Method and system for characterizing at least one optical aberration in an optical lens to correct it by digital processing

Abstract

The invention relates to a method (100) for characterizing an optical objective (OO) for imaging, said method (100) comprising: - a step (104) of measuring, with an image sensor, a lateral chromatic aberration function LCAF of said optical objective (OO), and / or - a step (108) of measuring, with an image sensor, a geometrical aberration function GAF of said optical objective (OO); so that, after acquisition of an image with said optical objective (OO), at least one of said aberrations, in particular each of said aberrations, is at least partially corrected in said image by digital processing of said image. The invention also relates to a system implementing such a method. The invention also relates to a method and a facility for manufacturing an optical objective implementing such a characterization method and system. The invention also relates to a method for acquiring an image with an objective characterized by such a characterization method and system.

Description

[0001] This invention relates to a method and system for characterizing at least one optical aberration of an optical objective lens for correction via digital processing. The invention also relates to a system for implementing this method. Furthermore, the invention relates to a method and apparatus for manufacturing optical objectives using this characterization method and system. Finally, the invention relates to a method for acquiring images using an objective lens characterized by this characterization method and system.

[0002] The field of this invention is generally used to characterize optical objectives, especially optical objectives for imaging, to correct at least one optical aberration. Background Technology

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

[0004] Currently, the quality of optical objectives is tested by measuring the modulation transfer function (MTF), which depends on all the optical aberrations of the objective.

[0005] However, MTF cannot provide optical aberration values. Therefore, it is difficult, and sometimes even impossible, to correct one or more optical aberrations introduced into an image by digitally processing the image taken with an optical objective.

[0006] One object of the present invention is to overcome at least one of the above-mentioned disadvantages.

[0007] Another object of the present invention is to provide a solution for characterizing optical objectives, enabling the determination of at least one optical aberration that can be corrected by digital processing.

[0008] Another object of the present invention is to provide a solution for characterizing optical objectives, which makes it easier to correct at least one optical aberration through digital processing.

[0009] Another object of the present invention is to provide a solution for characterizing optical objectives, enabling the improvement of image quality using said optical objectives through digital processing. Summary of the Invention

[0010] This invention proposes a method for characterizing an optical objective lens used for imaging to achieve at least one of the above objectives, the method comprising:

[0011] - The step of measuring at least one lateral dispersive aberration function of the optical objective using an image sensor, and / or

[0012] - The step of measuring at least one geometric aberration function of the optical objective using an image sensor;

[0013] At least one aberration, and in particular each of the aberrations, in the image is corrected at least partially by digitally processing the image acquired using the optical objective.

[0014] Therefore, this invention proposes to measure the lateral dispersive aberration and / or geometric aberration of the optical objective lens separately in order to understand these aberrations independently, i.e., without mixing them with other aberrations. Once each of these aberrations is understood individually, they can be corrected by digitally processing the images acquired with the optical objective lens. Similarly, when manufacturing the optical objective lens, a correction function can be derived for each of these aberrations, enabling the correction of said aberrations. This or these correction functions can be used to correct these aberrations in each image taken with the optical objective lens by digitally processing the images.

[0015] In fact, the inventors have noticed that some optical aberrations, known as displacement aberrations or "displacement aberrations" in the following text, can be corrected very effectively through digital image processing. Correcting these aberrations makes it possible to improve the quality of images acquired with optical objectives.

[0016] Optical aberration refers to the concept that a point in a scene becomes a spot of light, either wide or narrow, at the location where the image is formed (usually flat). Aberrations cause various types of effects: some aberration effects are characterized by a displacement of the average position of the spot produced at a point in the scene relative to the ideal location where the spot would occur. These are called displacement aberrations. Other effects are that the spot has a spatially expanded energy distribution along the image trajectory, rather than being point-like. These are called diffusion aberrations.

[0017] Aberrations caused by optical objectives are usually called dispersive aberrations, geometric aberrations, and third-order aberrations.

[0018] "Third-order aberrations" refer to all optical aberrations introduced into an image acquired by an optical objective, excluding dispersive and geometric aberrations. These third-order (and higher) aberrations include, for example, spherical aberration, coma, astigmatism, field curvature, and distortion (of spot shape and energy distribution). These third-order (and higher) aberrations are diffusion-type. In the following text, for the sake of brevity, "third-order aberrations" will refer to third-order aberrations and higher.

[0019] Chromatic aberration arises from the decomposition of light into multiple color bands, referring to optical aberrations that occur at different locations in the focal space depending on the wavelength. In the case of lateral chromatic aberration, it is caused by the wavelength-dependent shift of the focal point in the image trajectory. The result is an image with iridescent edges or colored stripes around objects of uniform color (such as, for example, white). In the case of axial chromatic aberration, it is caused by the focal point moving away 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 are blurred. As long as lateral chromatic aberration can be quantified, i.e. measured, during the optical objective design / manufacturing process, it can be corrected by digitally processing the image captured by the optical objective. It belongs to the category of displacement aberrations. On the other hand, axial chromatic aberration belongs to the category of diffusion aberrations because, for example, if green is focused on the image plane sensor, red may be focused upstream of the plane sensor and broaden when the red beam reaches the sensor located outside the focal point.

