform operator (in 2D); - TF 1 the inverse Fourier transform operator (in 2D); - MCÿk correction matrix for the region R; of the image sensor, at the distance lens-sensor distance DOQ, and to the lens-scene distance DOSk for said region Ri; - MAijk the aberration matrix obtained for the region R; of the image sensor and the distances DOQ and DOSk; and - MTijk the test light beam matrix, i.e. the matrix describing the test light beam used to measure the aberration matrix MAijk; and - MTOBSijk the illumination matrix observed in the sensor plane relative to the MTijk test matrix presented at the input of the optical objective.

[0047] At least one correction matrix can be calculated from at least one aberration kernel matrix, comprising coefficients making it possible to deduce said at least one aberration matrix, and previously calculated.

[0048] The use of an aberration kernel matrix makes it possible to avoid storing all the aberration matrices used for determining the correction matrices, and therefore to reduce the memory space used for storing the aberration matrices.

[0049] In this case, several aberration matrices can be determined, before the correction phase. Then, from these matrices, a common matrix can be identified. This common matrix, called aberration kernel matrix, can be stored in place of the multitude of aberration matrices, in relation to one or more relations, to allow the calculation of each aberration matrix, the latter then being used to determine a correction matrix as described later.

[0050] The aberration kernel matrix can, according to a non-limiting exemplary embodiment, be determined in the following manner, from the aberration matrices.

[0051] Firstly, a base of FA functions is established to describe the values ​​of the coefficients of the aberration matrices as a function of the positions (X,Y) in the field of the image sensor, such that: MA(X,Y) = Ei aAi(X,Y) FAj(X,Y) + E(X,Y) where - 1 scans the basis of FA functions, with 1<1<L, et L> 1. - the term E(X,Y) models the differences between the combination of the functions FAi and MY.

[0052] The basis FA can preferably be chosen so as to be sufficiently broad so that the term E(X,Y) keeps a negligible effect, or even zero. These functions can be orthogonal to each other in the sense of a scalar product, but not necessarily. For example, the basis of functions FAi can be the basis of functions of the Zernike polynomials. To obtain the functions aAi(X,Y), it is sufficient to use a method known from the state of the art such as a projection of MA(X,Y) onto the FAi(X,Y), in the sense of a scalar product, and to apply the appropriate matrix product to take into account their non-orthogonality, if applicable, to obtain the functions aAi(X,Y). Establishing an aberration kernel precursor (ANP) amounts to searching for a parametric model of the functions aAi(X,Y), such that for example a polynomial expression represents aAi(X,Y), for example, if 1 € {1, 2}, such that aAi(X,Y) = aOi .((X-x0i)2+(Y-y0i)2) and aA2(X,Y) = a02.((X-x02)*(Y-y02)) +z02. The model representing the aAi(X,Y), here aAi(X,Y) and aA2(X,Y), is then the table of values ​​((aOi, xOi, yOi); (a02, x 02, y02, z02)) in this example. We can call this set of coefficients the precursor matrix of aberration kernels called PNA (here it can be a matrix of 1 row x 7 columns, or 2 rows by 4 columns with a zero coefficient added to the first row). As the FAi() functions are chosen in such a way as to best model the modes of the aberrations obtained, the parametric model which represents the functions aAl(X,Y) as a function of the geometric parameters contains significantly fewer coefficients than the numerical representation of the FAi(X,Y) functions.Here for example, it contains 8 coefficients instead of the 16 million coefficients that would have been needed to represent the aberration functions represented by 4x4 coefficients on an X, Y field of 1000x1000 positions. There remains one last step to obtain the aberration matrix which is to represent the evolutions of the PNA coefficients as a function of the sensor lens and scene lens distance parameters DOC and DOS, which again makes a set of several parameters involved in functions modeling the PNA values ​​as a function of DOC and DOS. It is this last set of coefficients which can, advantageously, constitute the aberration kernel matrix.

[0053] According to another exemplary embodiment, the aberration kernel matrix can be a table of matrices containing the PNA coefficients, or directly the PNA for several sets of DOC and DOS parameters. The essential thing is to be able to find the aberration matrices of the objective from the geometric parameters, preferably by storing less data than these aberration matrices represent.

[0054] The aberration kernel matrix can be determined in the device performing the image capture, or outside the device performing the image capture.

[0055] For example, the basis of functions FAi can be the basis of functions of the Zernike polynomials.

[0056] At least one correction matrix can be calculated from at least one correction kernel matrix, comprising coefficients making it possible to deduce said at least one correction matrix, and previously calculated.

[0057] The use of a correction kernel matrix makes it possible to avoid storing all the correction matrices used to correct each image captured during each iteration of the correction phase, and therefore reduce the memory space used for storing the correction matrices.

[0058] The correction kernel matrix can be determined in the following manner. Several correction matrices can be determined from several aberration matrices or from an aberration kernel matrix. Then, from these correction matrices, a common correction matrix, denoted MC, can be identified. This common correction matrix can be stored in place of the multitude of correction matrices, in association with one or more relations, to allow the calculation of each correction matrix.

[0059] The determination of the correction kernel matrix can be determined in a manner similar to that described above for the aberration kernel matrix using the same basis of functions FAi, or another basis of functions which would be appropriate.

