Image sensor, shooting method and device

Abstract

The present application discloses an image sensor, a shooting method and a device, belonging to the technical field of image processing. The image sensor includes: at least two pixel components; at least one deformation component, with a deformation component provided between two adjacent pixel components; when the deformation component is powered on, the deformation component deforms to change the distance between the corresponding two adjacent pixel components.

Description

Technical Field

[0001] This application belongs to the technical field of camera imaging, and particularly relates to an image sensor, a shooting method and a device. Background Art

[0002] With the development of Internet technology and the rise of self-media, taking photos and recording videos have become part of the daily life and work content of some users. Therefore, users' requirements for the experience of using cameras to take pictures are getting higher and higher, and how to improve the imaging quality of cameras is one of the technical challenges faced in improving the camera shooting experience.

[0003] As an important component of camera imaging, the quality of the camera lens directly affects the imaging quality of the camera. Among them, the distortion of the camera lens will cause image distortion where the lines at the edges of the imaged image are bent, especially when the edge part is a straight line, this phenomenon is more obvious. To avoid this phenomenon, in related technologies, the shooting angle is appropriately fine-tuned to make the straight line area closer to the center of the picture, or the imaged image is post-processed through a distortion correction algorithm. During the post-processing, the face features or object features extracted from the image through the distortion correction algorithm are used to determine the distortion correction parameters, and then based on the distortion correction parameters, global distortion correction is performed on the image.

[0004] However, the accuracy of the above-mentioned distortion correction method is insufficient. Summary of the Invention

[0005] The purpose of the embodiments of this application is to provide an image sensor, a shooting method and a device, which can accurately correct the distortion of the camera lens.

[0006] In a first aspect, an embodiment of this application provides an image sensor, including:

[0007] At least two pixel components;

[0008] At least one deformation component, and the deformation component is provided between two adjacent pixel components;

[0009] When the deformation component is powered on, the deformation component deforms to change the distance between the corresponding two adjacent pixel components.

[0010] In a second aspect, an embodiment of this application provides an electronic device, and the electronic device includes the image sensor as described in the first aspect.

[0011] In a third aspect, an embodiment of this application provides a shooting method, which is applied to the electronic device provided in the second aspect, and the method includes:

[0012] Controlling the image sensor to collect original image data;

[0013] Determine image distortion data based on the original image data;

[0014] Control a target deformation component to deform based on the image distortion data to change the position of a target pixel component;

[0015] Control the image sensor to acquire target image data;

[0016] Wherein, at least one deformation component includes the target deformation component, and at least two pixel components include the target pixel component.

[0017] In a fourth aspect, an embodiment of the present application provides a photographing device, which is applied to the electronic device provided in the second aspect. The device includes:

[0018] A first control unit, configured to control an image sensor to acquire original image data;

[0019] A distortion determination unit, configured to determine image distortion data based on the original image data;

[0020] A deformation unit, configured to control a target deformation component to deform based on the image distortion data to change the position of a target pixel component;

[0021] A second control unit, configured to control the image sensor to acquire target image data;

[0022] Wherein, at least one deformation component includes the target deformation component, and at least two pixel components include the target pixel component.

[0023] In a fifth aspect, an embodiment of the present application provides an electronic device, which includes a processor and a memory. The memory stores a program or instruction that can run on the processor. When the program or instruction is executed by the processor, the steps of the photographing method provided in the third aspect are implemented.

[0024] In a sixth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the photographing method provided in the third aspect are implemented.

[0025] In a seventh aspect, an embodiment of the present application provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor, and the processor is configured to run a program or instruction to implement the steps of the photographing method provided in the third aspect.

[0026] In an eighth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium and is executed by at least one processor to implement the steps of the photographing method provided in the third aspect.

[0027] In the embodiment of the present application, the image sensor includes at least two pixel components and at least one deformation component, and a deformation component is provided between two adjacent pixel components. When the deformation component is powered on, the deformation component deforms to change the distance between the corresponding two adjacent pixel components. Therefore, in the case where the camera has lens distortion, by changing the distance between at least two adjacent pixel components through the deformation component, the light passing through the distorted lens can still reach the correct pixel components, eliminating the adverse effect of lens distortion on the imaging of the image sensor and improving the accuracy of correcting lens distortion. Description of the Drawings

[0028] Figure 1 Structural schematic diagram of the image sensor provided by the embodiment of the present application Figure 1 ;

[0029] Figure 2 Structural schematic diagram of the image sensor provided by the embodiment of the present application Figure 2 ;

[0030] Figure 3 Structural schematic diagram of the image sensor provided by the embodiment of the present application Figure 3 ;

[0031] Figure 4 Structural schematic diagram of the image sensor provided by the embodiment of the present application Figure 4 ;

[0032] Figure 5 Flow schematic diagram of the shooting method provided by the embodiment of the present application;

[0033] Figure 6 Imaging optical path schematic diagram of a distorted camera lens;

[0034] Figure 7a Example of a calibration object Figure 1 ;

[0035] Figure 7b Example of a calibration object Figure 2 ;

[0036] Figure 8 Structural block diagram of the distortion correction device provided by the embodiment of the present application;

[0037] Figure 9 Structural block diagram of an electronic device for implementing the embodiment of the present application;

[0038] Figure 10 Hardware structure schematic diagram of an electronic device for implementing the embodiment of the present application.

[0039] Explanation of the reference numerals in the drawings:

[0040] 10 - pixel component; 101 - microlens unit; 102 - photosensitive unit; 20 - deformation component; 30 - conductive member. Specific implementation manners

[0041] Next, the technical solutions in the embodiments of the present application will be clearly described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of the present application.

[0042] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are usually of the same category, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims means at least one of the connected objects, and the character " / " generally indicates an "or" relationship between the associated objects before and after.

[0043] In the description of the present application, it should be understood that the orientation or positional relationship indicated by the terms "longitudinal", "transverse", "length", "upper", "lower", "front", "rear", "inner", "outer", "clockwise", "counterclockwise", "axial", "circumferential", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present application.

[0044] In the description of the present application, it should be noted that unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific situations.

