SDN (Software Defined Network)-based 4K and 8K ultra-high-definition linkage made IP studio control method

Abstract

The invention discloses an IP studio control method based on 4K and 8K ultra-high-definition linkage manufacturing of an SDN, and relates to the technical field of video signal control, and the method comprises the steps: arranging an 8K camera and a 4K camera in a studio to collect video signals, and carrying out the color matching and signal consistency adjustment of the 4K camera based on the output of the 8K camera, the 8K camera, the 4K camera and the sensor are all connected to the SDN platform, and route path parameters are monitored through the sensor; and after the SDN platform receives the routing switching instruction, calculating routing path characteristics according to routing path parameters, performing characteristic dimension reduction by using principal component analysis, outputting optimal routing path parameters in combination with a genetic algorithm and a naive Bayesian network, and calculating an error between the optimal routing path parameters and the monitored routing path parameters to select a routing path. According to the invention, the stability and high efficiency of signal transmission are ensured, the waste of manufacturing resources is greatly reduced, and the system flexibility and the equipment utilization rate are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of video signal control, and particularly to an IP studio control method for 4K and 8K ultra-high definition linked production based on SDN. Background Art

[0002] With the continuous development of ultra-high definition television technology, especially in the field of video production with 4K and 8K resolutions, the construction and optimization of IP studio systems have become an important research direction in modern radio and television production. Currently, the core video devices of IP studio systems usually include cameras and other signal source devices, video switchers, IP scheduling systems, servers, and storage devices, etc. In the process of jointly producing 4K and 8K ultra-high definition TV programs, common production modes include: separate production of 4K and 8K, 4K down-conversion after 8K production, and 8K up-conversion after 4K production. However, these modes have exposed many technical bottlenecks and resource waste problems in practical applications.

[0003] First of all, the separate production mode of 4K and 8K requires two sets of independent production platforms to complete program production respectively, that is, a set of 4K production system and a set of 8K production system. Although this mode can ensure the independent production of each resolution to a certain extent, its disadvantages are also very obvious: on the one hand, there is obvious waste of system device resources, especially in the two independent systems, it is difficult to reuse devices efficiently; on the other hand, there are also great inconveniences in the management and operation and maintenance of the two independent systems. For example, there may be problems such as camera position conflicts, device coordination problems, and uneven distribution of human resources in the studio hall, resulting in inflexible system operation and low efficiency.

[0004] In the mode of 4K down-conversion after 8K production, first, an 8K program is produced through an 8K production system, and then the 8K signal is converted into a 4K signal through a down-conversion device. Although this mode can carry out 4K production after 8K production, it has the defect of resource waste. In the case of only 4K program requirements, it is still necessary to use 8K resources to complete the production, which not only wastes the high-performance resources of 8K devices but also increases the equipment usage cost and operation and maintenance complexity. In addition, the signal down-conversion from 8K to 4K usually relies on specific hardware devices or software, and the signal quality is often affected to a certain extent during the conversion process, and it is impossible to maintain the details and clarity of the native 4K signal, reducing the program production quality.

[0005] In the mode of upscaling to 8K after 4K production, first, a 4K program is produced through a set of 4K production systems, and then the 4K signal is converted into an 8K signal through an upscaling device. The disadvantage of this mode is that although upscaling can make 4K content reach 8K resolution, the quality of the generated 8K signal is far inferior to that of the native 8K signal. During the upscaling process, the loss of signal details and distortion are relatively obvious, resulting in the final 8K image quality being inferior to the original 8K signal, affecting the visual effect of program broadcasting and failing to meet the high-quality standards of ultra-high-definition content. Summary of the Invention

[0006] In view of the above existing problems, the present invention is proposed.

[0007] Therefore, the present invention provides an IP studio control method for 4K and 8K ultra-high-definition linked production based on SDN to solve the problems of the prior art.

