An autofocus method and system based on a TFT liquid crystal panel

Abstract

The present invention discloses an autofocus method and system based on a TFT liquid crystal panel, specifically related to the technical field of TFT liquid crystal panels; by acquiring image data of a shooting scene, calculating the optimal focal length adjustment parameters, and then dynamically adjusting the refractive index of the liquid crystal panel by applying a control voltage to achieve the focus adjustment of the optical system, collecting the adjusted image, and using a sharpness evaluation algorithm to compare the image quality. If the sharpness does not reach the preset threshold, the voltage control is iteratively optimized until the optimal focus is obtained. When the focus is determined, the system maintains the current voltage state and combines a scene change detection mechanism to automatically optimize the autofocus process. The present invention overcomes the problems of optical distortion, halos, and aberrations caused by the uniformity and response characteristics of liquid crystal molecules in the existing optical adjustment process of liquid crystal panels, improves the focusing accuracy and imaging quality, is particularly suitable for high-resolution and large-aperture application scenarios, and enhances the stability and adaptability of autofocus.

Description

Technical Field

[0001] The present invention relates to the technical field of TFT liquid crystal panels, and particularly relates to an autofocus method and system based on a TFT liquid crystal panel. Background Art

[0002] Autofocus based on a TFT liquid crystal panel is an autofocus method that uses thin-film transistor (TFT) liquid crystal technology to dynamically adjust the focal length of an optical system. Its basic principle is to control the voltage of the liquid crystal panel, change the arrangement state of liquid crystal molecules, thereby adjusting the refractive index or light transmittance of the liquid crystal panel, affecting the propagation path of light, and achieving automatic adjustment of the focal point position. Compared with the traditional mechanical focusing method, this technology does not require moving lenses, but relies on the action of an electric field to quickly adjust the focal length of the optical system, and has the advantages of small size, no mechanical wear, fast response speed, etc., so it is widely used in fields such as smart phones, micro projectors, AR / VR devices, and high-end optical instruments.

[0003] This autofocus technology usually combines an image sharpness analysis algorithm, and uses an imaging sensor (such as CMOS / CCD) to detect the image sharpness in real time, and adjusts the control voltage of the liquid crystal panel according to the change in sharpness to optimize the focal length position. In the specific implementation process, the system continuously collects the current image, calculates sharpness indexes (such as gradient contrast, Laplace transform value), and iteratively optimizes the control voltage until the image sharpness reaches the optimum. Compared with traditional mechanical focusing, this method not only reduces power consumption and structural complexity, but also can respond faster to focal length changes in a dynamic scene, improving the imaging quality, and is particularly suitable for application scenarios with high requirements for focusing speed and accuracy.

[0004] The prior art has the following deficiencies:

[0005] The optical adjustment of a liquid crystal panel relies on an externally applied electric field to control the alignment direction of liquid crystal molecules, thereby changing their refractive index or light transmittance and adjusting the focal position of the optical system. However, due to the uniformity error, response speed limitation, and non-linear characteristics of the liquid crystal material itself, under the action of an electric field, the liquid crystal molecules may not achieve completely consistent orientation, which can lead to deviations in the optical performance of local areas. Specifically, this non-uniformity can trigger light scattering and diffraction effects, causing additional bending or interference of the light passing through the liquid crystal panel, thereby reducing the imaging quality. In addition, since the response speed of liquid crystal molecules is affected by the change of the electric field, the phase adjustment may have non-linear deviations, resulting in unstable or difficult-to-precisely-control focal length adjustment. These problems are particularly obvious in optical systems with high resolution or large aperture, manifested as imaging defects such as blurred edges, halo effects, and aberrations in the picture, resulting in a decline in the overall image quality, especially more significantly in low-light environments or complex lighting conditions, thus limiting the application effect of liquid crystal autofocus technology. Summary of the Invention

[0006] The purpose of the present invention is to provide an autofocus method and system based on a TFT liquid crystal panel to solve the deficiencies in the background technology.