[0045] First, the terms involved in the present application are explained to facilitate the understanding of those skilled in the art:

[0046] Image sensor: An image sensor, also known as a camera sensor, serves the same purpose as film in a traditional camera in a digital camera. Image sensors are generally divided into two types. One is a Charge Coupled Device (CCD) element, and the other is a Complementary Metal Oxide Semiconductor (CMOS) device.

[0047] Among them, the working process of a CMOS device is roughly as follows: It senses the optical signal and converts the optical signal into an electrical signal; then, it amplifies and performs analog-to-digital conversion on the electrical signal to form a digital signal matrix (i.e., an image); then, it performs image processing (Image Signal Processor, ISP) on the digital signal matrix to obtain the processed image; finally, it compresses and stores the processed image.

[0048] Among them, the CMOS Camera Module (CCM) is one of the mainstream camera modules currently used on terminals, mainly composed of a lens, a voice coil motor, an IR filter, an image sensor (CMOS), a Digital Signal Processing (DSP), and a Flexible Printed Circuit board (FPC).

[0049] Distortion: The degree of distortion of the image formed by an optical system with respect to the object itself. It is a type of lens defect, an inherent characteristic of the lens, and a common optical phenomenon. The direct reason is that the magnification ratios of the edge part and the central part of the lens are inconsistent.

[0050] In optical imaging, the magnification of an optical lens system is not a constant. The magnification of the lens varies with the angle formed between the light beam and the main axis. Therefore, the fundamental reason for distortion is that the magnification ratio in the central region of the lens is inconsistent with that in the edge region. Commonly, the magnification ratio in the central region of the lens is greater than that in the edge region. Taking the straight line of a corner as an example, simply put, the middle part of the wall is closer to the center of the image, with a larger magnification ratio, while the top and bottom are farther from the center of the image, with a smaller magnification ratio. Therefore, it can be seen that a barrel distortion is formed outward in the middle region.

[0051] In the related art, distortion correction is performed by finely adjusting the lens angle or through post - processing of the image. However, finely adjusting the lens angle tests the user's professional level, and the distortion correction effect is not stable; the post - processing of the image extracts the features of the human body or other objects in the image through a distortion correction algorithm, compares the features of the human body or other objects with the estimated reasonable features, and obtains the distortion correction parameters. Since reasonable features need to be estimated, the distortion correction accuracy of this method is not high, and the computational consumption is increased.

[0052] To solve the above problems, the present application provides an image sensor, a shooting method, and a device. In the present application, the image sensor includes at least two pixel components and at least one deformation component. The deformation component is disposed between two adjacent pixel components. By deforming the deformation component, the distance between two adjacent pixel components is changed, so that the light passing through the distorted lens can be correctly sensed by the pixel components, eliminating the influence of lens distortion on the imaging of the image sensor. In this way, lens distortion correction is achieved, the accuracy of distortion correction is improved, and the calculation in the distortion correction process is simple.

[0053] The following will, with reference to the accompanying drawings, through specific embodiments and their application scenarios, elaborate in detail on the image sensor, shooting method, and device provided by the embodiments of the present application.

[0054] Reference Figure 1 and Figure 2 , Figure 1 is the structural schematic Figure 1 , Figure 2 is the structural schematic Figure 2 .

[0055] As Figure 1 and Figure 2 shown, the image sensor includes:

[0056] At least two pixel components 10;

[0057] At least one deformation component 20, and the deformation component 20 is disposed between two adjacent pixel components 10;

[0058] When the deformation component 20 is powered on, the deformation component 20 deforms to change the distance between the corresponding two adjacent pixel components 10.

[0059] Among them, Figure 1 and Figure 2 take 4 pixel components 10 as an example.

[0060] In an image sensor, a pixel component 10 senses an optical signal, converts the optical signal into an electrical signal, and further converts it into a pixel value of a pixel point in an image. Therefore, the pixel components 10 in the image sensor correspond one-to-one with the pixel points in the image. In the case where the lens is distorted, the light that should have fallen on a certain pixel component 10 will, after being refracted by the lens, fall on another pixel component 10 and be sensed by this other pixel component 10, resulting in distortion of the image generated by the image sensor.

[0061] In this embodiment, in the case where the distortion of the camera lens causes image distortion, the image sensor can power on the deformation component 20, causing the deformation component 20 to deform. The deformation of the deformation component 20 causes the distance between two adjacent pixel components 10 corresponding to the deformation component 20 to become larger or smaller, causing the position of the pixel component 10 in the image sensor to change. As a result, the incident light can still fall on the correct pixel component 10 after passing through the distorted camera lens, eliminating the influence of the camera lens distortion on imaging and ensuring the accuracy of the pixel values of each pixel point in the image formed by the image sensor.

[0062] Thus, this embodiment realizes a distortion correction process with the pixel component 10 as the adjustment unit, effectively improving the accuracy of distortion correction. Moreover, compared with the later distortion correction algorithm, the distortion correction method proposed in this embodiment has a lower computational complexity and higher efficiency.

[0063] As an example, from Figures 1 to 2 , the width of the deformation component 20 thickens, resulting in an increase in the distance between two adjacent pixel components corresponding to the deformation component 20; from Figures 2 to 1 , the width of the deformation component 20 narrows, resulting in a decrease in the distance between two adjacent pixel components corresponding to the deformation component 20.

[0064] In some embodiments, each pixel component 10 includes a microlens unit 101 and a photosensitive unit 102. Incident light can pass through the microlens unit 101 and enter the photosensitive unit 102. After being sensed by the photosensitive unit 102, a pixel value of a pixel point on the image is formed. Among them, the microlens unit 101 is used to converge light, and the light converged by the microlens unit 101 enters the photosensitive unit 102; the photosensitive unit 102 may include components for filtering light, converting the optical signal into an electrical signal, and / or performing analog-to-digital conversion on the electrical signal, such as a filter, a photoelectric converter, an analog-to-digital conversion circuit, etc. (not shown in the figure).

[0065] Based on the fact that each pixel component 10 includes a microlens unit 101 and a photosensitive unit 102, in a possible implementation manner, a deformation component 20 is provided between the microlens units 101 of two adjacent pixel components 10; when the deformation component 20 is powered on, the deformation component 20 deforms to change the distance between the corresponding two adjacent pixel components 10.

