Image processing method of LED dome-screen display screen

Abstract

The invention relates to the technical field of image processing, and discloses an image processing method of an LED dome screen display screen, comprising the following steps: S1, according to the size of the LED dome screen display screen and the size of a source image supported by a playing system, generating a virtual target image having the same shape as a dome screen, the size of the virtual target image being proportional to the actual size of the dome screen; s2, performing plane cutting on the virtual target image according to each row of pixel points forming the LED dome screen display screen to form corresponding hemispherical arcs; and S3, unfolding the generated hemispheroid arc and projecting the hemispheroid arc into a two-dimensional projection plane. Through accurate image mapping and deformation processing, the visual effect of a source image presented on an LED dome screen is the same as that of the source image presented on a flat panel display screen, an adaptive mapping algorithm is used, the deformation degree of the image can be dynamically adjusted according to image features, it is ensured that each frame of image can keep high-quality display at different visual angles, and the image quality is improved. And the viewing experience of the user is greatly enhanced.

Description

Technical Field

[0001] The invention relates to the technical field of image processing, and in particular to an image processing method for an LED spherical screen display. Background Art

[0002] With the development of science and technology, LED ball screens have become an important medium for displaying information and visual effects, and are widely used in commercial advertising, cultural exhibitions, sports events and other fields. However, the existing LED ball screens still have deficiencies in image processing, which affects their overall display effects and user experience.

[0003] At present, many LED dome screens use traditional image deformation technology, which relies on experience or multiple experiments to achieve the appropriate visual effect. As a result, the presentation of the source image on the dome screen cannot be compared with that on a flat screen, and the image is severely deformed, resulting in a lack of high-quality visual experience for viewers at different viewing angles.

[0004] The existing technology lacks real-time environmental perception capabilities and cannot dynamically adjust the brightness, contrast and color settings of the displayed content according to changes in the surrounding light. Therefore, in an environment with changing light, the visual effect of the LED dome screen will be reduced and cannot meet the needs of different occasions;

[0005] Existing LED display systems lack a user-friendly interactive interface, which limits users' ability to adjust image settings. Users need to rely on complex control panels or specialized software to make adjustments. They lack intuitive touch or voice interactive functions, which reduces user participation and satisfaction.

[0006] Image processing methods have problems of slow computing speed and high latency when processing large-scale image data. Especially in dynamic display scenarios that require fast response, such as live broadcasts and performances, existing technologies cannot guarantee smooth image playback, which in turn affects the audience's experience.

[0007] The existing technology lacks flexibility when applied to LED ball screens of different sizes and curvatures, resulting in poor adaptability in diverse application scenarios, failure to fully utilize the advantages of the LED ball screen, and limiting its potential for use in various occasions.

[0008] Therefore, those skilled in the art provide an image processing method for an LED spherical screen display to solve the problems raised in the above background technology. Summary of the invention

[0009] In view of the deficiencies in the prior art, the present invention provides an image processing method for an LED ball screen display screen, which solves the problems of the prior LED ball screen display screen in terms of image deformation, real-time adaptability, user interactivity, processing efficiency and adaptability.

[0010] To achieve the above object, the present invention is implemented by the following technical scheme: an image processing method of an LED ball screen display screen, comprising the following steps: S1, generating a virtual target image with the same shape as the ball screen according to the size of the LED ball screen display screen and the source image size supported by the playback system, wherein the size of the virtual target image is proportional to the actual size of the ball screen;

[0011] S2, plane-cutting the virtual target image according to each row of pixel points constituting the LED ball screen display screen to form a corresponding hemispherical arc: P = R × θ, where P is the arc length of each row of the hemispherical arc, R is the radius of the source image, and θ is the angle between the arc and the bottom center of the sphere;

[0012] S3, unfolding the generated hemispherical arc and projecting it into a two-dimensional projection plane, and at the same time, projecting the source image and the virtual target image onto the same plane to calculate the projection position of each row of the hemispherical arc;

[0013] S4. Use the ellipse formula and the trigonometric function formula to process the deformation of the projected image so that the arc of the hemisphere after plane cutting forms a deformation corresponding relationship with the source image. The specific calculation formula is:

[0014] c=R×sin(θ), d=RR×cos(θ)

[0015] Among them, c is the radius of the ellipse arc, and d is the distance from the center of the ellipse to the bottom of the sphere;

[0016] S5, adaptive mapping algorithm based on image features, analyzes the texture, edge and color information of the source image, dynamically adjusts the image deformation mapping, and introduces parallel processing technology and cache mechanism;

[0017] S6, reconstructing the image by matching the valid pixel points on the arc of the hemisphere with the pattern in the source image one by one according to the pattern in the virtual target image;

[0018] S7, introduce the environment perception module to detect the surrounding light changes in real time and dynamically adjust the brightness, contrast and color settings of the dome screen image;

[0019] S8. Through the user interface, the user can use touch or voice commands to adjust the displayed image in real time;

[0020] S9, processing the plurality of source image sequence frames in a loop according to the above method, and outputting them to the LED ball screen display through the playback system to achieve the same visual effect as the flat screen display.

