A multi-screen display method and system for video images

Abstract

This application relates to the technical field of video data transmission, and specifically relates to a multi-screen display method and system for video images. The method includes: obtaining the video frame images to be displayed on each screen and the bandwidth data during transmission corresponding to each screen, determining the motion significance value of each region in the video frame image, combining the texture distribution in the region, obtaining the video coding quality coefficient of each region in the video frame image, calculating the jump and sudden reduction coefficient of each bandwidth data, and obtaining the screen compression degree value when each screen displays each video frame image; based on the screen compression degree value, optimizing the compression coding parameters of each video frame image on each screen. This application can improve the stability of multi-screen display of video images.

Description

Technical Field

[0001] This application relates to the technical field of video data transmission, and particularly to a multi-screen display method and system for video images. Background Art

[0002] Multi-screen display is a technology that utilizes multiple displays to expand the visual space and improve work efficiency, dispersing the output of a single computer onto multiple physical screens. Currently, video coding technology has become the core for achieving efficient video transmission and storage. Digital content multi-network channel transmission can improve the reliability of screen display to a certain extent. Among them, the High Efficiency Video Coding (HEVC) technology is commonly used for the encoding process before video transmission. And rate control, as a key link in video coding, plays a crucial role in balancing video quality and transmission bandwidth.

[0003] The rate control in HEVC controls the size of the encoded bitstream output at the encoding end by dynamically adjusting the Quantization Parameter (QP) value to ensure that the bitstream in the video communication process can be stably and reliably transmitted to the receiving end. In the actual application process, due to the insufficient consideration of the amount of data to be transmitted required by different video frame contents and the influence of network bandwidth changes, it is difficult to maintain a high video transmission rate in the adjustment of the QP parameter in the HEVC algorithm, and thus there are defects in the insufficient stability of multi-screen display. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a multi-screen display method and system for video images, and the specific technical solutions adopted are as follows:

[0005] An embodiment of this application provides a multi-screen display method for video images, including the following steps:

[0006] Obtain the video frame images to be displayed on each screen and the bandwidth data during the transmission of each screen;

[0007] Based on the motion difference between pixel points and the distance between pixel points in each area of the video frame image, determine the motion significance value of each area in the video frame image, and combine the texture distribution situation within the area to obtain the video coding quality coefficient of each area in the video frame image;

[0008] Take each bandwidth data and its previous preset number of bandwidth data as the neighboring bandwidth data of each bandwidth data, analyze the deviation situation and change degree of all neighboring bandwidth data of each bandwidth data, and obtain the jump and sudden decrease coefficient of each bandwidth data;

[0009] According to the similarity degree of the video coding quality coefficients of each region in each video frame image displayed on different screens, combining the video coding quality coefficients of all regions in each video frame image of each screen, and the jump and sudden reduction coefficients of each bandwidth data during the transmission of each screen, obtain the picture compression degree value of each screen when displaying each video frame image;

[0010] Based on the picture compression degree value, optimize the compression coding parameters of each video frame image in each screen.

[0011] Preferably, the determination of the motion significance value of each region in the video frame image further includes:

[0012] For each region in the video frame image, determine the total motion vector of each pixel point in the region according to the change conditions of each pixel point in the horizontal and vertical directions in adjacent frame images;

[0013] Cluster the total motion vectors of all pixel points in the region, and calculate the motion significance value of each region according to the similarity degree of the total motion vectors of the pixel points in each cluster in the region and the distance relationship between the pixel points. The calculation formula is:

[0014] In the formula, represents the motion significance value of the j-th region in the i-th video frame image, N represents the total number of corresponding clusters in the region, B K represents the mean value of the norms of all total motion vectors in the K-th cluster, E K represents the cumulative sum of the absolute values of the cosine similarities between the average vector corresponding to the K-th cluster and the average vectors corresponding to all other clusters, C k represents the cumulative sum of the Manhattan distances between all pairs of pixel points corresponding to the total motion vectors within the K-th cluster.