[0066] Based on each pixel component 10 including a microlens unit 101 and a photosensitive unit 102, in another possible implementation, as Figure 1 shown, a deformation component 20 is provided between the photosensitive units 102 of two adjacent pixel components 10; when the deformation component 20 is powered on, the deformation component 20 deforms to change the distance between the corresponding two adjacent pixel components 10.

[0067] In some embodiments, on the image sensor, the pixel components 10 may be arranged in an array. As Figure 1 and Figure 2 shown, 4 pixel components 10 are arranged in an array.

[0068] Based on the pixel components 10 being arranged in an array, in a possible implementation: a deformation component 20 is provided between two adjacent pixel components 10 in the horizontal axis direction; a deformation component 20 is provided between two adjacent pixel components 10 in the vertical axis direction. Thus, by controlling the power-on of the deformation component 20, the position of the pixel components 10 on the image sensor can be changed in the horizontal axis direction or the vertical axis direction, improving the flexibility, comprehensiveness, and accuracy of the position control of the pixel components 10.

[0069] In some embodiments, when the number of pixel components 10 on the image sensor is greater than 2, a deformation component 20 may be provided between some adjacent two pixel components 10, or a deformation component 20 may be provided between all adjacent pixel components 10, which can be specifically determined according to the distortion area of the camera lens to improve the accuracy of the distortion correction of the camera lens and the imaging quality of the image sensor.

[0070] In some embodiments, the material of the deformation component 20 may be a piezoelectric material. Among them, the piezoelectric material can deform when a voltage is applied, in other words, the piezoelectric material deforms under the influence of an electric field. Therefore, the image sensor can accurately control the deformation component 20 to deform to different degrees by applying different voltages to the deformation component 20, improving the accuracy of the deformation of the deformation component 20.

[0071] As an example, the piezoelectric material may be a single crystal, ceramic, thin film, etc.

[0072] In some embodiments, the deformation component 20 is provided with a Micro-Electro-Mechanical System (MEMS). When the deformation component 20 uses a piezoelectric material, the piezoelectric material can be controlled to deform through the MEMS in the deformation component 20.

[0073] In this embodiment, in the deformation component 20, when the MEMS is powered on, the deformation component 20 deforms, causing the distance between two adjacent pixel components 10 corresponding to the deformation component 20 to increase or decrease. Among them, the MEMS has a simple structure, low cost, and occupies a small space, which is conducive to reducing the hardware cost of distortion correction. Moreover, the operation accuracy of the MEMS is high, which is conducive to improving the accuracy of distortion correction.

[0074] In some embodiments, as Figure 1 and Figure 2 shown, the deformation component 20 causes the distance between two adjacent pixel components 10 to increase or decrease. When the distance increases, the two adjacent pixel components 10 cannot contact each other, resulting in no signal transmission between the two adjacent pixel components 10. To solve the signal transmission problem between two adjacent pixel components 10, the following solutions are provided:

[0075] In a possible implementation manner, the deformation component 20 has conductivity, and the deformation component 20 contacts or is electrically connected to two adjacent pixel components 10 corresponding thereto. Therefore, signals between two adjacent pixel components 10 corresponding thereto can be transmitted through the deformation component 20.

[0076] In another possible implementation manner, as Figure 3 and Figure 4 shown, the image sensor further includes at least one conductive member 30, and the at least one conductive member 30 is respectively connected to two adjacent pixel components 10 corresponding to the deformation component 20, so as to realize signal transmission between two adjacent pixel components 10 provided with the deformation component 20 through the conductive member 30.

[0077] In this embodiment, the conductive member 30 has elasticity. When the distance between two pixel components 10 connected by the conductive member 30 increases, the conductive member 30 stretches; when the distance between two pixel components 10 connected by the conductive member 30 decreases, the conductive member 30 contracts. Thus, regardless of how the distance between two adjacent pixel components 10 changes, signal communication between two adjacent pixel components 10 can be realized.

[0078] As an example, from Figures 3 to 4 , the distance between two pixel components 10 connected by the conductive member 30 increases, and the conductive member 30 is stretched as the distance between the two pixel components 10 increases; from Figures 4 to 3 , when the distance between two pixel components 10 connected by the conductive member 30 decreases, the conductive member 30 automatically contracts as the distance between the two pixel components 10 decreases.

[0079] The embodiments of the present application also provide an electronic device, which includes an image sensor provided in any of the foregoing embodiments. For example, the electronic device is a camera, a mobile phone, a computer, etc. Thus, the electronic device can correct the distortion of the camera lens through the image sensor, improve the efficiency and accuracy of the camera lens distortion correction, and further improve the imaging quality of the electronic device.

[0080] Based on the electronic device provided in the foregoing embodiments, the embodiments of the present application also provide a shooting method.

[0081] Refer to Figure 5 , Figure 5 which is a flowchart of the shooting method provided by the embodiments of the present application Figure 1 , and the execution subject of this method can be the electronic device provided in the foregoing embodiments. As Figure 5 shown, the shooting method may include:

[0082] S501. Control the image sensor to collect original image data.

[0083] Among them, the image sensor is the image sensor provided in any of the foregoing embodiments, and its structure, working principle and technical effects can be referred to the foregoing embodiments and will not be elaborated here.

[0084] In this embodiment, when a lens distortion correction request is received, the image sensor can be controlled to collect the image data of the calibration object. For the sake of distinction, this image data is called the original image data. The calibration object can be various calibration plates such as a solid circle calibration plate and a checkerboard calibration plate. To ensure the accuracy of the original image data, when collecting the original image data, the optical axis of the camera on the electronic device can be made perpendicular to the calibration object as much as possible, and the image sensor can be restored to its original state (that is, the deformation component does not deform, and the distance between the two adjacent pixel components corresponding to the deformation component does not increase or decrease), and then the image sensor is controlled to collect the image data of the calibration object to obtain the original image data.

[0085] In a possible implementation manner, the lens distortion correction request can be triggered when the electronic device is started. Thus, the lens distortion correction is triggered in a timely manner after the electronic device is started, improving the timeliness and efficiency of the lens distortion correction and the shooting experience of the user.

