CN118590755A - Automatic focusing method, device, electronic device and storage medium for visible light television - Google Patents

Abstract

The present application discloses an automatic focusing method, device, electronic device and storage medium for a visible light television, and belongs to the field of image processing technology. The method includes: controlling the lens to move at a preset speed with a preset step length, obtaining first image data shot at different positions for a moving object during the movement of the lens; calculating a first clarity evaluation value and a second clarity evaluation value; obtaining a first relationship curve representing the relationship between the clarity of the lens at different positions and the first image data according to the first clarity evaluation value and the second clarity evaluation value; determining the focus position according to the first target position corresponding to the image data with the highest clarity in the first relationship curve, so as to control the lens to move to the focus position. The present application determines the focus position based on the clarity evaluation values of the images shot at different positions of the moving object by the lens during the movement, and can adapt to automatic focusing in different scenes, thereby improving the accuracy of automatic focusing.

Description

Automatic focusing method, device, electronic device and storage medium for visible light television

Technical Field

The present application belongs to the field of image processing technology, and in particular relates to an automatic focusing method, device, electronic device and storage medium for a visible light television.

Background Art

In various optical imaging systems, the importance of focusing technology is self-evident. The widespread application of autofocus technology enables us to obtain clear, high-quality images more conveniently in our daily life and work, providing a good foundation for subsequent image analysis and processing. From ordinary digital cameras and camcorders to professional space remote sensing systems and biomedical imaging, autofocus technology plays an indispensable role and promotes the development and progress of various fields.

Phase detection autofocus is a commonly used autofocus technology that uses pixels on the camera sensor to detect phase differences between different areas in the image to determine the focus position.

However, in low-light conditions or when shooting high-speed moving objects, phase detection autofocus often performs poorly, and is prone to inaccurate focus or even loss of focus, affecting the shooting effect.

Summary of the invention

The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes an automatic focusing method, device, electronic device and storage medium for a visible light television to improve the accuracy of automatic focusing.

In a first aspect, the present application provides an automatic focusing method for a visible light television, comprising:

Controlling the lens to move at a preset speed with a preset step length, and acquiring first image data captured at different positions of the moving object during the movement of the lens;

Calculating a first clarity evaluation value corresponding to a first target area in the first image data and a second clarity evaluation value corresponding to a second target area in the first image data according to gradients of pixels in different directions;

Based on a first weight of the first target area and a second weight of the second target area, the clarity of the first target image is calculated according to the first clarity evaluation value and the second clarity evaluation value, so as to obtain a first relationship curve representing the relationship between the clarity of the first image data at different positions of the lens;

The focus position is determined according to the first target position corresponding to the image data with the highest definition in the first relationship curve, so as to control the lens to move to the focus position.

According to the automatic focusing method of a visible light television of the present application, a lens is controlled to move at a preset speed with a preset step length, and first image data captured for a moving object at different positions during the movement of the lens is obtained; a first clarity evaluation value corresponding to a first target area in the first image data and a second clarity evaluation value corresponding to a second target area in the first image data are calculated according to the gradients of pixels in different directions; the clarity of the first target image is calculated according to the first clarity evaluation value and the second clarity evaluation value based on a first weight of the first target area and a second weight of the second target area, and a first relationship curve representing the relationship between the clarity of the lens at different positions and the first image data is obtained; a focus position is determined according to a first target position corresponding to image data with the highest clarity in the first relationship curve, so as to control the lens to move to the focus position. The embodiment of the present application can continuously track the moving object by acquiring image data captured at different positions of the moving object during the movement of the lens, and can maintain focus even if the speed or direction of the object changes. The clarity evaluation values of the first target area and the second target area are calculated respectively by performing pixel gradient analysis on the image data. Since the two areas represent different features or importance in the image, their clarity evaluation values can be weighted according to their respective weights to calculate the clarity of the overall image, and then the position where the image data with the highest clarity is captured is found, and the focus position is determined based on the position. This method does not have too high requirements on factors such as light and the object being photographed, and can adapt to automatic focusing in different scenarios, thereby improving the accuracy of automatic focusing.

According to an embodiment of the present application, controlling the lens to move at a preset speed with a preset step length to obtain first image data captured at different positions of the moving object during the movement of the lens includes:

Controlling the lens to move to a focus starting position;

The lens is controlled to move from a focus start position to a focus stop position at a preset speed with a preset step length, and first image data captured at different positions of the lens during the movement of the lens for the moving object is obtained.

This embodiment can capture image data at different positions by controlling the lens to move between the focus start position and the focus stop position with a preset step length, thereby facilitating finding the focus position.

According to an embodiment of the present application, the step of calculating a first clarity evaluation value corresponding to a first target area in the first image data and a second clarity evaluation value corresponding to a second target area in the first image data according to gradients of pixels in different directions includes:

Buffering three rows of pixels in the first image data;

Fill the three rows of pixels into a data template with a size of 3*3;

When the pixel in the data template is in the first target area or the second target area, the sum of the gradient values of each pixel in the data template in different directions is calculated;

The first definition evaluation value is obtained by accumulating the sum of the gradient values of each pixel in the first target area in different directions; and the second definition evaluation value is obtained by accumulating the sum of the gradient values of each pixel in the second target area in different directions.

