Method and system for efficient characterization of lenses

Abstract

This invention relates to a method (300) for characterizing a lens, the method comprising the steps of: measuring the optical transfer function (OTF) of a lens (OO) using an image sensor for at least one color; and comparing the measured OTF with at least one threshold OTF; the method further comprising at least one step: measuring at least one lateral dispersive aberration function (LCAF) and / or at least one geometrical aberration function (GAF) of the lens (OO) using an image sensor, in order to at least partially correct at least one aberration, particularly each of the aberrations, in the image acquired using the lens (OO) by digital processing. The invention also relates to a system for characterizing a lens, the system implementing this characterization method.

Description

[0001] This invention relates to a method and system for characterizing optical objectives. It also relates to a method and system for manufacturing optical objectives using this characterization method and system, a camera module using an optical objective characterized by this characterization method and system, and an image acquisition method using this camera module. Furthermore, the invention relates to apparatus and vehicles for implementing such a camera module.

[0002] The field of this invention is generally characterized by optical objectives, and particularly by optical objectives used for imaging. Background Technology

[0003] An optical objective lens comprises several optical features, such as lenses and spacers, stacked along a stacking direction within a lens barrel. Once manufactured, the optical objective lens undergoes performance testing to determine if its imaging quality is satisfactory. If the objective lens's quality is unsatisfactory, it is simply scrapped, which reduces manufacturing efficiency and results in losses of time and cost.

[0004] Currently, the quality of an optical objective is tested by measuring its modulation transfer function (MTF). The measured MTF value is compared with a predetermined threshold to determine whether the quality of the objective is considered satisfactory.

[0005] The inventors discovered that optical aberrations caused by the objective lens include, on the one hand, aberrations such as lateral dispersive aberration and geometric aberration, which can be effectively corrected by calculation; on the other hand, they include other aberrations such as axial dispersive aberration and third-order and higher-order aberrations (hereinafter referred to as "third-order aberrations" for the sake of brevity), which are extremely difficult (if not impossible) to correct by calculation.

[0006] However, current MTF measurements provide values ​​for all optical aberrations of the objective lens, including those that can be corrected by calculation. Therefore, MTF does not provide a relevant characterization of the optical quality of the objective lens. Furthermore, MTF measurements do not provide any information about aberrations that can be corrected by calculation.

[0007] One object of the present invention is to solve at least one of the above-mentioned defects.

[0008] Another object of the present invention is to provide a more relevant solution for characterizing optical objectives.

[0009] Another object of the present invention is to provide a solution for characterizing optical objectives, which enables the improvement of the quality of images captured with said optical objectives. Summary of the Invention

[0010] This invention proposes a method for characterizing optical objectives to achieve at least one of the above objectives, the method comprising an identification stage, the identification stage including the following steps:

[0011] - For at least one of the following light sources: green light, blue light, and red light, measure the optical transfer function (OTF) of the optical objective (OO) individually using an image sensor, and

[0012] - For at least one of the light: compare the measured OTF with at least one predetermined threshold OTF to determine whether the optical quality of the objective lens (OO) is satisfactory;

[0013] The method further includes a quantization phase, which is performed at least when the optical quality of the optical objective (OO) is satisfactory, and the quantization phase includes the following steps:

[0014] - Measure at least one lateral dispersive aberration function (LCAF) of the optical objective (OO) using an image sensor, and / or

[0015] - Measure at least one geometric aberration function (GAF) of the optical objective (OO) using an image sensor;

[0016] At least one aberration, particularly each of the aberrations, in the image is corrected at least partially by digitally processing the image acquired using the optical objective (OO).

[0017] The inventors have noted that displacement optical aberrations (hereinafter also referred to as "displacement aberrations") caused by optical objectives can be corrected very effectively through computation (i.e., through digital processing of the acquired image), while diffusion aberrations (hereinafter referred to as "diffusion aberrations") are very difficult to correct, and sometimes even impossible to correct, depending on the scene being imaged. Based on this observation, the present invention proposes to measure the optical quality of an optical objective using an OTF (instead of the MTF of the optical objective measured in white light as is currently the case) measured individually for at least one (especially each) of the red, green, and blue light components. In fact, characterizing the optical objective individually for each color yields a more relevant contrast quality characterization than under white light. Indeed, under white light, while high contrast is obtained for each detected color, moderate contrast may still be obtained, especially when lateral dispersion aberrations become on the same order of magnitude as the pattern spacing used to evaluate that contrast ratio (i.e., MTF).

[0018] Therefore, this invention proposes a new, more efficient solution that allows for better characterization of the optical objective.

[0019] Furthermore, this invention proposes to separately measure the lateral dispersive aberration and / or geometric aberration of the optical objective, so as to understand these aberrations individually, that is, without mixing them with other aberrations. Once each of these aberrations is understood individually, they can be corrected by digitally processing the images acquired using the optical objective. Similarly, during the manufacture of the optical objective, a correction function can be derived for each of these aberrations, making it possible to correct the aberrations. This correction function, or these correction functions, can be used to correct these aberrations in each of the images by digitally processing the images taken using the optical objective. Correcting these aberrations enables an improvement in the quality of the images acquired using the optical objective.

[0020] Optical aberration refers to the concept that points in a scene become spots of light, either wide or narrow, at locations that form the image (usually on a plane). Aberrations cause various types of effects: some aberrations have the characteristic of displacing the average position of the spots produced by points in the scene relative to the ideal position where the spots would be produced. These aberrations are called displacement aberrations. Other effects are that the spots have a spatial spread in the image trajectory rather than a point-like energy distribution. These aberrations are called diffusion aberrations.

[0021] Aberrations caused by optical objectives are usually called dispersive aberrations, geometric aberrations, and third-order aberrations.

[0022] "Third-order aberrations" refer to all aberrations introduced into an image acquired using an optical objective lens, excluding dispersive and geometric aberrations. These third-order (and higher) aberrations include, for example, spherical aberration, coma, astigmatism, field curvature, and distortion (the shape and energy distribution of the light spot). These third-order (and higher) aberrations are diffusion-type. For simplicity, the term "third-order aberrations" will be used in the following text to refer to third-order and higher aberrations.

[0023] Chromatic aberration, caused by the decomposition of light into multiple color bands, refers to optical aberrations that produce different positions in the space of the focal point according to wavelength. In the case of lateral chromatic aberration, it consists of the shift of the focal point in the image trajectory, which depends on the wavelength. The result is an image with iridescent edges, or colored stripes around objects of a uniform color (e.g., white). In the case of axial chromatic aberration, it consists of the focal point deviating from the image trajectory because the focal point is shifted along an axis perpendicular to the image trajectory (or the axis corresponding to the central ray reaching the image point, which may be tilted relative to the image trajectory). The result is that some colors in the image become blurred. Lateral chromatic aberration can be corrected by digital processing of the image captured by the optical objective, provided it is quantized, i.e., measured during the optical objective design / manufacturing process. Lateral chromatic aberration is a displacement aberration. On the other hand, axial chromatic aberration is a diffusion aberration because if green is focused on the image plane sensor, red may be focused upstream of it, and the red beam broadens as it reaches the sensor located outside the focal point.

[0024] "Geometric aberration" refers to the deviation between paraxial rays as defined in the Gaussian approximation and their corresponding actual rays. Geometric aberration can also be characterized by the deviation between the paraxial wavefront and the actual wavefront. For example, geometric aberration distorts the shape of the final image. For instance, a square might become a shape resembling a barrel (corners concave) or a pincushion (corners convex). Similarly, the straight, vertical edges of a building might become curved and non-perpendicular. This aberration can be corrected by digitally processing the captured image, provided it is quantized—that is, measured during the optical objective design / manufacturing process. Geometric aberration is a displacement-type aberration.

[0025] "Displacement aberration" or "displacement aberration" refers to lateral dispersive aberration and geometric aberration.

[0026] "Diffusion aberration" or "diffusion aberration" refers to axial dispersive aberration and third-order aberration.

[0027] According to some embodiments, the identification phase and the quantification phase can be performed at least partially simultaneously.

[0028] Therefore, the method according to the invention can be executed more quickly, which can be used when the invention is integrated into a production line.

[0029] For example, the identification phase can be carried out simultaneously with the quantification phase.

[0030] According to another example, the quantification phase can begin before the qualification phase is completed, and vice versa.

[0031] According to some embodiments, the identification phase and the quantification phase can be performed sequentially.

[0032] In particular, the identification phase can be performed before the quantification phase, so that the identification phase is completed before the quantification phase begins.

[0033] Therefore, the optical quality of the optical objective can be known before the quantization stage.

[0034] According to some embodiments, a quantization phase can be performed regardless of whether the quality of the optical objective is satisfactory.