[0021] Preferably, in step S1, a virtual target image having the same shape as the ball screen is generated according to the size of the LED ball screen display screen and the source image size supported by the playback system, and the algorithm formula is as follows:

[0022] The virtual target image size calculation:

[0023] Set the actual size of the LED ball screen display to width W screen and height H screen ;

[0024] Set the size of the source image to width W source and height H source ;

[0025] Set the width and height of the virtual target image to W respectively virtual and H virtual ;

[0026] The virtual target image size ratio is calculated as follows:

[0027]

[0028] The width and height of the virtual target image are calculated as:

[0029] W virtual =W source × Scale factor, H virtual =H source × scale factor.

[0030] Preferably, in step S3, the generated hemispherical arc is unfolded and projected into a two-dimensional projection plane, and at the same time, the source image and the virtual target image are projected onto the same plane together. The algorithm formula is as follows:

[0031] Define parameters: Set the center of the sphere of the virtual target image to O, the radius of the source image to R, and the position of the hemispherical arc of each row to P i , where i represents the number of rows, and the arc length of the hemispherical arc of each row is L i , the origin of the coordinate system on the projection plane is O′;

[0032] Arc expansion and projection: The projection position P of each hemispherical arc i ′, the calculation formula is: i ′=O′+L i n,

[0033] Among them, n is the unit normal vector of the arc of the hemisphere, indicating the direction of projection;

[0034] Relationship between arc and source image: For each row of hemispherical arc, calculate its projection intersection with the virtual target image, and set the intersection point as A i , obtained by the following formula:

[0035] A i =O+(R+d i )·u,

[0036] Among them, d i is the height of the arc from the center of the sphere to the row, and u is the direction vector representing the arc of the hemisphere of the row;

[0037] Projection of the source image: The projection position of the source image is S′, and considering the same height as the virtual target image on the projection plane, it is expressed as: S′=O′+R·v,

[0038] Where v is a unit vector representing the direction of the source image.

[0039] Preferably, in step S5, an adaptive mapping algorithm based on image features is used to perform image deformation mapping, and parallel processing technology and a cache mechanism are combined to improve processing efficiency. The following is the algorithm formula:

[0040] The image feature extraction: extracting features from the source image, the extracted features include texture, edge and color information, using the following method:

[0041] Edge detection algorithm:

[0042] Among them, G x and G y is the gradient in horizontal and vertical directions;

[0043] The adaptive mapping algorithm:

[0044] Set the feature vector of the source image to F, where F = [f1, f2, ..., f n ] represents the extracted n features, and the output image I′ of the adaptive mapping is calculated by the following formula:

[0045] I'(x, y)=I(x+Δx, y+Δy),

[0046] Among them, Δx and Δy are the deformations adjusted according to the characteristics, and the calculation formula is:

[0047] Δx=k1·f1(x, y)+k2·f2(x, y)+…+k n ·f n (x, y),

[0048] Δy=k1′·f1(x, y)+k2′·f2(x, y)+…+k n ′·f n (x, y),

[0049] Among them, k1, k2, ..., k n and k1′, k2′, …, k n ′ is the weight of the corresponding feature to the deformation amount.

[0050] Preferably, the parallel processing uses parallel processing to process the image in blocks. Assume that the image is divided into a plurality of blocks B i :

[0051] B i =process(I(x i ,y i )),

[0052] Among them, (x i ,y i ) are the starting coordinates of the block, and process is the parallel algorithm used to process each block.

[0053] Preferably, the cache mechanism caches the results of repeated calculations. Let the cache be C. When calculating I′, check the cache:

[0054] if(I(x,y)∈C)thenI′=C[I(x,y)],

[0055] elseI′=compute(I(x,y)).

[0056] Preferably, in step S6, the valid pixel points on the arc of the hemisphere correspond one-to-one with the pattern in the source image according to the pattern in the virtual target image to perform image reconstruction, and the algorithm formula is:

[0057] Identification of valid pixels: Set the valid pixel set on the hemisphere arc as P, the number of valid pixels as N, and the coordinates of each valid pixel as P i (x j ,y j ), where i = 1, 2, ..., N;

[0058] Virtual target image pixel mapping: for each valid pixel P i , through the corresponding position V in the virtual target image V j To carry out mapping, the specific calculation formula is:

[0059] V j (x j ,y j )=I(P i )fori=1,2,…,N,

[0060] Among them, I(P i ) represents the source image P i The corresponding pixel value;

[0061] Coordinate transformation: transform the effective pixel point P i When the source image is mapped to the virtual target image, the following formula is used for coordinate transformation: j =xi +Δxandy j =y i +Δy,

[0062] Among them, Δx and Δy are the deformations calculated based on the adaptive mapping algorithm;

[0063] Image reconstruction: The final reconstructed image I′ is obtained by combining the values ​​of all valid pixels:

[0064] Where δ is the Dirac impulse function, which is used to ensure that the pixel value in the reconstructed image I′ corresponds to the valid pixel point P i location.

[0065] Preferably, in step S7, an environment perception module is introduced to detect the ambient light changes in real time and dynamically adjust the brightness, contrast and color settings of the dome screen image. The algorithm formula is as follows:

[0066] The ambient light detection: using the light sensor to obtain the light intensity L of the current environment env , expressed by the following formula: L env =Sensor(x, y), where Sensor(x, y) represents the light intensity measured by the light sensor at position (x, y);

[0067] The target brightness calculation: Set the target brightness L of the display screen target , calculated by the following formula: L target = k·L env , where k is the brightness adjustment coefficient;

[0068] The brightness adjustment: adjust the brightness B of the displayed image according to the ambient light intensity and the target brightness: Among them, B′ is the adjusted brightness, L current is the brightness of the currently displayed image;

[0069] Contrast adjustment: Contrast adjustment is performed using the following formula:

[0070] C′=C+α·(L target -L env ), where C′ is the adjusted contrast and α is the contrast adjustment coefficient;

[0071] Color Adjustment: Adjust color settings (R', G', B') based on ambient light:

[0072]

[0073] Among them, R, G, B are the red, green, and blue components of the source image.