In this embodiment, by caching three rows of pixels of the image data each time, it is helpful to improve the timeliness of calculating the clarity of the image data. By generating a data template, the calculation of pixel gradients can be better organized and processed, reducing the complexity of the calculation. Furthermore, calculating the gradient values of pixels in different directions helps to obtain gradient information more comprehensively, thereby better describing the texture and structural characteristics of the image data and improving the accuracy of clarity evaluation.

According to an embodiment of the present application, the first target area is an area in the first image data that is within a preset range of the first image data center, and the second target area is an area in the first image data that is outside the preset range of the first image data center;

Alternatively, the first target area is an area where the moving object is located in the first image data, and the second target area is an area excluding the moving object in the first image data.

In this embodiment, since the central area of the image is often an important visual focus and usually contains key information, when the first target area is defined as an area within the central preset range and the second target area is an area outside the central preset range, this method can increase the focus priority in the central area of the image. On the other hand, the first target area is defined as the area where the moving object is located, and the second target area is the area excluding the moving object, which can automatically identify and focus on the dynamic elements in the image, and by giving priority to the clarity of the moving object, the viewing experience can be improved, so that the device can automatically adapt to different viewing scenarios and user needs.

According to an embodiment of the present application, determining the focus position according to the first target position corresponding to the image data with the highest definition in the first relationship curve so as to control the lens to move to the focus position includes:

determining the first target position as a focus position;

Controlling the lens to move from a focus stop position to a focus start position;

Taking the focus start position as a starting point, the lens is controlled to move to the focus position.

In this embodiment, the first target position is the position where the image data has the highest clarity, so that the first target position can be determined as the focus position. Returning the lens to the focus starting position and then moving it to the focus position is beneficial to eliminating the gear backlash of the motor and improving the accuracy of automatic focusing.

According to an embodiment of the present application, determining the focus position according to the first target position corresponding to the image data with the highest definition in the first relationship curve so as to control the lens to move to the focus position includes:

Controlling the lens to move from a focus stop position to a focus start position with a preset step length, and acquiring second image data captured at different positions during the movement of the lens;

Calculating the definition of the second image data to obtain a second relationship curve representing the relationship between the definition of the second image data and the lens at different positions;

The focus position is determined according to the second target position corresponding to the image data with the highest definition in the second relationship curve and the first target position, so as to control the lens to move to the focus position.

In this embodiment, since the motor that controls the movement of the lens may have gear backlash, the clarity of the image data captured during the process of the lens moving from the focus stop position to the focus start position can be calculated, and the second target position corresponding to the image data with the highest clarity during this shooting process can be determined. Then, the focus position is determined by comprehensively considering the first target position and the second target position, thereby further improving the accuracy of automatic focusing.

According to an embodiment of the present application, determining the focus position according to the second target position corresponding to the image data with the highest definition in the second relationship curve and the first target position so as to control the lens to move to the focus position includes:

determining an intermediate position between the first target position and the second target position as the focus position;

Taking the focus start position as a starting point, the lens is controlled to move to the focus position.

In this embodiment, the image data captured between the first target position and the second target position has a relatively high clarity as a whole, and thus determining the middle position between the first target position and the second target position as the focus position can improve the accuracy of the automatic focusing.

In a second aspect, the present application provides an automatic focusing device for a visible light television, comprising:

An acquisition module, used to control the lens to move at a preset speed with a preset step length, and acquire first image data captured at different positions of the moving object during the movement of the lens;

A first calculation module, used for calculating a first clarity evaluation value corresponding to a first target area in the first image data and a second clarity evaluation value corresponding to a second target area in the first image data according to gradients of pixels in different directions;

a second calculation module, configured to calculate the clarity of the first target image according to the first clarity evaluation value and the second clarity evaluation value based on a first weight of the first target area and a second weight of the second target area, and obtain a first relationship curve representing a relationship between the clarity of the first image data at different positions of the lens;

The determination module is used to determine the focus position according to the first target position corresponding to the image data with the highest definition in the first relationship curve, so as to control the lens to move to the focus position.

According to the automatic focusing device of the visible light television of the present application, the lens is controlled to move at a preset speed with a preset step length, so as to obtain first image data shot for a moving object at different positions during the movement of the lens; a first clarity evaluation value corresponding to a first target area in the first image data and a second clarity evaluation value corresponding to a second target area in the first image data are calculated according to the gradients of pixels in different directions; the clarity of the first target image is calculated according to the first clarity evaluation value and the second clarity evaluation value based on a first weight of the first target area and a second weight of the second target area, so as to obtain a first relationship curve representing the relationship between the clarity of the lens at different positions and the first image data; and a focus position is determined according to a first target position corresponding to the image data with the highest clarity in the first relationship curve, so as to control the lens to move to the focus position. The embodiment of the present application can continuously track the moving object by acquiring image data captured at different positions of the moving object during the movement of the lens, and can maintain focus even if the speed or direction of the object changes. The clarity evaluation values of the first target area and the second target area are calculated respectively by performing pixel gradient analysis on the image data. Since the two areas represent different features or importance in the image, their clarity evaluation values can be weighted according to their respective weights to calculate the clarity of the overall image, and then the position where the image data with the highest clarity is captured is found, and the focus position is determined based on the position. This method does not have too high requirements on factors such as light and the object being photographed, and can adapt to automatic focusing in different scenes, thereby improving the accuracy of automatic focusing.

In a third aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the automatic focusing method as described in the first aspect above when executing the computer program.

In a fourth aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the automatic focusing method as described in the first aspect above.