[0060] The correction kernel matrix can be determined in the device performing the image capture or outside the device performing the image capture.

[0061] The method according to the invention may further comprise, prior to the first iteration of the acquisition phase, a characterization phase comprising a determination of at least one, and in particular of each, aberration matrix.

[0062] The characterization phase can generally be carried out outside the device carrying out the image acquisition. In this case, the characterization phase is carried out with the optical objective, or the image sensor, which is not yet mounted in the device.

[0063] Of course, according to alternative embodiments, the characterization phase can also be carried out within the device, in particular with the optical objective, or the image sensor, mounted in the device.

[0064] The characterization phase may include a determination of: - multiple aberration matrices for multiple R regions; of the image sensor; - multiple aberration matrices for multiple DOC distance values; ; and / or - of several aberration matrices for several values ​​of distance DOSj.

[0065] Indeed, an aberration matrix MA can be determined for the entire image sensor. Alternatively, aberration matrices MA; can be determined, each for a region R; of the image sensor, with i=l,...,I ​​and I>2.

[0066] Alternatively, or in addition, aberration matrices MAj can be determined, each for a lens-sensor distance DOQ, with j=1,...,J and J>2.

[0067] Alternatively, or in addition, aberration matrices MAk can be determined, each for a lens-scene distance DOSk, with k=l,...,K and K>2.

[0068] According to a non-limiting combination, several aberration matrices MAijk can be determined, each for a region R;, a distance DOQ, and a lens-scene distance DOSk in said region R;.

[0069] According to another non-limiting combination, several aberration matrices MAik can be determined, each for a region R;, and a lens-scene distance DOSk in said region R;. In this case, the aberration matrix, and therefore the image correction, does not take into account the lens-image sensor distance DOC.

[0070] According to embodiments, at least one aberration matrix can be determined by optical measurement, on the actual optical objective, with an optical measuring apparatus.

[0071] The optical measuring device may comprise an MTF (for “Modulation Transfer Function” in English, and FTM for “Modulation Transfer Function” in French), or OTF (Optical Transfer Function” in English, and FTO for “Optical Transfer Function” in French) measuring device, or a PSF (for “Point Spread Function” in English, or “Point Spread Function” in French) measuring device, or even a wavefront measuring device. Such devices are well known to those skilled in the art and will not be described in more detail here for the sake of brevity. They generally comprise a light source, a target or pattern to be observed, an image sensor (or several) and a computing unit.

[0072] Alternatively, or in addition, at least one aberration matrix may be determined by simulation in a digital simulator on a digital model of the optical lens.

[0073] In this case, the optical lens and the image sensor are modeled in software, such as ZEMAX® software, in which it is possible to simulate the MTF, OTF or PSF functions, or even wavefront functions, by simulating the emission and propagation of a test light beam and by measuring the illumination received on the image sensor.

[0074] Whatever the embodiment, by measurement on the optical objective or by simulation on a digital model of the optical objective, an aberration matrix can be determined in the following manner.

[0075] The optical lens associated with the image sensor is illuminated by a test light beam, then the illumination received at the image sensor is measured. This illumination received at the sensor includes information on the optical aberrations introduced by the optical lens in each captured image.

[0076] The aberration matrix can be obtained by region of the image sensor, each corresponding to one or more pixels on said image sensor. In this case, an illumination pattern is presented in front of the optical lens, such as for example a checkerboard pattern alternating white patterns and black patterns, then the illumination received at the sensor is measured. This illumination received at the sensor includes the information of the optical aberrations introduced by the optical lens in each captured image.

[0077] A transformation of the captured images may be necessary in order to obtain by example the point spread function PSF which would correspond to for example a test beam coming from a single light point illuminating the objective, moved in several regions of the field visible by the objective to obtain the PSFs of several regions of the sensor. But if the measurement, respectively the simulation, allows to illuminate the optical objective from a single movable point, these transformations can generally be omitted.

[0078] According to non-limiting exemplary embodiments, at least one, in particular each, aberration matrix may be: - a PSF matrix of values ​​of a point spread function (or PSF), and / or - an OTF matrix of values ​​of an optical transfer function (“Optical Transfer Function” or “OTF” in English), and / or - a matrix of values ​​obtained by wavefront analysis.

[0079] Of course, other types of aberration matrices can be used and the invention is not limited to a particular type of aberration matrix.

[0080] The method according to the invention may comprise a step of calculating a matrix, called aberration kernel matrix, comprising coefficients making it possible to deduce at least one aberration matrix.

[0081] The aberration kernel matrix can be determined as described above, within or outside the device capturing the image to be corrected.

[0082] The method according to the invention may further comprise a step of calculating a matrix, called a correction kernel matrix, comprising coefficients making it possible to deduce at least one correction matrix.

[0083] The correction kernel matrix can be determined as described above, within or outside the device capturing the image to be corrected.

[0084] According to another aspect of the present invention, there is provided an image acquisition system with an apparatus comprising a camera module comprising an optical lens associated with an image sensor, said system comprising: - a device for characterizing said optical lens to determine at least one matrix, called an aberration matrix, representative of optical aberrations introduced by said optical lens in an image captured by said camera module, - said camera module for capturing an image, and - a computing unit in said device; configured to implement the method according to the invention for acquiring data(s).