[0015] Preferably, the total motion vector of each pixel point in each region further includes:

[0016] Use the optical flow method to obtain the motion vectors of each pixel point in the horizontal and vertical directions in each region, and use the sum value of the motion vectors in the horizontal and vertical directions as the total motion vector of each pixel point.

[0017] Preferably, the corresponding calculation formula for the video coding quality coefficient of each region in the video frame image is:

[0018] In the formula, represents the video coding quality coefficient of the j-th region in the i-th video frame image, respectively represent the motion significance value and the detailed texture richness coefficient of the j-th region in the i-th video frame image, where the detailed texture richness coefficient is determined by combining the gradient information and the gray level distribution of the pixel points within the region.

[0019] Preferably, the detailed texture richness coefficient is further the product of the average value of the gradients of all pixel points within the region and the entropy of the gray values of all pixel points.

[0020] Preferably, the corresponding calculation formula for the jump and sudden decrease coefficient of each bandwidth data is:

[0021] In the formula, T i represents the jump and sudden decrease coefficient of the i-th bandwidth data, and exp() is the exponential function with the natural constant as the base; D i is the transmission deviation degree of the i-th bandwidth data, which is calculated by the deviation degree of each neighboring bandwidth data of the bandwidth data; all neighboring bandwidth data of the i-th bandwidth data are arranged in ascending order of time to form a neighboring bandwidth sequence, and S is the sum of all elements in the first-order difference sequence of the neighboring bandwidth sequence.

[0022] Preferably, the true disturbance index includes: fitting all neighboring bandwidth data of each bandwidth data, calculating the minimum distance between each neighboring bandwidth data and the corresponding fitting line, and taking the sum of all the minimum distances of all neighboring bandwidth data of the i-th bandwidth data as the transmission deviation degree of the i-th bandwidth data.

[0023] Preferably, the corresponding calculation formula for the screen compression degree value when each screen displays each video frame image is:

[0024] In the formula, Y i (U) represents the screen compression degree value when the U-th screen displays the i-th video frame image, H i (U) represents the sum value of the video coding quality coefficients of all regions in the i-th video frame image of the U-th screen, L is the total number of screens, and X U,V represents: the Jaccard similarity coefficient between the sequence composed of the video coding quality coefficients corresponding to all regions in the i-th video frame image of the U-th screen and the sequence composed of the video coding quality coefficients corresponding to all regions in the i-th video frame image of the V-th screen at the same moment.

[0025] Preferably, the optimization of the compression coding parameters of each video frame image in each screen includes:

[0026] The expression of the compression coding parameters of the optimized video frame image is: Among them, QP new,U,i is the optimized QP parameter value of the i-th video frame image of the U-th screen, QPold,U,i The QP parameter of the i-th video frame image of the U-th screen obtained for HEVC encoding is the normalized result of the picture compression degree value of the i-th video frame image of the U-th screen, where QP is the quantization parameter of HEVC encoding in the video data compression and encoding process.

[0027] An embodiment of the present application further provides a multi-screen display system for video pictures, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of the method described in any one of the above are implemented.

[0028] As can be seen from the above, a method and system for multi-screen display of video pictures provided by the present application at least have the following beneficial effects:

[0029] The present application obtains the motion vectors of the same area between adjacent frames through the dense optical flow algorithm, analyzes the direction difference characteristics and motion amplitude sizes of different motion vectors by combining the clustering algorithm, and obtains the motion saliency value. The motion saliency value helps to distinguish the motion characteristics between different regions in the traffic surveillance video image. And compared with the calculation of individual pixel points, the region-level features can reduce the calculation amount, which is in line with the subsequent processing of using each frame image as the encoding object instead of encoding based on a small number of pixel points.