In a fifth aspect, the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the automatic focusing method as described in the first aspect above.

In a sixth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the automatic focusing method as described in the first aspect above.

The above one or more technical solutions in the embodiments of the present application have at least one of the following technical effects:

According to the automatic focusing method of a visible light television of the present application, a lens is controlled to move at a preset speed with a preset step length, and first image data captured for a moving object at different positions during the movement of the lens is obtained; a first clarity evaluation value corresponding to a first target area in the first image data and a second clarity evaluation value corresponding to a second target area in the first image data are calculated according to the gradients of pixels in different directions; the clarity of the first target image is calculated according to the first clarity evaluation value and the second clarity evaluation value based on a first weight of the first target area and a second weight of the second target area, and a first relationship curve representing the relationship between the clarity of the lens at different positions and the first image data is obtained; a focus position is determined according to a first target position corresponding to image data with the highest clarity in the first relationship curve, so as to control the lens to move to the focus position. The embodiment of the present application can continuously track the moving object by acquiring image data captured at different positions of the moving object during the movement of the lens, and can maintain focus even if the speed or direction of the object changes. The clarity evaluation values of the first target area and the second target area are calculated respectively by performing pixel gradient analysis on the image data. Since the two areas represent different features or importance in the image, their clarity evaluation values can be weighted according to their respective weights to calculate the clarity of the overall image, and then the position where the image data with the highest clarity is captured is found, and the focus position is determined based on the position. This method does not have too high requirements on factors such as light and the object being photographed, and can adapt to automatic focusing in different scenarios, thereby improving the accuracy of automatic focusing.

Furthermore, in some embodiments, by controlling the lens to move between the focus start position and the focus stop position at a preset step length, image data at different positions can be captured, which is helpful for finding the focus position.

Furthermore, in some embodiments, caching three rows of pixels of the image data each time is helpful to improve the timeliness of calculating the clarity of the image data. By generating a data template, the calculation of pixel gradients can be better organized and processed, reducing the complexity of the calculation. Furthermore, calculating the gradient values of pixels in different directions helps to obtain gradient information more comprehensively, thereby better describing the texture and structural features of the image data and improving the accuracy of clarity evaluation.

Furthermore, in some embodiments, since the central area of the image is often an important visual focus and usually contains key information, when the first target area is defined as an area within the central preset range and the second target area is an area outside the central preset range, this method can increase the focus priority on the central area of the image. On the other hand, the first target area is defined as the area where the moving object is located, and the second target area is the area excluding the moving object, which can automatically identify and focus on the dynamic elements in the image, and by giving priority to the clarity of the moving object, the viewing experience can be improved, so that the device can automatically adapt to different viewing scenarios and user needs.

Furthermore, in some embodiments, the first target position is the position where the image data has the highest clarity, so that the first target position can be determined as the focus position, and returning the lens to the focus starting position and then moving to the focus position is beneficial to eliminating the gear backlash of the motor and improving the accuracy of automatic focusing.

Furthermore, in some embodiments, since the motor that controls the movement of the lens may have gear backlash, the clarity of the image data captured during the process of the lens moving from the focus stop position to the focus start position can be calculated, and the second target position corresponding to the image data with the highest clarity during this shooting process can be determined. Then, the focus position is determined by comprehensively considering the first target position and the second target position, thereby further improving the accuracy of automatic focusing.

Furthermore, in some embodiments, the image data captured between the first target position and the second target position has a relatively high clarity as a whole, and thus determining the middle position between the first target position and the second target position as the focus position can improve the accuracy of autofocusing.

Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and/or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

FIG1 is a schematic flow chart of an automatic focusing method for a visible light television provided in an embodiment of the present application;

FIG2 is a diagram showing a relationship curve between lens position and image data clarity in an embodiment of the present application;

FIG3 is a schematic diagram of a lens movement trajectory during the automatic focusing process of an embodiment of the present application;

FIG4 is a schematic diagram of the structure of an automatic focusing device for a visible light television provided in an embodiment of the present application;

FIG. 5 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

DETAILED DESCRIPTION

The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

The terms "first", "second", etc. in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, 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 represents at least one of the connected objects, and the character "/" generally indicates that the objects associated with each other are in an "or" relationship.

Autofocus is achieved through an autofocus system in the lens. This system uses sensors to detect the focus point in the scene, and then adjusts the lens position through a motor so that the focus falls accurately on the subject, thereby achieving the autofocus function.

Phase detection autofocus technology uses lenses and mirrors in the optical system to split the light into two paths, and then compares the phase difference between the two paths to determine the focus position. Phase detection autofocus can usually focus quickly and accurately, and is suitable for autofocus needs in many different scenarios.

However, in low light conditions, insufficient light may cause the camera sensor to receive a weak signal, making it difficult for the phase detection system to accurately detect the phase difference, thus affecting the accuracy of focusing. At this time, the camera may not be able to quickly and accurately determine the focus position, resulting in inaccurate focus or out of focus.

When shooting high-speed moving objects, the rapid movement of the object will cause the position of the object in the image to change rapidly, and the phase detection system may not be able to track and adjust the focus position in time, resulting in inaccurate focus or loss of focus. In this case, the camera may not be able to maintain the stability of the focus during the movement of the object, affecting the shooting effect.

Therefore, in low-light conditions or when shooting high-speed moving objects, phase detection autofocus performs poorly, and is prone to inaccurate focus or even loss of focus, affecting the quality and accuracy of the shooting effect.

