Image content conversion system based on artificial intelligence model

Abstract

The invention relates to a picture content conversion system based on an artificial intelligence model, and the system comprises a numerical value detection device which is disposed in a control room of an industrial park, and is used for obtaining the signal-to-noise ratio of a picture content obtained after a spatial enhanced image executes a current smoothing algorithm through employing the artificial intelligence model; and the selection smoothing device is used for taking the smoothing algorithm corresponding to the maximum numerical value in the signal-to-noise ratios corresponding to the smoothing algorithms as an optimal smoothing algorithm so as to execute corresponding smoothing processing on the airspace enhanced image. According to the invention, on the basis of using the artificial intelligence model with a customized structure, the smoothing algorithm corresponding to the maximum value in the signal-to-noise ratio corresponding to each smoothing algorithm is used as the preferable smoothing algorithm for executing corresponding smoothing processing on the airspace enhanced image after targeted sharpening processing on the aerial view image of the industrial park; and a corresponding optimal smooth picture is obtained and output, so that the visual monitoring effect of the industrial park is improved.

Description

Technical Field

[0001] This invention relates to the field of image processing, and in particular to an image content conversion system based on an artificial intelligence model. Background Technology

[0002] Artificial intelligence (AI) is an important component of the discipline of intelligence. It attempts to understand the essence of intelligence and produce new intelligent machines that can react in a way similar to human intelligence. Research in this field includes robotics, speech recognition, image recognition, natural language processing, and expert systems. Since its inception, AI has seen increasing maturity in both theory and technology, and its application areas have continued to expand. It is conceivable that future AI-driven technological products will serve as "containers" of human wisdom. AI can simulate the information processes of human consciousness and thought. While AI is not human intelligence, it can think like a human and may even surpass human intelligence.

[0003] In existing technologies, the content of aerial views of industrial parks varies at different times. This means that if the same smoothing algorithm is used to smooth all aerial views of industrial parks in the same way, the final image quality is often not optimal. Therefore, it is necessary to find a smoothing algorithm that can obtain the best image quality for aerial views of industrial parks at different times, which is the technical solution that needs to be provided.

[0004] CN115037872A discloses a video processing method and related apparatus. The method includes: a terminal device displaying a first interface; the first interface including a first control and a first video frame, the first video including: transition information between a first video segment and a second video segment, the first video segment and the second video segment; the terminal device receiving and responding to a trigger operation for the first control on the first interface; the terminal device adding a transition effect according to the transition information to obtain a second video; in the second video, a portion of the first video segment close to the second video segment, and / or, a portion of the second video segment close to the first video segment, playing at a reduced playback speed; and the terminal device playing a preview of the second video. CN113934883A discloses a method for synchronous playback and display of multiple types of data, including the following steps: (1) Data acquisition and storage; wherein, for the first type of data stored locally, the upload time is used as the standard time, and a timestamp is added to the data frame; for the second type of data not stored locally, the time of the off-site storage system is periodically calibrated, and a timestamp of the initial moment is added to the data segment; (2) Data playback and display, including: determining the initial playback moment and standard frame rate; indexing the data through the timestamp; and data playback and display. This invention addresses the problems of inconsistent data frame rates and difficulty in synchronizing playback and display of multiple types of data. By storing different types of data in a standardized format and indexing them according to the standard frame rate during playback, consistency of data playback is achieved. It has the advantages of simple data processing, smooth playback and display without lag, and low system resource consumption. Summary of the Invention

[0005] To address technical issues in related fields, this invention provides a screen content conversion system based on an artificial intelligence model. Using a customized artificial intelligence model, the system selects the smoothing algorithm with the highest signal-to-noise ratio among various smoothing algorithms as the preferred smoothing algorithm. This algorithm is then used to perform corresponding smoothing processing on the spatial enhancement image after targeted sharpening of an aerial view of an industrial park, obtaining and outputting the corresponding optimal smoothed image, thereby improving the visual monitoring effect of the industrial park.

[0006] According to the present invention, a screen content conversion system based on an artificial intelligence model is provided, the system comprising:

[0007] A mode switching device is installed in the control room of the industrial park to turn off the visible light camera during nighttime hours and turn it on during daytime hours.

[0008] A visible light camera is positioned directly above the center of the industrial park and is used to perform bird's-eye view photography of the industrial park during the daytime period, driven by the mode switching device, to obtain bird's-eye view images.