[0085] The system according to the invention may comprise, in terms of hardware and / or software means, any combination of the optional characteristics set out above for the method according to the invention and which are not repeated here for the sake of brevity.

[0086] The characterization device may comprise an optical measuring apparatus for measuring at least one aberration matrix on the actual optical lens. Alternatively, the characterization device may comprise a digital simulator for determining at least one aberration matrix by simulation on a digital model of the optical lens.

[0087] The computing unit may be a processor, a calculator or any programmable electronic chip. The computing unit may be a processor or a graphics card of the device capturing the image.

[0088] According to another aspect of the present invention, there is provided an image acquisition apparatus comprising: - a camera module comprising an optical lens associated with an image sensor, and - a computing unit; configured to implement the steps of the method according to the image acquisition invention.

[0089] The apparatus according to the invention may comprise, in terms of hardware and / or software means, any combination of the optional characteristics stated above for the method according to the invention and which are not repeated here for the sake of brevity.

[0090] According to non-limiting exemplary embodiments, the device according to the invention may be a camera, a video camera, a smartphone, a tablet, a computer, a web-cam, etc. Description of figures and embodiments

[0091] Other advantages and characteristics will appear on examining the detailed description of non-limiting embodiments, and the appended drawings in which: - [Fig.l] is a schematic representation of a non-limiting exemplary embodiment of an optical element which can be used in an optical objective within the meaning of the present invention; - [Fig.2] is a schematic representation of a non-limiting exemplary embodiment of a camera module within the meaning of the present invention; - [Fig. 3] is a schematic representation of a non-limiting exemplary embodiment of a characterization phase which can be implemented in a method according to the present invention; - FIGURES 4, 5a, 5b and 5c are schematic representations of non-limiting exemplary embodiments of an image acquisition method

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[0098] according to the present invention; - [Fig.6] is a schematic representation of an example of a non-realization limiting a device for characterizing an optical objective; - [Fig.7] is a schematic representation of an example of a non-realization limiting of an apparatus according to the invention for image acquisition; and - [Fig.8] is a schematic representation of an example of a non-realization limiting another apparatus according to the invention for image acquisition according to the invention. 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. In particular, all the variants and embodiments described can be combined with each other if there is no technical obstacle to this combination. In the figures and in the rest of the description, the elements common to several figures retain the same reference. [Fig.l] is a schematic representation of a non-limiting exemplary embodiment of an optical element that can be used to manufacture an optical lens. The optical element 100 of [Fig. 1] may be used with at least one other optical element to manufacture an optical lens. An example of an optical lens, given by way of non-limiting example, will be described with reference to [Fig. 2]. The optical element 100 may be a lens, a blade, etc. In the following, and without loss of generality, it is considered that the optical element is a lens. The optical lens 100 may, for example, be manufactured by injection molding. An injection molding process generally follows the following sequence of steps: - polymer injection and mold filling, - pressurization, - maintaining pressure, - cooling, and - demolding Injection lens manufacturing processes, although common, can fluctuate and generate errors in the characteristic parameters of the lenses, particularly with regard to its geometry.

[0099] The lens 100 has a given geometric shape. It comprises two interfaces 102i and 1022, each also having a given geometric shape. Thus, the geometric shape of the lens 100 is determined by: - a geometric shape of each of the optical interfaces 102i and 1022; - a center of curvature, noted CCI and CC2, of each of the optical interfaces 102! and 1022; - a position of an apex, denoted Al and A2, of each of the optical interfaces 102! and 1022; - at least one thickness, noted H1 and H2, of the lens 100 along its periphery; - an inner diameter, respectively DI 1 and D21, and / or an outer diameter, respectively D12 and D22, of each of the interfaces 102i and 1022; - a concentricity or eccentricity value of the interfaces 102i and 1022 - a surface roughness of each of the optical interfaces 102i and 1022; - etc.

[0100] The value of at least one of these geometric parameters may be provided by the manufacturer. Alternatively, or in addition, the value of at least one geometric parameter may be measured, for example, by optical or mechanical profilometry. Alternatively, or in addition, the value of at least one geometric parameter may be determined by simulation, from a numerical modeling of the lens 100. Alternatively, or in addition, the value of at least one geometric parameter may be measured, for example, by optical interferometry.

[0101] In addition, the lens 100 has optical characteristics since it is an optical element. It is therefore characterized by at least one optical parameter such as for example: - a refractive index, noted II and 12, of each of the optical interfaces 102i and 1022; - an Abbot number, noted Ab, - etc.

[0102] Any combination of these individual parameters, and in particular all of these parameters, may be used to numerically model the optical element 100.

[0103] [Fig.2] is a schematic representation of a non-limiting exemplary embodiment of a camera module comprising an optical lens and an image sensor within the meaning of the present invention.

[0104] The camera module 200 comprises an image sensor 202. The image sensor can be any type of photosensitive sensor such as a CMOS sensor (called “CMOS Imager System” which provides the acronym CIS), or a CCD sensor.