The present application takes into account that if it is possible to calculate the clarity of image data captured by the lens at different positions from the perspective of image processing, and then determine the focus position based on the shooting position where the image data with the highest clarity is located, it is expected to solve the problem of poor focusing effect in low light or when shooting high-speed moving objects in the prior art.

In conjunction with the accompanying drawings, the automatic focusing method, device, electronic device and storage medium of the visible light television provided in the embodiments of the present application are described in detail through specific embodiments and their application scenarios.

The automatic focusing method of a visible light television may be applied to a terminal, and may be specifically executed by hardware or software in the terminal.

The terminal includes, but is not limited to, a portable communication device such as a mobile phone or tablet computer with a touch-sensitive surface (e.g., a touch screen display and/or a touch pad). It should also be understood that in some embodiments, the terminal may not be a portable communication device, but a desktop computer with a touch-sensitive surface (e.g., a touch screen display and/or a touch pad).

In the following various embodiments, a terminal including a display and a touch-sensitive surface is described. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, a mouse and a joystick.

The automatic focusing method provided in the embodiment of the present application, the execution subject of the automatic focusing method of the visible light television can be an electronic device or a functional module or functional entity in the electronic device that can implement the automatic focusing method. The electronic devices mentioned in the embodiment of the present application include but are not limited to mobile phones, tablet computers, computers, cameras and wearable devices, etc. The automatic focusing method of the visible light television provided in the embodiment of the present application is explained below using the electronic device as an example of the execution subject.

As shown in FIG. 1 , the automatic focusing method of the visible light television includes: step 110 , step 120 , step 130 and step 140 .

Step 110: Control the lens to move at a preset speed with a preset step length, and obtain first image data captured at different positions of the moving object during the movement of the lens.

Visible light television is a photoelectric sensor used to convert visible light signals into electronic signals. It can be used to obtain image information of the target to help users monitor and observe. Visible light television can capture optical images of scenes through devices such as visible light cameras or cameras. These devices usually contain one or more image sensors (such as CCD or CMOS sensors) that can convert light signals into electrical signals. The analog-to-digital converter (ADC) inside the camera converts the analog image signals captured by the sensor into digital signals. These digital signals represent the pixel values of the image, usually stored in the form of grayscale values or color values.

In visible light television, the camera may generally include a lens assembly and a drive device. The lens assembly includes optical elements such as a convex lens and a concave lens, which are used to adjust the convergence and divergence of light to achieve focus and imaging. The drive device may be used to control the movement of the lens assembly to achieve fine-tuning and adjustment of focus. The drive device may be a drive motor.

In the embodiment of the present application, the lens may be a focusable lens (Zoom Lens) or a zoom lens (PrimeLens), and the position of the lens may be moved by a driving device to achieve focusing.

In an embodiment of the present application, the first image data can be obtained by driving the lens to move within a certain range and photographing the moving object during the movement, finding the position of the lens when the photographed image is in focus, and moving the lens to this position to complete the focusing. Specifically, the lens can be controlled to move at a preset speed with a preset step length, and the first image data can be photographed at different positions during the movement of the lens. For example, the distance from the starting position to the end position of the lens movement is set to 4000AD values, the speed can be set to a step length of 200AD values per frame, and the frame rate of the camera is 30Hz, then multiple frames of image data can be obtained during the movement of the lens. By continuously photographing a moving object, it is possible to track the moving object in real time, and the focus can be maintained even if the object moves quickly or suddenly changes direction.

In some embodiments, controlling the movement of the lens with a preset step length to obtain image data captured at different positions during the movement of the lens includes:

Control the lens to move to the focus starting position;

The lens is controlled to move from a focus start position to a focus stop position at a preset speed with a preset step length, and first image data captured at different positions of the lens during the movement of the lens is obtained.

This embodiment can capture image data at different positions by controlling the lens to move between the focus start position and the focus stop position with a preset step length, thereby facilitating finding the focus position.

Step 120 : Calculate a first clarity evaluation value corresponding to a first target area in the first image data and a second clarity evaluation value corresponding to a second target area in the first image data according to gradients of pixels in different directions.

Gradient refers to the concept of the rate of change or slope of a function at a certain point in mathematics and physics. In digital image processing, gradient usually refers to the rate of change of pixel values in an image or the direction of intensity change. Considering that clear images usually have more edge and texture details, gradient calculation can capture edge and texture details, which can be used to judge the clarity of the image. Specifically, in an image, edges are usually formed by places where pixel values change sharply. By calculating the gradient, the locations of these pixel value changes can be detected, thereby finding the edges in the image. Furthermore, clear images usually contain more details and textures, which are reflected in the image as changes in pixel values. Calculating the gradient can help capture these details and textures.

For example, suppose there is an image containing a black straight line and a uniform gray background. The edge of the straight line is very clear, while the background has no obvious changes. By calculating the gradient of the image pixels, it can be found that the gradient value is very high at the position of the straight line, while the gradient value is close to zero in the background area. Such a gradient distribution can be used to judge the clarity of the image, because a clear image will have obvious gradient changes.