[0030] Further analyze the impact of bandwidth data on video transmission, calculate the picture compression degree value of the screen by measuring the video quality similarity relationship between different screens, and then optimize the QP parameter in the HEVC algorithm, which can reduce the impact of the first video transmission content and bandwidth instability in multi-screen display, and make up for the defect of insufficient stability in multi-screen display. Description of the Drawings

[0031] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0032] Figure 1 It is a flowchart of the steps of a method for multi-screen display of video pictures provided by the present application. Detailed Embodiments

[0033] In order to further elaborate on the technical means and effects adopted by this application to achieve the intended invention purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details a multi-screen display method and system for video images according to this application, including its specific implementation manner, structure, features, and effects, as follows. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0034] Unless otherwise specified and limited, terms such as "including", "comprising", or any other variant thereof are intended to cover non-exclusive inclusion, such that a circuit structure, article, or device including a series of elements not only includes those elements but also includes other elements not explicitly listed, or further includes elements inherent to such article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the article or device including the said element. Additionally, the term "and / or" used herein includes any and all combinations of one or more of the related listed items. All technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs.

[0035] The following specifically describes the specific solution of a multi-screen display method and system for video images provided by this application in conjunction with the accompanying drawings.

[0036] Please refer to Figure 1 , which shows the step flowchart of a multi-screen display method for video images provided by an embodiment of this application, including the following steps:

[0037] Step 1: Obtain the video frame images to be displayed on each screen and the bandwidth data during transmission corresponding to each screen.

[0038] This application takes the multi-screen display in remote traffic monitoring video transmission applications as an example. The captured monitoring video can be transmitted to the screen terminal in the form of digital content multi-network channels. During the video transmission process, it is often restricted by the communication network bandwidth. In order to make full use of the limited network bandwidth, it is usually necessary to compress the obtained video. Bitrate control plays an important role in the video compression process. In this embodiment, the High Efficiency Video Coding (HEVC) algorithm is used to encode the captured video frames. The monitoring video data is obtained by using a camera, and the bandwidth data during screen display is obtained through a network detection tool. In this embodiment, the video data frame rate is set to 30 FPS, and the acquisition frequency of the network bandwidth data is 30 times per second.

[0039] So far, the video data of traffic monitoring and the bandwidth data during transmission are obtained.

[0040] Step 2: Based on the motion differences and distances between pixel points within each region of the video frame image, determine the motion significance value of each region in the video frame image. Combine with the texture distribution within the region to obtain the video coding quality coefficient of each region in the video frame image.

[0041] The video data collected by the front camera needs to be compressed and encoded, and then the encoded data is transmitted. In the HEVC encoding process, rate control plays a crucial role and is an important indicator of video quality to ensure that the output bitstream meets specific bitrate constraints. Among them, QP is an important parameter factor affecting the video bitrate, and the QP value reflects the compression degree of the video. If the video quality is higher, the compression degree is lower, and the QP value is lower; if the video quality is lower, the compression degree is higher, and the QP value is also higher at this time. In practical applications, to meet the stability of multi-screen display, it is also necessary to comprehensively consider the content characteristics of the encoded video and the state of the transmission bandwidth to select an appropriate QP size.

[0042] Considering that the HEVC encoding algorithm allows independent encoding of different regions in the video frame image, and in the remote traffic monitoring video scenario, the motion states and scene complexity degrees of targets in different regions of the video frame image are different. Therefore, the motion and scene complexity characteristics of different regions can be comprehensively considered to compress the video image to different degrees. Specifically, in this embodiment, each video frame image is divided into 20 regions with the same size.

[0043] Taking the j-th region in the i-th video frame image as an example, if there are many moving objects in this region, such as a large traffic flow, and the scene is relatively complex, such as the internal image of the region contains more detailed content and obvious texture features, at this time, the compression encoding needs to ensure a high video quality to capture details more clearly. For regions with fewer moving objects and less detailed content, the video quality after compression encoding can be relatively low, which can reduce the data transmission volume. Thus, each region in the video frame is analyzed based on the above characteristics.