[0074] Preferably, in step S8, the user can use touch or voice commands to adjust the displayed image in real time through the user interaction interface. The following is the algorithm formula:

[0075] User input acquisition: Set the command input by the user as U, and obtain it through the touch interface or voice recognition module. Assume that the instructions input by the user include brightness adjustment, contrast adjustment, and color adjustment:

[0076] U={B adjust , C adjust , R adjust , G adjust , B adjust},

[0077] Among them, B adjust is the brightness adjustment value, C adjust is the contrast adjustment value, R adjust Adjust the value for the red component, G adjust Adjust the value of the green component, B adjust Adjust the value for the blue component;

[0078] Brightness adjustment: adjust the brightness value B according to the user input adjust To make brightness adjustments:

[0079] B′=B+B adjust , where B′ is the adjusted brightness;

[0080] Contrast adjustment: According to the contrast adjustment value C input by the user adjust To make a contrast adjustment:

[0081] C′=C+C adjust , where C′ is the adjusted contrast;

[0082] Color adjustment: Make corresponding color adjustments based on the color adjustment value entered by the user:

[0083] R′=R+R adjust , G′=G+G adjust , B′=B+B adjust ,

[0084] Among them, R′, G′, B′ are the adjusted red, green, and blue components;

[0085] Image update: Apply the adjusted image parameters to the current display image I′:

[0086] I′(x,y)=f(B′,C′,R′,G′,B′),

[0087] Here, f represents the new image generated according to the new brightness, contrast, and color settings.

[0088] Preferably, in step S9, multiple source image sequence frames are processed cyclically according to the above method, and output to the LED ball screen display screen through the playback system to achieve the same visual effect as the flat screen display screen. The following is the algorithm formula:

[0089] Sequence frame loading: Set the source image sequence to I k , where k represents the index of the frame and the total number of frames is N:I k fork = 1, 2, ..., N,

[0090] Image processing loop: Process each frame of source image to generate the target image I displayed on the LED ball screen k ′:I k ′=Process(I k ),

[0091] Wherein, Process represents the processing operation of steps S1 to S8;

[0092] Playback system output: The processed image is output to the LED ball screen through the playback system, and the playback interval is set to T:

[0093] Output(I k ′)fork=1, 2,...,Nwith intervalT,

[0094] Image buffering: When playing each frame of the image, use buffer B to ensure smooth playback:

[0095] B={I k ′|k=1,2,…,N},

[0096] Loop playback: If the user wants to loop the image sequence, when playing to the last frame, return to the first frame: Ifk=Nthenk=1.

[0097] The present invention provides an image processing method for an LED ball screen display screen. It has the following beneficial effects:

[0098] 1. The present invention uses precise image mapping and deformation processing to make the visual effect of the source image presented on the LED ball screen no different from that on the flat display screen, and uses an adaptive mapping algorithm to dynamically adjust the degree of image deformation according to image features, ensuring that each frame of the image can maintain high-quality display at different viewing angles, greatly enhancing the user's viewing experience.

[0099] 2. The present invention integrates an environmental perception module, which can detect changes in ambient light in real time and dynamically adjust the brightness, contrast and color settings of the image. This real-time adaptive capability ensures that the LED ball screen can always maintain the best visual effect under different environmental conditions to meet the needs of different occasions.

[0100] 3. The present invention provides a user-friendly interactive interface, allowing users to conveniently use touch or voice commands to adjust the displayed image in real time. Its high interactivity enhances user participation and makes the image display more personalized, meeting the specific needs of users and improving the overall user experience.

[0101] 4. The present invention utilizes parallel processing technology and caching mechanism to significantly improve the efficiency of image processing. When processing large-scale image data, it can quickly complete calculations, reduce delays, and ensure smooth image playback. This efficient processing performance is of great significance for scenes that require dynamic display, such as live broadcasts and performances.

[0102] 5. The method of the present invention has good adaptability and can handle LED ball screens of different sizes and curvatures. This flexibility enables the technology to be widely used in various occasions, such as stadiums, shopping malls, museums, etc., to improve the display effect and broaden the application scope of LED ball screens. BRIEF DESCRIPTION OF THE DRAWINGS

[0103] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0104] In order to make the technical personnel in the technical field understand the scheme of the present invention, the technical scheme in the embodiment of the present invention will be clearly and completely described below in combination with the drawings in the embodiment of the present invention. Obviously, the described embodiment is a partial embodiment of the present invention, not a complete embodiment. Based on the embodiment of the present invention, other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present invention.