[0086] In another possible implementation manner, the lens distortion correction request can be triggered when it is detected that the image sensor on the electronic device has not performed lens distortion correction, or when it is detected that the lens distortion correction does not meet the requirements, for example, the image captured by the electronic device still has relatively serious image distortion, improving the intelligence level of the lens distortion correction trigger and the shooting experience of the user.

[0087] In yet another possible implementation, when a lens distortion correction request input by a user is received, the image sensor may be controlled to collect original image data.

[0088] S502. Determine image distortion data based on the original image data.

[0089] Among them, the image distortion data may include at least one image region in the original image data where image distortion occurs due to lens distortion and the distortion data corresponding to the at least one image region. The distortion data of the image region may reflect the degree of distortion of the image region due to lens distortion.

[0090] In this embodiment, the distortion data of at least one image region on the original image data may be determined through the distortion calibration method of the camera lens, so as to improve the accuracy of the image distortion data through distortion calibration.

[0091] S503. Control the target deformation component to deform based on the image distortion data, so as to change the position of the target pixel component.

[0092] Among them, the target pixel component is at least one pixel component corresponding to the pixel points in the image region where image distortion is caused by lens distortion; the target deformation component is a deformation component provided between the target pixel components. The position setting of the deformation component may refer to the foregoing embodiments related to the image sensor, and will not be elaborated in this embodiment.

[0093] For clear description and easy understanding of the solution, in combination with Figure 6 the principle of image distortion caused by the camera lens will be explained. Figure 6 The following is a schematic diagram of the imaging optical path of the distorted camera lens:

[0094] As Figure 6 shown, the image plane represents the imaging plane, the object plane represents the position where the object is located, z represents the optical axis of the lens, and f represents the focal length. P1 and P2 respectively represent two objects, and P 1A is the imaging point of P1 under ideal conditions, P 1D is the imaging point of P1 under actual conditions, P 2A is the imaging point of P2 under ideal conditions, and P 2D is the imaging point of P2 under actual conditions. d r1 represents the distance between P 1A and P 1D , and d r2 represents the distance between P 2A and P 2D . r1 represents the distance between P 1A and the optical axis, and r2 represents the distance between P 2A and the optical axis.

[0095] Taking P1 as an example: The optical path of P1 should follow the dashed line to P after passing through the camera lens 1A , but due to the distortion of the camera lens, it actually reaches P 1D , that is, the light that should have entered the pixel component at P 1A enters the pixel component at P 1D ; Taking P2 as an example: The optical path of P2 should follow the dashed line to P 2A , but due to the distortion of the camera lens, it actually reaches P 2D , that is, the light that should have entered the pixel component at P 2A enters the pixel component at P 2D .

[0096] Therefore, to achieve camera lens distortion correction, it is necessary to control the deformation of the deformation component so that the pixel component at P 1A moves to P 1D , and the light affected by the camera lens distortion can still reach the pixel component at P 1A ; It is necessary to control the deformation of the deformation component so that the pixel component at P 2A moves to P 2D , and the light affected by the camera lens distortion can still reach the pixel component at P 2A .

[0097] Therefore, in this embodiment, in order to make the imaging point of the object fall on the accurate position on the image plane, considering that the position of the imaging point on the image plane (i.e., the position of the pixel point) corresponds one-to-one with the position of the pixel component, the deformation direction and deformation degree of the target deformation component can be determined based on the image distortion data, and the target deformation component can be controlled to deform according to the deformation direction and deformation degree. The deformation of the target deformation component increases or decreases the distance between two adjacent pixel components corresponding to the target deformation component; affected by the increase or decrease of the distance between two adjacent pixel components, the target pixel component moves to the corresponding position, and the light can reach the target pixel component that has moved to the corresponding position after passing through the camera lens.

[0098] When the material of the deformation component is a piezoelectric material, the target deformation component can be deformed by applying power and corresponding voltage to the target deformation component.

[0099] S504. Control the image sensor to collect target image data.

[0100] In this embodiment, after correcting the distortion of the camera lens of the electronic device through S503, the image sensor is controlled again to collect image data, and the target image data is obtained. Compared with the original image data, the target image data is the image data captured after the distortion correction of the camera lens, and the quality of the image data is higher, effectively improving the user experience of taking pictures through the electronic device.

[0101] In the embodiment of the present application, based on the original image data collected by the image sensor, the image distortion data is determined. Based on the image distortion data, the target deformation component is controlled to deform, so that the position of the pixel component in the image sensor changes, and the light passing through the distorted camera lens can still be correctly sensed by the pixel component, thereby realizing the correction of the camera lens distortion and improving the accuracy of the camera lens distortion correction. Furthermore, the quality of the images taken by the camera is improved, and the user's photo-taking experience is improved.

[0102] Next, based on Figure 5 the embodiments shown below, some embodiments of "determining image distortion data based on original image data" in the shooting method are provided:

[0103] In some embodiments, the original image data includes data corresponding to at least two image regions, and the image distortion data includes distortion data corresponding to the target image region in at least two image regions. At this time, the shape data of at least two image regions can be determined according to the original image data; according to the shape data of at least two image regions, the distortion data corresponding to the target image region can be determined. Thus, the distortion calibration of the camera lens is performed based on the shape data of at least two image regions, and the accuracy of the distortion calibration.

[0104] Among them, the data of at least two image regions may include the image positions of each pixel point in at least two image regions in the original image data.

[0105] Among them, the target image region is one or more image regions in at least two image regions.

[0106] In this embodiment, shape features of at least two image regions can be extracted from the original image data to obtain shape data of the at least two image regions. In one way, the shape data of the image region can be obtained by extracting and recognizing the edge features of the image region; in another way, the shape data of the image region can be obtained based on the image positions of the edge points or corner points of the image region. After obtaining the shape data of the at least two image regions, the distortion data of the target image region can be determined by comparing the shape data of the at least two image regions. In one way, the shape data of the at least two image regions can be compared with reference shape data, which can be input by the user or obtained from a database. The reference shape data is the shape data of the image region when it is not distorted; in another way, the image region with the smallest distortion degree among the at least two image regions can be determined as the reference image region, and the shape data of the reference image region is compared with the shape data of the remaining image regions.