[0035] Alternatively, the quantization phase may be performed only when the optical quality of the optical objective is satisfactory.

[0036] According to some embodiments, the method according to the invention may include the step of retaining or not retaining the optical objective lens based on the result of the comparison step.

[0037] If the comparison step shows that the optical quality of the objective lens is unsatisfactory, then the objective lens can be discarded. Otherwise, the objective lens can be retained.

[0038] The procedure for retaining or not retaining the optical objectives can be performed after the qualification phase and before the quantization phase. Alternatively, the procedure for retaining or not retaining the optical objectives can be performed after the qualification phase and after the quantization phase.

[0039] When measuring OTF for a single colored light (i.e., red, green, or blue light), the optical objective can be retained if the measured OTF for that light meets at least one predetermined threshold OTF.

[0040] When the OTF is measured for multiple colored lights (i.e., red light and / or green light and / or blue light), the optical objective can be retained for each light being measured if the measured OTF satisfies at least one predetermined threshold OTF for the corresponding light.

[0041] Each of the identification and quantification phases will now be described in turn. The order in which these phases are described does not imply that they are performed in that order. As mentioned earlier, these phases may be performed in a different order, or at least partially simultaneously.

[0042] Furthermore, as described below, some steps in these stages can be combined or shared. For example, the step of identifying the measurement plane can be performed only once, and the selected measurement plane can be used in both the identification and quantization stages.

[0043] According to some embodiments, the optical transfer function (OTF) can be the modulation transfer function (MTF).

[0044] According to some embodiments, the optical transfer function (OTF) can be the point spread function (PSF).

[0045] Regardless of whether the OTF is MTF or PSF, the measured OTF and the threshold OTF are of the same type; they are either both MTF or both PSF.

[0046] According to some embodiments, at least one (especially each) measured OTF can be represented by OTF values ​​measured at multiple points (e.g., at the center of the objective lens, the edge of the objective lens, etc.). Preferably, the measured OTF can be represented by a value range that includes multiple measured OTF values, each value for a location (x, y) of the image sensor used to perform the measurement, particularly a pixel location (x, y).

[0047] Alternatively, a mathematical relationship can be derived from the measured values, which takes the position (x, y) of the image sensor as input and outputs the measured OTF value.

[0048] Of course, at least one measured OTF can be provided in other forms, such as a matrix, vector, etc.

[0049] According to some embodiments, for multiple locations (x, y) or multiple pixel locations (x, y) of an image sensor: for example, at the center, edge, etc. of the sensor, at least one (particularly each) threshold OTF can be represented by a set of values ​​(also called a value range). According to one example, for at least one location (x, y), the value range may include a minimum OTF value to be satisfied. Alternatively or additionally, for at least one location (x, y), the value range may include a pair of values ​​consisting of a minimum OTF value and a maximum OTF value.

[0050] Alternatively, at least one threshold OTF can be provided in the form of at least one mathematical relation that takes the position (x, y) of the image sensor as input and gives the following as output:

[0051] - Threshold OTF value, and especially the minimum OTF value, or

[0052] - Includes a pair of values: minimum OTF value and maximum OTF value.

[0053] Of course, at least one measured threshold OTF can be provided in other forms, such as a matrix, vector, etc.

[0054] At least one threshold OTF can be determined through experience or a test plan. Alternatively or additionally, at least one threshold OTF can be determined during the design or conception of the optical objective. Of course, these examples are by no means limiting, and at least one threshold OTF can be determined in other ways.

[0055] According to some embodiments, the measurement steps may be performed on a single light source using OTF measurement.

[0056] In this case, the OTF measured for that single light is compared with a predetermined threshold OTF for that single light. If the measured OTF meets the threshold OTF, the optical objective is considered to have satisfactory optical quality.

[0057] According to some embodiments, the single light used to measure OTF can be green light.

[0058] In fact, the inventors discovered that, in terms of image perception, green is the most representative of the three colors.

[0059] According to some embodiments, during the identification phase, the measurement steps can be performed individually for at least two (in particular each) of red, green and blue light.

[0060] In other words, the OTF measurement process involves performing OTF measurements individually for multiple light sources, including red, green, and blue light.

[0061] In this scenario, for each light being measured, a measured OTF is obtained. For example, if the measurement is performed for red light, the measured OTF for red light is obtained. For example, if the measurement is performed for green light, the measured OTF for green light is obtained. For example, if the measurement is performed for blue light, the measured OTF for blue light is obtained.

[0062] Preferably, the OTF measurement step is performed separately for each of the red, green, and blue light. In this case, the measured OTF for red light, the measured OTF for green light, and the measured OTF for blue light are obtained.

[0063] During the identification phase, when the OTF measurement step is performed individually for multiple (or even each) of red, green, and blue light, the comparison step can compare each measured OTF with at least one predetermined threshold OTF.

[0064] In this case, the optical quality of an optical objective can be considered satisfactory if and only if each measured OTF satisfies the threshold OTF with which it is compared.

[0065] According to some embodiments, the same threshold OTF can be used for at least two types of light, and in particular for all types of light.

[0066] According to some embodiments, different threshold OTFs can be used for at least two types of light, and in particular for all types of light.

[0067] in other words:

[0068] - The threshold OTF is associated with red light, and the OTF measured for said red light is compared with the threshold OTF;

[0069] - A threshold OTF is associated with green light, and the OTF measured for said green light is compared with the threshold OTF; and

[0070] - The threshold OTF is associated with blue light, and the OTF measured for said blue light is compared with the threshold OTF.

[0071] According to some embodiments, for at least one light, an OTF measurement can be performed on a measurement plane corresponding to the maximum focus, or on a plane that achieves satisfactory focus.

[0072] Such a measuring plane is preferably perpendicular to the optical axis of the optical objective.

[0073] Therefore, the method according to the invention may include the step of identifying the measurement plane by measuring focus over multiple planes and identifying the plane from which maximum and satisfactory focus is obtained. For example, a test pattern may be arranged in front of the objective lens. The relative position of the test pattern with respect to the lens may be modified along the optical axis of the optical objective lens, and the focus value may be monitored to identify the measurement plane.

[0074] When the measurement step performs OTF measurements for multiple lights, the same measurement plane can be used for multiple lights, in particular for all lights.

[0075] Alternatively, the measurement plane can be identified as follows: The measurement plane is placed at a given distance from the optical objective, and the focus of the camera module formed by the optical objective and the image sensor is adjusted to obtain optimal sharpness at that distance.

[0076] Of course, other embodiments are possible, and these non-limiting examples are provided for illustrative purposes only.

[0077] This measurement plane can be used in both the identification and quantification stages.

[0078] According to some embodiments, for at least one light, the measurement step in the identification phase can perform OTF value measurements at multiple points. For that light, the measured OTF is represented by the values ​​measured at those multiple points, or obtained from those values.

[0079] As mentioned earlier, for at least one light source, the measured OTF can be represented by a range of values, including the measured value and optionally other estimates, such as values ​​obtained by interpolation. Alternatively, the measured OTF can be represented by a mathematical relationship derived from the measured values.

[0080] According to some embodiments, for at least one light, the measurement steps of the identification phase can be performed using a test pattern positioned in front of the optical objective and comprising one or more patterns.

[0081] For at least one light source, the test pattern may directly comprise a pattern whose color corresponds to the color of the light (i.e., red, green, or blue). Alternatively, the test pattern may comprise a transparent pattern illuminated by red, green, or blue light.

[0082] If OTF is MTF, then the MTF measurement at a point corresponds to the contrast measured for that point.

[0083] According to one example embodiment, a test pattern is positioned at a selected distance (i.e., the so-called scene distance) from the sensor and the objective lens. This distance can also be achieved using optics inserted between the test pattern and the objective lens to alter the apparent distance of the test pattern from the sensor beyond the physical distance between the test pattern and the objective lens. This apparent distance can even be set to infinity to obtain a so-called "infinity" scene distance. The objective lens can optionally be moved relative to the sensor to select the optimal sharpness of the test pattern for this apparent scene distance. (Optimal sharpness can be obtained over a region of the sensor, over one color component, but not necessarily over all three color components at once or over the entire sensor…). The test pattern alternately includes:

[0084] - So-called dark patterns do not allow light to pass through, and

[0085] - The so-called bright pattern corresponds to the color of the radiation.

[0086] Dark patterns are considered to produce non-radioactive patterns on the sensor because they do not allow any radiation to pass through. Bright patterns are considered to produce patterns of the same color as the radiation because they allow the radiation to pass through.