[0105] The present invention is described in detail below in conjunction with the accompanying drawings:

[0106] Example:

[0107] Please refer to the attached Figure 1 , an embodiment of the present invention provides an image processing method of an LED ball screen display, comprising the following steps: S1, generating a virtual target image having the same shape as the ball screen according to the size of the LED ball screen display and the size of the source image supported by the playback system, wherein the size of the virtual target image is proportional to the actual size of the ball screen;

[0108] S2, plane-cutting the virtual target image according to each row of pixel points constituting the LED ball screen display screen to form a corresponding hemispherical arc: P = R × θ, where P is the arc length of each row of the hemispherical arc, R is the radius of the source image, and θ is the angle between the arc and the bottom center of the sphere;

[0109] S3, unfolding the generated hemispherical arc and projecting it into a two-dimensional projection plane, and at the same time, projecting the source image and the virtual target image onto the same plane to calculate the projection position of each row of the hemispherical arc;

[0110] S4. Use the ellipse formula and the trigonometric function formula to process the deformation of the projection image so that the arc of the hemisphere after plane cutting forms a deformation corresponding relationship with the source image. The specific calculation formula is:

[0111] c=R×sin(θ), d=RR×cos(θ)

[0112] Among them, c is the radius of the ellipse arc, and d is the distance from the center of the ellipse to the bottom of the sphere;

[0113] S5, adaptive mapping algorithm based on image features, analyzes the texture, edge and color information of the source image, dynamically adjusts the image deformation mapping, and introduces parallel processing technology and cache mechanism;

[0114] S6, reconstructing the image by matching the valid pixel points on the arc of the hemisphere with the pattern in the source image one by one according to the pattern in the virtual target image;

[0115] S7, introduce the environment perception module to detect the surrounding light changes in real time and dynamically adjust the brightness, contrast and color settings of the dome screen image;

[0116] S8. Through the user interface, the user can use touch or voice commands to adjust the displayed image in real time;

[0117] S9, processing the plurality of source image sequence frames in a loop according to the above method, and outputting them to the LED ball screen display through the playback system to achieve the same visual effect as the flat screen display.

[0118] The benefit of S1 is that it lays the foundation for the image processing process and avoids distortion of the final displayed image due to size mismatch; the benefit of S2 is that it can effectively convert the spherical surface into processable plane data, making subsequent image deformation and mapping more accurate and reducing the distortion and distortion of the image when displayed on the spherical screen; the benefit of S3 is that it helps to clarify the projection position of each row of hemispherical arcs, so that the spatial characteristics of the image can be converted into two-dimensional information, providing the necessary data support for subsequent deformation processing; the benefit of S4 is that it maintains the clarity of the image, ensures the viewing effect at different viewing angles, and makes the final display more natural; the benefit of S5 is that it optimizes the display effect according to the texture, edge and color information of the source image, and the flexibility makes the display The benefits of S6 ensure that the image displayed on the dome is highly consistent with the source image, ensuring that the details and quality of the image are preserved, thereby enhancing the viewing experience; the benefits of S7 greatly enhance the user's viewing experience in different occasions, allowing the dome to provide high-quality visual presentation in various environments; the benefits of S8 enhance the user's sense of participation, making the display content more personalized, meeting the needs of different audiences, and improving the overall user experience; the benefits of S9 achieve the same visual effects as flat screens, ensure smooth playback of dynamic content, adapt to rapidly changing display needs, such as live performances and advertising, and enhance the practical application value of the LED dome.

[0119] In step S1, a virtual target image having the same shape as the spherical screen is generated according to the size of the LED spherical screen display and the source image size supported by the playback system. The algorithm formula is as follows:

[0120] Virtual target image size calculation:

[0121] Set the actual size of the LED ball screen display to width W screen and height H screen ;

[0122] Set the size of the source image to width W source and height H source ;

[0123] Set the width and height of the virtual target image to W respectively virtual and H virtual ;

[0124] Calculation of virtual target image size ratio:

[0125]

[0126] The width and height of the virtual target image are calculated as:

[0127] W virtual =W source × Scale factor, H virtual =Hsource × scale factor.

[0128] By calculating the scale factor and adjusting the width and height of the virtual target image according to it, it is ensured that the generated virtual target image matches the actual size of the LED ball screen display. This matching is the basis for subsequent image processing to avoid image distortion caused by size mismatch;

[0129] Generating a virtual target image in the same shape as the dome screen can provide accurate image mapping and deformation processing in subsequent steps, thereby improving the display effect and ensuring that the audience can obtain a clear, high-quality visual experience at different viewing angles;

[0130] By calculating the ratio of the source image to the size of the dome, the system can flexibly adapt to various source image sizes, enhancing the versatility and adaptability of the LED dome, making it suitable for different types of display occasions.

[0131] In step S3, the generated hemispherical arc is unfolded and projected into a two-dimensional projection plane. At the same time, the source image and the virtual target image are projected onto the same plane. The algorithm formula is as follows:

[0132] Define parameters: Set the center of the sphere of the virtual target image to O, the radius of the source image to R, and the position of the hemispherical arc of each row to P i , where i represents the number of rows, and the arc length of the hemispherical arc of each row is L i , the origin of the coordinate system on the projection plane is O′;

[0133] Arc expansion and projection: The projection position P of each hemispherical arc i ′, the calculation formula is: i ′=O′+L i n,

[0134] Among them, n is the unit normal vector of the arc of the hemisphere, indicating the direction of projection;

[0135] Relationship between arc and source image: For each row of hemispherical arc, calculate its projection intersection with the virtual target image, and set the intersection point as A i , obtained by the following formula:

[0136] A i =O+(R+d i )·u,

[0137] Among them, d i is the height of the arc from the center of the sphere to the row, and u is the direction vector representing the arc of the hemisphere of the row;

[0138] Projection of the source image: The projection position of the source image is S′, and considering the same height as the virtual target image on the projection plane, it is expressed as: S′=O′+R·v,

[0139] Where v is a unit vector representing the direction of the source image.