[0107] In a possible implementation, before extracting the shape features of at least two image regions from the original image data to obtain the shape data of the at least two image regions, the original image data can be preprocessed to improve the accuracy of extracting the shape features of the image regions from the original image data.

[0108] Among them, preprocessing the original image data may include: performing grayscale processing on the original image data; performing binarization processing on the grayscale-processed original image data to obtain the binarized image data corresponding to the original image data; performing image thinning processing on the binarized image data. After that, corner detection can be performed on the preprocessed original image data, that is, on the binarized image data after image thinning processing, to obtain the corner points of the image region, that is, to obtain the shape data of the image region.

[0109] Among them, for image thinning processing of the binarized image data, for example, the binarized image data can be dilated first and then eroded, so as to more accurately identify the edge lines of the image region in the binarized image data, and thus more accurately detect the corner points of the image region.

[0110] Furthermore, the Kitchen-Rosenfeld corner detection algorithm can be used for corner detection to improve the accuracy of corner detection for the original image data.

[0111] In a possible implementation, the shapes of at least two image regions are square. At this time, determining the distortion data of the target image region according to the shape data of the at least two image regions may include: determining the distortion data of the target image region according to the ratio of the diagonal length of the target image region to the diagonal length of the reference image region. Thus, by the ratio of the diagonal lengths of different square regions, the accuracy of the distortion data of the image region is improved, that is, the accuracy of camera lens calibration is improved. Among them, the target image region is an image region in the at least two image regions with a distortion degree greater than the first preset threshold, and the reference image region is an image region in the at least two image regions with a distortion degree less than or equal to the first preset threshold.

[0112] Among them, the shape of the image region is square. For example, there are multiple cells on the calibration object.

[0113] In this implementation, the diagonal lengths of the at least two image regions can be determined according to the shape data of the at least two image regions. For example, the diagonal lengths of the at least two image regions can be determined based on the image positions of two corner points on the diagonal in the at least two image regions. The reference image region can be determined among the at least two image regions. In one way, the user can determine the reference image region among the at least two image regions; in another way, considering that the closer to the center of the image, the smaller the distortion of the image region, the reference image region can be determined as the image region closest to the center of the image among the at least two image regions. In particular, the reference image region can be determined as the central region in the original image data.

[0114] After determining the reference image region, the diagonal length of each image region among the at least two image regions can be compared with the diagonal length of the reference image region to obtain the ratio of the diagonal length of each image region among the at least two image regions to the diagonal length of the reference image region. Among them, the ratio of the diagonal length of the image region to the diagonal length of the reference image region reflects the distortion degree of the image region. The closer this ratio is to 1, the smaller the distortion degree of the image region. Therefore, the distortion degree of each image region can be determined based on the ratio of the diagonal length of each image region among the at least two image regions to the diagonal length of the reference image region. According to the distortion degree of each image region and the first preset threshold, the target image region is determined among the at least two image regions, and the distortion data of the target image region is determined to include the ratio of the diagonal length of the target image region to the diagonal length of the reference image region.

[0115] Therefore, the original image data including at least two square image regions can be used for the distortion calibration of the camera lens. Moreover, considering that the image distortion caused by the camera lens distortion, such as barrel distortion and pincushion distortion, will cause the shape change of the image region, based on the ratio of the diagonal lengths that can accurately reflect the shape distortion degree of the image region, the accuracy of the distortion calibration can be effectively improved.

[0116] Furthermore, in the process of determining the reference image region, in each quadrant of the original image data, the reference image region corresponding to the quadrant can be determined as the central region of the quadrant. Among them, the central region of the quadrant is the image region closest to the center of the original image data in the quadrant. In the process of determining the distortion data of the target image region, the distortion data of the image region can be determined according to the ratio of the diagonal length of the image region in the quadrant to the diagonal length of the reference image region corresponding to the quadrant; among the distortion data of the image region, the distortion data of the target image region is determined. Thus, considering that the distortion in different quadrants may be different, the reference image region is determined separately in each quadrant, improving the accuracy of the camera lens distortion calibration.

[0117] As an example, taking the image region as a cell, there are n cells in the original image data, and the diagonal lengths of the n cells are X1 to Xn respectively, and these distances are in pixels. Taking the image center of the original image data as the origin, 4 quadrants can be divided, and the reference cell containing the origin can be determined respectively in the 4 quadrants. In the first quadrant, according to the diagonal length of the cell in the first quadrant and the diagonal length of the reference cell in the first quadrant, the distortion coefficient of the cell in the first quadrant is determined; in the second quadrant, according to the diagonal length of the cell in the second quadrant and the diagonal length of the reference cell in the second quadrant, the distortion coefficient of the cell in the second quadrant is determined, and so on.

[0118] In another possible implementation, the shapes of at least two image regions are circular or elliptical. At this time, determining the distortion data of the target image region according to the shape data of at least two image regions may include: determining the distortion data of the target image region according to the ratio of the diameter length of the target image region to the diameter length of the reference image region. Thus, by the ratio of the diameter lengths of different circular regions or elliptical regions, the accuracy of the distortion data of the image region is improved, that is, the accuracy of the camera lens calibration is improved.

[0119] Among them, the shape of the image region is circular or elliptical. For example, as Figure 7a ( Figure 7a an example of the calibration object Figure 1 ) shown, the calibration object has at least two circular patterns.

[0120] Among them, different from the distortion calibration process when the shape of the image area is square, the shape data in the distortion calibration process of this implementation method is the diameter length of the image area. For the rest, reference can be made to the distortion calibration process when the shape of the image area is square, which will not be elaborated here.

[0121] In another possible implementation, the calibration object may include multiple dot patterns. For example Figure 7b ( Figure 7b is an example of the calibration object Figure 2 ) As shown, there are multiple dots on the calibration object. At this time, according to the shape data of at least two image areas, determining the distortion data of the target image area may include: determining the distance between at least one dot pattern in the original image data and the image center of the original image data; determining the distance between the corresponding dot pattern on the calibration object and the plane center of the calibration object; according to the distance between at least one dot pattern in the original image data and the image center of the original image data and the distance between the corresponding dot pattern on the calibration object and the plane center of the calibration object, determining the distortion data of at least one dot pattern in the original image data.