[0020] "Geometric aberration" refers to the deviation between paraxial rays as defined in the Gaussian approximation and the corresponding actual rays. Geometric aberration can also be characterized by the deviation between the paraxial wavefront and the actual wavefront. For example, geometric aberration can distort the shape of the resulting image. For instance, a square might become shaped like a barrel (corners concave) or a pincushion (corners convex). Similarly, the straight, vertical edges of a building might become curved and not perpendicular. As long as this aberration is quantified—that is, measured—during the optical objective design / manufacturing process, it can be corrected by digitally processing the captured image. Geometric aberration is a type of displacement aberration.

[0021] "Displacement aberration" or "displacement aberration" refers to lateral dispersive aberration and geometric aberration.

[0022] "Diffusion aberration" or "diffusion aberration" refers to axial dispersive aberration and third-order aberration.

[0023] The measured LCAF can take any form.

[0024] According to some embodiments, LCAF can take the form of a range that includes at least one displacement vector for each of a plurality of locations (x, y) of the image sensor. According to one example embodiment, for at least one location (x, y), the range may include:

[0025] - For the displacement vector relative to the reference position measured in red,

[0026] - The displacement vector relative to the reference position for the green measurement, and

[0027] - The displacement vector relative to the reference position measured in blue.

[0028] The reference position can be any previously selected location. For example, the reference position could be the center of gravity of the three colors.

[0029] According to one example embodiment, the location of one of the three colors can be selected as a reference location. 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, the location of green can be selected as the reference location: in this case, for at least one location (x, y), the value range can include displacement vectors for red and displacement vectors for blue.

[0030] 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.

[0031] LCAF can be measured in a variety of ways.

[0032] According to an example embodiment, a test pattern consisting of patterns (such as dots, lines, etc.) can be positioned in front of an optical objective, on 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. The detected positions of the three color spots are then used to calculate a displacement vector relative to a reference position, which can be the position of one of the three spots or another position.

[0033] LCAF can then be determined by simultaneously or sequentially measuring multiple positions (x, y) in the sensor plane (also known as the image plane).

[0034] According to some embodiments, LCAF can be measured for the positions of all image sensors. Alternatively, LCAF can be measured for the positions of only some image sensors.

[0035] The measured GAF ​​can take any form.

[0036] According to some embodiments, GAF can take the form of a range that includes multiple angles (θ) relative to the optical objective axis. i At least one displacement distance (θi) of γi i γi is the angle relative to the optical objective axis, and γi is the rotation angle about the optical axis. According to an example embodiment, for at least one angle (θ... i The range can include: ,γi),

[0037] - For red, the displacement distance relative to the center of the image sensor.

[0038] - The displacement distance relative to the center of the image sensor for green measurement, and

[0039] - The displacement distance relative to the center of the image sensor, measured for blue.

[0040] According to the example embodiment, for at least one angle (θ) i The range of values ​​can include a single displacement distance obtained from the displacement distances of the three colors, such as the average value of the displacement distances.

[0041] Alternatively, the geometric aberration function GAF can be a mathematical function that takes the angle (θ) as an example. i ,γi) as input, and provide a single displacement distance for all three colors, or provide a displacement distance individually for each color.

[0042] GAF can be measured in a variety of ways.

[0043] According to an example embodiment, a test pattern consisting of a pattern (such as dots, lines, etc.) can be positioned in front of the optical objective lens, 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 axis of the optical objective lens. i The pattern (γi) generates spots 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 be based on the angle θ of the light beam entering the optical objective relative to the axis of the optical objective. i Obtain the angle measurement.

[0044] By targeting multiple angles θ relative to the optical axis of the optical objective. i GAF can be determined by measuring simultaneously or sequentially.

[0045] According to some embodiments, GAF can be measured for the positions of all image sensors. Alternatively, GAF can be measured for the positions of only some image sensors.

[0046] According to some embodiments, the method according to the invention may include the step of providing at least one lateral dispersion correction function (LCACF) based on measured lateral dispersion aberration.

[0047] According to some embodiments, the LCACF can take the form of a range for each of a plurality of locations (x, y) of the image sensor, including at least one displacement vector to be applied to correct lateral astigmatism at that location. For at least one location (x, y) of the sensor, the LCACF may include:

[0048] - For each of the red, green, and blue colors, a single displacement vector; or

[0049] - For at least one color, a displacement vector specifically for that color.

[0050] Alternatively, LCACF can be a mathematical function that takes the position (x,y) of the image sensor as input and provides one or more displacement vectors to be applied to correct aberrations at position (x,y).

[0051] According to another alternative, LCACF can take the form of a mapping table that indicates the correction position for each of the multiple pixels in the image sensor, and is performed separately for each color:

[0052] - For each color, or

[0053] - When green is used as a reference, it is applied to red and blue.

[0054] According to some embodiments, the method according to the invention may include the step of providing at least one geometric aberration correction function (GACF) based on measured geometric optical aberrations.