[0140] By unfolding the hemispherical arc and projecting it onto a two-dimensional plane, step S3 can effectively convert the spherical spatial information into processable plane data, which provides the necessary data basis for subsequent image deformation processing and display;

[0141] Calculating the projection position of each row of hemispherical arcs and the intersection with the virtual target image can ensure the accuracy of the projection process, so that the final displayed image can maintain consistency and clarity at different viewing angles, thereby improving the viewing experience;

[0142] By calculating the relationship between the arc and the source image, the source image is ensured to be at the same height as the virtual target image during projection, thus enhancing the coherence between different images and avoiding visual discomfort caused by height differences.

[0143] During the source image projection process, it lays the foundation for the smooth playback of dynamic images, which is particularly important in display occasions that require rapid response and change, ensuring the dynamics and visual appeal of the display content;

[0144] By simultaneously processing the projection of the virtual target image and the source image, step S3 can provide the audience with a richer visual experience, support multi-level image display effects, and enhance the overall display effect and the diversity of application scenarios.

[0145] In step S5, an adaptive mapping algorithm based on image features is used to perform image deformation mapping, and parallel processing technology and a cache mechanism are combined to improve processing efficiency. The following is the algorithm formula:

[0146] Image feature extraction: Extract features from the source image. The extracted features include texture, edge, and color information. The following methods are used:

[0147] Edge detection algorithm:

[0148] Among them, G x and G y is the gradient in horizontal and vertical directions;

[0149] Adaptive mapping algorithm:

[0150] Set the feature vector of the source image to F, where F = [f1, f2, ..., f n ] represents the extracted n features, and the output image I′ of the adaptive mapping is calculated by the following formula:

[0151] I'(x, y)=I(x+Δx, y+Δy),

[0152] Among them, Δx and Δy are the deformations adjusted according to the characteristics, and the calculation formula is:

[0153] Δx=k1·f1(x, y)+k2·f2(x, y)+…+k n ·f n (x, y),

[0154] Δy=k1′·f1(x, y)+k2′·f2(x, y)+…+k n ′·f n (x, y),

[0155] Among them, k1, k2, ..., k n and k1′, k2′, …, k n ′ is the weight of the corresponding feature to the deformation amount;

[0156] Parallel processing, using parallel processing to process the image in blocks, assuming that the image is divided into multiple blocks B i :

[0157] B i =process(I(x i ,y i )),

[0158] Among them, (x i ,y i ) is the starting coordinate of the block, process is the parallel algorithm used to process each block;

[0159] The cache mechanism caches the results of repeated calculations. Let the cache be C. When calculating I′, check the cache:

[0160] if(I(x,y)∈C)thenI′=C[I(x,y)],

[0161] elseI′=compute(I(x,y)).

[0162] Extract texture and edge features through edge detection algorithm to analyze the source image more accurately, ensuring that the adaptive mapping algorithm can be optimized according to the actual content of the image, thereby improving the final display effect;

[0163] The adaptive mapping algorithm uses the source image features to dynamically adjust the deformation amount, making the image deformation process more flexible and adaptable to different types of source images. Its flexibility improves the image processing effect and ensures the consistency of display effects under different viewing angles.

[0164] By introducing parallel processing technology, the image is divided into multiple blocks for simultaneous processing, which improves processing efficiency, especially when processing large-scale image data, significantly reducing computing time and delay;

[0165] Using a cache mechanism to store calculation results and avoid repeated calculation of the same data during the processing process can significantly improve processing efficiency, especially when the same source image is called multiple times, which helps save computing resources and time.

[0166] In step S6, the valid pixel points on the arc of the hemisphere correspond one-to-one with the pattern in the source image according to the pattern in the virtual target image to perform image reconstruction. The algorithm formula is:

[0167] Identification of valid pixels: Set the valid pixel set on the hemisphere arc as P, the number of valid pixels as N, and the coordinates of each valid pixel as P i (x j ,y j ), where i = 1, 2, ..., N;

[0168] Virtual target image pixel mapping: for each valid pixel P i , through the corresponding position V in the virtual target image V j To carry out mapping, the specific calculation formula is:

[0169] V j (x j ,y j )=I(P i )fori=1,2,…,N,

[0170] Among them, I(P i ) represents the source image P i The corresponding pixel value;

[0171] Coordinate transformation: transform the effective pixel point P i When the source image is mapped to the virtual target image, the following formula is used for coordinate transformation: j =x i +Δxandy j =y i +Δy,

[0172] Among them, Δx and Δy are the deformations calculated based on the adaptive mapping algorithm;

[0173] Image reconstruction: The final reconstructed image I′ is obtained by combining the values ​​of all valid pixels:

[0174] Where δ is the Dirac impulse function, which is used to ensure that the pixel value in the reconstructed image I′ corresponds to the valid pixel point P i location.

[0175] By identifying the valid pixel point set P on the arc of the hemisphere, the pixel range that needs to be mapped and reconstructed can be determined, providing a clear benchmark for subsequent image reconstruction and ensuring the accuracy of processing;

[0176] The pixel mapping formula between the virtual target image and the source image ensures that the effective pixels can accurately reflect the content of the source image, so that the final reconstructed image can be visually consistent with the source image, avoiding visual distortion caused by deformation;

[0177] The coordinate transformation formula ensures that the deformation is taken into account when mapping, so that the pixels of the source image can be accurately transferred to the virtual target image, improving the flexibility of image processing and adapting to different deformation requirements;

[0178] The final image reconstruction ensures that the reconstructed image accurately reflects the characteristics of the original image in terms of position and content through the combination of effective pixels and the application of the Dirac impulse function, providing high-quality visual effects for the content finally displayed on the LED dome.