[0122] In this implementation method, in the case of no distortion, the distance between at least one dot pattern in the original image data and the image center of the original image data is equal to the distance between the corresponding dot pattern on the calibration object and the plane center of the calibration object. Therefore, the distance x between at least one dot pattern in the original image data and the image center of the original image data can be determined, and the distance y (such as in centimeters) between the corresponding dot pattern on the calibration object and the plane center of the calibration object can be determined. The distance y between the corresponding dot pattern on the calibration object and the plane center of the calibration object can be converted into the pixel distance y' between the corresponding dot pattern on the calibration object and the plane center of the calibration object. The ratio of the distance x between at least one dot pattern in the original image data and the image center of the original image data and the pixel distance y' between the corresponding dot pattern on the calibration object and the plane center of the calibration object is obtained to get the distortion data x / y' of at least one dot pattern in the original image data.

[0123] In some embodiments, controlling the target deformation component to deform based on the image distortion data may include: determining the image distortion type according to the image distortion data; in the case where the image distortion type is pincushion distortion, controlling the width of the target deformation component to increase by a first value according to the image distortion data, so that the distance between the target pixel components increases by the first value; in the case where the image distortion type is barrel distortion, controlling the width of the target deformation component to decrease by a second value according to the image distortion data, so that the distance between the target pixel components decreases by the second value. Wherein, the first value and the second value are determined according to the image distortion data.

[0124] Among them, barrel distortion is a distortion phenomenon in which the magnification of the edge region in the field of view is much smaller than that of the central region, and the imaging picture shows a barrel-shaped expansion. Pincushion distortion is a distortion phenomenon in which the magnification of the edge region in the field of view is much larger than that of the central region, and the imaging picture shows a distortion of shrinking from the outer end to the middle.

[0125] Among them, the distortion data of the target image region in the image distortion data can be compared with a distortion threshold to obtain a comparison result, and according to the comparison result, the image distortion type of the image region can be determined.

[0126] In one way, when the shape of the image region is square, the distortion data of the target image region can include the ratio of the diagonal length of the target image region to the diagonal length of the reference image region, and the distortion threshold can be 1. If the ratio of the diagonal length of the target image region to the diagonal length of the reference image region is greater than 1, it indicates that the magnification of the edge region in the original image data is greater than that of the central region, and the image distortion type of the target image region is pincushion distortion. On the contrary, if the ratio of the diagonal length of the target image region to the diagonal length of the reference image region is less than 1, it indicates that the magnification of the edge region in the original image data is greater than that of the central region, and the image distortion type of the target image region is barrel distortion.

[0127] In another way, when the shape of the image region is circular or elliptical, the distortion data of the target image region can include the ratio of the diameter length of the target image region to the diameter length of the reference image region, and the distortion threshold can be 1. If the ratio of the diameter length of the target image region to the diameter length of the reference image region is greater than 1, it indicates that the magnification of the edge region in the original image data is greater than that of the central region, and the image distortion type of the target image region is pincushion distortion. On the contrary, if the ratio of the diameter length of the target image region to the diameter length of the reference image region is less than 1, it indicates that the magnification of the edge region in the original image data is greater than that of the central region, and the image distortion type of the target image region is barrel distortion.

[0128] In another way, when the calibration object includes multiple dot patterns, the distortion data of the target image region can include the ratio x / y' of the distance x between the dot pattern in the target image region and the image center in the original image data to the pixel distance y' between the corresponding dot pattern on the calibration object and the plane center of the calibration object, and the distortion threshold can be 1. If x / y' is greater than 1, it indicates that the magnification of the edge region in the original image data is greater than that of the central region, and the image distortion type of the target image region is pincushion distortion. On the contrary, if x / y' is less than 1, it indicates that the magnification of the edge region in the original image data is greater than that of the central region, and the image distortion type of the target image region is barrel distortion.

[0129] When the image distortion type of the target image area is pincushion distortion, the magnification of the target image area is greater than that of the reference image area, that is, the number of pixels in the target image area is more than that in the reference image area. It is necessary to widen the spacing of the target pixel components at the target image area to reduce the number of pixel components in the target image area. Therefore, the first value can be determined according to the distortion data of the target image area, and according to the first value, the thickness of the target deformation component at the target image area is controlled to increase by the first value, so that the spacing between two adjacent pixel components corresponding to the target deformation component increases by the first value.

[0130] When the image distortion type of the target image area is barrel distortion, the magnification of the target image area is less than that of the reference image area, that is, the number of pixels in the target image area is less than that in the reference image area. It is necessary to reduce the spacing of the target pixel components at the target image area to increase the number of pixel components in the target image area. Therefore, the second value can be determined according to the distortion data of the target image area, and the thickness of the target deformation component at the target image area is controlled to decrease by the second value, so that the spacing between two adjacent pixel components corresponding to the target pixel component decreases by the second value.

[0131] It can be seen that by controlling the deformation direction and deformation amount of the deformation component, the position of the pixel component can be accurately adjusted to achieve the effect of eliminating distortion and improve the accuracy of camera lens distortion correction.

[0132] In the shooting method provided by the embodiment of the present application, the execution subject may be a distortion correction device. In the embodiment of the present application, taking the distortion correction device executing the shooting method as an example, the distortion correction device provided by the embodiment of the present application is described.

[0133] Reference Figure 8 , Figure 8 is the structural block diagram of the distortion correction device provided by the embodiment of the present application.

[0134] As Figure 8 shown, the distortion correction device includes:

[0135] The first control unit 801 is used to control the image sensor to collect the original image data;

[0136] The distortion determination unit 802 is used to determine the image distortion data based on the original image data;

[0137] The deformation unit 803 is used to control the target deformation component to deform based on the image distortion data to change the position of the target pixel component;

[0138] The second control unit 804 is used to control the image sensor to collect the target image data;

[0139] Among them, at least one deformation component includes a target deformation component, and at least two pixel components include a target pixel component.