[0055] According to some embodiments, GACF can take the form of a range that spans multiple angles (θ). i Each of , γi) includes: at least one distance vector to be applied to correct geometric aberrations. For at least one angle (θ) i ,γi), GACF can include:

[0056] - A single distance correction value to apply for each of red, green, and blue; or

[0057] - For at least one color, a distance correction value specifically for that color.

[0058] Alternatively, GACF can be a mathematical function that represents the angle (θ) relative to the axis of the optical objective. i ,γi) is taken as input, and one or more distance correction values ​​are provided.

[0059] According to another alternative, GACF can take the form of a mapping table that indicates the correction position of each of the multiple pixels on the image sensor, and is performed separately for each color.

[0060] According to some embodiments, the step of providing at least one correction function may include:

[0061] - A separate correction function for lateral dispersive aberration, and / or

[0062] - A separate correction function for geometric aberrations.

[0063] Therefore, these aberrations can be corrected individually in any desired order. For example, it might be useful to correct lateral dispersive aberrations first, then geometric aberrations, and vice versa.

[0064] According to some embodiments, the step of providing at least one correction function can provide a general correction function for lateral dispersive aberration and / or geometric aberration.

[0065] In this scenario, applying this single correction function will enable the simultaneous correction of both lateral chromatic aberration (CLA) and geometric aberration (GA). A universal correction function allows correction to be performed on all colors without distinguishing between chromatic and geometric aberrations.

[0066] Furthermore, this universal correction function allows for better correction and avoidance of overcorrection. In fact, according to one 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 might ultimately lead to overcorrection, which is undesirable. This can be avoided by using the universal correction function.

[0067] According to some non-limiting embodiments, at least one, and especially each, of the correction functions may be, or may take the form of a range or mapping table, which indicates the corrected position of said component in an image acquired with an optical objective for at least one color component (red, green, blue) of at least one pixel of an image sensor.

[0068] According to some embodiments, the method according to the invention may include the step of identifying a plane (referred to as a measurement plane) corresponding to the maximum or satisfactory focus obtained by the optical objective, and performing at least one aberration measurement on the measurement plane.

[0069] This measuring plane is preferably perpendicular to the axis of the optical objective.

[0070] The same measurement plane can be used to measure both lateral dispersive aberration functions and geometric aberration functions. Different measurement planes can be used to measure both lateral dispersive aberration functions and geometric aberration functions.

[0071] There are several methods for identifying the measurement plane. For example, a test pattern can be placed in front of an optical objective. The relative position of the test pattern with respect to the lens can be modified along the axis of the optical objective, and the focus value can be monitored to identify the measurement plane.

[0072] Alternatively, the measurement plane can be identified as follows: The 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.

[0073] Of course, other embodiments are possible, and these non-limiting examples are for illustrative purposes only.

[0074] As described 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.

[0075] According to another aspect of the invention, a system for characterizing optical objectives used for imaging is proposed, the system comprising at least one measuring device configured to measure using an image sensor:

[0076] - The lateral dispersive aberration function LCAF of the optical objective, and / or

[0077] - The geometric aberration function (GAF) of the optical objective lens;

[0078] After acquiring an image using the optical objective, the image is digitally processed to correct at least one, and in particular each, of the aberrations in the acquired image.

[0079] The system according to the invention may include, in terms of hardware and / or configuration, any combination of features disclosed in the characterization method according to the invention above, which are not mentioned herein for the sake of brevity.

[0080] According to some embodiments, the system according to the invention may include a single measuring device for measuring the lateral dispersive aberration function and for measuring geometric aberrations.

[0081] According to some embodiments, the system may include a first measuring device for measuring a lateral dispersive aberration function and a second measuring device for measuring a geometric aberration function.

[0082] At least one measuring device may include a light source associated with at least one test pattern, or a grid or other device that uses the pattern to illuminate an optical objective.

[0083] The light source may emit red and / or green and / or blue light. Alternatively, the light source may emit white light.

[0084] At least one test pattern may include a transparent pattern.

[0085] At least one pattern may include a pattern of the same given color selected from red, green and blue.

[0086] At least one measuring device may include a calculation module for determining a point (x,y) and / or an angle θ based on the performed measurement. i Aberrations at the location.

[0087] The system according to the invention may further include a processing unit configured or programmed to determine at least one of the following correction functions:

[0088] - Lateral chromatic aberration correction function based on measured lateral chromatic aberration, and / or

[0089] - Geometric aberration correction function based on measurement geometric aberrations.

[0090] Optionally, the processing unit may be further configured or programmed to determine:

[0091] - The lateral dispersive aberration function measured based on measurements taken at different points, and / or

[0092] - Based on the geometric aberration function of measurements taken at different points.

[0093] According to another aspect of the present invention, a method for manufacturing an optical objective lens is provided, for at least one optical objective lens, the method comprising the following steps:

[0094] - Manufacturing the optical objective lens,

[0095] - The optical objective lens is characterized by the method according to the invention.