[0007] To achieve the above purpose, the present invention provides the following technical solutions: An autofocus method based on a TFT liquid crystal panel, comprising the following steps:

[0008] S1: Obtain the image data of the current shooting scene, analyze the clarity information of the image through an imaging sensor, and calculate the optimal focal length adjustment parameter according to the clarity information of the image;

[0009] S2: Apply a control voltage to the TFT liquid crystal panel to change the alignment state of the liquid crystal molecules, thereby dynamically adjusting the refractive index of the liquid crystal panel, and judge the change of the focal position of the optical system;

[0010] S3: Collect the adjusted image, and compare the image quality before and after adjustment based on the clarity evaluation algorithm. If the image clarity does not reach the preset threshold, iterate and adjust the control voltage until the optimal focal position is obtained;

[0011] S4: After determining the optimal focal position, maintain the current voltage state to maintain the stable focus of the optical system, and automatically optimize the focusing process according to the change of the detected scene to ensure the stability of the focusing state.

[0012] Preferably, in S1, the image data is obtained through an imaging sensor, and the Laplace transform method is used to calculate the image clarity information to determine whether the current focal length needs to be adjusted, including calculating the clarity evaluation value S of the image through the Laplace transform, and the expression is: ; In the formula, is the Laplace transform, P is the number of rows of the image, and Q is the number of columns of the image.

[0013] Preferably, the control voltage applied in S2 is calculated based on the focal length adjustment parameter, and the refractive index of the liquid crystal panel The relationship expression with the voltage V is: ; where: is the initial refractive index without voltage, and β is the voltage response coefficient of the liquid crystal material, which determines the amplitude of the refractive index change.

[0014] Preferably, the focal length is determined by the refractive index n of the liquid crystal panel, and the calculation formula is: ; where d is the equivalent optical thickness of the liquid crystal layer.

[0015] Preferably, S3 optimizes the focal length by iteratively adjusting the control voltage, and the calculation formula for adjusting the voltage V is: ; where: γ is the adaptive step size, represents the gradient of the calculated image sharpness change with voltage.

[0016] Preferably, calculate the current sharpness and the sharpness of the previous frame The change between them is: ; If ΔS>0, it means the image becomes clearer and the adjustment direction is correct; if ΔS<0, it means the image becomes blurred and the voltage direction or step size needs to be adjusted; set a preset sharpness threshold , if it satisfies ≥ , the focusing is completed, the control voltage is iteratively adjusted to optimize the focal position, and if the optimal focal length is not reached, the voltage V is continuously optimized.

[0017] Preferably, in S4, if the current sharpness is lower than the set threshold , it means the focus has shifted, and the optical flow algorithm is used to detect whether the position of the photographed object has changed. Specifically:

[0018] Use the imaging sensor to obtain two adjacent frames of images. Let the current frame grayscale image be , and let the previous frame grayscale image be ; Convert the two frames of images into grayscale images; calculate the gradients of the images in the x and y directions to obtain the spatial change information: ; Use the Sobel operator to calculate the gradient: ; where: ; Calculate the temporal gradient: ; Since a single pixel cannot solve for two unknowns u and v, the Lucas-Kanade method solves for the optimal solution within an n×n window: ; Let: ; Solve for the optical flow vector: ;

[0019] Determine whether the position of the photographed object has changed, and calculate the average value of the optical flow vectors of all feature points: ; Calculate the total amount of movement: ; Where: M represents the overall movement amount of the object, N is the number of feature points, set the motion detection threshold MT, if M > MT, it is determined that the photographed object has moved significantly, and autofocus is triggered.

[0020] The present invention also provides an autofocus system based on a TFT liquid crystal panel, including an image acquisition module, an optical adjustment module, an autofocus control module, and an adaptive optimization module;

[0021] Image acquisition module: Obtain the image data of the current shooting scene, analyze the clarity information of the image through an imaging sensor, and calculate the best focal length adjustment parameter according to the clarity information of the image;

[0022] Optical adjustment module: Apply a control voltage to the TFT liquid crystal panel to change the arrangement state of liquid crystal molecules, thereby dynamically adjusting the refractive index of the liquid crystal panel, and judge the change of the focal position of the optical system;

[0023] Autofocus control module: Acquire the adjusted image, and compare the image quality before and after adjustment based on the clarity evaluation algorithm. If the image clarity does not reach the preset threshold, iterate and adjust the control voltage until the optimal focal position is obtained;

[0024] Adaptive optimization module: After determining the best focal position, maintain the current voltage state to maintain the stable focus of the optical system, and automatically optimize the focusing process according to the change of the detected scene to ensure the stability of the focusing state.