[0087] In this configuration, the MTF of a point (x, y) of the sensor is calculated as follows. For a region centered at point (x, y) and comprising multiple alternating patterns, multiple contrast values ​​are calculated based on the values ​​received by pixels in the region, each contrast value corresponding to an alternating pattern in the region. The MTF value of point (x, y) is calculated based on the measured values, for example, by averaging the values.

[0088] If the OTF is a PSF, then the PSF measurement at a point is performed in the usual manner.

[0089] According to one example embodiment, a test pattern is arranged in front of the sensor and objective lens, for example, on a plane corresponding to maximum focus. This arrangement can be done directly or using distance-adaptive optics. The test pattern comprises multiple points through which radiation can pass. The remainder of the test pattern is opaque, preventing any radiation from passing through.

[0090] Each point at position (x, y) is captured on the sensor as a light spot with varying width and shape.

[0091] When the light spot is a perfect circle, the PSF value of point (x, y) corresponds to the radius of the light spot captured on the sensor.

[0092] When the light spot has other shapes, the PSF can be calculated, for example, as the average radius of the light spot. The average radius can be calculated as follows: First, extract the center of the light spot, for example by determining the centroid of the location where the light spot forms, weighted by the intensity detected at each location. Next, calculate the sum of the detected amplitudes multiplied by the squares of the distances to the centroid. Divide this sum by the sum of the detected amplitudes. This gives the square of the average radius of the light spot. Take its square root. This gives the effective average radius of the light spot.

[0093] The measured lateral dispersive aberration function LCAF can take any form.

[0094] According to some embodiments, LCAF can take the form of a range, which includes at least one displacement vector for each of a plurality of locations (x, y) on the image sensor. According to one example embodiment, for at least one location (x, y), the range may include:

[0095] - The displacement vector measured relative to the reference position, specifically for the red measurement.

[0096] - The displacement vector relative to the reference position, measured for the green area, and

[0097] - The displacement vector relative to the reference position, measured for the blue area.

[0098] The reference location can be any previously selected location. For example, the reference location could be the centroid of the three colors.

[0099] According to one example embodiment, a location of one of three colors can be selected as a reference. In this case, for at least one location (x, y), the value range can include displacement vectors for each of the other two colors. For example, a green location can be selected as a reference: in this case, for at least one location (x, y), the value range can include displacement vectors for red and displacement vectors for blue.

[0100] Alternatively, LCAF can be a mathematical function that takes the sensor’s position (x, y) as input and provides one or more displacement vectors (such as those mentioned above).

[0101] LCAF can be measured in a variety of ways.

[0102] According to an example embodiment, a test pattern consisting of patterns (e.g., dots, lines, etc.) can be placed in front of an optical objective, located at the measurement plane. The test pattern is illuminated with white light, or sequentially with green, red, and blue light. The pattern corresponding to the position (x, y) of the image sensor generates a spot on the image sensor for each color. The position of each color spot can be detected by the image sensor. Then, the displacement vector relative to a reference position is calculated using the detected positions of the three color spots, which can be the position of one of the three spots or another position.

[0103] LCAF can then be determined by simultaneously or sequentially measuring multiple positions (x, y) in the sensor plane (also known as the image plane).

[0104] According to some embodiments, LCAF can be measured for all image sensor locations. Alternatively, LCAF can be measured only for some image sensor locations.

[0105] The measured geometric aberration function (GAF) can take any form.

[0106] According to some embodiments, GAF can take the form of a range that includes multiple angles Θ relative to the optical axis of the optical objective. i and multiple rotation angles γ around the optical axis of the optical objective. i This includes at least one displacement distance. According to one example embodiment, for at least one angle (Θ) i ,γ i This value range can include:

[0107] - The displacement distance measured relative to the center of the image sensor, specifically for the red area.

[0108] - The displacement distance relative to the center of the image sensor, measured for green, and

[0109] - The displacement distance measured relative to the center of the image sensor for the blue area.

[0110] According to an example embodiment, for at least one angle (Θ) i ,γ i This range can include a single displacement distance, which is obtained from the displacement distances for the three colors, for example, the average of the displacement distances.

[0111] Alternatively, GAF can be a mathematical function that expresses the angle (Θ) as a constant. i ,γ i As input, it provides a single displacement distance for all three colors, or a displacement distance for each color individually.

[0112] GAF can be measured in a variety of ways.

[0113] According to an example embodiment, a test pattern composed of patterns (e.g., dots, lines, etc.) can be placed in front of the optical objective, at the measurement plane. The test pattern is illuminated with white light, or sequentially with green, red, and blue light. It is angled (Θ) relative to the optical axis of the optical objective. i ,γ i The pattern generates a spot on the image sensor for each of the three colors: red, green, and blue. The position of each color spot can be detected by the image sensor. The detected positions of the three spots are then used to calculate the displacement distance of each color relative to the center of the optical objective. Optionally, the displacement distance can be divided by the focal length to obtain an angle (Θ) based on the angle of the light beam entering the optical objective relative to the axis of the optical objective. i ,γ i ( ) angular measurement.

[0114] By targeting multiple angles (Θ) relative to the optical axis of the optical objective lens i ,γ i By performing measurements (which can be performed simultaneously or sequentially), the GAF can be determined.

[0115] According to some embodiments, GAF can be measured for all image sensor locations. Alternatively, GAF can be measured only for some image sensor locations.

[0116] According to some embodiments, the quantization stage may include the step of providing at least one lateral chromatic aberration correction function (LCACF) based on the measured lateral chromatic aberration.

[0117] According to some embodiments, the LCACF can take the form of a range, which, for each of a plurality of locations (x, y) of the image sensor, includes at least one displacement vector to be applied to correct lateral dispersive aberration at that location. For at least one location (x, y) of the sensor, the LCACF may include:

[0118] - A single displacement vector for each of the red, green, and blue colors; or

[0119] - For at least one color, a displacement vector dedicated to that color.

[0120] Alternatively, LCACF can be a mathematical function that takes a position (x, y) within the image sensor as input and provides one or more displacement vectors to be applied to correct aberrations at that position (x, y).

[0121] According to another alternative, LCACF can take the form of a mapping table that indicates the corrected position of each of a plurality of pixels in the image sensor, and provides individual indication for the following cases:

[0122] - For each color, or

[0123] - When using green as a reference, this applies to red and blue.

[0124] According to some embodiments, the quantization stage may include the step of providing at least one geometric aberration correction function (GACF) based on the measured geometric aberrations.

[0125] According to some embodiments, GACF can take the form of a range for multiple angles (Θ). i ,γ i For each of the values ​​in ), the range includes at least one distance vector to be applied to correct geometric aberrations. For at least one angle (Θ) i ,γ i ), GACF can include:

[0126] - A single distance correction value to apply for each of the red, green, and blue colors; or

[0127] - For at least one color, a distance correction value specifically for that color.

[0128] Alternatively, GACF can be a mathematical function that takes the angle (Θ) relative to the axis of the optical objective. i ,γ i (and the second angle γ used to completely position the incident light relative to the sensor) i ( ) as input, and provide one or more distance correction values.

[0129] According to another alternative, GACF can take the form of a mapping table that indicates the corrected position of each pixel among multiple pixels on the image sensor, and indicates it separately for each color.

[0130] According to some embodiments, the step of providing at least one correction function may include:

[0131] - A separate correction function for lateral dispersive aberration, and / or

[0132] - A separate correction function for geometric aberrations.

[0133] Therefore, these aberrations can be corrected individually in any desired order. For example, it may be useful to correct lateral dispersive aberrations first before correcting geometric aberrations, and vice versa.

[0134] According to some embodiments, the step of providing at least one correction function can provide a common correction function for lateral dispersive aberration and / or for geometric aberration.

[0135] In this case, applying this single correction function will be able to correct both CAF and GA simultaneously. The common correction function can perform corrections on all colors without distinguishing between dispersive aberrations and geometric aberrations.

[0136] Furthermore, using this common correction function allows for better correction and avoidance of overcorrection. In fact, according to an example embodiment, applying lateral dispersive aberration correction at point (x, y) can partially or completely correct the geometric aberration at that point. In this case, applying geometric correction alone may ultimately lead to undesirable overcorrection. This can be avoided by using the common correction function.

[0137] According to some non-limiting embodiments, at least one (especially each) correction function may be in the form of a range or mapping table, or take the form of a range or mapping table for at least one color component (red, green, blue) of at least one pixel of an image sensor, indicating the corrected position of said component in an image acquired using an optical objective.

[0138] According to some embodiments, the method according to the invention may include the step of identifying a plane (referred to as a measurement plane) obtained by the optical objective lens corresponding to the maximum focus or satisfactory focus, wherein at least one aberration measurement is performed with respect to the measurement plane.

[0139] Such a measuring plane is preferably perpendicular to the optical axis of the optical objective.