[0179] In step S7, an environment perception module is introduced to detect the changes in ambient light in real time and dynamically adjust the brightness, contrast and color settings of the dome screen image. The algorithm formula is as follows:

[0180] Ambient light detection: Use the light sensor to obtain the current ambient light intensity L env , expressed by the following formula: L env =Sensor(x, y), where Sensor(x, y) represents the light intensity measured by the light sensor at position (x, y);

[0181] Target brightness calculation: Set the target brightness L of the display target , calculated by the following formula: L target = k·L env , where k is the brightness adjustment coefficient;

[0182] Brightness adjustment: adjust the brightness of the displayed image according to the ambient light intensity and target brightness B: Among them, B′ is the adjusted brightness, L current is the brightness of the currently displayed image;

[0183] Contrast Adjustment: Contrast adjustment is performed using the following formula:

[0184] C′=C+α·(L target -L env ), where C′ is the adjusted contrast and α is the contrast adjustment coefficient;

[0185] Color Adjustment: Adjust color settings (R', G', B') according to ambient light:

[0186]

[0187] Among them, R, G, B are the red, green, and blue components of the source image.

[0188] Through ambient light detection, the system can obtain the light intensity of the current environment in real time, ensuring that the LED ball screen can respond quickly according to external conditions. The adaptability ensures that the display effect always remains in the best state under various environmental conditions.

[0189] The target brightness calculation can dynamically set the required brightness level of the display screen according to the actual ambient light intensity. Through adjustment, it can effectively avoid the phenomenon of the image being too dark or too bright due to light changes, and improve the readability and visual effect of the image;

[0190] Adjustment of brightness and contrast ensures that images remain clear and colorful under different lighting conditions. Optimization directly improves the user's viewing experience, making the displayed content more vivid and attractive.

[0191] By adjusting the color settings according to the ambient light conditions, the color performance of the image can be guaranteed to be natural and realistic under different lighting conditions, improving the accuracy of the visual effects and allowing the audience to have a better visual experience.

[0192] In step S8, the user can use touch or voice commands to adjust the displayed image in real time through the user interaction interface. The following is the algorithm formula:

[0193] User input acquisition: Set the command input by the user as U, and obtain it through the touch interface or voice recognition module. Assume that the instructions input by the user include brightness adjustment, contrast adjustment, and color adjustment:

[0194] U={B adjust , C adjust , R adjust , G adjust , B adjust},

[0195] Among them, B adjust is the brightness adjustment value, C adjust is the contrast adjustment value, R adjust Adjust the value for the red component, G adjust Adjust the value of the green component, B adjust Adjust the value for the blue component;

[0196] Brightness adjustment: adjust the brightness value B according to the user input adjust To make brightness adjustments:

[0197] B′=B+B adjust , where B′ is the adjusted brightness;

[0198] Contrast adjustment: According to the contrast adjustment value C input by the user adjust To make a contrast adjustment:

[0199] C′=C+C adjust , where C′ is the adjusted contrast;

[0200] Color adjustment: Make corresponding color adjustments based on the color adjustment value entered by the user:

[0201] R′=R+R adjust , G′=G+G adjust , B′=B+B adjust ,

[0202] Among them, R′, G′, B′ are the adjusted red, green, and blue components;

[0203] Image update: Apply the adjusted image parameters to the current display image I′:

[0204] I′(x,y)=f(B′,C′,R′,G′,B′),

[0205] Here, f represents the new image generated according to the new brightness, contrast, and color settings.

[0206] Through touch or voice input, users can adjust the displayed image intuitively and conveniently, which significantly improves the user's sense of participation during operation and enhances interactivity, allowing users to adjust the display effect in real time according to their preferences;

[0207] Users can adjust the brightness, contrast and color settings of the image according to environmental changes and personal preferences. Its flexibility enables users to obtain a personalized visual experience to meet the needs of different users;

[0208] This algorithm ensures that each user's adjustment can be immediately fed back to the image display, achieving dynamic changes. The real-time feedback mechanism improves the user's control over the image quality, making the viewing experience smoother.

[0209] By integrating the touch interface and voice recognition module, users can determine the input method that best suits them. Its diverse input methods can attract a wider user group and improve the applicability of the system.

[0210] In step S9, multiple source image sequence frames are processed cyclically according to the above method and output to the LED ball screen display through the playback system to achieve the same visual effect as the flat screen display. The following is the algorithm formula:

[0211] Sequence frame loading: Set the source image sequence to I k , where k represents the index of the frame and the total number of frames is N:I k fork = 1, 2, ..., N,

[0212] Image processing loop: Process each frame of source image to generate the target image I displayed on the LED ball screen k ′:I k ′=Process(I k ),

[0213] Wherein, Process represents the processing operation of steps S1 to S8;

[0214] Playback system output: The processed image is output to the LED ball screen through the playback system, and the playback interval is set to T:

[0215] Output(I k ′)fork=1, 2,...,Nwith intervalT,

[0216] Image buffering: When playing each frame of the image, use buffer B to ensure smooth playback:

[0217] B={I k ′|k=1,2,…,N},

[0218] Loop playback: If the user wants to loop the image sequence, when playing to the last frame, return to the first frame: Ifk=Nthenk=1.