[0008] To solve the above technical problems, the present invention provides the following technical solutions:

[0009] In a first aspect, the present invention provides an IP studio control method for 4K and 8K ultra-high-definition linked production based on SDN, which includes,

[0010] Deploy 8K cameras and 4K cameras in the studio to collect video signals, perform color matching and signal consistency adjustment on the 4K cameras based on the output of the 8K cameras, and monitor the routing path parameters through sensors. The 8K cameras, 4K cameras, and sensors are all connected to the SDN platform;

[0011] After receiving a routing switch instruction, the SDN platform calculates the routing path characteristics based on the routing path parameters, performs feature dimensionality reduction using principal component analysis, and then combines genetic algorithms and naive Bayesian networks to output the optimal routing path parameters, and calculates the error between the optimal routing path parameters and the monitored routing path parameters to select the routing path;

[0012] The SDN platform forwards the video signal based on the routing path through the NMOS protocol, switches the video signal according to requirements, and the studio displays the video signal through a multi-view splitter.

[0013] As a preferred solution of the IP studio control method for 4K and 8K ultra-high-definition linked production based on SDN of the present invention, wherein: after receiving a routing switch instruction, the SDN platform calculates the routing path characteristics based on the routing path parameters, performs feature dimensionality reduction using principal component analysis, and then combines genetic algorithms and naive Bayesian networks to output the optimal routing path parameters, and calculates the error between the optimal routing path parameters and the monitored routing path parameters to select the routing path includes:

[0014] The SDN platform receives a routing path, and calculates the available bandwidth A of the routing path according to the difference in the number of bytes received in a single time interval for the routing path;

[0015] Calculates the routing path delay D according to the routing path switch delay, and calculates the path jitter J according to the routing path delays at different time points;

[0016] Calculates the packet loss rate L according to the difference in the number of bytes between the output port and the receiving port of the routing path;

[0017] Concatenates the available bandwidth A, delay D, path jitter J, and packet loss rate L of the routing path to form the routing path feature X, combines the features of all routing paths to form a feature set, and performs dimensionality reduction processing on the feature set using the principal component analysis method;

[0018] Forms each routing path feature into a genetic individual and combines them into an initial population, collects the routing path historical parameters, and evaluates each genetic individual based on the naive Bayesian network to output the posterior probability P(Z|X) of the genetic individual;

[0019] Uses the posterior probability of the genetic individual as the individual fitness, performs iterative operations of crossover and mutation and outputs new genetic individuals to update the genetic population. When the fitness of the iterative genetic individuals converges, stops the iteration, outputs the genetic individual with the maximum fitness, and extracts the optimal routing path feature in the genetic individual;

[0020] Extracts the parameters in the optimal routing path feature and calculates the absolute value differences of the available bandwidth A, delay D, path jitter J, and packet loss rate L calculated with the parameters in the routing path feature X, and calculates the posterior probability of error P * (Z|X) of each path again based on the absolute value differences through the naive Bayesian network;

[0021] Selects the routing path with the maximum posterior probability of error P * (Z|X) as the selected routing path, and adjusts the selected routing path according to the parameters in the optimal routing path feature to form the final routing path.

[0022] As a preferred solution of the IP studio control method for 4K and 8K ultra-high-definition linked production based on SDN of the present invention, wherein: the step of arranging 8K cameras and 4K cameras in the studio to collect video signals means setting the 8K cameras as the main cameras and the 4K cameras as the auxiliary cameras in the studio, and configuring a three-sync signal generator for all 8K cameras and 4K cameras.

[0023] As a preferred solution of the IP studio control method for 4K and 8K ultra-high definition linked production based on SDN according to the present invention, wherein: the color matching and signal consistency adjustment of the 4K camera based on the output of the 8K camera means that the color matching of the 4K camera is performed using a color transformation matrix according to the output video signal of the 8K camera;

[0024] The video signals output by all cameras are uniformly converted into the HLG format through signal conversion, and PTP is used for video signal time synchronization. Frame synchronization of 4K and 8K video signals is performed through the FPGA hardware caching method.