[0140] The same measurement plane can be used to measure lateral dispersive aberration functions and to measure geometric aberration functions. Different measurement planes can be used to measure lateral dispersive aberration functions and to measure geometric aberration functions.

[0141] There are several methods for identifying the measurement plane. For example, a test pattern can be arranged in front of an optical objective. The relative position of the test pattern with respect to the optical objective can be modified along the optical axis, and the focus value can be monitored to identify the measurement plane.

[0142] Alternatively, the measurement plane can be identified as follows: Place the plane at a given distance from the optical objective, and adjust the focus of the camera module formed by the optical objective and the image sensor to obtain optimal sharpness at that distance.

[0143] Of course, other embodiments are possible, and these non-limiting examples are provided for illustrative purposes only.

[0144] Furthermore, this measurement plane identification step is optional and may not be performed, or it may be shared with the authentication phase. More specifically, when a measurement plane is identified / selected in the authentication phase, it can also be used in the quantization phase.

[0145] As shown above, for at least one aberration, the step of measuring the aberration can be performed using at least one test pattern comprising one or more patterns.

[0146] According to another aspect of the invention, a system for characterizing optical objectives is provided, the system comprising:

[0147] - At least one measuring device; and

[0148] - Computational unit;

[0149] The system is configured to implement the method according to the invention.

[0150] In terms of hardware and / or configuration, the characterization system according to the invention may include any combination of the features disclosed above with reference to the characterization method according to the invention, which will not be mentioned again here for the sake of brevity.

[0151] According to another aspect of the invention, a method (500) for manufacturing an optical objective lens is provided, the method comprising the following steps for at least one optical objective lens:

[0152] - Manufacturing the optical objective lens,

[0153] - The optical objective lens is characterized by the characterization method according to the invention.

[0154] According to some embodiments, each manufactured optical objective can be characterized.

[0155] Alternatively, only certain manufactured optical objectives can be characterized. For example, within the same batch of optical objectives, only one or a few objectives can be characterized. The OTF measured for said one or more objectives in the batch can be used for all objectives in the same batch.

[0156] A batch of optical objectives can correspond to objectives with the same design.

[0157] Alternatively, a batch of optical objectives may correspond to objectives with the same design and assembled according to the same assembly formula.

[0158] According to another aspect of the present invention, an apparatus for manufacturing optical objectives is provided, comprising:

[0159] - Optical objective lens production line, and

[0160] - A characterization system according to the invention for characterizing at least one optical objective.

[0161] In terms of hardware and / or configuration, the manufacturing apparatus according to the invention may include any combination of the features disclosed above with reference to the manufacturing method according to the invention, which will not be mentioned again here for the sake of brevity.

[0162] According to another aspect of the present invention, a method for acquiring an image of a scene using an optical objective lens characterized by the method according to the present invention is provided, the method comprising the following steps:

[0163] - Acquire images using the optical objective lens, and

[0164] - The image is digitally processed to at least partially correct lateral dispersive aberration and / or geometric aberration.

[0165] In some embodiments, the optical lens assembly can be used for 2D or 3D imaging.

[0166] According to some embodiments, optical lens assemblies can be used for image acquisition to image a scene at a given moment, or to acquire an image stream or video of the scene.

[0167] According to another aspect of the present invention, a camera module is provided, comprising:

[0168] - An optical objective lens, characterized by the characterization method according to the invention; and

[0169] - An image sensor associated with an optical objective.

[0170] The image sensor can be any type of image sensor associated with an optical lens assembly, such as a CMOS or CCD image sensor, but is not limited to these image sensors.

[0171] According to another aspect of the invention, a user equipment is also provided, which includes at least one optical objective lens characterized by the method of the invention.

[0172] In particular, the user equipment according to the present invention may include at least one camera module according to the present invention.

[0173] Specifically, the user device can be a user device such as a smartphone, tablet, etc.

[0174] User equipment may optionally include a display screen, particularly a touch screen.

[0175] Specifically, the user device can be a virtual reality headset or an augmented reality headset, designed for the user to wear.

[0176] Head-mounted devices may optionally include a display screen, particularly a touchscreen.

[0177] In particular, the user equipment can be, for example, a camera or a still camera.

[0178] Camera-type user equipment may optionally include a display screen, particularly a touch screen.

[0179] In particular, the user equipment can be a computer-type user equipment.

[0180] Computer-type user equipment may optionally include a display screen, particularly a touch screen.

[0181] Computer-type user equipment may optionally include a keyboard, or include any other device integrated into or associated with the device.

[0182] Specifically, the user equipment can be a television set.

[0183] Televisions may optionally include a display screen, particularly a touch screen.

[0184] In particular, the user equipment can be a medical imaging device.

[0185] Medical imaging equipment can be, for example, endoscopes, ultrasound equipment, etc.

[0186] Of course, the user equipment according to the present invention is not limited to the examples disclosed above.

[0187] According to another aspect of the invention, a vehicle is also proposed, which includes at least one optical objective lens characterized by the characterization method according to the invention.

[0188] In particular, the vehicle according to the invention may include at least one camera module according to the invention.

[0189] According to some embodiments, the vehicle may be a land vehicle (e.g., a car), such as a land vehicle with non-autonomous, semi-autonomous, or autonomous driving capabilities.

[0190] According to some embodiments, the vehicle may be an aircraft (e.g., a drone, an airplane, or a helicopter), such as an aircraft with non-autonomous, semi-autonomous, or autopilot functions.

[0191] According to some embodiments, the vehicle may be a waterborne vehicle (e.g., a boat or submarine), such as a waterborne vehicle with non-automatic, semi-automatic or automatic driving capabilities.

[0192] Description of the Drawings and Detailed Description of the Embodiments

[0193] Other advantages and features will become apparent from a study of the detailed description of the non-limiting embodiments and the accompanying drawings, in which:

[0194] - Figures 1a-1b This is a schematic diagram of a non-limiting example embodiment of the identification stage of an optical objective lens that can be implemented in this invention according to the present invention;

[0195] - Figures 2a-2b This is a schematic diagram of a non-limiting example embodiment of the quantization stage of an optical objective lens that can be implemented in this invention according to the present invention;

[0196] - Figures 3a-3c This is a schematic diagram of a non-limiting example embodiment of the method for characterizing optical objectives according to the present invention;

[0197] - Figure 4 This is a schematic diagram of a non-limiting example embodiment of a system for characterizing optical objectives according to the present invention;

[0198] - Figure 5 This is a schematic diagram of a non-limiting example embodiment of a method for manufacturing one or more optical objectives according to the present invention;

[0199] - Figure 6 This is a schematic diagram of a non-limiting example embodiment of an apparatus for manufacturing one or more optical objectives according to the present invention;

[0200] - Figure 7 This is a schematic diagram of a non-limiting example embodiment of a camera module according to the present invention;

[0201] - Figure 8 This is a schematic diagram of a non-limiting example embodiment of the method for acquiring images according to the present invention;

[0202] - Figures 9a-9c These are schematic diagrams of non-limiting exemplary embodiments of the device according to the present invention; and

[0203] - Figure 10 This is a schematic diagram of a non-limiting example embodiment of a vehicle according to the present invention.

[0204] It should be fully understood that the implementation examples described below are by no means limiting. In particular, it is conceivable that variations of the invention may include only a portion of the features described below, separate from the other features, provided that such selection of a feature is sufficient to provide a technical advantage or to distinguish the invention from the prior art. Such a selection may include at least one, preferably functional, feature, excluding structural details, or including only a portion of structural details, provided that this portion alone is sufficient to provide a technical advantage or to distinguish the invention from prior art embodiments.

[0205] In particular, if there are no technical obstacles, all the described variations and embodiments can be combined with each other.

[0206] In the remainder of the accompanying drawings and description, the same reference numerals are used for features common to multiple drawings.

[0207] The present invention, particularly the following examples, can be implemented to characterize an optical objective OO for imaging (i.e., for acquiring images, image streams, or video). Such an objective OO can be associated with an image sensor to form an imaging module or camera module and integrated into various devices or vehicles.

[0208] An optical objective lens typically consists of multiple optical elements (such as lenses, spacers, etc.). The various elements of an optical objective lens are stacked along a stacking direction, which also corresponds to the axis of the optical objective lens.

[0209] The optical objective lens OO can be used with an image sensor ( Figures 1a-1b (Not shown in 2a-2b and 3a-3c). In this case, an image sensor is used to characterize the optical objective OO. Alternatively, the optical objective may not be associated with an image sensor. In this case, the image sensor of the measuring device is used to characterize the optical objective OO.