[0025] In the above technical solution, the technical effects and advantages provided by the present invention:

[0026] 1. The present invention provides an autofocus method and system based on a TFT liquid crystal panel. By applying a control voltage to adjust the refractive index of the liquid crystal panel, dynamic focusing without a mechanical structure is achieved, overcoming the problems of wear and response hysteresis of traditional mechanical focusing systems. This method uses an imaging sensor to obtain image data and employs sharpness evaluation algorithms such as Laplace transform to calculate the optimal focal length adjustment parameters, so as to precisely control the change of the refractive index of the liquid crystal panel and make the focus adjustment more accurate. In addition, an iterative optimization mechanism is adopted. By comparing the image sharpness before and after adjustment in real time, the control voltage is continuously optimized to ensure that the system can achieve autofocus quickly and stably. It is especially suitable for high-resolution and large-aperture optical systems, significantly improving the imaging quality and reducing problems such as edge blurring, halo effect, and aberration.

[0027] 2. The present invention also combines an optical flow detection algorithm to intelligently sense the movement of the shooting object, ensuring that it can refocus quickly when the scene changes and improving the intelligence level of autofocus. By calculating the optical flow vector, the system can accurately judge the overall movement trend of the shooting object and trigger autofocus adjustment when significant movement is detected to ensure that the picture remains clear. At the same time, a temperature compensation mechanism is adopted to overcome the sensitivity of liquid crystal materials to environmental temperature and ensure the stability of the focal length during long-term use. The present invention not only improves the accuracy and response speed of autofocus, but also enhances the adaptability to complex environments, making it have wide application value in fields such as smart phones, micro projectors, and high-end optical instruments. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0029] Figure 1 It is the flowchart of the method of the present invention.

[0030] Figure 2 It is the system module diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0032] Example 1, please refer toFigure 1 As shown in Figure 1 , an automatic focusing method based on a TFT liquid crystal panel in this embodiment includes the following steps:

[0033] S1: Obtain the image data of the current shooting scene, analyze the clarity information of the image through an imaging sensor, and calculate the optimal focal length adjustment parameter according to the clarity information of the image;

[0034] S2: Apply a control voltage to the TFT liquid crystal panel to change the arrangement state of liquid crystal molecules, thereby dynamically adjusting the refractive index of the liquid crystal panel, and judge the change of the focal position of the optical system;

[0035] S3: Collect the adjusted image, and compare the image quality before and after adjustment based on the clarity evaluation algorithm. If the image clarity does not reach the preset threshold, iterate and adjust the control voltage until the optimal focal position is obtained;

[0036] S4: After determining the optimal focal position, maintain the current voltage state to maintain the stable focusing of the optical system, and automatically optimize the focusing process according to the change of the detected scene to ensure the stability of the focusing state.

[0037] In S1, a CMOS or CCD sensor is used to capture the image I(x, y) of the current scene. The image data is stored as a grayscale image , which is used for subsequent clarity calculation. The formula is as follows: ; respectively represent the red, green, and blue channel values at the pixel point (x, y).

[0038] Calculate the clarity evaluation value S of the image through the Laplace transform. The expression is: ; is the Laplace transform (Laplacian) using a 3×3 filter kernel, P is the number of rows of the image (the number of pixels in the vertical direction), and Q is the number of columns of the image (the number of pixels in the horizontal direction). The larger the S value, the clearer the image.

[0039] Define the current focal length state as , the refractive index of the liquid crystal panel is , the target clarity threshold , then the steps to adjust the focal length are:

[0040] Calculate the new focal length. Let be the current clarity value. If , it is necessary to adjust the focal length f to improve the clarity; adjust the focal length through the gradient ascent method: ; where: α is the step size parameter (adaptive adjustment); is calculated from the change of image clarity: ;

[0041] Calculate the voltage adjustment value of the liquid crystal panel. Assume that the focal length f of the liquid crystal panel is controlled by the refractive index n, and n is determined by the driving voltage V: ; where d is the thickness of the liquid crystal layer.