[0096] According to some embodiments, each manufactured optical objective can be characterized.

[0097] Alternatively, only certain manufactured optical objectives can be characterized. For example, within the same batch of optical objectives, only one or a few can be characterized. One or more measured aberration functions and / or one or more determined correction functions can be used for all objectives in the same batch to correct for lateral dispersive aberration and / or geometric aberration.

[0098] A batch of optical objectives can correspond to objectives with the same design.

[0099] Alternatively, a batch of optical objectives can correspond to objectives with the same design and assembled according to the same assembly formula.

[0100] According to another aspect of the present invention, an apparatus for manufacturing optical objectives is provided, comprising:

[0101] - Optical objective lens production line, and

[0102] - A system for characterizing optical objectives according to the present invention.

[0103] The facility according to the invention may include, in terms of hardware and / or configuration, any combination of features disclosed in reference to the method according to the invention above, which are not mentioned herein for the sake of brevity.

[0104] According to another aspect of the present invention, a method for acquiring scene images using an optical objective lens characterized by the method according to the present invention is proposed, the method comprising the following steps:

[0105] - Acquire images using the optical objective lens, and

[0106] - The image is digitally processed to at least partially correct lateral dispersive aberration and / or geometric aberration.

[0107] In some embodiments, the optical objective lens can be used for 2D or 3D imaging.

[0108] According to some embodiments, optical objectives 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.

[0109] According to another aspect of the present invention, a camera module is provided, comprising:

[0110] - An optical objective lens characterized by the characterization method according to the invention; and

[0111] - An image sensor associated with an optical objective.

[0112] The image sensor can be any type of image sensor associated with an optical objective, such as a CMOS or CCD image sensor, but is not limited to these image sensors.

[0113] According to another aspect of the invention, a user device is also proposed, which includes at least one optical objective lens characterized by the method according to the invention.

[0114] In particular, the user equipment according to the present invention may include at least one camera module according to the present invention.

[0115] Specifically, the user device can be a user device such as a smartphone or tablet.

[0116] User equipment may optionally include a display screen, especially a touch screen.

[0117] Specifically, the user device can be a virtual reality headset or an augmented reality headset designed to be worn by a user.

[0118] Head-mounted devices may optionally include displays, especially touchscreens.

[0119] In particular, the user equipment can be a user device such as a camera or camcorder.

[0120] Camera-type user equipment may optionally include a display screen, especially a touch screen.

[0121] In particular, the user equipment can be a computer-type user equipment.

[0122] Computer-type user equipment may optionally include a display screen, especially a touch screen.

[0123] Computer-type user equipment may optionally include a keyboard, or any other equipment integrated into or associated with the device.

[0124] Specifically, the user device can be a television.

[0125] Televisions may optionally include a display screen, especially a touch screen.

[0126] In particular, the user equipment can be a medical imaging device.

[0127] Medical imaging equipment can be, for example, endoscopes, ultrasound equipment, etc.

[0128] Of course, the user equipment according to the present invention is not limited to the examples disclosed above.

[0129] 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.

[0130] In particular, the vehicle according to the invention may include at least one camera module according to the invention.

[0131] According to some embodiments, the vehicle can be a land vehicle, such as a car, for example a car with non-autonomous, semi-autonomous or autonomous driving capabilities.

[0132] According to some embodiments, the vehicle can be an aircraft, such as a drone, airplane, or helicopter, for example, a drone, airplane, or helicopter with non-autonomous, semi-autonomous, or autonomous driving capabilities.

[0133] According to some embodiments, the vehicle can be a water vehicle, such as a boat or submarine, for example a boat or submarine with non-autonomous, semi-autonomous or autonomous driving. Description of the Drawings and Detailed Description of the Embodiments

[0134] Other advantages and features will become apparent from the detailed description of the non-limiting embodiments and the accompanying drawings, in which:

[0135] - Figure 1 This is a schematic diagram of a non-limiting example embodiment of the method according to the present invention;

[0136] - Figure 2 This is a schematic diagram of another non-limiting example embodiment of the method according to the present invention;

[0137] - Figure 3 This is a schematic diagram of a non-limiting example embodiment of the system according to the present invention;

[0138] - Figure 4 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;

[0139] - Figure 5 This is a schematic diagram of a non-limiting example embodiment of a facility for manufacturing one or more optical objectives according to the present invention; Figure 6 This is a schematic diagram of a non-limiting example embodiment of a camera module according to the present invention;

[0140] - Figure 7 This is a schematic diagram of a non-limiting example embodiment of the method for acquiring images according to the present invention;

[0141] - Figures 8a-8c These are schematic diagrams of non-limiting exemplary embodiments of the device according to the present invention; and

[0142] - Figure 9 This is a schematic diagram of a non-limiting example embodiment of a vehicle according to the present invention.

[0143] It is clearly understood that the embodiments described below are by no means limiting. In particular, variations of the invention are conceivable that include only selections of the features disclosed below, independent of the other disclosed features, if such selection is sufficient to impart a beneficial technical effect or distinguish the invention from the prior art. Such selections include at least one preferably functional feature that has no structural details, or only a portion thereof, if that portion alone is sufficient to impart a beneficial technical effect or distinguish the invention from the prior art.