[0025] As a preferred solution of the IP studio control method for 4K and 8K ultra-high definition linked production based on SDN according to the present invention, wherein: the SDN platform forwards video signals based on the routing path through the NMOS protocol means that the SDN platform queries the capabilities of the receiving device through the NMOS protocol and judges the receiving capabilities of the receiving device by setting smart contracts. When the SDN platform judges that the receiving capabilities of the receiving device are qualified, the video signals collected by the 8K camera and the 4K camera are sent based on the final routing path.

[0026] As a preferred solution of the IP studio control method for 4K and 8K ultra-high definition linked production based on SDN according to the present invention, wherein: the switching of video signals according to requirements means that the SDN platform switches the video signals according to the final video signal output requirements. When it is necessary to convert from a 4K video signal to an 8K video signal, the SDN platform performs the conversion through up-conversion technology and flow table control. Conversely, video encoder compression coding conversion is used.

[0027] As a preferred solution of the IP studio control method for 4K and 8K ultra-high definition linked production based on SDN according to the present invention, wherein: the studio displays video signals through a multi-view divider means that the studio is equipped with a multi-view divider to synchronously display 4K and 8K video signals, and the routing path characteristics of each routing path are extracted and displayed through the SDN platform.

[0028] As a preferred solution of the IP studio control method for 4K and 8K ultra-high definition linked production based on SDN according to the present invention, wherein: after the SDN platform obtains the optimal routing path each time and forwards video signals through the optimal routing path, a routing path switching record is automatically generated and stored, and a time stamp and routing path parameters are attached to the routing path switching record.

[0029] Second aspect, the present invention provides a computer device, including a memory and a processor, where the memory stores a computer program, and: when the computer program is executed by the processor, any step of the IP studio control method for 4K and 8K ultra-high-definition linked production based on SDN as described in the first aspect of the present invention is implemented.

[0030] Third aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and: when the computer program is executed by the processor, any step of the IP studio control method for 4K and 8K ultra-high-definition linked production based on SDN as described in the first aspect of the present invention is implemented.

[0031] The beneficial effects of the present invention are as follows: The present invention dynamically calculates and allocates the optimal routing path according to the routing path parameters through the SDN platform to ensure the stability and efficiency of signal transmission, and uses the SDN platform for signal switching, which can realize the linked production between different signal sources and different picture qualities during the program production process, greatly reducing the waste of production resources and improving the flexibility of the system and the utilization rate of equipment. Description of the Drawings

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0033] Figure 1 It is a flowchart of the IP studio control method for 4K and 8K ultra-high-definition linked production based on SDN in Embodiment 1. Detailed Embodiments

[0034] To make the above objects, features, and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention will be described in detail below with reference to the drawings in the specification.

[0035] Many specific details are set forth in the following description to facilitate a thorough understanding of the present invention, but the present invention may be implemented in other ways different from those described herein. Those skilled in the art can make similar generalizations without departing from the spirit of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0036] Secondly, the so-called "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation manner of the present invention. The appearances of "in one embodiment" in different places in this specification do not all refer to the same embodiment, nor are they separate or alternative embodiments that exclude each other.

[0037] Example 1, referring to Figure 1 , which is the first embodiment of the present invention. This embodiment provides an IP studio control method for 4K and 8K ultra-high-definition linked production based on SDN, including the following steps:

[0038] S1. Arrange 8K cameras and 4K cameras in the studio to collect video signals, perform color matching and signal consistency adjustment on the 4K cameras based on the output of the 8K cameras, and monitor the routing path parameters through sensors. The 8K cameras, 4K cameras, and sensors are all connected to the SDN platform;

[0039] Specifically, arranging 8K cameras and 4K cameras in the studio to collect video signals means setting the 8K cameras as the main cameras and the 4K cameras as the auxiliary cameras in the studio, and configuring a three-synchronous signal generator for all 8K cameras and 4K cameras.