[0042] Adjust the refractive index through voltage: ; where: is the initial refractive index, and β is the response coefficient of the liquid crystal refractive index to voltage.

[0043] Calculate the required voltage adjustment value: ; where γ is the adaptive step size, Calculate the gradient of the image sharpness with respect to voltage.

[0044] Optimize f and V iteratively until the sharpness reaches the preset threshold .

[0045] In S2, step 1: Apply the initial control voltage: According to the calculated optimal focal length adjustment parameters, apply the initial control voltage to the TFT liquid crystal panel , driving the orientation change of liquid crystal molecules.

[0046] Step 2: Adjust the arrangement of liquid crystal molecules: After the voltage acts on the liquid crystal layer, the liquid crystal molecules are rearranged, changing the equivalent refractive index of the liquid crystal layer , and the refractive index is calculated as: ; where: is the initial refractive index without voltage, and β is the voltage response coefficient of the liquid crystal material, which determines the refractive index change amplitude.

[0047] Step 3: Adjust the focal length of the optical system: The change in the refractive index of the liquid crystal layer affects the light propagation path, causing the equivalent focal length of the optical system to change, and the calculation formula is: ; where d is the equivalent optical thickness of the liquid crystal layer.

[0048] Step 4: Obtain the adjusted image data: After adjusting the focal length, obtain a new image through the imaging sensor , and compare the imaging effects before and after adjustment.

[0049] Step 5: Determine the change in the focus position: Use the image sharpness evaluation algorithm (such as gradient contrast, Laplace transform) to calculate the current sharpness value , and compare it with the previous sharpness value : If > , it means that the focus moves towards the optimal position, and the voltage can be further fine-tuned to optimize the focus. If < , it indicates that the focus deviates from the optimal position, and the voltage direction or step size needs to be adjusted. If reaches the preset threshold , it is considered that the focusing is completed, and the current voltage value is locked .

[0050] In S3, calculate the current sharpness and the sharpness of the previous frame The change between them is: ; if ΔS>0, it means the image becomes clearer and the adjustment direction is correct; if ΔS<0, it means the image becomes blurred and the voltage direction or step size needs to be adjusted. Set the preset sharpness threshold , if it satisfies ≥ , the focusing is completed, iteratively adjust the control voltage to optimize the focus position. If the optimal focal length is not reached, continue to optimize the voltage V.

[0051] To ensure the focusing accuracy, the system sets a preset sharpness threshold . When the current sharpness reaches or exceeds , it indicates that the optimal focus has been obtained, and the system locks the current voltage to end the focal length adjustment process. If still does not reach the threshold, the system continuously iteratively adjusts the control voltage V, and by finely optimizing the refractive index, makes the focus of the optical system closer to the best imaging position. This method ensures the accuracy and stability of autofocus, and avoids focusing failure caused by insufficient or excessive adjustment.

[0052] The advantage of this method is that it performs dynamic feedback adjustment through the sharpness change amount ΔS, can quickly judge the focusing direction, and adaptively adjust the voltage step size to improve the focusing efficiency. At the same time, the preset sharpness threshold ensures that the system can quickly and stably lock after reaching the best focus, preventing focal length oscillation caused by excessive adjustment. Compared with traditional fixed-step or blind scanning methods, the iterative optimization strategy of the present invention can reduce the calculation amount, improve the response speed, enable the system to obtain higher-quality imaging effects in various shooting environments, and is particularly suitable for dynamic scenes or high-resolution imaging applications.

[0053] In S4, if the image sharpness ≥ , it is considered that the best focus position has been obtained. At this time, keep the current voltage Vopt to stabilize the refractive index of the liquid crystal panel to maintain the best focusing state of the optical system.

[0054] Continuously monitor the input image of the imaging sensor, analyze the dynamic changes of the scene content, and judge whether the focal length needs to be readjusted. The scene change detection method includes: if the current sharpness is lower than the set threshold , it indicates that the focus may shift. The optical flow algorithm is used to detect whether the position of the photographed object has changed. Specifically:

[0055] Use an imaging sensor (CMOS / CCD) to obtain two adjacent frames of images: Let the current frame grayscale image be , and let the previous frame grayscale image be ; Convert the two frames of images into grayscale images to reduce the computational complexity; Calculate the gradients of the images in the x and y directions to obtain the spatial variation information: ; Use the Sobel operator to calculate the gradients: ; Where: ; Calculate the temporal gradient, that is, calculate the pixel difference between the two frames of images, and the expression is: .