[0144] In particular, all the described variations and embodiments can be combined with each other if there are no technical obstacles to such combinations.

[0145] In the following description of the accompanying drawings and specification, the same reference numerals are used for features common to multiple drawings.

[0146] Figure 1 This is a schematic diagram of a non-limiting example embodiment of the method according to the present invention.

[0147] Figure 1 Method 100 can be used to characterize an optical objective OO for imaging, i.e., for acquiring images or videos (image streams) using an image sensor. The objective OO is associated with the image sensor within an imaging module or camera module and can be integrated into various devices. Non-limiting examples of imaging modules are given below.

[0148] An optical objective lens typically consists of several optical features, such as lenses and spacers. These features are stacked in the lens barrel along a stacking direction that corresponds to the axis of the optical objective lens.

[0149] Figure 1 Method 100 includes step 102: identifying a measurement plane for aberration measurement, the measurement plane being perpendicular to the optical axis of the optical objective OO.

[0150] For this purpose, for example, a test pattern can be arranged in front of the optical objective lens OO. The relative position of the test pattern with respect to the optical objective lens OO can be modified along the axis of the optical objective lens OO, and the focus value can be monitored to identify the measurement plane that provides the maximum focus or a satisfactory focus value relative to a predetermined focus threshold.

[0151] Method 100 then includes step 104: measuring the lateral dispersive aberration function LCAF of the optical objective.

[0152] LCAF can be measured in a variety of ways.

[0153] In one example, a test pattern consisting of a pattern (such as 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. The pattern corresponding to the position (x, y) on the image sensor generates spots 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 positions of the three detected spots are then used to calculate a displacement vector relative to a reference position, which can be the position of one of the three spots or another position.

[0154] LCAF can then be determined by simultaneously or sequentially measuring multiple points (x, y) in the sensor plane (also known as the image plane).

[0155] As mentioned earlier, the measured LCAF can take any form. In the disclosed examples, LCAF can take the form of a range of values ​​that includes each of multiple points (x, y) on the image sensor:

[0156] - The displacement vector of the red spot, measured from the position of the green spot.

[0157] - The displacement vector of the blue spot's position, measured from the position of the green spot.

[0158] Therefore, step 104 provides LCAF indicating the chromatic aberration measured at several locations (x, y) on the sensor, i.e., provides LCAF indicating the chromatic aberration measured at several pixels of the sensor.

[0159] Method 100 then includes step 106: calculating the lateral dispersive aberration correction function LCACF based on LCAF.

[0160] LCACF can be determined in different ways.

[0161] In the disclosed examples, the LCACF can take the form of a range that, for each of a plurality of locations (x, y) on the image sensor, includes at least one displacement vector to be applied to correct lateral aberration at said point. For at least one location (x, y), the LCACF may include:

[0162] - When using green as a reference, for the red displacement vector, and

[0163] - The displacement vector relative to the blue vector when using green as a reference.

[0164] Alternatively, LCACF can take the form of a mapping table that indicates the correction position for each of a plurality of pixels in the image sensor, and is performed individually for the following cases:

[0165] - Each color, or

[0166] - When green is used as a reference, it is applied to red and blue.

[0167] Method 100 then includes step 108: measuring the geometric aberration function (GAF) of the optical objective.

[0168] GAF can be measured in a variety of ways.

[0169] exist Figure 1In the example shown, a test pattern consisting of a pattern (such as 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 A pattern of (γi) is generated on the image sensor to produce spots 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 be based on the angle (θ) of the light beam entering the optical objective relative to the axis of the optical objective. i ,γi) amount obtained.

[0170] By targeting multiple angles (θ) relative to the optical axis of the optical objective. i GAF can be determined by measuring γi simultaneously or sequentially.

[0171] As mentioned earlier, the measured GAF ​​can take any form. In the published example, the GAF takes the form of a range of values ​​that spans multiple angles (θ) relative to the axis of the optical objective. i ,γi) includes:

[0172] - For the red measurement, the displacement distance relative to the center of the sensor,

[0173] - The displacement distance relative to the center of the sensor for green measurement, and

[0174] - The displacement distance relative to the center of the sensor measured for blue.

[0175] Method 100 then includes step 106: calculating the geometric aberration correction function GACF based on GAF.

[0176] GACF can be determined in different ways.

[0177] In the publicly available examples, GACF can take the form of a range that spans multiple angles θ. i Each of them includes:

[0178] - To apply the distance correction value to the red area.

[0179] - The distance correction value to be applied to green, and

[0180] - To apply the distance correction value to the blue area.

[0181] Alternatively, GACF can take the form of a range that spans multiple angles θ. iEach of these includes: a single distance correction value to be applied to each of the red, green, and blue.

[0182] Alternatively, GACF can take the form of a mapping table that indicates the correction position for each of the multiple pixels in the image sensor, and is performed separately for each color.