[0040] Reasonable camera allocation greatly improves the coordination and flexibility of the shooting process in the studio, maximizes the advantages of 8K and 4K cameras, and ensures that the shooting content is fully presented from multiple angles. In addition, due to the clear roles, problems such as picture crossover and conflict during shooting are avoided, significantly improving production efficiency and content quality. By configuring a three-synchronous signal generator, the present invention effectively solves the problem of signal synchronization in multi-camera shooting. The enhanced synchronization of the cameras not only improves the stability of on-site shooting but also provides higher-quality original video materials for post-editing. Especially when switching multiple shots, the transition of the picture switch is smoother and more natural, reducing visual problems caused by time errors of different cameras. In this way, the studio can achieve more efficient content creation during the production process and reduce the workload of correction in post-production.

[0041] Further, performing color matching and signal consistency adjustment on the 4K cameras based on the output of the 8K cameras means performing color matching on the 4K cameras using a color transformation matrix according to the output video signal of the 8K cameras:

[0042]

[0043] where (R‘, G ′ , B ′ ) is the color value after color matching, M ij is the weight of the color transformation matrix, determined by actual measurement, (R, G, B) is the original color value of the 4K camera, and r, g, and b are the color offset compensation amounts;

[0044] The video signals output by all cameras are uniformly converted to the HLG format through signal conversion, and PTP is used for video signal time synchronization. Frame synchronization of 4K and 8K video signals is performed through the FPGA hardware caching method.

[0045] During multi-camera shooting, through precise matching, it ensures that all pictures are consistent in color, provides an efficient workflow, and improves the overall quality of the work. Converting the signals uniformly to the HLG format not only ensures the compatibility of video signals between various display devices but also enhances the visual effect of ultra-high-definition videos, ensuring that viewers can obtain a consistent picture experience when watching on different devices, especially suitable for the efficient dissemination of 4K and 8K content. PTP synchronization makes the timing between cameras precisely consistent, avoiding synchronization problems caused by time differences in multi-camera shooting, ensuring smooth switching of video pictures, and improving the overall production quality and viewer experience. The FPGA hardware cache provides an efficient and low-latency frame synchronization solution, ensuring smooth switching and synchronization of multi-resolution signals, avoiding problems such as picture stuttering or time misalignment, especially suitable for ultra-high-definition live broadcast and production scenarios.

[0046] S2. After the SDN platform receives the routing switch instruction, it calculates the routing path characteristics according to the routing path parameters, uses principal component analysis for feature dimensionality reduction, and then combines genetic algorithms and naive Bayesian networks to output the optimal routing path parameters, and calculates the error between the optimal routing path parameters and the monitored routing path parameters to select the routing path;

[0047] Specifically, after the SDN platform receives the routing switch instruction, it calculates the routing path characteristics according to the routing path parameters, uses principal component analysis for feature dimensionality reduction, and then combines genetic algorithms and naive Bayesian networks to output the optimal routing path parameters. Calculating the error between the optimal routing path parameters and the monitored routing path parameters to select the routing path includes:

[0048] The SDN platform receives the routing path and calculates the available bandwidth A of the routing path according to the difference in the number of bytes received in a single time interval of the routing path:

[0049]

[0050] where C is the maximum bandwidth of the routing path, b t1 and b t2 are the number of received bytes at time t1 and time t2 respectively, and Δt is the time interval;

[0051] Calculate the routing path delay D according to the routing path switch delay, and calculate the path jitter J according to the routing path delays at different time points:

[0052] D = T - D1 - D2;

[0053] J = D(t1) - D(t2);

[0054] where T is the total delay of the routing path, and D1 and D2 are the delays of the sending and receiving switches respectively;

[0055] Calculate the packet loss rate L based on the difference in the number of bytes between the output port and the receiving port of the routing path:

[0056]

[0057] where sxop is the number of bytes of the output port and rxip is the number of bytes of the receiving port;

[0058] Concatenate the available bandwidth A, delay D, path jitter J, and packet loss rate L of the routing path to form the routing path feature X, and combine the features of all routing paths to form a feature set. Use the principal component analysis method to perform dimensionality reduction on the feature set;

[0059] Form genetic individuals from each routing path feature and combine them into an initial population. Collect the historical parameters of the routing path and evaluate each genetic individual based on the naive Bayesian network to output the posterior probability P(Z|X) of the genetic individual;