[0009] A filtering and sharpening device is installed in the control room of the industrial park and connected to the visible light camera. It is used to perform high-pass filtering and sharpening processing on the received bird's-eye view video to obtain and output the corresponding filtered and sharpened image.

[0010] A signal conversion device, connected to the filtering and sharpening device, is used to perform USM filter-based sharpening processing on the received filtered and sharpened image to obtain and output the corresponding real-time sharpened image.

[0011] The content enhancement device, connected to the signal conversion device, is used to perform image spatial enhancement processing on the received real-time sharpened image to obtain and output the corresponding spatial enhancement image;

[0012] A numerical detection device, located in the control room of an industrial park, is connected to the content enhancement equipment and includes a region resolution unit, a content processing unit, and a signal-to-noise ratio (SNR) identification unit. The content processing unit is connected to both the region resolution unit and the SNR identification unit. The numerical detection device is used to identify each foreground imaging region in the received spatial domain enhancement image, and to detect multiple information parameters of each foreground imaging region to obtain multiple information parameters of each foreground imaging region. The multiple information parameters of each foreground imaging region are the grayscale value, horizontal coordinate value, and vertical coordinate value of each pixel in the foreground imaging region. The multiple information parameters of each foreground imaging region, the contrast of the spatial domain enhancement image, the number of noise-invaded pixels, and the binary value of the code corresponding to the current smoothing algorithm are synchronously input into an artificial intelligence model and the artificial intelligence model is run to obtain the SNR of the image content obtained after the current smoothing algorithm is applied to the spatial domain enhancement image. The artificial intelligence model is a radial basis function neural network that has undergone multiple training iterations, and the number of training iterations is proportional to the total number of pixels in the foreground imaging region.

[0013] A smoothing device is selected and connected to the numerical detection device. It is used to select the smoothing algorithm with the largest signal-to-noise ratio among the various smoothing algorithms as the preferred smoothing algorithm to perform corresponding smoothing processing on the spatial domain enhanced image, thereby obtaining and outputting the corresponding optimal smoothed image. Attached Figure Description

[0014] The embodiments of the present invention will now be described with reference to the accompanying drawings.

[0015] Figure 1 The diagram below shows a structural block diagram of a screen content conversion system based on an artificial intelligence model, according to an embodiment A of the present invention.

[0016] Figure 2The diagram below shows a structural block diagram of a screen content conversion system based on an artificial intelligence model according to embodiment B of the present invention.

[0017] Figure 3 The diagram illustrates a structural block diagram of an image content conversion system based on an artificial intelligence model according to embodiment C of the present invention. Detailed Implementation

[0018] The following will describe in detail the implementation scheme of the image content conversion system based on the artificial intelligence model of the present invention with reference to the accompanying drawings.

[0019] Implementation Plan A

[0020] Figure 1 The above is a structural block diagram of a screen content conversion system based on an artificial intelligence model according to embodiment A of the present invention. The system includes:

[0021] A mode switching device is installed in the control room of the industrial park to turn off the visible light camera during nighttime hours and turn it on during daytime hours.

[0022] For example, the mode switching device can be implemented using a programmable logic device to turn off the visible light camera during nighttime hours and turn it on during daytime hours;

[0023] A visible light camera is positioned directly above the center of the industrial park and is used to perform bird's-eye view photography of the industrial park during the daytime period, driven by the mode switching device, to obtain bird's-eye view images.

[0024] A filtering and sharpening device is installed in the control room of the industrial park and connected to the visible light camera. It is used to perform high-pass filtering and sharpening processing on the received bird's-eye view video to obtain and output the corresponding filtered and sharpened image.

[0025] A signal conversion device, connected to the filtering and sharpening device, is used to perform USM filter-based sharpening processing on the received filtered and sharpened image to obtain and output the corresponding real-time sharpened image.