[0183] In optional step 112, at least one aberration function measured in steps 104 and 108 and / or at least one aberration correction function determined in steps 106 and 110 can be stored for subsequent use of the functions. In particular, at least one of these functions can be used to correct the image acquired using the optical objective lens OO by digitally processing the image.

[0184] Figure 2 This is a schematic diagram of another non-limiting example embodiment of the method according to the present invention.

[0185] Figure 2 Method 200 includes step 102 of identifying the measurement plane, followed by step 108 of measuring LCAF and step 108 of measuring GAF.

[0186] and Figure 1 There are 100 different methods. Figure 2 Method 200 does not include steps 106 and 110. These optional steps are replaced by optional step 202, which determines a single aberration correction function ACF based on the measured LCAF and the measured GACF to correct for both:

[0187] - Lateral chromatic aberration, and

[0188] - Geometric aberrations.

[0189] In optional step 204, the individual aberration correction function determined in step 202 can be stored for later use. Specifically, this function can be used to correct an image acquired using the optical objective OO by digitally processing the image.

[0190] Figure 3 This is a schematic diagram of a non-limiting example embodiment of a system for characterizing optical objectives according to the present invention.

[0191] Figure 3 The system 300 can be used to implement the method according to the invention, especially to implement any one of method 100 or 200.

[0192] System 300 includes a first measuring device 302 for measuring lateral dispersive aberration (LCA).

[0193] The measuring device 302 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.

[0194] Alternatively, the measuring device 302 may include a light source that emits red, green and blue light in sequence, and a test pattern with a transparent pattern.

[0195] According to another alternative, the measuring device 302 may include a light source that emits white light, which sequentially illuminates three test patterns, one of which includes a red pattern, another includes a green pattern, and the last includes a blue pattern.

[0196] The measuring device 302 may include an image sensor. Alternatively, if the optical objective to be characterized is already assembled with the image sensor, the measuring device 302 may not include the sensor.

[0197] System 300 includes a second measuring device 304 for measuring geometric aberrations GA.

[0198] The measuring device 304 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.

[0199] Alternatively, the measuring device 304 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.

[0200] According to another alternative, the measuring device 304 may include a light source that emits white light, which sequentially illuminates three test patterns, one of which includes a red pattern, another includes a green pattern, and the last includes a blue pattern.

[0201] The measuring device 304 may include an image sensor. Alternatively, if the optical objective to be characterized is already assembled with an image sensor, the measuring device 304 may not include a sensor.

[0202] The system 300 also includes a computing unit 308.

[0203] The computing unit 308 includes a computing module 310. The computing module 310 can be configured or programmed to determine:

[0204] - LCA for a point (x,y) of the sensor, and LCAF based on measurements performed for multiple points, and / or

[0205] - Angle θ at the entrance of the optical objective lens iThe GA, and the GAF based on measurements performed for multiple angles.

[0206] The calculation module 310 can be optionally configured or programmed to perform calculations:

[0207] - The transverse chromatic aberration correction function LCACF obtained from the measured transverse chromatic aberration function; and / or

[0208] - The geometric aberration correction function (GACF) is obtained based on the measured geometric aberration function.

[0209] The calculation unit 308 may optionally include a control module 312 for controlling at least one of the measuring devices 302-304, and in particular each of the measuring devices 302-304, to perform lateral dispersive aberration measurements and / or geometric aberration measurements. Alternatively, each measuring device may include its own control module.

[0210] At least one of modules 310-312 may be a hardware unit, such as a processor, chip, computer, server, etc. Alternatively, at least one of modules 310-312 may be a software unit, such as a computer application or program. Alternatively, at least one of modules 310-312 may be a combination of at least one hardware unit and at least one software unit.

[0211] At least one of modules 310-312 can be independent of the other modules 310-312. Two modules 310-312 can be integrated into the same module.

[0212] According to an alternative (not shown) to the characterization system, the two measuring devices 302-304 can be integrated into a single measuring device.

[0213] Figure 4 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.

[0214] Figure 4 Method 400 can be used to manufacture optical objectives for imaging, i.e., optical objectives for acquiring images or videos.

[0215] Method 400 includes step 402 of manufacturing an optical objective lens. The manufacturing of optical objectives lenses is a conventional and well-known method, and therefore will not be described in detail herein.

[0216] Method 400 includes step 404, which characterizes an optical objective lens manufactured in step 402 by means of the method according to the invention, particularly by method 100 or method 200.

[0217] In method 400, each manufactured objective lens can be characterized.

[0218] Alternatively, only certain manufactured objectives may be characterized. For example, when manufacturing optical objectives in the same batch, only one (or a few) of the objectives may be characterized. One or more aberration functions measured and / or one or more correction functions determined may be used for all objectives in the same batch to at least partially correct lateral dispersive aberration and / or geometric aberration.

[0219] In this disclosure, "a batch of optical objectives" can refer to objectives having the same design. Alternatively, "a batch of optical objectives" can refer to objectives having the same design and assembled according to the same assembly procedure.

[0220] Figure 5 This is a schematic diagram of a non-limiting example embodiment of a facility for manufacturing optical objectives according to the present invention.