In an embodiment of the present application, the gradient of the pixel in different directions can be calculated first, and then the clarity of the image data can be determined based on the gradient. Specifically, the different directions can be any two or more directions of the pixel such as the horizontal direction (0 degrees), 45 degrees, vertical direction (90 degrees), 135 degrees, 180 degrees, or the different directions can also be multiple directions at other angles. After determining the direction to be calculated, the gradient of the pixel in different directions can be obtained by calculation. Assuming that a certain pixel position is (x, y), the gradient of the pixel in the horizontal direction is:

G _0ο ＝I(x+1,y)-I(x-1,y)

Wherein, G _0ο represents the gradient value of the pixel in the horizontal direction, and I(x, y) represents the pixel value of the image at the position (x, y).

Similarly, the gradient of the pixel in the vertical direction is:

G _90ο =I(x,y+1)-I(x,y-1)

Wherein, G _90ο represents the gradient value of the pixel in the horizontal direction.

Similarly, adaptive changes based on the above formula can be used to calculate the gradient values of pixels in other directions.

After calculating the gradient of one pixel in different directions, the gradients in different directions can be added to obtain the total gradient value of the pixel, which can reflect the image texture and edge information of the pixel. Furthermore, the total gradient values of all pixels in the image or pixels within a certain range can be counted, that is, the total gradient values of these pixels are added to obtain the clarity evaluation value of the image data. The larger the value obtained by adding the total gradient values of these pixels, the more obvious the changes in the edge and texture of the image, and the clearer the image.

In the embodiment of the present application, the clarity evaluation values of the first target area and the second target area can be calculated respectively. Specifically, the total gradient value of each pixel in the first target area can be calculated to obtain the first clarity evaluation value corresponding to the first target area; the total gradient value of each pixel in the second target area can be calculated to obtain the second clarity evaluation value corresponding to the second target area.

In some embodiments, the first target area is an area in the first image data that is within a preset range of the first image data center, and the second target area is an area in the first image data that is outside the preset range of the first image data center;

Alternatively, the first target area is an area in the first image data where the moving object is located, and the second target area is an area in the first image data excluding the moving object.

Since the central area of the image is often an important visual focus and usually contains key information, when the first target area is defined as the area within the central preset range and the second target area is the area outside the central preset range, this method can increase the focus priority in the central area of the image. On the other hand, the first target area is defined as the area where the moving object is located, and the second target area is the area excluding the moving object. It can automatically identify and focus on the dynamic elements in the image, and by giving priority to the clarity of the moving object, the viewing experience can be improved, so that the device can automatically adapt to different viewing scenarios and user needs.

In some embodiments, calculating a first clarity evaluation value corresponding to a first target area in the first image data and a second clarity evaluation value corresponding to a second target area in the first image data according to gradients of pixels in different directions includes:

Buffering three rows of pixels in the first image data;

Fill three rows of pixels into a data template of size 3*3;

When the pixel in the data template is in the first target area or the second target area, the sum of the gradient values of each pixel in the data template in different directions is calculated;

The first definition evaluation value is obtained by accumulating the sum of the gradient values of each pixel in the first target area in different directions; and the second definition evaluation value is obtained by accumulating the sum of the gradient values of each pixel in the second target area in different directions.

Specifically, the captured image data usually displays pixels row by row. Therefore, during the image data display process, three rows of pixels can be cached each time for subsequent processing to improve the timeliness of the calculation. Further, the data can be expanded to generate a data template with a size of 3*3, which can be a matrix with a size of 3*3. Then fill the three rows of cached pixels into the data template to form a small data area. By filling the pixels into the data template, the original data can be structured in a certain form, providing more comprehensive local information support for the calculation of the gradient value of each pixel, thereby making the data easier to process and analyze, reducing the complexity of the calculation, and making the calculation process more efficient and easy to implement.

For the pixels filled into the data template, it can be determined whether the pixel is in the first target area or the second target area. If the pixel is neither in the first target area nor in the second target area, the gradient value of the pixel is not calculated. If the pixel is in the first target area, the pixel can be marked to indicate that the pixel belongs to the first target area, and the gradient value of the pixel in different directions is calculated. Then, the gradient values of the pixel in different directions are added to obtain the sum of the gradient values until the pixels in the first target area are traversed. The sum of the gradient values of each pixel in the first target area in different directions is accumulated to obtain the first clarity evaluation value. Of course, if the pixel is in the second target area, similar processing can be performed to obtain the second clarity evaluation value. Among them, since the gradient value can represent the change of the pixel grayscale, the clarity evaluation value can reflect the image texture and edge information of the pixel.

In this embodiment, by caching three rows of pixels of the image data each time, it is helpful to improve the timeliness of calculating the clarity of the image data. By generating a data template, the calculation of pixel gradients can be better organized and processed, reducing the complexity of the calculation. Furthermore, calculating the gradient values of pixels in different directions helps to obtain gradient information more comprehensively, thereby better describing the texture and structural characteristics of the image data and improving the accuracy of clarity evaluation.

Step 130: Based on the first weight of the first target area and the second weight of the second target area, the clarity of the first target image is calculated according to the first clarity evaluation value and the second clarity evaluation value, and a first relationship curve representing the relationship between the clarity of the first image data at different positions of the lens is obtained.

In an embodiment of the present application, the weight setting can be based on the importance of different target areas to the overall clarity of the image. For example, if the first target area is the central area of the image or the area containing the main visual content, a higher weight can be assigned to the first target area, while a lower weight can be assigned to the second target area. Specifically, the first target area and the second target area can be identified by image analysis, and key information in the image, such as moving objects, the position of the target area in the image, etc., can be extracted, and weights can be assigned to the first target area and the second target area according to the extracted information. Of course, weights can also be set in advance for the first target area and the second target area based on the properties of the first target area and the second target area; or, the weight ratio of the first target area and the second target area can be determined according to the ratio of the first clarity evaluation value and the second clarity evaluation value, thereby confirming the weight of each target area.