[0105] The camera module 200 further comprises an optical lens 204. The optical lens 204 has the function of focusing an image of a scene in an image plane, namely the plane of the image sensor 202.

[0106] An optical lens 204 is generally comprised of a stack of optical elements comprising any combination of optical elements such as lenses, spacers and opacifiers, etc.

[0107] During the manufacture of the optical lens, each optical element of said lens is selected individually and stacked with the other optical elements in an assembly barrel, in a given order. The stack is then secured to the barrel by known techniques, for example by gluing.

[0108] In [Fig.2], and by way of non-limiting example only, the optical lens 204 comprises four lenses 206i-2064 stacked, in a stacking direction 210, also called the Z axis, in a barrel 212. At least two of the lenses 206r2064 may be separated from each other by an empty space, called an “air gap”, or by a spacer, or washer, also called a “spacer”.

[0109] At least one of the lenses 206i-2064 may for example be the lens 100 of [Fig.l].

[0110] Each of the lenses 206r2064 has two interfaces, namely an interface, called upstream, and an interface, called downstream, in the direction of the stack 210. Thus, the lens 206i has an upstream interface 214i and a downstream interface 2142, the lens 2062 has an upstream interface 2143 and a downstream interface 2144, the lens 2063 has an upstream interface 2145 and a downstream interface 2146 and the lens 2084 has an upstream interface 2147 and a downstream interface 2148.

[0111] Thus, for the optical objective 204 of [Fig. 2], and generally for any optical objective comprising a stack of optical elements, it is possible to determine a data set, called geometric set, noted JG in the following, comprising data relating to at least one geometric parameter of at least one, and in particular of each, optical interface 206; of said stack.

[0112] Such a geometric game JG may comprise data relating to, or values ​​of, any of the following geometric parameters: - at least one position of at least one optical interface 206r2064 of the lens 204 along the Z axis; - at least one decentering value of at least one optical interface 2061-2064 relative to the Z axis, or relative to a center position of another interface, in the XY plane; or - at least one tilt value of at least one optical interface 206r2064 relative to the Z axis, or relative to the tilt of another interface; - at least one topography or shape profile value of at least one optical interface 206i-2064.

[0113] Generally, the geometric set JG can comprise for each optical interface of the optical objective 204 M geometric parameters with M>1 and preferably M>2. If the optical objective 204 comprises N optical elements, each optical element comprising two interfaces, then the geometric set JG can comprise 2NxM parameters and can correspond to a matrix comprising 2N rows and M columns. Of course, the geometric set JG can comprise the same number of geometric parameters for at least two optical interfaces, or different numbers of geometric parameters for at least two optical interfaces.

[0114] The geometric game JG can directly comprise the values ​​of the geometric parameters. These values ​​can be measured by optical interferometry or by confocal measurement(s), preferably from one side or one face of the optical objective 204, so as to avoid rotating it.

[0115] The geometric clearance of the optical lens 204, possibly with the individual parameters of each optical element, such as any combination of the parameters described with reference to [Fig.l], can be used to numerically model the camera module in a digital simulator, such as for example, and without loss of generality the “ZEMAX ®” simulator available on the market.

[0116] Optionally, the distance, denoted DOC, between the optical lens 204 and the image sensor 202 may be changeable, for example by a focusing or zoom modification mechanism. The value of this distance DOC may be measured by a sensor provided for this purpose, or may be provided by the zoom mechanism, or from a configuration of said zoom mechanism.

[0117] Furthermore, the distance noted DOS, between the optical objective and the imaged scene is generally changing from one image to another. Furthermore, within the same image, objects located in the scene may be at different distances from the optical objective. For a given image, this DOS distance, and possibly the DOS distances for different regions of the optical sensor, may be determined either by analysis of the captured image, or by one or more sensors, such as LIDAR sensors.

[0118] [Fig. 3] is a schematic representation of a non-limiting exemplary embodiment of a characterization phase that can be implemented in the present invention.

[0119] Phase 300 of [Fig.3] makes it possible to determine one or more aberration matrices, representative of the optical aberrations introduced into an image taken by an optical objective, and in particular by the optical objective 200 of [Fig.2].

[0120] The characterization phase 300 can be implemented outside the image acquisition apparatus, i.e. before the optical objective, or the camera module, is mounted in the image acquisition apparatus. Alternatively, the characterization phase 300 can be implemented in the image acquisition apparatus, after the optical objective, or the camera module, is mounted in the image acquisition apparatus. In this case, some or all of the steps of the characterization phase are implemented in said image acquisition apparatus.

[0121] Phase 300 comprises a step 302 of emitting a test light beam towards the optical lens, and in particular towards the camera module comprising the optical lens and the image sensor. The test light beam can be described by a matrix of values, denoted MT.

[0122] The test light beam passes through the optical lens and is received at the image sensor. The illumination having passed through the optical lens is measured by the optical sensor during a step 304. This illumination received at the sensor includes information on the optical aberrations introduced by the optical lens in each captured image. The illumination observed and measured at the image sensor can be described by a matrix of values ​​denoted MTOBS.