[0140] In some embodiments, the original image data includes data corresponding to at least two image regions, and the image distortion data includes distortion data corresponding to a target image region among the at least two image regions. In the process of determining the image distortion data based on the original image data, the distortion determination unit 802 is specifically configured to: determine the shape data of at least two image regions according to the original image data; and determine the distortion data of the target image region according to the shape data of the at least two image regions.

[0141] In some embodiments, when the shapes of the at least two image regions are square, in the process of determining the distortion data of the target image region according to the shape data of the at least two image regions, the distortion determination unit 802 is specifically configured to: determine the distortion data of the target image region according to the ratio of the diagonal length of the target image region to the diagonal length of the reference image region; the target image region is an image region among the at least two image regions with a distortion degree greater than a first preset threshold, and the reference image region is an image region among the at least two image regions with a distortion degree less than or equal to the first preset threshold.

[0142] In some embodiments, when the shapes of the at least two image regions are circular or elliptical, in the process of determining the distortion data of the target image region according to the shape data of the at least two image regions, the distortion determination unit 802 is specifically configured to: determine the distortion data of the target image region according to the ratio of the diameter length of the target image region to the diameter length of the reference image region; the target image region is an image region among the at least two image regions with a distortion degree greater than a second preset threshold, and the reference image region is an image region among the at least two image regions with a distortion degree less than or equal to the second preset threshold.

[0143] In some embodiments, in the process of controlling the target deformation component to deform based on the image distortion data, the deformation unit 803 is specifically configured to: determine the image distortion type according to the image distortion data; in the case where the image distortion type is pincushion distortion, control the width of the target deformation component to increase by a first value according to the image distortion data, so that the distance between the target pixel components increases by the first value; in the case where the image distortion type is barrel distortion, control the width of the target deformation component to decrease by a second value according to the image distortion data, so that the distance between the target pixel components decreases by the second value.

[0144] The distortion correction device in the embodiments of the present application can be an electronic device or a component in an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices other than terminals. Exemplarily, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a palmtop computer, a vehicle-mounted electronic device, a Mobile Internet Device (MID), an augmented reality (AR) / virtual reality (VR) device, a robot, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), etc. It can also be a server, a Network Attached Storage (NAS), a personal computer (PC), a television (TV), a teller machine, or a self-service machine, etc. The embodiments of the present application do not make specific limitations.

[0145] The distortion correction device in the embodiments of the present application can be a device with an operating system. The operating system can be the Android operating system, the iOS operating system, or other possible operating systems. The embodiments of the present application do not make specific limitations.

[0146] The distortion correction device provided in the embodiments of the present application can implement Figure 5 each process implemented by the method embodiments. To avoid repetition, details are not described here again.

[0147] Optionally, as Figure 9 shown, the embodiments of the present application further provide an electronic device 900, including a processor 901 and a memory 902. A program or instruction that can run on the processor 901 is stored on the memory 902. When the program or instruction is executed by the processor 901, it implements each step of the method embodiments of the above shooting method and can achieve the same technical effect. To avoid repetition, details are not described here again.

[0148] It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned mobile electronic devices and non-mobile electronic devices.

[0149] Figure 10 It is a schematic diagram of the hardware structure of an electronic device for implementing the embodiments of the present application.

[0150] The electronic device 1000 includes, but is not limited to, components such as a radio frequency unit 1001, a network module 1002, an audio output unit 1003, an input unit 1004, a sensor 1005, a display unit 1006, a user input unit 1007, an interface unit 1008, a memory 1009, a processor 1010, and an image sensor. Among them, the image sensor may include: at least two pixel components; at least one deformation component, with a deformation component provided between two adjacent pixel components; when the deformation component is powered on, the deformation component deforms to change the distance between the corresponding two adjacent pixel components.

[0151] Optionally, the material of the deformation component is a piezoelectric material.

[0152] Optionally, the image sensor further includes a conductive member that connects two adjacent pixel components; when the distance between the two pixel components connected by the conductive member increases, the conductive member stretches; when the distance between the two pixel components connected by the conductive member decreases, the conductive member contracts.

[0153] Those skilled in the art can understand that the electronic device 1000 may further include a power source (such as a battery) for supplying power to each component. The power source can be logically connected to the processor 1010 through a power management system, so as to implement functions such as management of charging, discharging, and power consumption management through the power management system. Figure 10 The structure of the electronic device shown does not limit the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0154] Among them, the processor 1010 is used to: control the image sensor to collect original image data; determine image distortion data based on the original image data; control the target deformation component to deform based on the image distortion data to change the position of the target pixel component; control the image sensor to collect target image data; where at least one deformation component includes the target deformation component, and at least two pixel components include the target pixel component.

[0155] Optionally, the original image data includes data corresponding to at least two image regions, and the image distortion data includes distortion data corresponding to a target image region in at least two image regions. During the process of determining the image distortion data based on the original image data, the processor 1010 is further used to: determine the shape data of at least two image regions according to the original image data; determine the distortion data of the target image region according to the shape data of at least two image regions.

[0156] Optionally, when the shapes of at least two image regions are square, in the process of determining the distortion data of the target image region according to the shape data of the at least two image regions, the processor 1010 is further configured to: determine the distortion data of the target image region according to the ratio of the diagonal length of the target image region to the diagonal length of the reference image region; the target image region is an image region with a distortion degree greater than a first preset threshold among the at least two image regions, and the reference image region is an image region with a distortion degree less than or equal to the first preset threshold among the at least two image regions.

[0157] Optionally, when the shapes of at least two image regions are circular or elliptical, in the process of determining the distortion data of the target image region according to the shape data of the at least two image regions, the processor 1010 is further configured to: determine the distortion data of the target image region according to the ratio of the diameter length of the target image region to the diameter length of the reference image region; the target image region is an image region with a distortion degree greater than a second preset threshold among the at least two image regions, and the reference image region is an image region with a distortion degree less than or equal to the second preset threshold among the at least two image regions.

[0158] Optionally, in the process of controlling the target deformation component to deform based on the image distortion data, the processor 1010 is further configured to: determine the image distortion type according to the image distortion data; when the image distortion type is pincushion distortion, control the width of the target deformation component to increase by a first value according to the image distortion data, so that the distance between the target pixel components increases by the first value; when the image distortion type is barrel distortion, control the width of the target deformation component to decrease by a second value according to the image distortion data, so that the distance between the target pixel components decreases by the second value.