[0210] Figure 1a This is a schematic diagram of a non-limiting example implementation of the identification phase that can be carried out in the present invention (particularly in the method for characterizing optical objectives according to the present invention).

[0211] The identification phase 100 is performed, for example, to characterize the optical objective lens OO.

[0212] Prior to the identification stage, the method according to the invention may include step 102 of identifying a measurement plane for measuring at least one optical transfer function (OTF), the measurement plane being perpendicular to the optical axis of the optical objective lens OO.

[0213] Identifying the measurement plane can be accomplished in several ways.

[0214] According to one example embodiment, a test pattern can be arranged in front of an optical objective OO. The relative position of the test pattern with respect to the optical objective OO can be modified along the optical axis of the optical objective (optionally via adaptive optics), and focus values ​​can be monitored to identify a measurement plane that provides maximum focus or provides a satisfactory focus value relative to a predetermined focus threshold.

[0215] According to another example embodiment, the measurement plane can also be identified as follows: The measurement plane is placed at a given distance from the optical objective, and the focus of the camera module formed by the optical objective OO and the image sensor is adjusted to obtain optimal sharpness at that distance.

[0216] Of course, other example embodiments are possible, and the examples given are non-limiting.

[0217] The measurement plane identified in step 102 can be used in either the identification stage or the quantization stage. In other words, step 102, which identifies the measurement plane, can be performed only once in the method according to the invention. Alternatively, one measurement plane can be identified for the identification stage, and another measurement plane can be identified for the quantization stage.

[0218] exist Figure 1a In the non-limiting example shown, the identification phase 100 includes step 104 for the MTF of the green light measuring optical objective OO.

[0219] exist Figure 1a In a non-limiting example, the green light can be green light with a wavelength between 500 nm and 570 nm, particularly green light with a wavelength of 535 nm.

[0220] MTF can be measured using the techniques described above. Specifically, a test pattern is positioned within the measurement plane identified in step 102. This test pattern is associated with a light source that emits an image in the form of a green pattern toward the objective lens. These images of the patterns pass through the optical objective lens and are captured by an image sensor. For a sensor point, MTF can be measured as the average contrast obtained across multiple patterns, or the average contrast obtained across multiple lines of the pattern surrounding the point.

[0221] Step 104 performs multiple measurements of MTF values ​​for multiple points of the image sensor and provides the measured MTF as represented by the value range of the measured MTF, each value corresponding to the sensor position (x, y).

[0222] Next, step 106 compares the MTF measured for green light with at least one predetermined threshold MTF for said green light.

[0223] In one example, the measured MTF is compared to a threshold MTF that gives the minimum MTF value. If the measured MTF is greater than the threshold MTF, then evaluation phase 100 continues. Otherwise, the evaluation phase stops, and the optical objective is considered to be of unsatisfactory quality.

[0224] According to one example, the measured MTF is compared with a first MTF threshold that gives the minimum MTF value and a second MTF threshold that gives the maximum MTF value. If the measured MTF is between the first and second MTF thresholds, the evaluation phase 100 continues. Otherwise, the evaluation phase 100 stops, and the optical quality of the optical objective is considered unsatisfactory.

[0225] The comparison of the measured MTF with a threshold MTF (specifically, each one) can be performed value by value. In other words, for a sensor position (x, y), the MTF value measured at that position (x, y) is compared with the MTF threshold for that position. The measured MTF satisfies the MTF threshold if and only if the MTF value measured for each measurement position (x, y) satisfies the MTF threshold. Finally, the threshold MTF can also depend on (x, y).

[0226] When the MTF measured for green light in step 106 is satisfactory, the qualification phase 100 includes step 108 of measuring the MTF for red light, similar to the MTF measurement for green light in step 104.

[0227] exist Figure 1a In a non-limiting example, the red light can be red light with a wavelength between 570 nm and 730 nm, and in particular red light with a wavelength of 650 nm.

[0228] In step 110, the MTF measured for red light is compared with at least one predetermined threshold MTF for red light. If the comparison shows that the MTF measured for red light does not meet at least one threshold MTF, then the optical quality of the optical objective OO is considered unsatisfactory, and the evaluation phase stops. Otherwise, the optical objective OO is retained, and the evaluation phase 100 continues.

[0229] When the MTF measured for red light in step 110 is satisfactory, method 100 includes step 112 of measuring the MTF for blue light, similar to the MTF measurement for green light in step 104.

[0230] exist Figure 1a In a non-limiting example, blue light can be blue light with a wavelength between 400 nm and 500 nm, particularly blue light with a wavelength of 450 nm.

[0231] In step 114, the MTF measured for blue light is compared with at least one predetermined threshold MTF for blue light. If the comparison shows that the MTF measured for blue light does not meet at least one threshold MTF, then the quality of the optical objective OO is considered unsatisfactory. Otherwise, the quality of the optical objective OO is considered satisfactory.

[0232] In the example shown in Figure 1, the MTF measured for one color is compared with at least one threshold MTF before measuring the MTF for another color. This avoids the need to measure the MTF for another color when the MTF measured for the current color is unsatisfactory.

[0233] According to an alternative not shown, steps 104, 108, and 112 may be performed before performing comparison steps 106, 110, and 114.

[0234] Figure 1b This is a schematic diagram of another non-limiting example implementation of the identification phase that can be carried out in the present invention (especially in the method for characterizing optical objectives according to the present invention).

[0235] and Figure 1a The evaluation stage for the optical quality of the optical objective lens OO is different for each color (green, red, and blue). Figure 1b The quality of the optical objective lens OO is tested in the identification phase 150 based on the MTF measured separately for a single color.

[0236] exist Figure 1b In the example shown, the single color used to characterize the optical objective is green. Of course, red or blue could also be used.

[0237] The identification phase 150 includes references Figure 1a The disclosed steps are 102-106, but do not include step 110 and subsequent steps.

[0238] When the MTF measured for green light in step 106 meets at least one threshold MTF, the quality of the optical objective OO is considered satisfactory, and the evaluation phase 150 terminates. If the MTF measured for green light does not meet at least one threshold MTF, the optical quality of the optical objective OO is considered unsatisfactory, and the evaluation phase 150 terminates.

[0239] According to an alternative not shown in the accompanying drawings, the optical objective OO can be characterized based on two colors chosen from green, red, and blue.

[0240] exist Figure 1a and 1bIn the example, the measured OTF is MTF. Alternatively, PSF can be used instead of MTF as OTF.

[0241] Figure 2a This is a schematic diagram of a non-limiting example implementation of the quantization stage that can be carried out in the present invention (especially in the characterization method according to the present invention).

[0242] Prior to the quantization stage, the method according to the invention may include step 102 of identifying a measurement plane for measuring at least one optical transfer function (OTF), the measurement plane being perpendicular to the optical axis of the optical objective lens OO.

[0243] As mentioned above, identifying the measurement plane can be done in a variety of ways.

[0244] If step 102 has already been performed in the method according to the invention (e.g., for the testing step), then this step is optional. In other words, the measurement step may be performed only once for the identification and quantification phases.

[0245] The quantization stage 200 includes step 204 of measuring the lateral dispersive aberration function (LCAF) of the optical objective.

[0246] LCAF can be measured in a variety of ways.

[0247] In one example, a test pattern consisting of a pattern (e.g., dots, lines, etc.) is placed in front of the optical objective OO, at the measurement plane identified in step 102. The test pattern is illuminated with white light, or sequentially with green, red, and blue light. The pattern corresponding to the position (x, y) of the image sensor generates a spot on the image sensor for each color: a red spot, a green spot, and a blue spot. The position of each spot can be detected by the image sensor. The displacement vector relative to a reference position is then calculated using the positions of the three detected spots, which can be either the position of one of the three spots or another position.

[0248] LCAF can then be determined by simultaneously or sequentially measuring multiple points (x, y) in the sensor plane (also known as the image plane).

[0249] As mentioned above, the measured LCAF can take any form. In the disclosed example, LCAF can take the form of a range for each of multiple points (x, y) of the image sensor, which includes:

[0250] - The displacement vector measured relative to the position of the red light spot, based on the position of the green light spot.

[0251] - The displacement vector measured relative to the position of the blue light spot, with reference to the position of the green light spot.

[0252] Therefore, step 204 provides LCAF, which indicates the dispersive aberration measured for multiple locations (x, y) on the sensor (i.e., for multiple pixels of the sensor).

[0253] Then, the quantization stage 200 includes an optional step 206 of calculating the lateral dispersive aberration correction function LCACF based on LCAF.

[0254] LCACF can be determined in different ways.

[0255] In the disclosed example, the LCACF can take the form of a range for each of a plurality of locations (x, y) of the image sensor, the range including at least one displacement vector to be applied to correct lateral dispersive aberration at said point. For at least one location (x, y), the LCACF may include:

[0256] - When using green as a reference, for the displacement vector of red, and

[0257] - When using green as a reference, the displacement vector is relative to blue.