[0044] For the motion characteristics of objects in the target area, the Farneback dense optical flow algorithm is used in this embodiment for motion detection. The input of this algorithm is the i-th frame image and its previous frame image, and the output is the motion vectors of each pixel point in the i-th frame image in the horizontal and vertical directions. Therefore, the corresponding motion vectors in the horizontal and vertical directions can be obtained for all pixel points in each area. Further, taking a certain pixel point as an example, calculate the sum of the corresponding motion vectors in the horizontal and vertical directions as the total motion vector of this pixel point. The direction of the total motion vector is recorded as the motion direction of this pixel point, and the magnitude of the modulus of the total motion vector is the magnitude of the motion amplitude of this pixel point. In the scenario of remote traffic monitoring video, the detection of complex road conditions and illegal driving behaviors is the focus of traffic monitoring and also an important area that needs to be paid attention to on multi-screen displays. If there are complex road conditions and illegal driving behaviors in a certain area, the more significant the motion characteristics in this area, the more pixel points with different-direction total motion vectors inside, and the greater the corresponding motion amplitude of the pixel points. And for these areas, it is necessary to ensure the quality of the transmitted video. The following processing is carried out based on the above characteristics.

[0045] First, analyze the difference of the total motion vectors in the area. Taking the j-th area in the i-th video frame image as an example, the AP clustering algorithm is used in this embodiment to cluster the total motion vectors of all pixel points in this area, and the output is multiple clustering clusters. If the number of output clustering clusters is more, and the position distribution of the pixel points corresponding to each clustering cluster in the area is more discrete, it indicates that there are more likely targets moving in different directions in this area, and the traffic conditions in this area are more complex. For the K-th clustering cluster, calculate the Manhattan distance between the pixel points corresponding to any two total motion vectors, and record the sum of all the Manhattan distances within the clustering cluster as C k . The directions of the total motion vectors in the same clustering cluster are usually the same, while the directions of the corresponding total motion vectors between different clustering clusters may be different. If the direction difference between the total motion vectors of different clustering clusters is greater, it indicates that the difference in the target motion directions in the area is stronger. Thus, take the average value of all the total motion vectors in each clustering cluster as the average vector of each clustering cluster.

[0046] Furthermore, combining the similarity degree of the total motion vectors of the pixel points within each clustering cluster in each area and the distance relationship between the pixel points, calculate the motion significance value of each area. In this embodiment, the specific calculation formula is as follows:

[0047] In the formula, represents the motion significance value of the j-th area in the i-th video frame image, N represents the total number of corresponding clustering clusters in the area, B K represents the mean value of the moduli of all the total motion vectors in the K-th clustering cluster, and the obtained B KThe larger it is, the greater the motion amplitude of the pixel points corresponding to the Kth cluster, C k represents the sum of the Manhattan distances between all pairs of pixel points corresponding to the total motion vectors within the Kth clustering cluster, C K The larger it is, the more discrete the position distribution of the pixel points corresponding to the Kth cluster within the region, E K represents the sum of the absolute values of the cosine similarities between the average vector corresponding to the Kth clustering cluster and the average vectors corresponding to all other clustering clusters. The smaller its value, the greater the direction difference of the total motion vectors between different clusters. The larger the motion significant value, the more obvious the multi-direction and amplitude characteristics of the pixel points within the region.

[0048] Furthermore, the detailed features of the image within the region are closely related to the complexity of the content. Compared with those regions with simple content, regions with a large traffic flow usually have richer details and more obvious texture changes. In this embodiment, the average value of the gradients of all pixel points within the jth region and the entropy of the gray values corresponding to all pixel points are calculated. The average value of the gradients of all pixel points reflects the richness of the texture in the region, and the entropy value reflects the degree of information and details contained in the region. Therefore, the product of the average value of the gradients of all pixel points and the entropy of the gray values of all pixel points is used as the detailed texture richness coefficient of the jth region in the ith frame video image, denoted as Calculated The larger it is, the more details and texture features the region contains.

[0049] Furthermore, in the traffic surveillance video scenario, if the multi-direction and amplitude characteristics of the pixel points in a certain region are more obvious, and at the same time it contains more details and texture features, a higher video quality needs to be ensured during the compression encoding process. Then calculate the video coding quality coefficient, and the specific calculation formula is:

[0050] In the formula, represents the video coding quality coefficient of the jth region in the ith video frame image, calculated The larger it is, the more running and detailed information the region contains, and the higher the video quality required during compression encoding, and more data needs to be transmitted.