[0221] Figure 5 The manufacturing facility 500 can be used to manufacture optical objectives for imaging, that is, optical objectives for acquiring images or videos.

[0222] Facility 500 includes optical objective lens production line 502. Production line 502 is a known conventional optical objective lens production line, and therefore will not be described in detail herein.

[0223] Facility 500 also includes system 504, which can be Figure 3 System 300 is used to characterize one or each optical objective lens manufactured by production line 502.

[0224] Figure 6 This is a schematic diagram of a non-limiting example embodiment of a camera module.

[0225] Figure 6 The camera module 600 includes an optical objective 602 as characterized according to the present invention, particularly by means of... Figure 1 Method 100 or Figure 2 The optical objective 602 is characterized by method 200. The optical objective 602 can be... Figure 1-5 The optical objective lens OO shown is shown.

[0226] exist Figure 6 In the non-limiting example shown, the optical objective 602 includes four lenses 604-610 that are stacked in the lens barrel 612 along a stacking direction 614, which also corresponds to the axis 614 of the optical objective 602.

[0227] The camera module 600 also includes an image sensor 616 associated with the optical objective lens 602. The image sensor 616 can be any type of image sensor, such as a CCD or CMOS sensor.

[0228] Of course, camera module 600 may include modules not included in... Figure 4 Other components shown include mechanisms for modifying the imaging angle or for modifying the imaging sharpness distance.

[0229] Camera module 600 may optionally include module 618 for digitally processing data captured by image sensor 616. Such digital processing module 618 may be arranged, for example, to correct the image captured by image sensor 616, with a view to, for example, correcting lateral chromatic aberration and / or geometric aberrations. Module 618 may, for example, integrate one or more previously determined aberration correction functions, such as the one or more correction functions determined in steps 106, 110, or 202.

[0230] The processing module 618 can be a standalone module. Alternatively, the processing module 618 can be integrated into another module or another application, such as a photo application for image acquisition.

[0231] Module 618 may be a hardware unit, such as a processor, chip, computer, server, etc. Alternatively, module 618 may be a software unit, such as a computer application or program. Alternatively, module 618 may be any combination of at least one hardware unit and at least one software unit. Module 618 may be a standalone module. Alternatively, module 618 may be integrated into an existing module within a device, such as a photo application, for example, in a device equipped with camera module 600.

[0232] Figure 7 This is a schematic diagram of a non-limiting example embodiment of the method for acquiring images according to the present invention.

[0233] Method 700 includes step 702, which utilizes an optical objective lens characterized by the present invention or a camera module according to the present invention, particularly utilizing... Figure 6 The camera module 600 is used to acquire images.

[0234] Method 700 further includes a step 704, which digitally processes the acquired image. This digital processing may 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. This aberration correction may be performed, for example, using at least one aberration correction function, such as one or more aberration correction functions provided in any of steps 106, 110 of method 100 or step 202 of method 200.

[0235] Figure 8a This is a schematic diagram of a non-limiting example embodiment of the device according to the present invention.

[0236] Figure 8a The device 810 includes at least one imaging module according to the invention, particularly including Figure 6 The imaging module 600.

[0237] exist Figure 8a In the example shown, device 810 is a smartphone or tablet.

[0238] Optionally, the device 810 may also include a display screen 812 equipped with a touch-sensitive surface 814, such as a display screen 812 equipped with a capacitive touch-sensitive surface.

[0239] Imaging device 810 may also include imaging application 816, such as photo application and / or video application installed on and executed by device 810. Application 816 may, for example, integrate processing module 618 of the imaging module. Alternatively, processing module 618 may be independent of application 816.

[0240] Figure 8b This is a schematic diagram of another non-limiting example embodiment of the device according to the present invention.

[0241] Figure 8b The device 820 includes at least one imaging module according to the invention, particularly including Figure 6 The imaging module 600.

[0242] exist Figure 8b In the example shown, device 820 is a virtual reality headset (VR) or an augmented reality headset (VA).

[0243] Optionally, the head-mounted device 820 may also include a display screen 822. Optionally, the head-mounted device 820 may also include a sensor (not shown) for detecting the position of one or both of the user's eyes on the display screen 822.

[0244] The head-mounted device 820 may also include imaging applications (not shown), such as photo and / or video applications mounted on the device and executed by the device 820. The imaging application may, for example, be integrated into the processing module 618 of the imaging module. Alternatively, the processing module 618 may be independent of the imaging application of the head-mounted device 820.

[0245] Figure 8c This is a schematic diagram of another non-limiting example embodiment of the device according to the present invention.

[0246] Figure 8c The device 830 includes at least one imaging module according to the invention, particularly including Figure 6 The imaging module 600.

[0247] exist Figure 8cIn the example shown, device 830 is a medical imaging device, such as an endoscope or ultrasound device.

[0248] Optionally, the medical imaging device 830 may also include a display screen 832.

[0249] Optionally, the medical imaging device 830 may also be equipped with a sensing surface 834, such as a capacitive sensing surface.