[0258] Alternatively, LCACF can take the form of a mapping table that indicates the corrected position of each of multiple pixels in the image sensor, and provides individual indication for the following cases:

[0259] - For each color, or

[0260] - When using green as a reference, this applies to red and blue.

[0261] Then, the quantization stage 200 includes step 208 of measuring the geometric aberration function (GAF) of the optical objective.

[0262] GAF can be measured in a variety of ways.

[0263] In one example, a test pattern consisting of a pattern (e.g., dots, lines, etc.) is positioned in front of the optical objective OO, at the measurement plane identified in step 102. The test pattern is illuminated with white light, or sequentially with green, red, and blue light. It is angled (Θ) relative to the axis of the optical objective OO. i ,γ i The pattern generates a spot on the image sensor for each color: a red spot, a green spot, and a blue spot. The position of each color spot is detected by the image sensor. The detected positions of the three spots are then used to calculate the displacement distance of each color relative to the center of the optical objective OO. Optionally, the displacement distance can be divided by the focal length to obtain the angle (Θ) of the light beam entering the optical objective OO relative to the axis of the optical objective. i ,γi The amount of ).

[0264] By considering multiple angles (Θ) relative to the optical axis of the optical objective lens OO. i ,γ i ) and multiple angles γ rotating around the center of the objective lens. i By performing measurements (which can be performed simultaneously or sequentially), the GAF can be determined.

[0265] As mentioned earlier, the measured GAF ​​can be in any form. For example, GAF can be in the form of a range that spans multiple angles (Θ) relative to the optical axis of the optical objective. i ,γ i )include:

[0266] - For the displacement distance measured relative to the center of the sensor, as indicated by the red line.

[0267] - For the displacement distance measured relative to the center of the sensor, as measured in green, and

[0268] - For blue, the displacement distance relative to the center of the sensor is measured.

[0269] Then, the quantization stage 200 includes step 210 of calculating the geometric aberration correction function GACF based on GAF.

[0270] GACF can be determined in different ways.

[0271] In the published examples, GACF can take the form of a range that covers multiple angles (Θ). i ,γ i Each of the following includes:

[0272] - To apply the distance correction value to the red area.

[0273] - The distance correction value to be applied to green, and

[0274] - To apply the distance correction value to the blue area.

[0275] Alternatively, GACF can take the form of a range that covers multiple angles (Θ). i ,γ i Each of these includes a single distance correction value to be applied to each of the red, green, and blue.

[0276] Alternatively, GACF can take the form of a mapping table that indicates the corrected position of each of the multiple pixels in the image sensor, and indicates it separately for each color.

[0277] In optional step 212, at least one aberration function measured in steps 204 and 208 and / or at least one aberration correction function determined in steps 206 and 210 can be stored for subsequent use. Specifically, at least one of these functions can be used to correct the image by digitally processing the image acquired using the optical objective OO.

[0278] Figure 2b This is a schematic diagram of another non-limiting example implementation of the quantization stage that can be carried out in the present invention (especially in the characterization method according to the present invention).

[0279] and Figure 2a The quantification stages are different. Figure 2b The quantization phase 250 does not include steps 206 and 210. These optional steps are replaced by optional step 252, which determines a single aberration correction function ACF based on the measured LCAF and the measured GAF ​​to correct simultaneously:

[0280] - Lateral chromatic aberration, and

[0281] - Geometric aberrations.

[0282] In optional step 254, a single aberration correction function determined in step 252 can be stored for subsequent use. Specifically, this function can be used to correct the image by digitally processing the image acquired using the optical objective OO.

[0283] Figure 3a This is a schematic diagram of a non-limiting example embodiment of the method for characterizing optical objectives according to the present invention.

[0284] Figure 3a Method 300 can be used to characterize optical objectives, especially optical objectives OO.

[0285] As mentioned above Figure 1a The method 300 includes a step 102 of identifying a measurement plane. This step 102 is performed only once, and the identified measurement plane is used in both the identification and quantization phases. In other words, neither the identification nor the quantization phase includes the step of identifying a measurement plane, and the measurement plane identified during step 102 is used for various measurements to be performed during said phases.

[0286] exist Figure 3a In the example, method 300 first includes an identification phase 302. The identification phase 302 could be, for example, an identification phase 302. Figure 1a and 1b Either evaluation stage 100 or 150. Evaluation stage 302 determines whether the optical objective has sufficient / satisfactory optical quality.

[0287] During step 304, it is determined whether the optical objective is retained based on the results of the identification phase 302.

[0288] If step 304 results in the retention of the optical objective lens OO because the optical quality of the objective lens OO is deemed satisfactory at the end of the evaluation stage 302, then method 300 includes a quantization stage 306. The quantization stage 306 could, for example, be... Figure 2a and 2b Either quantization stage 200 or 250. This quantization stage 306 determines lateral dispersive aberration and / or geometric aberration, and optionally, but preferably, determines at least one correction function for the lateral dispersive aberration and / or geometric aberration.

[0289] If step 304 results in the rejection of retaining the optical objective OO due to its unsatisfactory optical quality, it is placed in method 300 and the quantization phase is not performed.

[0290] Figure 3b This is a schematic diagram of another non-limiting example embodiment of the method for characterizing optical objectives according to the present invention.

[0291] Figure 3b Method 310 can be used to characterize optical objectives, especially optical objectives OO.

[0292] Method 310 includes Figure 3a Method 300 includes all steps. Figure 3b In method 310, with Figure 3a Unlike method 300, step 304, which involves retaining or not retaining the optical objective, is performed after identification stage 302 and after quantization stage 306. In other words, quantization stage 306 is performed before determining whether the optical objective OO is retained.

[0293] Figure 3c This is a schematic diagram of another non-limiting example embodiment of the method for characterizing optical objectives according to the present invention.

[0294] Figure 3c Method 320 can be used to characterize optical objectives, especially optical objectives OO.

[0295] Method 320 includes Figure 3a Method 300 includes all steps. Figure 3c In method 320, with Figure 3a Unlike method 300, step 304, which involves retaining or not retaining the optical objective lens OO, is performed after identification stage 302 and after quantization stage 306, as in... Figure 3bThe method is the same as in method 310. In other words, the quantization stage 306 is performed before determining whether the optical objective OO is retained.

[0296] In addition, Figure 3c In method 320, with Figure 3a Method 300 and Figure 3b Unlike method 310, the quantification phase 306 is performed at least partially concurrently with the identification phase 302.

[0297] According to some embodiments, the identification phase 302 and the quantification phase 304 can be executed in parallel.

[0298] According to some embodiments, the identification phase 302 and the quantization phase 304 can be performed alternately, allowing the steps to be mixed. Specifically, measurements of a given color performed during these phases 302 and 306 can be grouped together. For example, when measuring OTF for a colored radiation (green, red, or blue), the LCAF and / or GAF for that radiation can be measured simultaneously and immediately thereafter.

[0299] Of course, other embodiments are also possible.

[0300] Figure 4 This is a schematic diagram of a non-limiting example embodiment of a system for characterizing optical objectives according to the present invention.

[0301] Figure 4 The system 400 can be used to implement the method according to the invention, in particular Figures 3a-3c Any of the methods 300, 310, or 320.

[0302] System 400 includes a first measuring device 402 for measuring OTF using green light. Measuring device 402 may include a green light source illuminating a test pattern having a transparent pattern, such that an optical objective receives the green pattern. Alternatively, measuring device 402 may include a white light source illuminating a test pattern having a green pattern, such that an optical objective receives the green pattern.

[0303] System 400 includes a second measuring device 404 for measuring OTF using red light. Measuring device 404 may include a red light source illuminating a test pattern having a transparent pattern, such that an optical objective receives the red pattern. Alternatively, measuring device 404 may include a white light source illuminating a test pattern having a red pattern, such that an optical objective receives the red pattern.

[0304] System 400 includes a third measuring device 406 for measuring OTF using blue light. Measuring device 406 may include a blue light source that illuminates a test pattern having a transparent pattern, such that an optical objective receives the blue pattern. Alternatively, measuring device 406 may include a white light source that illuminates a test pattern having a blue pattern, such that an optical objective receives the blue pattern.

[0305] It should be noted that OTF can be either MTF or PSF.

[0306] System 400 includes a fourth measuring device 408 for measuring lateral dispersive aberration (LCA).

[0307] The measuring device 408 may include a light source that emits a white light beam that illuminates a test pattern with a transparent pattern, such that each pattern produces a red spot, a green spot, and a blue spot on an image sensor.