[0051] Step 3: Use each bandwidth data and the previously preset number of bandwidth data as the neighboring bandwidth data of each bandwidth data, analyze the deviation situation and change degree of all neighboring bandwidth data of each bandwidth data, and obtain the jump and sudden decrease coefficient of each bandwidth data.

[0052] During the multi-network channel transmission of digital content for the multi-screen display of video images, the bandwidth status also affects the stability of video transmission. If there is signal interference during the transmission process, the random noise may increase, or the bandwidth data may drop suddenly due to temporary network congestion, making it difficult to provide a stable data transmission volume and affecting the smoothness of video image display. Therefore, compared with a good transmission process, the bandwidth data during video transmission is characterized by an increase in random noise, that is, there is more data deviating from the average bandwidth data in the short term, and a rapid decrease in amplitude. Thus, the change characteristics of the broadband are analyzed.

[0053] For each bandwidth data, in this embodiment, the i-th bandwidth data and its first 29 bandwidth data are used as the neighboring bandwidth data of the i-th bandwidth data, and all the neighboring bandwidth data of the i-th bandwidth data are arranged in ascending order of time to form the neighboring bandwidth sequence of the i-th bandwidth data. A straight line fitting is performed on the neighboring bandwidth sequence to obtain the corresponding fitting straight line, and the minimum distance between each neighboring bandwidth data of the i-th bandwidth data and the fitting straight line is calculated respectively. The sum of all the minimum distances of all the neighboring bandwidth data of the i-th bandwidth data is denoted as the transmission deviation degree of the i-th bandwidth data. The larger the obtained transmission deviation degree, the more random noise exists in the neighboring bandwidth sequence where the i-th bandwidth data is located. To analyze its rapid decrease characteristic, calculate the cumulative sum of all elements in the first-order difference sequence of the neighboring bandwidth sequence, denoted as S. If the rapid decrease characteristic of the bandwidth data is more obvious, the value of the sum of the first-order difference sequence is smaller. Thus, the jump and sudden decrease coefficient of each bandwidth data is obtained. In this embodiment, the calculation formula is as follows:

[0054] In the formula, T i represents the jump and sudden decrease coefficient of the i-th bandwidth data, and exp() is the exponential function with the natural constant as the base; D i is the transmission deviation degree of the i-th bandwidth data; S is the cumulative sum of all elements in the first-order difference sequence of the neighboring bandwidth sequence. The smaller the obtained exp(S), the more obvious the rapid decrease characteristic of the neighboring bandwidth sequence. The obtained T i is larger, indicating that the random noise of the bandwidth data at this time is more, it is more likely to have a rapid decrease, and it is more difficult to provide a stable data transmission volume.

[0055] Step Four: According to the similarity degree of the video coding quality coefficients of each region in each video frame image displayed on different screens, combined with the video coding quality coefficients of all regions in each video frame image of each screen, and the jump and sudden decrease coefficients of each bandwidth data during the transmission of each screen, obtain the picture compression degree value of each screen when displaying each video frame image.

[0056] Furthermore, during the simultaneous display of multiple screens, different video images are transmitted to different screen terminals via the network. If the video image quality displayed on each screen is relatively high at the same time and the network stability characteristics are relatively poor, it is more likely to affect the stability of multi-screen display at this time. The specific manifestation of relatively high video image quality displayed on each screen is that there are relatively many regions requiring high video quality in the video frame images displayed on each screen at the same moment, and the overall video quality is relatively close between different screens. Based on the above characteristics, the following processing is performed.