[0219] By loading multiple source image sequence frames, step S9 can achieve dynamic visual effects and enhance the audience's viewing experience. Its dynamic nature is particularly suitable for occasions where content needs to change frequently, such as advertising displays, sports events, etc.

[0220] The image processing loop ensures that each frame of source image undergoes complete processing steps from S1 to S8 to generate a high-quality target image of the LED dome, ensuring the consistency and reliability of the display effect;

[0221] Setting the playback interval T and using the buffer B ensures smooth switching of each frame of the image and reduces delays and freezes, which is crucial to enhancing the user's visual enjoyment.

[0222] Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the invention, and the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An image processing method for an LED ball screen display, characterized in that: The steps include: S1. Generate a virtual target image with the same shape as the dome screen according to the size of the LED dome screen display and the source image size supported by the playback system. The size of the virtual target image is proportional to the actual size of the dome screen. S2, plane-cutting the virtual target image according to each row of pixel points constituting the LED ball screen display screen to form a corresponding hemispherical arc: P = R × θ, where P is the arc length of each row of the hemispherical arc, R is the radius of the source image, and θ is the angle between the arc and the bottom center of the sphere; S3, unfolding the generated hemispherical arc and projecting it into a two-dimensional projection plane, and at the same time, projecting the source image and the virtual target image onto the same plane to calculate the projection position of each row of the hemispherical arc; S4. Use the ellipse formula and the trigonometric function formula to process the deformation of the projection image so that the arc of the hemisphere after plane cutting forms a deformation corresponding relationship with the source image. The specific calculation formula is: Among them, c is the radius of the ellipse arc, and d is the distance from the center of the ellipse to the bottom of the sphere; S5, adaptive mapping algorithm based on image features, analyzes the texture, edge and color information of the source image, dynamically adjusts the image deformation mapping, and introduces parallel processing technology and cache mechanism; S6, reconstructing the image by matching the valid pixel points on the arc of the hemisphere with the pattern in the source image one by one according to the pattern in the virtual target image; S7, introduce the environment perception module to detect the surrounding light changes in real time and dynamically adjust the brightness, contrast and color settings of the dome screen image; S8. Through the user interface, the user can use touch or voice commands to adjust the displayed image in real time; S9, processing the plurality of source image sequence frames in a loop according to the above method, and outputting them to the LED ball screen display through the playback system to achieve the same visual effect as the flat screen display.

2. The image processing method of an LED ball screen display according to claim 1, characterized in that: In step S1, a virtual target image having the same shape as the spherical screen is generated according to the size of the LED spherical screen display screen and the source image size supported by the playback system. The algorithm formula is as follows: The virtual target image size calculation: Set the actual size of the LED ball screen display to width W screen and height H screen ; Set the size of the source image to width W source and height H source ; Set the width and height of the virtual target image to W respectively virtual and H virtual ; The virtual target image size ratio is calculated as follows: The width and height of the virtual target image are calculated as: W virtual =W source × Scale factor, H virtual =H source × scale factor.

3. The image processing method of an LED ball screen display according to claim 1, characterized in that: In step S3, the generated hemispherical arc is unfolded and projected into a two-dimensional projection plane. At the same time, the source image and the virtual target image are projected onto the same plane. The algorithm formula is as follows: Define parameters: Set the center of the sphere of the virtual target image to O, the radius of the source image to R, and the position of the hemispherical arc of each row to P i , where i represents the number of rows, and the arc length of the hemispherical arc of each row is L i , the origin of the coordinate system on the projection plane is O′; Arc expansion and projection: The projection position P of each hemispherical arc i ′, the calculation formula is: i ′=O′+L i n, Among them, n is the unit normal vector of the arc of the hemisphere, indicating the direction of projection; Relationship between arc and source image: For each row of hemispherical arc, calculate its projection intersection with the virtual target image, and set the intersection point as A i , obtained by the following formula: A i =O+(R+d i )·u, Among them, d i is the height of the arc from the center of the sphere to the row, and u is the direction vector representing the arc of the hemisphere of the row; Projection of the source image: The projection position of the source image is S′, and considering the same height as the virtual target image on the projection plane, it is expressed as: S′=O′+R·v, Where v is a unit vector representing the direction of the source image.

4. The image processing method of an LED ball screen display according to claim 1, characterized in that: In step S5, an adaptive mapping algorithm based on image features is used to perform image deformation mapping, and parallel processing technology and a cache mechanism are combined to improve processing efficiency. The following is the algorithm formula: The image feature extraction: extracting features from the source image, the extracted features include texture, edge and color information, using the following method: Edge detection algorithm: Among them, G x and G y is the gradient in horizontal and vertical directions; The adaptive mapping algorithm: Set the feature vector of the source image to F, where F = [f1, f2, ..., f n ] represents the extracted n features, and the output image I′ of the adaptive mapping is calculated by the following formula: I'(x, y)=I(x+Δx, y+Δy), Among them, Δx and Δy are the deformations adjusted according to the characteristics, and the calculation formula is: Δx=k1·f1(x,y)+k2·f2(x,y)+…+k n ·f n (x,y), Δy=k1′·f1(x,y)+k2′·f2(x,y)+…+k n ′·f n (x,y), Among them, k1, k2, ..., k n and k1′, k2′, …, k n ′ is the weight of the corresponding feature to the deformation amount.