[0056] The optical flow assumes that the grayscale value of the pixel remains unchanged during the movement, and satisfies the optical flow constraint equation: ; Where: u and v are the movement speeds of the pixel in the x and y directions (optical flow vectors) is the image gradient, is the temporal gradient;

[0057] Since a single pixel cannot solve two unknowns (u, v), the Lucas-Kanade method solves the optimal solution within an n×n window: ; Let: ; Solve the optical flow vector: ;

[0058] Judge whether the position of the photographed object has changed, and calculate the mean value of the optical flow vectors of all feature points: ; Calculate the total movement amount: ; Where: M represents the overall movement amount of the object, N is the number of feature points, and a motion detection threshold MT is set. If M > MT, it is determined that the photographed object has moved significantly, and autofocus is triggered.

[0059] In this embodiment, by acquiring the image data of the current shooting scene, analyzing the image sharpness information, and calculating the optimal focal length adjustment parameters. Subsequently, a control voltage is applied to the TFT liquid crystal panel to change the arrangement state of the liquid crystal molecules, dynamically adjust the refractive index of the liquid crystal panel, and judge the change of the focal position of the optical system. On this basis, the adjusted image is collected, and the image quality before and after the adjustment is compared based on the sharpness evaluation algorithm. If the sharpness does not reach the preset threshold, the control voltage is iteratively adjusted until the optimal focal position is obtained. When the best focus is determined, the current voltage state is maintained to maintain the stable focus of the optical system, and the autofocus process is automatically optimized according to the change of the detection scene to ensure the continuous stability of the focus state.

[0060] Example 2, please refer to Figure 2 As shown, the automatic focusing system based on the TFT liquid crystal panel in this embodiment includes an image acquisition module, an optical adjustment module, an automatic focusing control module, and an adaptive optimization module;

[0061] Image acquisition module: Obtain the image data of the current shooting scene, analyze the clarity information of the image through the imaging sensor, and calculate the optimal focal length adjustment parameter according to the clarity information of the image;

[0062] Optical adjustment module: Apply a control voltage to the TFT liquid crystal panel to change the arrangement state of the liquid crystal molecules, thereby dynamically adjusting the refractive index of the liquid crystal panel, and judging the change of the focal position of the optical system;

[0063] Automatic focusing control module: Collect the adjusted image, and compare the image quality before and after adjustment based on the clarity evaluation algorithm. If the image clarity does not reach the preset threshold, iterate and adjust the control voltage until the optimal focal position is obtained;

[0064] Adaptive optimization module: After determining the optimal focal position, maintain the current voltage state to maintain the stable focusing of the optical system, and automatically optimize the focusing process according to the change of the detected scene to ensure the stability of the focusing state.

[0065] The above formulas are all dimensionless and take their numerical calculations. The formula is obtained by software simulation of a large amount of collected data to get a formula closest to the real situation. The preset parameters in the formula are set by those skilled in the art according to the actual situation.

[0066] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wired or wireless (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that contains one or more collections of available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, or magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0067] It should be understood that the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood by referring to the context before and after.

[0068] It should be understood that in various embodiments of the present application, the magnitudes of the sequence numbers of the above processes do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0069] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this document can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0070] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application.