[0123] By knowing the matrix MT and by measuring the matrix MTOBS, it is possible to determine, during a step 306, an aberration matrix, MA, as being a convolution of the matrices between the MT and and MA, such that MTOBS = MT * MA

[0124] Optionally, but particularly advantageously, the aberration matrix can be obtained, individually for different distances DOQ between the optical lens and the image sensor, with j=1,...,J and J>2. In this case, during a step 308, the distance DOC is modified, for example by moving the image sensor closer to or further away from the optical lens, and steps 302-306 are repeated for each distance DOCj.

[0125] Optionally, but particularly advantageously, the aberration matrix can be obtained, individually for different distances DOSk between the optical objective and the image sensor, with k=1,...,K and K>2. In this case, during a step 310, the DOS distance is modified, for example by bringing the source of the test light beam closer to, or further away from, the optical objective, and steps 302-308 are repeated for each distance DOSk.

[0126] The aberration matrix can be obtained at once for the entire extent of the image sensor.

[0127] Alternatively, the aberration matrix can be obtained, individually for different regions of the image sensor, R; with i=l,...,I ​​and I>2, each corresponding to one or more pixels on said image sensor, in the plane of the image sensor. In this case, during a step 312, the test region is modified and steps 302-310 are repeated for each region R; individually.

[0128] Thus, the characterization phase 300 provides at least one aberration matrix MA. In the following, and without loss of generality, it is considered that the characterization phase 300 provides a number NB = I x J x K aberration matrices MAijk for different regions R;, different distances DOQ and different distances DOSk.

[0129] During an optional step 314, the aberration matrices can be stored in a database.

[0130] Phase 300 of [Fig. 3] may be part of a method according to the invention for image acquisition, such as the method examples which will be described later. However, the method according to the invention for image acquisition does not necessarily comprise such a characterization phase.

[0131] At least one aberration matrix can be determined by optical measurement on the real optical objective with an optical measuring device comprising an optical beam source, and optionally a calculation unit. The optical measuring device can comprise an MTF (for “Modulation Transfer Function” in English, or OTF or FTO for “Optical Transfer Function” in French) measuring device, or a PSF (for “Point Spread Function” in English, or “Point Spread Function”) measuring device. Such devices are well known to those skilled in the art.

[0132] Alternatively, at least one aberration matrix may be determined by simulation in a digital simulator on a digital model of the optical lens. A digital model of the optical lens may be defined in a simulator, for example from any combination of the geometric parameters described with reference to [Fig.2] and / or individual parameters described with reference to [Fig.l]. In this case, the optical lens and the image sensor are modeled in software, such as ZEMAX® software, in which it is possible to simulate the MTF, OTF or PSF functions, by simulating the emission and propagation of a test light beam and by measuring the illumination received on the image sensor.

[0133] [Fig.4] is a schematic representation of an exemplary embodiment not limiting of a method according to the invention for image acquisition.

[0134] The method 400 of [Fig.4] comprises at least one iteration of a phase 402 of acquiring an image with a camera module, and in particular with the camera module 200 of [Fig.2].

[0135] Phase 402 comprises a step 404 of capturing an image. The captured image is in the form of a matrix of values, provided by the image sensor, and denoted IMa. The matrix IMa comprises digital values ​​for each pixel of the sensor. For example, for an RGB image, the IMa matrix includes three values ​​for each pixel, one for each color. The acquired image, and therefore the IMa matrix, includes the optical aberrations introduced by the optical lens, such as optical blur or displacement.

[0136] Optionally, but particularly advantageously, the acquisition phase 402 may comprise a step 406 of determining, by measurement or by calculation, the distance DOC between the optical objective and the image sensor, during the acquisition of the image. The correction of the captured image may then be carried out by selecting, or by calculating, the correction matrix corresponding to said distance DOC.

[0137] Optionally, but particularly advantageously, the acquisition phase 402 may comprise a step 408 of determining, by measurement or by calculation, at least one DOS distance between the optical objective and the imaged scene, during the acquisition of the image. In particular, a DOS distance may be measured / calculated for each region R; of the image sensor. The correction of the captured image may then be carried out by selecting, or by calculating, the correction matrix(s) corresponding to said DOS distance, or to said DOS distances for each region R;.

[0138] During a step 410, at least one correction matrix is ​​selected, or calculated, optionally as a function of the DOC and / or DOS distances determined during the optional steps 406 and 408. When the, or each, correction matrix is ​​previously calculated and stored in a database, then step 410 only performs a selection of the, or each, correction matrix in said database. When the, or each, correction matrix is ​​not previously calculated, then step 410 performs an on-the-fly calculation of the, or each, correction matrix.

[0139] The captured image, and in particular the matrix IMa representing the captured image, is corrected, in part or in full, during a step 412. To do this, at least some of the values ​​of the matrix IMa are corrected using at least one correction matrix selected / calculated during step 410. In the following, and without loss of generality, it is considered that a correction matrix, denoted MCijk, is used for each region R; of the sensor, for the distance DOCj determined during step 406, and for the distance DOSk determined during step 408 for said region R;. Denoting IMC as the matrix representing the corrected image, the correction of the image can be carried out by convolution of the matrix IMa with each correction matrix MCijk, for each region R; of the image sensor: IMC = IMa * MCijk, with i=l,.., I and I>2

[0140] In the corrected image thus obtained, the aberrations introduced by the optical lens are corrected, or at least attenuated.