After determining the weight of each target area, each clarity evaluation value can be multiplied by its corresponding weight in a linear weighted manner, and then the products are added to obtain the clarity of the first target image. Of course, the clarity evaluation values can also be weighted in an exponentially weighted manner to obtain the clarity of the first target image.

After calculating the clarity of the first image data, a first relationship curve between the clarity of the first image data and the lens at different positions can be obtained, as shown in FIG2 , where curve 1 is the first relationship curve, wherein the horizontal axis represents the position of the lens, i.e., the focusing position, and the vertical axis represents the clarity.

Step 140: determine a focus position according to a first target position corresponding to the image data with the highest definition in the first relationship curve, so as to control the lens to move to the focus position.

Focusing refers to the process of adjusting the focal length of an optical system (such as a camera, telescope, etc.) so that objects on the imaging plane are clearly visible. In the field of photography and optical imaging, correct focus adjustment is a key factor in ensuring image clarity and quality.

When the lens is in the focused position, the captured image can be clear. In the embodiment of the present application, by controlling the lens to move at different positions and capturing image data, a first relationship curve representing the relationship between the clarity of the image data and the lens position is obtained. In the first relationship curve, the lens position corresponding to the highest clarity of the image data can be found, and this position is determined as the first target position. Since the clarity of the image data is the highest at the first target position, the first target position can be determined as the focused position. Of course, it can be seen from the first relationship curve that the clarity of the captured image is also very high at a position within a certain range to the left or right near the first target position, so the position within a preset range near the first target position can also be determined as the focused position.

According to the automatic focusing method of visible light television of the present application, the lens is controlled to move at a preset speed with a preset step length, and the first image data captured at different positions of the moving object during the movement of the lens is obtained; the clarity of the first image data is calculated based on the gradient of the pixels in the first image data in different directions, and a first relationship curve representing the relationship between the clarity of the lens at different positions and the first image data is obtained; the focus position is determined according to the first target position corresponding to the image data with the highest clarity in the first relationship curve, so as to control the lens to move to the focus position. The embodiment of the present application can continuously track the moving object by acquiring the image data captured at different positions of the moving object during the movement of the lens, and can maintain focus even if the speed or direction of the object changes. The gradient of the pixels in different directions based on the image data can reflect the image texture and edge information of the pixels to a certain extent, so as to determine the clarity of the image data, and then find the position where the image data with the highest clarity is captured, and determine the focus position based on the position. This method has no high requirements for factors such as light and the object being photographed, and can adapt to automatic focusing in different scenes, thereby improving the accuracy of automatic focusing.

In some embodiments, determining the focus position according to the first target position corresponding to the image data with the highest definition in the first relationship curve so as to control the lens to move to the focus position includes:

determining a first target position as a focus position;

Control the lens to move from the focus stop position to the focus start position;

Taking the focus start position as the starting point, control the lens to move to the focus position.

In this embodiment, since the clarity of the image data is the highest at the first target position, the first target position can be determined as the focus position.

In this embodiment, the movement process of the lens is shown in FIG3. Step 1: First, the lens is controlled to move from the current position to the focus start position; Step 2: The lens is controlled to move from the focus start position to the focus stop position at a given speed and step length; Step 3: To eliminate the gear backlash, the lens is first controlled to move to the focus start position; Step 4: The lens is controlled to move from the focus start position to the focus position.

In step 2, image data can be captured during the process of moving the lens, and the first relationship curve is obtained through calculation. After the focus position is determined, due to the gear backlash, if the lens is directly controlled to move from the focus stop position to the focus position, the position of the lens will be inaccurate. Therefore, the lens is first controlled to move to the focus start position through step 3, and then the lens is controlled to move from the focus start position to the focus position.

In this embodiment, the first target position is the position where the image data has the highest clarity, so that the first target position can be determined as the focus position. Returning the lens to the focus starting position and then moving it to the focus position is beneficial to eliminating the gear backlash of the motor and improving the accuracy of automatic focusing.

In some embodiments, determining the focus position according to the first target position corresponding to the image data with the highest definition in the first relationship curve so as to control the lens to move to the focus position includes:

Controlling the lens to move from a focus stop position to a focus start position with a preset step length, and acquiring second image data captured at different positions during the movement of the lens;

Calculating the clarity of the second image data to obtain a second relationship curve representing the relationship between the clarity of the second image data and different positions of the lens;

The focus position is determined according to the second target position and the first target position corresponding to the image data with the highest definition in the second relationship curve, so as to control the lens to move to the focus position.

In this embodiment, since the motor controlling the movement of the lens may have gear backlash during the reciprocating motion, further, in the process of controlling the lens to move from the focus stop position to the focus start position, the lens movement can be controlled with a preset step length, and the preset step length and the movement speed of the lens can be consistent with the preset step length and the movement speed of the lens during the process of acquiring the first image data.

In the process of controlling the lens to move from the focus stop position to the focus start position, the second image data can be obtained. Referring to the clarity calculation method based on the first image data, a second relationship curve representing the relationship between the clarity of the lens at different positions and the second image data can be calculated, as shown by curve 2 in FIG. 2 .