[0308] Alternatively, the measuring device 408 may include a light source that emits red, green and blue light in sequence, and a test pattern with a transparent pattern.

[0309] According to another alternative, the measuring device 408 may include a light source that emits white light to sequentially illuminate three test patterns, one including a red pattern, another including a green pattern, and the last including a blue pattern.

[0310] The measuring device 408 may include an image sensor. Alternatively, if the optical objective to be characterized is already assembled with an image sensor, the measuring device 408 may not include a sensor.

[0311] System 400 includes a fifth measuring device 410 for measuring geometric aberrations (GA).

[0312] The measuring device 410 may include a light source that emits a white light beam that illuminates a test pattern with a transparent pattern, such that each pattern produces a red spot, a green spot, and a blue spot on an image sensor.

[0313] Alternatively, the measuring device 410 may include a light source that sequentially emits a red beam, a green beam, and a blue beam, as well as a test pattern with a transparent pattern.

[0314] According to another alternative, the measuring device 410 may include a light source that emits white light to sequentially illuminate three test patterns, one including a red pattern, another including a green pattern, and the last including a blue pattern.

[0315] The measuring device 410 may include an image sensor. Alternatively, if the optical objective to be characterized is already assembled with an image sensor, the measuring device 410 may not include a sensor.

[0316] According to an alternative not shown in the system 400, at least two measuring devices 402-410 can be integrated into a single measuring device.

[0317] According to one example embodiment, measuring devices 402 and 404 can be integrated into a single device.

[0318] According to one example embodiment, measuring devices 406-410 can be integrated into a single device.

[0319] According to one example embodiment, all measuring devices 402-410 can be integrated into a single device.

[0320] The system 400 also includes at least one computing unit 412.

[0321] Calculation unit 412 includes calculation module 414. For a given color, calculation module 414 can be configured / programmed as follows:

[0322] - The measured OTF value is calculated based on the measurements performed.

[0323] - Compare the measured OTF with one or more predetermined threshold OTFs.

[0324] - Calculate LCA for a point (x, y) on the sensor, and calculate LCAF based on measurements taken at multiple points.

[0325] - Calculate LCA for a point (x, y) on the sensor, and calculate LCAF based on measurements taken at multiple points.

[0326] - Calculate at least one LCACF based on LCAF.

[0327] - Angle at the point of incidence of the optical objective (Θ) i ,γ i Calculate GA, calculate GAF based on measurements taken for multiple angles, and / or

[0328] - Calculate at least one GACF based on GAF.

[0329] Alternatively, at least one of these operations can be performed in a computing module integrated into one of the measuring devices 402-410.

[0330] The calculation unit 412 may optionally include a control module 416 of at least one (in particular each) of the measuring devices 402-410 to perform lateral dispersive aberration measurements and / or geometric aberration measurements. Alternatively, each measuring device may include its own control module.

[0331] According to one alternative, the computing unit can be integrated into at least one measuring device. In particular, when all measuring devices 402-410 are integrated into a single measuring device, the computing unit 412 can be integrated into said measuring device.

[0332] At least one of modules 414-416 may be a hardware unit, such as a processor, chip, computer, server, etc. Alternatively, at least one of modules 414-416 may be a software unit, such as a computer application or computer program. Alternatively, at least one of modules 414-416 may be a combination of at least one hardware unit and at least one software unit.

[0333] At least one of modules 414-416 can be independent of the other modules 414-416. Two modules 414-416 can be integrated into the same module.

[0334] Typically, the computing unit 412 can be a hardware unit, such as a processor, chip, computer, server, etc. Alternatively, the computing unit 412 can be a software unit, such as a computer application or computer program. Or, the computing unit 412 can be any combination of at least one hardware unit and at least one software unit.

[0335] Figure 5 This is a schematic diagram of a non-limiting example embodiment of the method for manufacturing an optical objective lens according to the present invention.

[0336] Figure 5 Method 500 can be used to manufacture optical objectives for imaging (i.e., for acquiring images or videos).

[0337] Method 500 includes step 502 of manufacturing an optical objective lens. The manufacture of an optical objective lens is a conventional and well-known method, and therefore will not be described in detail herein.

[0338] Method 500 includes using the method according to the invention (particularly by...) Figures 3a-3c Step 504, characterized by any one of methods 310, 320 or 330, is used to characterize the optical objective lens manufactured in step 502.

[0339] In method 500, each manufactured objective lens can be characterized.

[0340] Alternatively, only some manufactured objectives may be characterized. For example, when manufacturing optical objectives from the same batch, only one (or a few) may be characterized. One or more measured aberration functions and / or one or more determined correction functions may be used for all objectives from the same batch to at least partially correct lateral aberration and / or geometric aberration.

[0341] "A batch of optical objectives" refers to objectives with the same design.

[0342] Alternatively, "a batch of optical objectives" can refer to objectives with the same design and assembled according to the same assembly procedure.

[0343] Figure 6 This is a schematic diagram of a non-limiting example embodiment of an apparatus for manufacturing optical objectives according to the present invention.

[0344] Figure 6 The manufacturing equipment 600 can be used to manufacture optical objectives for imaging (i.e., for acquiring images or videos).

[0345] The equipment 600 includes a production line 602 for one or more optical objectives. Production line 602 is a known, conventional optical objective production line, and therefore will not be described in detail herein.

[0346] Device 600 also includes system 604, which can be Figure 4 System 400 is used to characterize one or each optical objective lens manufactured by production line 602.

[0347] The apparatus 600 is configured to implement the manufacturing method according to the invention, in particular Figure 5 Manufacturing method 500.

[0348] Figure 7 This is a schematic diagram of a non-limiting example embodiment of a camera module according to the present invention.

[0349] Figure 7 The camera module 700 includes, according to the present invention (particularly by means of...) Figures 3a-3c The optical objective 702 is characterized by any of methods 300, 310, and 320 in the figures. The optical objective 702 may be the optical objective OO in Figures 1-6.

[0350] exist Figure 7 In the non-limiting example shown, the optical objective 702 includes four lenses 704-710 stacked in the lens barrel 712 along a stacking direction 714, which also corresponds to the axis 714 of the optical objective 702. This example is provided for illustrative purposes only and is not intended to be limiting.

[0351] The camera module 700 also includes an image sensor 716 associated with the optical objective lens 702. The image sensor 716 can be any type of image sensor, such as a CCD or CMOS sensor.

[0352] Of course, the camera module 700 may include Figure 7Other components not shown, such as mechanisms for modifying the imaging angle or for modifying the focusing or imaging sharpness distance.

[0353] Camera module 700 may optionally include module 718 for digitally processing data captured by image sensor 716. Such digital processing module 718 may be arranged, for example, to correct the image captured by image sensor 716, with a view to, for example, correcting lateral chromatic aberration and / or geometric aberrations. Module 718 may, for example, integrate one or more previously determined aberration correction functions, such as the one or more correction functions determined in steps 206, 210, and 252.

[0354] The processing module 718 can be a standalone module. Alternatively, the processing module 718 can be integrated into another module or another application, such as a photo application for image acquisition.

[0355] Module 718 can be a hardware unit, such as a processor, chip, computer, server, etc. Alternatively, module 718 can be a software unit, such as a computer application or computer program. Alternatively, module 718 can be any combination of at least one hardware unit and at least one software unit. Module 718 can be a standalone module. Alternatively, module 718 can be integrated into an existing module within a device, such as a photo application in a device equipped with camera module 700.

[0356] Figure 8 This is a schematic diagram of a non-limiting example embodiment of a method for acquiring images according to the present invention.

[0357] Method 800 includes step 802 of acquiring an image using an optical objective lens characterized by the present invention, or using a camera module according to the present invention (particularly...) Figure 7 Step 802: The camera module 700 (or the objective lens OO in Figure 1-6) acquires the image.

[0358] Method 800 further includes a step 804 of digitally processing the acquired image. Such digital processing can correct the acquired image to, for example, at least partially correct lateral chromatic aberration and / or geometric aberrations caused by the optical objectives used to acquire the image. Such aberration correction can be performed, for example, using at least one aberration correction function, such as one or more functions provided in any of steps 206, 210, and 252.

[0359] Figure 9a This is a schematic diagram of a non-limiting example embodiment of the device according to the present invention.

[0360] Figure 9a The device 910 includes at least one imaging module according to the invention, particularly Figure 7 The imaging module 700.

[0361] exist Figure 9a In the example shown, device 910 is a smartphone or tablet.

[0362] Optionally, the device 910 may also include a display screen 912 equipped with a touch-sensitive surface 914 (e.g., capacitive).