[0060]

[0061] where P(Z|X) is the posterior probability that the routing path Z is the optimal path given the routing path feature X, P(X|Z) is the probability that the routing path feature X appears given the routing path Z, and P(Z) and P(X) are the prior probabilities of the routing path Z and the routing path feature X respectively, calculated from the historical parameters of the routing path;

[0062] Take the posterior probability of the genetic individual as the individual fitness, perform iterative operations using crossover and mutation operations and output new genetic individuals to update the genetic population. Stop the iteration when the fitness of the iterative genetic individual converges, output the genetic individual with the maximum fitness, and extract the optimal routing path feature in the genetic individual;

[0063] Extract the parameters in the optimal routing path feature and calculate the absolute differences between the parameters for calculating the available bandwidth A, delay D, path jitter J, and packet loss rate L in the routing path feature X respectively. Then, calculate the posterior probability of the error P * (Z|X):

[0064] P * (Z|X) = P(Z) * P(ΔA|Z) * P(ΔD|Z) * P(ΔJ|Z) * P(ΔL|Z);

[0065] where ΔA, ΔD, ΔJ, and ΔL are the absolute differences of the available bandwidth A, latency D, path jitter J, and packet loss rate L, respectively, and P(ΔA|Z), P(ΔD|Z), P(ΔJ|Z), and P(ΔL|Z) are the occurrence probabilities of the routing path feature X under the corresponding absolute differences;

[0066] Select the routing path with the maximum posterior probability P * (Z|X) as the selected routing path, and adjust the selected routing path according to the parameters in the optimal routing path feature to form the final routing path.

[0067] By performing real-time calculation and monitoring on parameters such as the available bandwidth, latency, jitter, and packet loss rate of the network path, it can accurately reflect the dynamic performance of the network. This real-time monitoring mechanism solves the problem in the prior art that it is unable to adapt to network changes in real time, can ensure more accurate routing selection, avoid network congestion or degradation of transmission quality. The steps of CA dimensionality reduction effectively reduce the dimension of the routing path feature and remove redundant information, thereby improving the efficiency of subsequent calculations. Using the genetic algorithm in combination with the naive Bayes network can not only find the optimal solution in the multi-solution space by the genetic algorithm but also combine the naive Bayes network to evaluate the posterior probability of the path. This combination method can learn the stability and performance of the path through historical data and accurately select the best path. When selecting the optimal routing path, calculating the posterior probability of error can help accurately measure the differences between paths. Through this mechanism, the system can select the path with the smallest error, thereby reducing the performance loss caused by incorrect path selection.

[0068] S3. The SDN platform forwards video signals based on the routing path through the NMOS protocol and switches the video signals according to requirements. The studio displays the video signals through a multi-view splitter;

[0069] Specifically, the SDN platform forwards video signals based on the routing path through the NMOS protocol means that the SDN platform queries the capabilities of the receiving device through the NMOS protocol and judges the receiving capabilities of the receiving device by setting smart contracts. When the SDN platform determines that the receiving capabilities of the receiving device are qualified, it sends the video signals collected by the 8K camera and the 4K camera based on the final routing path.

[0070] By querying and evaluating the capabilities of automated devices, the need for manual intervention is reduced, device compatibility and system flexibility are improved, ensuring that video signals can be transmitted accurately and stably in an environment with multiple devices, avoiding playback problems caused by device mismatches or insufficient capabilities. The smart contract provides an efficient and automatic device capability verification mechanism for the SDN platform. This process not only reduces human errors but also improves the system response speed, enabling the system to quickly adapt to changes in receiving devices, enhancing work efficiency and stability in studio production. Through dynamic routing path selection, the SDN platform can achieve more efficient and stable signal transmission according to different network and device conditions. This design greatly improves the transmission effect of multi-camera and different-resolution signals in the same network environment, ensuring the stable output of high-quality video signals. Especially in complex studio or live broadcast environments, it can provide a seamless switching playback effect.