Further, in this embodiment, the lens position corresponding to the highest clarity of the second image data can be found according to the second relationship curve, and the position is determined as the second target position. Since the image data is very clear at the first target position and the second target position, the focus position can be determined in combination with the second target position and the first target position. For example, the first target position or the second target position can be determined as the focus position, or any position between the first target position and the second target position can be determined as the focus position.

In this embodiment, since the motor that controls the movement of the lens may have gear backlash, the clarity of the image data captured during the process of the lens moving from the focus stop position to the focus start position can be calculated, and the second target position corresponding to the image data with the highest clarity during this shooting process can be determined. Then, the focus position is determined by comprehensively considering the first target position and the second target position, thereby further improving the accuracy of automatic focusing.

In some embodiments, determining the focus position according to the second target position and the first target position corresponding to the image data with the highest definition in the second relationship curve, so as to control the lens to move to the focus position, includes:

determining a middle position between the first target position and the second target position as a focus position;

Taking the focus start position as the starting point, control the lens to move to the focus position.

Specifically, in this embodiment, the middle position between the first target position and the second target position may be determined as the focus position, and the automatic focusing process may be completed by controlling the lens to move to the focus position.

In this embodiment, the image data captured between the first target position and the second target position has a relatively high clarity as a whole, and thus determining the middle position between the first target position and the second target position as the focus position can improve the accuracy of the automatic focusing.

The automatic focusing method of a visible light television provided in the embodiment of the present application can be performed by an automatic focusing device of a visible light television. In the embodiment of the present application, the automatic focusing method of a visible light television performed by an automatic focusing device of a visible light television is taken as an example to illustrate the automatic focusing device of a visible light television provided in the embodiment of the present application.

The embodiment of the present application also provides an automatic focusing device for a visible light television.

As shown in FIG4 , the automatic focusing device of the visible light television includes:

An acquisition module 410 is used to control the lens to move at a preset speed with a preset step length, and acquire first image data captured at different positions of the moving object during the movement of the lens;

A first calculation module 420, configured to calculate a first clarity evaluation value corresponding to a first target area in the first image data and a second clarity evaluation value corresponding to a second target area in the first image data according to gradients of pixels in different directions;

A second calculation module 430 is used to calculate the clarity of the first target image according to the first clarity evaluation value and the second clarity evaluation value based on the first weight of the first target area and the second weight of the second target area, and obtain a first relationship curve representing the relationship between the clarity of the first image data at different positions of the lens;

The determination module 440 is used to determine the focus position according to the first target position corresponding to the image data with the highest definition in the first relationship curve, so as to control the lens to move to the focus position.

According to the automatic focusing device of the visible light television of the present application, by controlling the lens to move at a preset speed with a preset step length, first image data captured for a moving object at different positions during the movement of the lens is obtained; a first clarity evaluation value corresponding to a first target area in the first image data and a second clarity evaluation value corresponding to a second target area in the first image data are calculated according to the gradients of pixels in different directions; based on a first weight of the first target area and a second weight of the second target area, the clarity of the first target image is calculated according to the first clarity evaluation value and the second clarity evaluation value, and a first relationship curve representing the relationship between the clarity of the lens at different positions and the first image data is obtained; and a focus position is determined according to a first target position corresponding to image data with the highest clarity in the first relationship curve, so as to control the lens to move to the focus position. The embodiment of the present application can continuously track the moving object by acquiring image data captured at different positions of the moving object during the movement of the lens, and can maintain focus even if the speed or direction of the object changes. The clarity evaluation values of the first target area and the second target area are calculated respectively by performing pixel gradient analysis on the image data. Since the two areas represent different features or importance in the image, their clarity evaluation values can be weighted according to their respective weights to calculate the clarity of the overall image, and then the position where the image data with the highest clarity is captured is found, and the focus position is determined based on the position. This method does not have too high requirements on factors such as light and the object being photographed, and can adapt to automatic focusing in different scenarios, thereby improving the accuracy of automatic focusing.

In some embodiments, the acquisition module 410 is further configured to:

Control the lens to move to the focus starting position;

The lens is controlled to move from a focus start position to a focus stop position at a preset speed with a preset step length, and first image data captured at different positions of the lens during the movement of the lens is obtained.

In some embodiments, the first calculation module 420 is further configured to:

Buffering three rows of pixels in the first image data;

Fill three rows of pixels into a data template of size 3*3;

When the pixel in the data template is in the first target area or the second target area, the sum of the gradient values of each pixel in the data template in different directions is calculated;

The first definition evaluation value is obtained by accumulating the sum of the gradient values of each pixel in the first target area in different directions; and the second definition evaluation value is obtained by accumulating the sum of the gradient values of each pixel in the second target area in different directions.

In some embodiments, the determination module 440 is further configured to:

determining a first target position as a focus position;

Control the lens to move from the focus stop position to the focus start position;

Taking the focus start position as the starting point, control the lens to move to the focus position.

In some embodiments, the determination module 440 is further configured to:

Controlling the lens to move from a focus stop position to a focus start position with a preset step length, and acquiring second image data captured at different positions during the movement of the lens;

Calculating the clarity of the second image data to obtain a second relationship curve representing the relationship between the clarity of the second image data and different positions of the lens;

The focus position is determined according to the second target position and the first target position corresponding to the image data with the highest definition in the second relationship curve, so as to control the lens to move to the focus position.

In some embodiments, the determination module 440 is further configured to:

determining a middle position between the first target position and the second target position as a focus position;

Taking the focus start position as the starting point, control the lens to move to the focus position.