[0363] The device 910 may also include an imaging application 916, such as a photo application and / or a video application, installed in and executed by the device 910. The application 916 may, for example, be integrated with the processing module 718 of the imaging module 700. Alternatively, the processing module 718 may be independent of the application 916.

[0364] Figure 9b This is a schematic diagram of another non-limiting example embodiment of the device according to the present invention.

[0365] Figure 9b The device 920 includes at least one imaging module according to the invention, particularly Figure 7 The imaging module 700.

[0366] exist Figure 9b In the example shown, device 920 is a virtual reality headset (VR) or an augmented reality headset (AR).

[0367] Optionally, the head-mounted device 920 may also include a display screen 922. Optionally, the head-mounted device 920 may also include a sensor (not shown) for detecting the position of one or both eyes of the user on the display screen 922.

[0368] The head-mounted device 920 may also include an imaging application (not shown), such as a photo application and / or a video application, installed in and executed by the head-mounted device 920. The imaging application may, for example, be integrated with the processing module 718 of the imaging module 700. Alternatively, the processing module 718 may be independent of the imaging application of the head-mounted device 920.

[0369] Figure 9c This is a schematic diagram of another non-limiting example embodiment of the device according to the present invention.

[0370] Figure 9c The device 930 includes at least one imaging module according to the invention, particularly Figure 7 The imaging module 700.

[0371] exist Figure 9c In the example shown, device 930 is a medical imaging device, such as an endoscope, ultrasound equipment, etc.

[0372] Optionally, the medical imaging device 930 may also include a display screen 932.

[0373] Optionally, the medical imaging device 930 may also be equipped with a sensing surface 934 (e.g., capacitive).

[0374] Optionally, the medical imaging device 930 may also include a distal objective lens 936 for collecting light radiation, which may or may not be part of the imaging module 700.

[0375] The imaging device 930 may also include an imaging application (not shown), such as a photo application and / or a video application, installed on and executed by the device 930. The imaging application may, for example, be integrated with the processing module 718 of the imaging module 700. Alternatively, the processing module 718 may be independent of the imaging application of the device 930.

[0376] Figure 10 This is a schematic diagram of a non-limiting example embodiment of a vehicle according to the present invention.

[0377] Figure 10 The vehicle 1000 includes at least one imaging module according to the invention, particularly Figure 7 The imaging module 700, for example, is integrated into the camera 1002.

[0378] In vehicle 1000, camera 1002 may be positioned, for example, behind the windshield, at the top of the windshield, or above the front windshield. Of course, this positioning is given only as a non-limiting example, and camera 1002 may be positioned in other locations.

[0379] exist Figure 10 In the example shown, vehicle 1000 is a land vehicle, particularly an automobile. Vehicle 1000 may also include a display screen 1004 arranged in the passenger compartment of vehicle 1000, the display screen 1004 being equipped with a touch-sensitive surface 1006 (e.g., capacitive).

[0380] The vehicle 1000 may also include an imaging application 1008, such as a photo application and / or a video application. The imaging application 1008 may, for example, integrate with the processing module 718 of the imaging module 700. Alternatively, the processing module 718 may be independent of the imaging application 1008.

[0381] Of course, this invention is not limited to land vehicles. Vehicles according to this invention can be aircraft, such as unmanned aerial vehicles, airplanes, helicopters, etc. Vehicles according to this invention can be water vehicles, such as maritime unmanned aerial vehicles, ships, submarines, etc.

[0382] This invention is not limited to the examples of devices and vehicles given with reference to the accompanying drawings. It can be used in all types of devices and vehicles, including those with camera modules.

[0383] Of course, the present invention is not limited to the examples disclosed above.

Claims

1. A method (300; 310; 320) for characterizing an optical objective (OO), said method (300; 310; 320) comprising an identification phase (100; 150; 302), said identification phase comprising the following steps: - For at least one of the following light sources: green light, blue light, and red light, individually measure the optical transfer function (OTF) of the optical objective (OO) using an image sensor (104, 108, 112); and - For at least one of the light: the measured OTF is compared with at least one predetermined threshold OTF (106, 110, 114) to determine whether the optical quality of the objective lens (OO) is satisfactory; The method (300; 310; 320) further includes a quantization phase (200; 250; 306), which is performed at least when the optical quality of the optical objective (OO) is satisfactory, and the quantization phase includes the following steps: - Measure at least one lateral dispersive aberration function LCAF of the optical objective (OO) using an image sensor (204), and / or - Measure at least one geometric aberration function (GAF) of the optical objective (OO) using an image sensor (208); At least one aberration, particularly each of the aberrations, in the image is corrected, at least partially by digitally processing the image acquired using the optical objective (OO).

2. The method according to the preceding claim (300; 310; 320), characterized in that, The identification phase (100; 150; 302) and quantification phase (200; 250; 306) are performed as follows: - Performed one after another, in particular the identification phases (100; 150; 302) are performed before the quantification phases (200; 250; 306); or - At least some of them will be executed simultaneously.

3. The method according to any one of the preceding claims (300; 310; 320), characterized in that, The method includes a step (304) of retaining or not retaining the optical objective (OO) based on the result of the comparison step.

4. The method according to any one of the preceding claims (100; 150; 302), characterized in that, The optical transfer function is: - Modulation Transfer Function (MTF); or - Point spread function (PSF).

5. The method according to any one of the preceding claims (300; 310; 320), characterized in that, During the identification phase (100; 302), the measurement steps (104, 108, 112) perform OTF measurements individually for at least two of the red, green, and blue light, and in particular, perform OTF measurements individually for each of the red, green, and blue light.

6. The method according to the preceding claim (300; 310; 320), characterized in that, During the identification phase (100; 302), for each light for which an OTF has been measured, the comparison step performs a comparison of the measured OTF with at least one predetermined threshold OTF.

7. The method according to any one of the preceding claims (300; 310; 320), characterized in that, For at least one light, the OTF measurement is performed against a measurement plane corresponding to maximum focus, or against a plane that achieves satisfactory focus.

8. The method according to any one of the preceding claims (300; 310; 320), characterized in that, For at least one light, the measurement steps (104; 108; 112) of the identification phase (100; 150; 302) perform OTF value measurements at multiple points.

9. The method according to any one of the preceding claims (300; 310; 320), characterized in that, For at least one light, a test pattern is used to perform the measurement steps (104; 108; 112) of the identification phase (100; 150; 302), wherein the test pattern comprises one or more patterns and is positioned in front of the optical objective (OO).

10. The method (300; 310; 320) according to any one of the preceding claims, characterized in that, The quantization stage (200; 250; 306) further includes the step (206; 210; 252) of providing at least one correction function: - A lateral chromatic aberration correction function based on the measured lateral chromatic aberration, and / or - Geometric aberration correction function based on the measured geometric aberrations.

11. The method according to the preceding claim (300; 310; 320), characterized in that, The step (206, 210) of providing at least one correction function provides: - A separate correction function for lateral dispersive aberration, and / or - A separate correction function for geometric aberrations.

12. The method according to claim 10 (300; 310; 320), characterized in that, The step (250) of providing at least one correction function provides a common correction function for lateral dispersive aberration and for geometric aberration.

13. The method according to any one of the preceding claims (300; 310; 320), characterized in that, For at least one aberration, prior to the step (204, 208) of measuring the aberration, the method includes a step (102) of identifying a plane corresponding to the maximum or satisfactory focus obtained by the optical objective (OO), and the step (204, 208) of measuring the aberration is performed on the plane.

14. The method (300; 310; 320) according to any one of the preceding claims, characterized in that, For at least one aberration, the step of measuring the aberration is performed using at least one test pattern comprising one or more patterns (204, 208).

15. A system (400) for characterizing an optical objective lens, the system (400) comprising: - At least one measuring device (402-410), and - At least one computing unit (412); The system is configured to implement all the steps of the method (300; 310; 320) according to any one of the preceding claims.

16. A method (500) for manufacturing an optical objective lens, for at least one optical objective lens (OO), the method comprising the steps of: - Manufacturing (502) the optical objective (OO), and - The optical objective (OO) of (504) is characterized by the method (300; 310; 320) according to any one of claims 1 to 14.

17. An apparatus (600) for manufacturing optical objectives, comprising: - Optical objective lens production line (602), and - A system for characterizing optical objectives according to claim 14 (604); 400), used to characterize at least one optical objective (OO) manufactured in the production line (602).

18. A method (800) for acquiring an image of a scene using an optical objective (OO) characterized by any one of the methods (300; 310; 320) according to any one of claims 1 to 14, the method (800) for acquiring the image comprising the following steps: - The image (802) is acquired using the optical objective (OO), and - The image is digitally processed (804) to at least correct the lateral dispersive aberration and / or the geometric aberration.

Images