[0141] [Fig.5a] is a schematic representation of another exemplary embodiment not limiting of a method according to the invention.

[0142] The method 500 of [Fig.5a] comprises the acquisition phase 402 of the method 400 of [Fig.4].

[0143] The method 500 further comprises, before the acquisition phase 402, a step 502 of calculating an aberration kernel matrix from the aberration matrices determined for the optical objective. Indeed, in order to reduce the storage resources necessary for storing the aberration matrices, it may be advantageous to calculate an aberration kernel matrix which will then be used to calculate, on the fly, the aberration matrix for each region R; of the image sensor, optionally as a function of the DOC distance and / or the DOS distance(s) measured for each captured image.

[0144] In this case, during step 410, each aberration matrix MAijk for each region R; is deduced, on the fly, from the aberration kernel matrix. Then, each aberration matrix MAijk is used to calculate the correction matrix MCijk for each region R; of the image sensor.

[0145] The aberration kernel matrix can be determined as described above, using a basis of functions.

[0146] [Fig.5b] is a schematic representation of another exemplary embodiment not limiting of a method according to the invention.

[0147] The method 510 of [Fig.5b] comprises the acquisition phase 402 of the method 400 of [Fig.4].

[0148] The method 510 further comprises, before the acquisition phase 402, a step 512 of calculating and storing all the correction matrices MCijk which can potentially be used to correct an image during the acquisition phase. In other words, step 512 performs a calculation, for each region R;, and possibly for each distance DOQ and / or each distance DOSk, a correction matrix MCijk from the aberration matrix MAijk determined during the characterization phase. Each of these correction matrices MCijk is then stored in a database.

[0149] In this case, step 410 of the acquisition phase 402 does not perform any correction matrix calculation. During this step 410, the database storing the correction matrices MCijk is read to select therein, for each region R; of the sensor, the desired correction matrix to correct the acquired image, possibly for the DOQ distance and / or the DOSk distance measured for said region Ri.

[0150] [Fig.5c] is a schematic representation of another exemplary embodiment not limiting of a method according to the invention.

[0151] The method 520 of [Fig.5c] comprises the acquisition phase 402 of the method 400 of [Fig.4].

[0152] The method 520 further comprises, before the acquisition phase 402, a step 522 of calculating all the correction matrices MCijk which can potentially be used to correct an image during the acquisition phase 402. In other words, the step 522 performs a calculation, for each region R;, and possibly for each distance DOQ and / or each distance DOSk, a correction matrix MCijk from the aberration matrix MAijk determined during the characterization phase.

[0153] The method 520 further comprises, still before the acquisition phase 402, a step 524 of calculating a correction kernel matrix from the MCijk correction matrices determined for the optical objective during step 522. Indeed, in order to reduce the storage resources necessary for storing all the MCijk correction matrices, it may be advantageous to calculate a correction kernel matrix which will be used to calculate, on the fly, each MCijk correction matrix for each region R; of the image sensor, optionally as a function of the DOC distance and / or the DOS distance(s) measured for each image captured during the acquisition phase 402.

[0154] In this case, during step 410 of the acquisition phase, each correction matrix for each region R; is deduced, on the fly, from the correction kernel matrix, and optionally as a function of the DOC distance and / or the measured DOS distance(s).

[0155] The correction kernel matrix can be determined as described above, using a function basis.

[0156] In the examples described with reference to FIGURES 5a, 5b and 5c, each of the steps 502, 512, 522 and 524 can be implemented either in the imaging device performing the image capture, i.e. the device equipped with the camera module, or outside of said imaging device.

[0157] For example, in the method 500 of [Fig.5a], the step 502 of calculating the aberration kernel matrix can be carried out in the imaging apparatus, or outside the imaging apparatus, for example in a device for characterizing the optical objective, for example implementing the characterization phase 300 of [Fig.3].

[0158] In the method 510 of [Fig.5b], the step 512 of calculating the correction matrices can be carried out in the imaging device, or outside the imaging device, for example in a device for characterizing the optical objective, for example implementing the characterization phase 300 of [Fig.3].

[0159] In the method 520 of [Fig.5c], the step 522 of calculating the correction matrices, respectively the step 524 of calculating the correction kernel matrix, can be carried out in the imaging device, or outside the imaging device for example in a device for characterizing the optical objective, for example implementing the characterization phase 300 of [Fig.3].

[0160] [Fig.6] is a schematic representation of a non-limiting exemplary embodiment of a device for characterizing an optical objective.

[0161] The device 600 of [Fig.6] can be used to characterize any type of optical objective used for image acquisition, and more particularly the objective 200 of [Fig.2],

[0162] The device 600 of [Fig.6] can be used to implement a characterization phase of an optical objective, and in particular the characterization phase 300 of [Fig.3], with a view to determining, at least, aberration matrices representative of the aberrations introduced by an optical objective in an image captured with said optical objective.

[0163] The device 600 comprises a source 602 for emitting one or more test light beams towards the optical objective, and in particular towards the camera module, such as for example the camera module 200 of [Fig.2].