[0057] In this embodiment, the time interval between video frames set during data acquisition is the same as the time interval for bandwidth data acquisition. Therefore, at the same moment, there are corresponding video frame images and bandwidth data. Furthermore, calculate the video frame image compression degree value of this screen. In this embodiment, the specific calculation formula is:

[0058] In the formula, Y i (U) represents the video frame image compression degree value of the U-th screen when displaying the i-th video frame image, and H i (U) represents the sum value of the video coding quality coefficients of all regions in the i-th video frame image of the U-th screen. The larger the obtained H i (U), it indicates that the amount of data to be transmitted by the U-th screen in this video frame is larger. L is the total number of screens, and X U,V represents the Jaccard similarity coefficient between the sequence composed of the video coding quality coefficients corresponding to all regions in the i-th video frame image of the U-th screen and the sequence composed of the video coding quality coefficients corresponding to all regions in the i-th video frame image of the V-th screen at the same moment. The larger the obtained , it indicates that the video quality between different screens is closer. When T i is larger, the amount of data that the network can transmit is more limited. The larger the calculated Y i (U), it indicates that a greater degree of compression needs to be performed on the video frame displayed on this screen.

[0059] Step Five: Optimize the compression coding parameters of each video frame image on each screen based on the video frame image compression degree value.

[0060] In this embodiment, by analyzing the quality of each screen video frame image and the change characteristics of network bandwidth data during multi-screen display, as well as the impact on video display stability, a video frame image compression degree value is constructed to reflect the compression degree during video coding, and the compression coding QP parameter of video data is optimized based on the video frame image compression degree value.

[0061] HEVC encoding can calculate the corresponding QP value for different regions of each video frame. Taking the i-th video frame image of any screen as an example, in this embodiment, the calculated picture compression degree value is first normalized using the tanh hyperbolic tangent function, and the normalization result is denoted as Z.

[0062] Furthermore, the optimized QP parameters for each region in the video frame image are constructed. In this embodiment, the calculation formula is: where QP new,U,i is the optimized QP parameter value of the i-th video frame image of the U-th screen, and QP old,U,i is the QP parameter of the i-th video frame image of the U-th screen calculated by HEVC encoding. The process of obtaining the QP parameter of the HEVC encoding algorithm is a well-known prior art and will not be elaborated in this embodiment. is the normalization result of the picture compression degree value of the i-th video frame image of the U-th screen. Among them, QP is the quantization parameter of HEVC encoding in the video data compression and encoding process. Then, QP new is used as the compression and encoding parameter of the video frame image, and then the bit rate of video transmission is adjusted to improve the stability of multi-screen display.

[0063] Based on the same inventive concept as the above method, an embodiment of the present application also provides a multi-screen display system for video pictures, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above methods for a multi-screen display method of video pictures.

[0064] It can be understood that the above sequence of embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above specific embodiments of this specification have been described. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0065] Each embodiment in this specification is described in a progressive manner. The same or similar parts between each embodiment can be referred to each other, and the key points of each embodiment are the differences from other embodiments.

[0066] The above content is only the implementation mode of the present application and is not used to limit the scope of the present application. Any equivalent structure or equivalent process transformation made using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, is similarly included in the protection scope of the present application.

Claims

1. A multi-screen display method for video images, characterized in that: The following steps are involved: Obtain the video frame images to be displayed on each screen and the bandwidth data corresponding to each screen during transmission; Based on the motion difference between pixels in each region of the video frame image and the distance between pixels, the motion saliency value of each region in the video frame image is determined, and the video encoding quality coefficient of each region in the video frame image is obtained in combination with the texture distribution in the region; Taking each bandwidth data and a preset number of bandwidth data before it as neighboring bandwidth data of each bandwidth data, analyzing the deviation and change degree of all neighboring bandwidth data of each bandwidth data, and obtaining the jump sudden reduction coefficient of each bandwidth data; According to the similarity of the video encoding quality coefficients of each area in each video frame image displayed by different screens, the video encoding quality coefficients of all areas in each video frame image of each screen, and the jump and sudden reduction coefficients of each bandwidth data when each screen is transmitted, the image compression degree value of each screen when displaying each video frame image is obtained; The compression encoding parameters of each video frame image in each screen are optimized, and the expression of the optimized QP parameter value is: Where QP new,U,i The optimized QP parameter value for the i-th video frame image of the U-th screen, QP old,U,i The QP parameter of the i-th video frame image of the U-th screen calculated for HEVC encoding, is the normalized result of the picture compression degree value of the i-th video frame image of the U-th screen, where QP is the quantization parameter of HEVC encoding in the video data compression encoding process.