[0071] Furthermore, switching the video signal according to requirements means that the SDN platform switches the video signal according to the final video signal output requirements. When it is necessary to convert from a 4K video signal to an 8K video signal, the SDN platform performs the conversion through upscaling technology and flow table control. Conversely, a video encoder is used for compression encoding conversion.

[0072] The upscaling technology and flow table control for achieving the 4K to 8K conversion make the video signal conversion process more flexible and efficient, capable of real-time adjustment according to actual network conditions, avoiding problems such as signal overload or quality degradation. Through flow table control, the SDN platform can provide the best routing path under various network conditions, ensuring that video quality is not affected and bandwidth usage is optimized during the signal conversion process. Using a video encoder to compress and convert the 8K signal to a 4K signal effectively solves the challenges of high-resolution video signals in terms of bandwidth and transmission efficiency. Through compression encoding, not only is video quality ensured, but also bandwidth usage is optimized, enabling more efficient utilization of network resources. Especially in environments with limited bandwidth or high transmission requirements, this compression technology can significantly improve the transmission efficiency of video signals and reduce the risk of network congestion.

[0073] Even further, the studio displays the video signal through a multi-view divider, which means that the studio is equipped with a multi-view divider to synchronously display 4K and 8K video signals, and the SDN platform extracts and displays the routing path characteristics of each routing path.

[0074] Even further, after the SDN platform obtains the optimal routing path each time and forwards the video signal through the optimal routing path, a routing path switching record is automatically generated and stored, and a timestamp and routing path parameters are attached to the routing path switching record.

[0075] This embodiment also provides a computer device, which is applicable to the situation of an IP studio control method for 4K and 8K ultra-high-definition linked production based on SDN, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the IP studio control method for 4K and 8K ultra-high-definition linked production based on SDN as proposed in the above embodiment.

[0076] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a carrier network, NFC (Near Field Communication), or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, a touchpad, or a mouse, etc.

[0077] This embodiment also provides a storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the IP studio control method for 4K and 8K ultra-high-definition linked production based on SDN as proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (abbreviated as SRAM), electrically erasable programmable read-only memory (abbreviated as EEPROM), erasable programmable read-only memory (abbreviated as EPROM), programmable read-only memory (abbreviated as PROM), read-only memory (abbreviated as ROM), magnetic memory, flash memory, a magnetic disk, or an optical disc.

[0078] In summary, the present invention dynamically calculates and allocates the optimal routing path according to the routing path parameters through the SDN platform to ensure stable and efficient signal transmission, and uses the SDN platform for signal switching, which can realize the linkage production between different signal sources and different picture qualities in the program production process, greatly reducing the waste of production resources and improving the system flexibility and equipment utilization.

[0079] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An IP studio control method for 4K and 8K ultra-high-definition linked production based on SDN, characterized in that: Including, An 8K camera and a 4K camera are arranged in the studio to collect video signals. Color matching and signal consistency adjustment are performed on the 4K camera based on the output of the 8K camera, and the routing path parameters are monitored by sensors. The 8K camera, 4K camera, and sensors are all connected to the SDN platform; After receiving the routing switch instruction, the SDN platform calculates the routing path characteristics according to the routing path parameters, performs feature dimensionality reduction using principal component analysis, and then combines genetic algorithms and naive Bayesian networks to output the optimal routing path parameters. The routing path is selected by calculating the error between the optimal routing path parameters and the monitored routing path parameters; The SDN platform forwards the video signals based on the routing path through the NMOS protocol and switches the video signals according to requirements. The studio displays the video signals through a multi-view splitter.