[0250] Optionally, the medical imaging device 830 may also include a distal objective lens 836 for collecting light, which may or may not be part of the imaging module 600.

[0251] Imaging device 830 may also include imaging applications (not shown), such as photo applications and / or video applications installed on and executed by device 830. The imaging application may, for example, be integrated with processing module 618 of the imaging module. Alternatively, processing module 618 may be independent of the imaging application of device 830.

[0252] Figure 9 This is a schematic diagram of a non-limiting example embodiment of a vehicle according to the present invention.

[0253] Figure 9 The vehicle 900 includes at least one imaging module according to the invention, particularly including Figure 6 The imaging module 600 may include, for example, an imaging module integrated into the camera 902.

[0254] In vehicle 900, camera module 902 may be positioned, for example, behind the windshield of vehicle 900, at the top of the windshield, or above the front windshield of vehicle 900. Of course, this position is given as a non-limiting example, and camera 902 may be positioned elsewhere.

[0255] exist Figure 9 In the example shown, vehicle 900 is a land vehicle, particularly an automobile. Vehicle 900 may also include a display screen 904 equipped with a touch-sensitive surface 906, such as a display screen 904 equipped with a capacitive touch-sensitive surface 906, which is arranged in the passenger compartment of vehicle 900.

[0256] The vehicle 900 may also include an imaging application 908, such as a photo application and / or a video application. The imaging application 906 may, for example, integrate with the processing module 618 of the imaging module. Alternatively, the processing module 618 may be independent of the imaging application 908.

[0257] Of course, this invention is not limited to land vehicles. Vehicles according to this invention can be aircraft, such as unmanned aerial vehicles (UAVs), airplanes, helicopters, etc. Vehicles according to this invention can be water vehicles, such as seaplanes, boats, submarines, etc.

[0258] This invention is not limited to the examples of devices and vehicles given with reference to the accompanying drawings. This invention can be used with all types of devices and vehicles.

[0259] Of course, the present invention is not limited to the examples disclosed above.

Claims

1. A method (100; 200) for characterizing an optical objective (OO) for imaging, said method (100; 200) comprising: - Step (104) of measuring at least one lateral dispersive aberration function (LCAF) of the optical objective (OO) using an image sensor, and / or - Step (108) of measuring at least one geometric aberration function (GAF) of the optical objective using an image sensor; 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 (100; 200) according to the preceding claim, characterized in that, It also includes the step of providing at least one of the following correction functions (106, 110; 202): - Lateral chromatic aberration correction function based on measured lateral chromatic aberration, and / or - Geometric aberration correction function based on measurement geometric aberrations.

3. The method (100) according to the preceding claim, characterized in that, The steps (106, 110) of providing at least one correction function are provided as follows: - A separate correction function for lateral dispersive aberration, and / or - A separate correction function for geometric aberrations.

4. The method (200) according to claim 2, characterized in that, Step (202) of providing at least one correction function provides a general correction function for lateral dispersive aberration and geometric aberration.

5. The method (100; 200) according to any one of claims 2 to 4, characterized in that, At least one correction function is a mapping table or at least one correction function includes a mapping table that indicates the corrected position of at least one color component of at least one pixel of an image sensor in an image acquired using an optical objective.

6. The method (100; 200) according to any one of the preceding claims, characterized in that, For at least one aberration, prior to the step (104, 108) of measuring the aberration, the method includes a step (102) of identifying a plane corresponding to the maximum or satisfactory focus obtained through the optical objective (OO), and the step (104, 108) of measuring the aberration is performed for the plane.

7. The method (100; 200) 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 (104, 108).

8. A system (300) for characterizing an optical objective (OO) for imaging, the system (300) comprising at least one measuring device (302, 304) configured to measure using an image sensor: - The lateral dispersive aberration function LCAF of the optical objective (OO), and / or - The geometric aberration function (GAF) of the optical objective (OO); After acquiring an image using the optical objective (OO), the image is digitally processed to correct at least one of the aberrations in the image, and in particular each of the aberrations.

9. The system (300) according to the preceding claim, characterized in that, It also includes a processing unit (308) configured to determine at least one of the following correction functions: - Lateral chromatic aberration correction function based on measured lateral chromatic aberration, and / or - Geometric aberration correction function based on measurement geometric aberrations.

10. A method (400) for manufacturing an optical objective lens, for at least one optical objective lens (OO), the method comprising the steps of: - Fabricate the optical objective (OO), - The optical objective (OO) is characterized using the method (100; 200) according to any one of claims 1 to 7.

11. An apparatus (500) for manufacturing optical objectives, comprising: - Optical objective lens production line (502), and - A system (300; 504) for characterizing an optical objective (OO) according to any one of claims 8 or 9.

12. A method (700) for acquiring an image of a scene using an optical objective (OO) characterized by any one of the methods (100; 200) according to claims 1 to 7, the method (700) for acquiring the image comprising the following steps: - The image (702) is acquired using the optical objective (OO), and - The image is digitally processed (704) to at least partially correct lateral dispersive aberration and / or geometric aberration.

Images