The automatic focusing device of the visible light television in the embodiment of the present application can be an electronic device, or a component in the electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal, or it can be other devices other than the terminal. Exemplarily, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, a car-mounted electronic device, a mobile Internet device (Mobile Internet Device, MID), an augmented reality (augmented reality, AR)/virtual reality (virtual reality, VR) device, a robot, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc., and can also be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), a television (television, TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

The automatic focusing device in the embodiment of the present application may be a device having an operating system. The operating system may be a Microsoft (Windows) operating system, an Android (Android) operating system, an IOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

In some embodiments, as shown in Figure 5, the embodiment of the present application also provides an electronic device 500, including a processor 501, a memory 502, and a computer program stored in the memory 502 and executable on the processor 501. When the program is executed by the processor 501, each process of the above-mentioned visible light television automatic focusing method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

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.

An embodiment of the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned visible light television automatic focusing method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

An embodiment of the present application also provides a computer program product, including a computer program, which implements the above-mentioned automatic focusing method when executed by a processor.

The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned automatic focusing method embodiment based on visible light television, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

It should be noted that, in this article, the term "comprises", "includes" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the method and device in the embodiment of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

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

The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

Claims (10)

1. An automatic focusing method for a visible light television, comprising: Controlling the lens to move at a preset speed with a preset step length, and acquiring first image data captured at different positions of the moving object during the movement of the lens; Calculating a first clarity evaluation value corresponding to a first target area in the first image data and a second clarity evaluation value corresponding to a second target area in the first image data according to gradients of pixels in different directions; Based on a first weight of the first target area and a second weight of the second target area, the clarity of the first target image is calculated according to the first clarity evaluation value and the second clarity evaluation value, so as to obtain a first relationship curve representing the relationship between the clarity of the lens at different positions and the first image data; The focus position is determined according to the first target position corresponding to the image data with the highest definition in the first relationship curve, so as to control the lens to move to the focus position. 2. The method according to claim 1, wherein the step of controlling the lens to move at a preset speed with a preset step length to obtain first image data captured at different positions of the moving object during the movement of the lens comprises: Controlling the lens to move to a focus starting position; The lens is controlled to move from a focus start position to a focus stop position at a preset speed with a preset step length, and first image data captured at different positions of the lens during the movement of the lens for the moving object is obtained. 3. The method according to claim 1, wherein the step of calculating a first definition evaluation value corresponding to a first target area in the first image data and a second definition evaluation value corresponding to a second target area in the first image data according to gradients of pixels in different directions comprises: Buffering three rows of pixels in the first image data; Fill the three rows of pixels into a data template with a size of 3*3; When the pixel in the data template is in the first target area or the second target area, the sum of the gradient values of each pixel in the data template in different directions is calculated; The first definition evaluation value is obtained by accumulating the sum of the gradient values of each pixel in the first target area in different directions; and the second definition evaluation value is obtained by accumulating the sum of the gradient values of each pixel in the second target area in different directions. 4. The method according to claim 3, characterized in that the first target area is an area in the first image data that is within a preset range of the first image data center, and the second target area is an area in the first image data that is outside the preset range of the first image data center; Alternatively, the first target area is an area where the moving object is located in the first image data, and the second target area is an area excluding the moving object in the first image data. 5. The method according to claim 1, characterized in that the step of determining the focus position according to the first target position corresponding to the image data with the highest definition in the first relationship curve so as to control the lens to move to the focus position comprises: determining the first target position as a focus position; Controlling the lens to move from a focus stop position to a focus start position; Taking the focus start position as a starting point, the lens is controlled to move to the focus position. 6. The method according to claim 1, characterized in that the step of determining the focus position according to the first target position corresponding to the image data with the highest definition in the first relationship curve so as to control the lens to move to the focus position comprises: Controlling the lens to move from a focus stop position to a focus start position with a preset step length, and acquiring second image data captured at different positions during the movement of the lens; Calculating the definition of the second image data to obtain a second relationship curve representing the relationship between the definition of the second image data and the lens at different positions; The focus position is determined according to the second target position corresponding to the image data with the highest definition in the second relationship curve and the first target position, so as to control the lens to move to the focus position. 7. The method according to claim 6, characterized in that the step of determining the focus position according to the second target position corresponding to the image data with the highest definition in the second relationship curve and the first target position so as to control the lens to move to the focus position comprises: determining an intermediate position between the first target position and the second target position as the focus position; Taking the focus start position as a starting point, the lens is controlled to move to the focus position. 8. An automatic focusing device for a visible light television, comprising: An acquisition module, used to control the lens to move at a preset speed with a preset step length, and acquire first image data captured at different positions of the moving object during the movement of the lens; A first calculation module, used for calculating a first clarity evaluation value corresponding to a first target area in the first image data and a second clarity evaluation value corresponding to a second target area in the first image data according to gradients of pixels in different directions; a second calculation module, configured to calculate the clarity of the first target image according to the first clarity evaluation value and the second clarity evaluation value based on a first weight of the first target area and a second weight of the second target area, and obtain a first relationship curve representing a relationship between the clarity of the first image data at different positions of the lens; The determination module is used to determine the focus position according to the first target position corresponding to the image data with the highest definition in the first relationship curve, so as to control the lens to move to the focus position. 9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the program. 10. A non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method according to any one of claims 1 to 7.