2. The IP studio control method for 4K and 8K ultra-high definition linked production based on SDN according to claim 1, characterized in that: After receiving the routing switch instruction, the SDN platform calculates the routing path characteristics according to the routing path parameters, performs feature dimensionality reduction using principal component analysis, and then combines genetic algorithms and naive Bayesian networks to output the optimal routing path parameters. Calculating the error between the optimal routing path parameters and the monitored routing path parameters to select the routing path includes: The SDN platform calculates the available bandwidth A of the routing path according to the difference in the number of bytes received by the routing path at a single time interval; Calculating the routing path delay D according to the routing path switch delay, and calculating the path jitter J according to the routing path delays at different time points; Calculating the packet loss rate L according to the difference in the number of bytes between the output port and the receiving port of the routing path; Concatenating the available bandwidth A, delay D, path jitter J, and packet loss rate L of the routing path to form the routing path feature X, combining the features of all routing paths to form a feature set, and performing dimensionality reduction processing on the feature set using the principal component analysis method; Forming genetic individuals for each routing path feature and combining them into an initial population, collecting the routing path historical parameters, and evaluating each genetic individual based on the naive Bayesian network to output the posterior probability P(Z|X) of the genetic individual; Taking the posterior probability of the genetic individual as the individual fitness, performing iterative operations using crossover and mutation operations and outputting new genetic individuals to update the genetic population. When the fitness of the iterative genetic individuals converges, stop the iteration, output the genetic individual with the maximum fitness, and extract the optimal routing path feature from the genetic individual; Extracting the parameters in the optimal routing path feature and calculating the absolute value differences of the available bandwidth A, delay D, path jitter J, and packet loss rate L from the parameters in the routing path feature X respectively, and then calculating the posterior probability of the error P*(Z|X) of each path based on the absolute value differences through the naive Bayesian network again; Selecting the routing path with the maximum posterior probability of error P*(Z|X) as the selected routing path, and adjusting the selected routing path according to the parameters in the optimal routing path feature to form the final routing path.

3. The IP studio control method for 4K and 8K ultra-high definition linkage production based on SDN according to claim 2, characterized in that: The statement of arranging an 8K camera and a 4K camera in the studio to collect video signals means setting the 8K camera as the main camera in the studio and the 4K camera as the auxiliary camera, and configuring a three-synchronization signal generator for all 8K cameras and 4K cameras.

4. The IP studio control method for 4K and 8K ultra-high definition linked production based on SDN according to claim 3, characterized in that: The color matching and signal consistency adjustment of the 4K camera based on the output of the 8K camera refers to performing color matching on the 4K camera using a color transformation matrix according to the output video signal of the 8K camera; All video signals output by the cameras are uniformly converted to the HLG format through signal conversion, and PTP is used for video signal time synchronization. Frame synchronization of 4K and 8K video signals is performed through the FPGA hardware caching method.

5. The IP studio control method for 4K and 8K ultra-high definition linked production based on SDN according to claim 4, characterized in that: The SDN platform forwards video signals based on the routing path through the NMOS protocol, which means that the SDN platform queries the capabilities of the receiving device through the NMOS protocol and determines the receiving capabilities of the receiving device by setting smart contracts. After the SDN platform determines that the receiving capabilities of the receiving device are qualified, it sends the video signals collected by the 8K camera and the 4K camera based on the final routing path.

6. The IP studio control method for 4K and 8K ultra-high definition linked production based on SDN according to claim 5, characterized in that: The switching of video signals according to requirements means that the SDN platform switches video signals according to the final video signal output requirements. When it is necessary to convert from a 4K video signal to an 8K video signal, the SDN platform performs the conversion through up-conversion technology and flow table control. Conversely, video encoder compression coding conversion is used.

7. The IP studio control method for 4K and 8K ultra-high definition linked production based on SDN according to claim 6, characterized in that: The studio displays video signals through a multi-view divider, which means that the studio is equipped with a multi-view divider to synchronously display 4K and 8K video signals, and the SDN platform extracts and displays the routing path characteristics of each routing path.

8. The IP studio control method for 4K and 8K ultra-high definition linked production based on SDN according to claim 7, wherein: After the SDN platform obtains the optimal routing path each time and forwards video signals through the optimal routing path, a routing path switching record is automatically generated and stored, and a timestamp and routing path parameters are attached to the routing path switching record.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the IP studio control method for 4K and 8K ultra-high-definition linked production based on SDN according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the IP studio control method for 4K and 8K ultra-high-definition linked production based on SDN according to any one of claims 1 to 8.

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