[0159] It should be understood that in the embodiments of the present application, the input unit 1004 may include a Graphics Processing Unit (GPU) 10041 and a microphone 10042. The graphics processor 10041 processes the image data of static pictures or videos obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 1006 may include a display panel 10061, and the display panel 10061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 1007 includes at least one of a touch panel 10071 and other input devices 10072. The touch panel 10071 is also called a touch screen. The touch panel 10071 may include two parts: a touch detection device and a touch controller. The other input devices 10072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which will not be elaborated here.

[0160] The memory 1009 can be used to store software programs and various data. The memory 1009 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data. Among them, the first storage area may store an operating system, application programs or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). In addition, the memory 1009 may include a volatile memory or a non-volatile memory, or the memory 1009 may include both a volatile memory and a non-volatile memory. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDR SDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synch link dynamic random access memory (SLDRAM), and a direct rambus random access memory (DRRAM). The memory 1009 in the embodiments of the present application includes, but is not limited to, these and any other suitable types of memories.

[0161] The processor 1010 may include one or more processing units; optionally, the processor 1010 integrates an application processor and a modem processor. Among them, the application processor mainly processes operations related to the operating system, user interface, and application programs, etc., and the modem processor mainly processes wireless communication signals, such as a baseband processor. It can be understood that the above modem processor may not be integrated into the processor 1010 either.

[0162] The embodiments of the present application also provide a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, it implements each process of the above-mentioned embodiment of the shooting method and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0163] Among them, the processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media such as computer read-only memory ROM, random access memory RAM, magnetic disks or optical discs, etc.

[0164] Another embodiment of the present application provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement each process of the above-mentioned shooting method embodiment, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0165] It should be understood that the chip mentioned in the embodiments of the present application may also be referred to as a system-on-chip, system chip, chip system, or system-on-chip, etc.

[0166] The embodiments of the present application provide a computer program product. The program product is stored in a storage medium and is executed by at least one processor to implement each process of the above-mentioned shooting method embodiment, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0167] It should be noted that in this article, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including that element. In addition, it should be pointed out that the methods and devices in the embodiments of the present application are not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in a reverse order according to the functions involved. For example, the methods described may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, the features described with reference to certain examples may be combined in other examples.

[0168] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases, the former is a better implementation. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art can be embodied in the form of a computer software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions for causing a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present application.

[0169] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present application, those of ordinary skill in the art can also make many forms without departing from the purpose of the present application and the scope protected by the claims, and all of them belong to the protection scope of the present application.

Claims

1. An image sensor, characterized in that, Comprising: At least two pixel components; At least one deformation component, with the deformation component provided between two adjacent pixel components; A conductive member, the conductive member connecting two adjacent pixel components, and the conductive member being used to realize signal transmission between two adjacent pixel components; When the deformation component is powered on, the deformation component deforms to change the distance between two corresponding adjacent pixel components; When the distance between two pixel components connected by the conductive member increases, the conductive member stretches; When the distance between two pixel components connected by the conductive member decreases, the conductive member contracts; Wherein, when there is lens distortion in the camera, the image sensor can change the distance between at least two adjacent pixel components through the deformation component, so that the light passing through the distorted lens can reach the correct pixel components.

2. The image sensor according to claim 1, characterized in that, The material of the deformation component is a piezoelectric material.

3. An electronic device, characterized in that, The electronic device includes the image sensor as described in any one of claims 1-2.

4. A shooting method, characterized in that, Applied to the electronic device described in claim 3, the photographing method includes: Controlling the image sensor to collect original image data; Determining image distortion data based on the original image data; Controlling the target deformation component to deform based on the image distortion data to change the position of the target pixel component; Controlling the image sensor to collect target image data; Wherein, at least one deformation component includes the target deformation component, and at least two pixel components include the target pixel component.

5. The shooting method according to claim 4, characterized in that, The original image data includes data corresponding to at least two image regions, the image distortion data includes distortion data corresponding to a target image region in the at least two image regions, and determining the image distortion data based on the original image data includes: Determining the shape data of the at least two image regions according to the original image data; Determining the distortion data of the target image region according to the shape data of the at least two image regions.

6. The photographing method according to claim 5, wherein When the shapes of the at least two image regions are square, the determining the distortion data of the target image region according to the shape data of the at least two image regions includes: Determining the distortion data of the target image region according to the ratio of the diagonal length of the target image region to the diagonal length of the reference image region; The target image region is an image region in the at least two image regions with a distortion degree greater than a first preset threshold, and the reference image region is an image region in the at least two image regions with a distortion degree less than or equal to the first preset threshold.

7. The photographing method according to claim 5, wherein When the shapes of the at least two image regions are circular or elliptical, the determining the distortion data of the target image region according to the shape data of the at least two image regions includes: Determining the distortion data of the target image region according to the ratio of the diameter length of the target image region to the diameter length of the reference image region; The target image region is an image region in the at least two image regions with a distortion degree greater than a second preset threshold, and the reference image region is an image region in the at least two image regions with a distortion degree less than or equal to the second preset threshold.

8. The photographing method according to any one of claims 5 to 7, characterized in that, Controlling the target deformation component to deform based on the image distortion data includes: Determining the type of image distortion according to the image distortion data; When the type of image distortion is pincushion distortion, controlling the width of the target deformation component to increase by a first value according to the image distortion data, so that the distance between the target pixel components increases by the first value; When the type of image distortion is barrel distortion, controlling the width of the target deformation component to decrease by a second value according to the image distortion data, so that the distance between the target pixel components decreases by the second value.

9. A photographing device, characterized in that, Applied to the electronic device according to claim 3, the photographing device includes: A first control unit for controlling the image sensor to collect original image data; A distortion determination unit for determining image distortion data based on the original image data; A deformation unit for controlling the target deformation component to deform based on the image distortion data to change the positions of the target pixel components; A second control unit for controlling the image sensor to collect target image data; Wherein, at least one deformation component includes the target deformation component, and at least two pixel components include the target pixel components.

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