2. A multi-screen display method for video images as claimed in claim 1, characterized in that: Determining the motion saliency value of each region in the video frame image further includes: For each region in the video frame image, determine the total motion vector of each pixel in each region according to the change of each pixel in the horizontal direction and the vertical direction in the adjacent frame image; The total motion vectors of all pixels in the region are clustered, and the motion saliency value of each region is calculated according to the similarity of the total motion vectors of the pixels in each cluster in the region and the distance relationship between the pixels. The calculation formula is: In the formula, represents the motion saliency value of the jth region in the i-th video frame image, N represents the total number of corresponding clusters in the region, and B K represents the mean value of the modulus of all total motion vectors in the Kth cluster, E K represents the sum of the absolute values ​​of the cosine similarities between the mean vector corresponding to the Kth cluster and the mean vectors corresponding to all other clusters, C k It represents the cumulative sum of the Manhattan distances between the pixels corresponding to any two total motion vectors in the Kth cluster.

3. A multi-screen display method for video images as claimed in claim 2, characterized in that: The total motion vector of each pixel point in each area further includes: The optical flow method is used to obtain the horizontal and vertical motion vectors of each pixel in each area, and the sum of the horizontal and vertical motion vectors is used as the total motion vector of each pixel.

4. The multi-screen display method of a video image according to claim 1, characterized in that: The corresponding calculation formula of the video encoding quality coefficient of each area in the video frame image is: In the formula, Represents the video coding quality coefficient of the jth region in the i-th video frame image, They respectively represent the motion saliency value and detail texture richness coefficient of the jth region in the ith video frame image, wherein the detail texture richness coefficient is determined by combining the gradient information and grayscale distribution of the pixel points in the region.

5. A multi-screen display method for video images as claimed in claim 4, characterized in that: The detail texture richness coefficient is further the product of the average value of the gradients of all pixels in the region and the entropy of the gray values ​​of all pixels.

6. A multi-screen display method for video images as claimed in claim 1, characterized in that: The corresponding calculation formula of the jump reduction coefficient of each bandwidth data is: Where, T i Indicates the jump-drop coefficient of the i-th bandwidth data, exp() is an exponential function with a natural constant as the base; D i is the transmission deviation of the i-th bandwidth data, which is calculated by the deviation degree of each neighboring bandwidth data of the bandwidth data; all neighboring bandwidth data of the i-th bandwidth data are arranged in ascending time order to form a neighbor bandwidth sequence, and S is the cumulative sum of all elements in the first-order difference sequence of the neighbor bandwidth sequence.

7. A multi-screen display method for video images as claimed in claim 6, characterized in that: The transmission deviation degree includes: fitting all neighboring bandwidth data of each bandwidth data, calculating the minimum distance between each neighboring bandwidth data and the corresponding fitting straight line, and taking the sum of all the minimum distances of all neighboring bandwidth data of the i-th bandwidth data as the transmission deviation degree of the i-th bandwidth data.

8. The multi-screen display method of a video image according to claim 1, characterized in that: The corresponding calculation formula for the image compression degree value of each screen when displaying each video frame image is: Where Y i (U) represents the image compression value of the U-th screen when displaying the i-th video frame image, H i (U) represents the sum of the video coding quality coefficients of all regions in the i-th video frame image of the U-th screen, L is the total number of screens, X U,V It represents: the Jaccard similarity coefficient between the sequence consisting of the video coding quality coefficients corresponding to all regions in the i-th video frame image of the U-th screen at the same time and the sequence consisting of the video coding quality coefficients corresponding to all regions in the i-th video frame image of the V-th screen.

9. A multi-screen display system for video images, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

Images