[0164] The device 600 may comprise a mechanism (not shown) for adjusting the position of the source 602: - in the Z direction of emission of the test light beam, so as to adjust the DOS distance and determine aberration matrices for different DOS distances, and / or - in the plane, noted XY, perpendicular to the direction Z of emission of the test light beam, to modify the region R; for which an aberration matrix is ​​determined.

[0165] The device 600 may include a mechanism (not shown) for adjusting the relative positions of the optical lens and the image sensor in the Z direction, so as to adjust the DOC distance between the image sensor and the optical lens and determine aberration matrices for different DOC distances.

[0166] The device 600 may comprise a computing unit 604.

[0167] This calculation unit 604 is designed to receive on the one hand a value matrix, denoted MT, representing the test light beam emitted by the source 602 and on the other hand a value matrix, denoted MTOBS, representing the illumination observed by the image sensor for this test light beam.

[0168] The calculation unit 604 may comprise a calculation module 606 provided for calculating, as a function of the matrices MT and MTOBS, an aberration matrix, denoted MA, for example using the following convolution relation: MTOBS = MT * MA When the aberration matrix is ​​determined for a region R;, a distance DOC j, and a distance DOSk for this region R;, the relation used can be noted as follows: MTOBSijk = MTijk * MAijk

[0169] The calculation unit 604 may further comprise a calculation module 608 provided for calculating an aberration kernel matrix, for example by implementing step 502 of the method 500, in which case this step 502 is not implemented in the imaging apparatus.

[0170] Alternatively, or in addition, the calculation module 608 may be provided to calculate: - at least one correction matrix, for example by implementing step 512 of the method 510, or step 522 of the method 520, in which case this step is not implemented in the imaging apparatus; and - optionally, at least one correction kernel matrix, for example by implementing step 524 of method 520, in which case this step is not implemented in the imaging device.

[0171] The computing unit 604 may be in a hardware form, such as a server, a computer, a processor, an electronic chip, etc. Alternatively, the computing unit 604 may be in a software form, such as one or more computer programs. According to yet another alternative, the computing unit 604 may be formed by any combination of at least one hardware means and at least one software means.

[0172] The modules 606 and 608 may each be an individual module and independent of the other module. Alternatively, the modules 606 and 608 may be integrated within a single module. Each of the modules 606 and 608 may be in a hardware form, such as a server, a computer, a processor, an electronic chip, etc. Alternatively, each of the modules 606 and 608 may be in a software form, such as a virtual machine, one or more computer programs, etc. According to yet another alternative, each of the modules 606 and 608 may be formed by any combination of at least one hardware means and at least one software means.

[0173] [Fig.7] is a schematic representation of a non-limiting exemplary embodiment of an image acquisition apparatus according to the invention.

[0174] The device 700 of [Fig.7] can be used to implement a method according to the invention for acquiring an image, and in particular any one of the methods 400, 500, 510 and 520 of FIGURES 4, 5a, 5b and 5c.

[0175] The device 700 comprises a camera module 702, which may for example be the camera module 200 of [Fig.2], comprising an image sensor, for example the image sensor 202, and an optical lens, for example the optical lens 204.

[0176] Optionally, the device 700 may comprise a sensor 706 provided for measuring the distance DOC between the optical lens 704 and the image sensor 702. Such a sensor 706 may be a capacitive sensor, a resistive sensor or even a sensor optical. This sensor 706 provides a value of the DOC distance, or a value of an electrical quantity representative of the DOC distance, such as for example a voltage, a current, etc.

[0177] Optionally, the device 700 may comprise a sensor 708 provided for measuring the DOS distance between the optical objective 204 and the imaged scene. Such a sensor 708 may be a LIDAR sensor for example. This sensor 708 provides a value of the DOS distance, or a value of an electrical quantity representative of this DOS distance, such as for example a voltage, a current, etc. Preferably, but in no way limitingly, this sensor 708 is provided for measuring the DOS distance individually for different regions R; of the image sensor 202.

[0178] The device 700 further comprises a calculation unit 710 configured to correct the image captured by the sensor 704, and in particular the matrix IMa representing the captured image, and to provide a matrix, denoted IMC, representing the corrected image, as a function of at least one correction matrix MCÿk.

[0179] The computing unit 710 may be a hardware unit such as a processor or a computer chip. Alternatively, the computing unit may be a computer program or an application.

[0180] According to embodiments, the at least one correction matrix MCÿk can be read from a memory area, or a database, 712. In this case, the calculation unit 710 reads said at least one correction matrix, optionally as a function of the distance(s) DOC and / or DOS measured during the image capture.

[0181] According to embodiments, the calculation unit 710 can further be configured to calculate, in particular on the fly, the at least one correction matrix, as a function of: - a correction kernel matrix, - at least one predetermined aberration matrix, or - an aberration kernel matrix; stored in the database 712. In this case, the calculation unit reads said at least one matrix and calculates the at least one correction matrix from said at least one read matrix.

[0182] In the example shown, the camera module 702 is composed of the optical lens 204 and the image sensor 202, and optionally the distance sensors 706 and 708. The camera module 702 may comprise other components than those shown, such as for example a focus adjustment mechanism (not shown) modifying the distance between the image sensor 704 and the optical lens 702.