5. The image processing method of the LED ball screen display according to claim 4, characterized in that: The parallel processing uses parallel processing to process the image in blocks. Suppose the image is divided into multiple blocks B i : B i =process(I(x i ,y i )), Among them, (x i ,y i ) are the starting coordinates of the block, and process is the parallel algorithm used to process each block.

6. The image processing method of an LED ball screen display according to claim 4, characterized in that: The cache mechanism caches the results of repeated calculations. Let the cache be C. When calculating I′, check the cache: if(I(x,y)∈C)thenI′=C[I(x,y)], elseI′=compute(I(x,y)).

7. The image processing method of an LED ball screen display according to claim 1, characterized in that: In step S6, the valid pixel points on the arc of the hemisphere correspond one-to-one with the pattern in the source image according to the pattern in the virtual target image to perform image reconstruction, and the algorithm formula is: Identification of valid pixels: Set the valid pixel set on the hemisphere arc as P, the number of valid pixels as N, and the coordinates of each valid pixel as P i (x j ,y j ), where i = 1, 2, ..., N; Virtual target image pixel mapping: for each valid pixel P i , through the corresponding position V in the virtual target image V j To carry out mapping, the specific calculation formula is: V j (x j ,y j )=I(P i )fori=1,2,…,N, Among them, I(P i ) represents the source image P i The corresponding pixel value; Coordinate transformation: transform the effective pixel point P i When the source image is mapped to the virtual target image, the following formula is used for coordinate transformation: j =x i +Δxandy j =y i +Δy, Among them, Δx and Δy are the deformations calculated based on the adaptive mapping algorithm; Image reconstruction: The final reconstructed image I′ is obtained by combining the values ​​of all valid pixels: Where δ is the Dirac impulse function, which is used to ensure that the pixel value in the reconstructed image I′ corresponds to the valid pixel point P i location.

8. The image processing method of an LED ball screen display according to claim 1, characterized in that: In step S7, an environment perception module is introduced to detect the ambient light changes in real time and dynamically adjust the brightness, contrast and color settings of the dome screen image. The algorithm formula is as follows: The ambient light detection: using the light sensor to obtain the light intensity L of the current environment env , expressed by the following formula: L env =Sensor(x, y), where Sensor(x, y) represents the light intensity measured by the light sensor at position (x, y); The target brightness calculation: Set the target brightness L of the display screen target , calculated by the following formula: L target = k·L env , where k is the brightness adjustment coefficient; The brightness adjustment: adjust the brightness B of the displayed image according to the ambient light intensity and the target brightness: Among them, B′ is the adjusted brightness, L current is the brightness of the currently displayed image; Contrast adjustment: Contrast adjustment is performed using the following formula: C′=C+α·(L target -L env ), where C′ is the adjusted contrast and α is the contrast adjustment coefficient; Color Adjustment: Adjust color settings (R', G', B') based on ambient light: Among them, R, G, B are the red, green, and blue components of the source image.

9. The image processing method of an LED ball screen display according to claim 1, characterized in that: In step S8, the user can use touch or voice commands to adjust the displayed image in real time through the user interaction interface. The following is the algorithm formula: User input acquisition: Set the command input by the user as U, and obtain it through the touch interface or voice recognition module. Assume that the instructions input by the user include brightness adjustment, contrast adjustment, and color adjustment: U={B adjust ,C adjust ,R adjust ,G adjust ,B adjust }, Among them, B adjust is the brightness adjustment value, C adjust is the contrast adjustment value, R adjust Adjust the value for the red component, G adjust Adjust the value of the green component, B adjust Adjust the value for the blue component; Brightness adjustment: adjust the brightness value B according to the user input adjust To make brightness adjustments: B′=B+B adjust , where B′ is the adjusted brightness; Contrast adjustment: According to the contrast adjustment value C input by the user adjust To make a contrast adjustment: C′=C+C adjust , where C′ is the adjusted contrast; Color adjustment: Make corresponding color adjustments based on the color adjustment value entered by the user: R′=R+R adjust ,G′=G+G adjust ,B′=B+B adjust , Among them, R′, G′, B′ are the adjusted red, green, and blue components; Image update: Apply the adjusted image parameters to the current display image I′: I′(x,y)=f(B′,C′,R′,G′,B′), Here, f represents the new image generated according to the new brightness, contrast, and color settings.

10. The image processing method of an LED ball screen display according to claim 1, characterized in that: In step S9, multiple source image sequence frames are processed cyclically according to the above method, and output to the LED ball screen display through the playback system to achieve the same visual effect as the flat screen display. The following is the algorithm formula: Sequence frame loading: Set the source image sequence to I k , where k represents the index of the frame and the total number of frames is N:I k fork = 1, 2, ..., N, Image processing loop: Process each frame of source image to generate the target image I displayed on the LED ball screen k ′:I k ′=Process(I k ), Wherein, Process represents the processing operation of steps S1 to S8; Playback system output: The processed image is output to the LED ball screen through the playback system, and the playback interval is set to T: Output(I k ′)fork=1,2,…,Nwith intervalT, Image buffering: When playing each frame of the image, use buffer B to ensure smooth playback: B={I k ′|k=1,2,…,N}, Loop playback: If the user wants to loop the image sequence, when playing to the last frame, return to the first frame: Ifk=Nthenk=1.

Images