Claims

1. An autofocus method based on a TFT liquid crystal panel, characterized in that: It includes the following steps: S1: Obtain the image data of the current shooting scene, analyze the clarity information of the image through an imaging sensor, and calculate the best focal length adjustment parameter according to the clarity information of the image; S2: Apply a control voltage to the TFT liquid crystal panel to change the arrangement state of liquid crystal molecules, thereby dynamically adjusting the refractive index of the liquid crystal panel, and judge the change of the focal position of the optical system; The control voltage applied in S2 is calculated based on the focal length adjustment parameter, and the refractive index of the liquid crystal panel The relational expression between the refractive index and the voltage V is: ; where: is the initial refractive index without voltage, and β is the voltage response coefficient of the liquid crystal material, which determines the amplitude of the refractive index change; S3: Collect the adjusted image, and compare the image quality before and after adjustment based on the clarity evaluation algorithm. If the image clarity does not reach the preset threshold, iteratively adjust the control voltage until the optimal focal position is obtained; S4: After determining the best focal position, maintain the current voltage state to maintain the stable focusing of the optical system, and automatically optimize the focusing process according to the change of the detected scene to ensure the stability of the focusing state; Specifically include: If the current clarity is lower than the set threshold , it indicates that the focus has shifted. Use the optical flow algorithm to detect whether the position of the shooting object has changed. Specifically: Acquire two adjacent frames of images using an imaging sensor. Let the grayscale image of the current frame be , and let the grayscale image of the previous frame be ; Convert the two frames of images into grayscale images; Calculate the gradients of the images in the x and y directions to obtain spatial variation information: ; Calculate the gradients using the Sobel operator: ; Where: ; Calculate the temporal gradient , and the expression is: ; Since two unknowns u and v cannot be solved for a single pixel, solve for the optimal solution within an n×n window using the Lucas-Kanade method: ; Let: ; Solve for the optical flow vector: ; Determine whether the position of the shooting object has changed, and calculate the average optical flow vector of all feature points: ; Calculate the total amount of movement: ; Where: M represents the overall movement amount of the object, N is the number of feature points, set the motion detection threshold MT, if M > MT, it is determined that the shooting object has moved significantly, and autofocus is triggered.

2. The automatic focusing method based on a TFT liquid crystal panel according to claim 1, wherein: The S1 obtains image data through an imaging sensor and calculates image sharpness information by using the Laplace transform method to determine whether the current focal length needs to be adjusted, including calculating the sharpness evaluation value S of the image by using the Laplace transform, and the expression is: ; in the formula, is the Laplace transform, P is the number of rows of the image, and Q is the number of columns of the image.

3. The automatic focusing method based on a TFT liquid crystal panel according to claim 1, wherein: The focal length is determined by the refractive index n of the liquid crystal panel, and the calculation formula is: ; where d is the equivalent optical thickness of the liquid crystal layer.

4. The automatic focusing method based on a TFT liquid crystal panel according to claim 3, characterized in that: The S3 optimizes the focal length by iteratively adjusting the control voltage, and the calculation formula for the adjustment voltage V is: where γ is the adaptive step size, represents the gradient of the calculated image sharpness varying with the voltage.

5. The automatic focusing method based on a TFT liquid crystal panel according to claim 4, wherein: Calculate the current clarity and the clarity of the previous frame The change between them is as follows: ; If ΔS > 0, it means the image becomes clearer and the adjustment direction is correct; if ΔS < 0, it means the image becomes blurred and the voltage direction or step size needs to be adjusted; Set a preset clarity threshold , if it satisfies ≥ , the focusing is completed, iteratively adjust the control voltage to optimize the focus position. If the optimal focal length is not reached, continue to optimize the voltage V.

6. An autofocus system based on a TFT liquid crystal panel, which is used to implement an autofocus method based on a TFT liquid crystal panel according to any one of claims 1-5, characterized in that: It includes an image acquisition module, an optical adjustment module, an automatic focusing control module, and an adaptive optimization module; Image acquisition module: Obtain the image data of the current shooting scene, analyze the clarity information of the image through an imaging sensor, and calculate the best focal length adjustment parameter according to the clarity information of the image; Optical adjustment module: Apply a control voltage to the TFT liquid crystal panel to change the arrangement state of liquid crystal molecules, thereby dynamically adjusting the refractive index of the liquid crystal panel, and judge the change of the focal position of the optical system; Automatic focusing control module: Collect the adjusted image, and compare the image quality before and after adjustment based on the clarity evaluation algorithm. If the image clarity does not reach the preset threshold, iteratively adjust the control voltage until the optimal focal position is obtained; Adaptive optimization module: After determining the best focal position, maintain the current voltage state to maintain the stable focusing of the optical system, and automatically optimize the focusing process according to the change of the detected scene to ensure the stability of the focusing state.

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