[0183] The calculation unit 710, and optionally the database 712, can be integrated into a photo and / or video application, 714, installed or executed within a device such as a Smartphone, a tablet, a computer, etc.

[0184] [Fig.8] is a schematic representation of a non-limiting exemplary embodiment of an image acquisition apparatus according to the invention.

[0185] The apparatus 800 may comprise all the elements of the apparatus 700 of [Fig.7].

[0186] According to embodiments, the device 800 can be a camera, a tablet, a Smartphone, a computer, a surveillance camera, and more generally a camera module intended to be integrated into another device, etc.

[0187] In the example shown, the device 800 is a Smartphone comprising a display screen 802 on the front face and the camera module 702 opening onto its rear face, the application 714 integrating the calculation unit 710 and the database 712.

[0188] Of course, the invention is not limited to the examples which have just been described.

Claims

Claims

1. Method (400;500;510;520) of image acquisition with an apparatus (700;800) comprising a camera module (200;702) comprising an optical lens (204) associated with an image sensor (704), said method (400;500;510;520) comprising at least one iteration of a phase (402) of acquisition of an image by said apparatus (700;800) comprising the following steps: - capture (404) of an image with said camera module (200;702); and - correction (412) of said captured image as a function of at least one correction matrix calculated, directly, or indirectly, from at least one matrix, called aberration matrix, determined for said optical objective (204), and representative of optical aberrations introduced by said optical objective (204) in an image; the acquisition phase (402) further comprises a step (408) of determining a distance, DOS, between the optical objective (204) and the scene;characterized in that the at least one correction matrix is a function of said DOS distance.;

2. Method (400; 500; 510; 520) according to the preceding claim, characterized in that the acquisition phase (402) of an image comprises a step (406) of determining a distance, DOC, between the optical objective (204) and the image sensor (202), the at least one correction matrix being a function of said distance DOC.

3. Method (400; 500; 510; 520) according to any one of the preceding claims, characterized in that it comprises a step (410; 512; 522) of calculating the at least one correction matrix within said apparatus (700; 800).

4. Method (400; 500; 520) according to the preceding claim, characterized in that the step of calculating (410) the at least one correction matrix is carried out during the acquisition phase (402) so that said at least one correction matrix is calculated on the fly for each captured image.

5. Method (510) according to any one of claims 1 to 3, characterized in that the step (512) of calculating the at least one matrix of correction is carried out prior to the acquisition phase (402) so that said calculation step (512) is common to several iterations of the image acquisition phase (402).

6. Method (400; 500; 510; 520) according to any one of claims 3 to 5, characterized in that at least one correction matrix is calculated from: - at least one aberration matrix; - at least one correction kernel matrix comprising coefficients making it possible to deduce said at least one correction matrix, previously calculated; or - at least one aberration kernel matrix, comprising coefficients making it possible to deduce said at least one correction matrix, and previously calculated.

7. Method (400; 500; 510; 520) according to any one of the preceding claims, characterized in that it further comprises, prior to the first iteration of the acquisition phase, a characterization phase (300) comprising a determination of the at least one aberration matrix.

8. Method (400; 500; 510; 520) according to the preceding claim, characterized in that the characterization phase (300) comprises a determination of: - several aberration matrices for several regions of the image sensor; - several aberration matrices for several DOC distance values; and / or - several aberration matrices for several DOS distance values.

9. Method (400;500;510;520) according to any one of claims 7 or 8, characterized in that at least one aberration matrix is determined by optical measurement, on the real optical objective, with an optical measuring device.

10. Method (400; 500; 510; 520) according to any one of claims 7 to 9, characterized in that at least one aberration matrix is determined by simulation in a digital simulator on a model digital optical lens.

11. Method (400; 500; 510; 520) according to any one of the preceding claims, characterized in that at least one aberration matrix is: - a matrix, called a PSF matrix, of values of a point spread function ("Point Spread Function" or "PSF" in English), and / or - a matrix, called an OTF matrix, of values of an optical transfer function ("Optical Transfer Function" or "OTF" in English), and / or - a matrix of values obtained by wavefront analysis.

12. Method (500) according to any one of the preceding claims, characterized in that it comprises a step (502) of calculating a matrix, called aberration kernel matrix, comprising coefficients making it possible to deduce at least one aberration matrix.

13. Image acquisition system with an apparatus (700; 800) comprising a camera module (702; 200) comprising an optical lens (204) associated with an image sensor (202), said system comprising: - a device (600) for characterizing said optical lens (204) to determine at least one matrix, called an aberration matrix, representative of optical aberrations introduced by said optical lens (204) in an image captured by said camera module (702; 200), - said camera module (702; 200) for capturing an image, and - a calculation unit (710) in said apparatus (700; 800); configured to implement the method (400; 500; 510; 520) according to any one of claims 7 to 12.

14. Apparatus (700; 800) for acquiring an image comprising: - a camera module (702; 200) comprising an optical lens (204) associated with an image sensor (202), and - a calculation unit (710); configured to implement the steps of the method (400; 500; 510; 520) according to any one of claims 1 to 6.

Images