[0026] The content enhancement device, connected to the signal conversion device, is used to perform image spatial enhancement processing on the received real-time sharpened image to obtain and output the corresponding spatial enhancement image;

[0027] A numerical detection device, located in the control room of an industrial park, is connected to the content enhancement equipment and includes a region resolution unit, a content processing unit, and a signal-to-noise ratio (SNR) identification unit. The content processing unit is connected to both the region resolution unit and the SNR identification unit. The numerical detection device is used to identify each foreground imaging region in the received spatial domain enhancement image, and to detect multiple information parameters of each foreground imaging region to obtain multiple information parameters of each foreground imaging region. The multiple information parameters of each foreground imaging region are the grayscale value, horizontal coordinate value, and vertical coordinate value of each pixel in the foreground imaging region. The multiple information parameters of each foreground imaging region, the contrast of the spatial domain enhancement image, the number of noise-invaded pixels, and the binary value of the code corresponding to the current smoothing algorithm are synchronously input into an artificial intelligence model and the artificial intelligence model is run to obtain the SNR of the image content obtained after the current smoothing algorithm is applied to the spatial domain enhancement image. The artificial intelligence model is a radial basis function neural network that has undergone multiple training iterations, and the number of training iterations is proportional to the total number of pixels in the foreground imaging region.

[0028] Select a smoothing device and connect it to the numerical detection device. Use it to select the smoothing algorithm with the largest value in each signal-to-noise ratio of each smoothing algorithm as the preferred smoothing algorithm to perform corresponding smoothing processing on the spatial domain enhanced image, and obtain and output the corresponding optimal smoothed image.

[0029] The mode switching device, located in the control room of the industrial park, is used to turn off the visible light camera during nighttime and turn it on during daytime. The mode switching device includes a data storage unit and a time judgment unit. The data storage unit is used to store the time distribution interval of the nighttime period in the area where the industrial park is located.

[0030] Implementation Plan B

[0031] Figure 2 The diagram below shows a structural block diagram of a screen content conversion system based on an artificial intelligence model according to embodiment B of the present invention.

[0032] Compared to embodiment A, embodiment B of the present invention illustrates an image content conversion system based on an artificial intelligence model, which may further include:

[0033] A parameter configuration device is connected to the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively, and is used to provide the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device with their respective required parameter configuration services;

[0034] The parameter configuration device is connected to the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively, and is used to provide the required parameter configuration services to the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively. The parameter configuration device uses an IIC configuration bus to provide the required parameter configuration services to the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively.

[0035] The parameter configuration device uses an IIC configuration bus to provide the required parameter configuration services to the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively, including: the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device each have different IIC configuration addresses;

[0036] The filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device each have different IIC configuration addresses, including: the different IIC configuration addresses of the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device are in binary numerical representation mode;

[0037] The different IIC configuration addresses of the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device are represented in binary numerical mode, including that the byte lengths of the different IIC configuration addresses of the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device are equal.

[0038] C Implementation Plan

[0039] Figure 3 The diagram illustrates a structural block diagram of an image content conversion system based on an artificial intelligence model according to embodiment C of the present invention.

[0040] Compared to embodiment A, embodiment C of the present invention illustrates an image content conversion system based on an artificial intelligence model, which may further include:

[0041] A positioning operation device is connected to the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively, and is used to provide positioning services for the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively.

[0042] The positioning operation device is connected to the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively, and is used to provide positioning services for the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively. The positioning operation device uses a GPS positioning mechanism to provide GPS positioning services for the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively.

[0043] The positioning operation device is connected to the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively, and is used to provide positioning services for the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively. The positioning operation device uses the BeiDou positioning mechanism to provide BeiDou positioning services for the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively.

[0044] In addition, in the image content conversion system based on the artificial intelligence model, the mode switching device, located in the control room of the industrial park, is used to turn off the visible light camera during nighttime and turn it on during daytime. It also includes: the time judgment unit is connected to the visible light camera and the data storage unit respectively, and is used to turn off the visible light camera during nighttime and turn it on during daytime.

[0045] Therefore, this invention has at least the following key technical innovations:

[0046] The first aspect is the use of a numerical detection device with a targeted structural design, including a region resolution unit, a content processing unit, and a signal-to-noise ratio (SNR) identification unit. The content processing unit is connected to the region resolution unit and the SNR identification unit respectively, providing key hardware resources for the intelligent analysis of the smoothing effects of different smoothing algorithms.

[0047] The second step is to identify each foreground imaging region in the received spatial domain enhancement image, detect multiple information parameters of each foreground imaging region, and obtain multiple information parameters of each foreground imaging region. The multiple information parameters of each foreground imaging region are the gray value corresponding to each pixel in the foreground imaging region, as well as the corresponding horizontal coordinate value and vertical coordinate value, thereby providing the necessary basic data for the intelligent analysis of the smoothing effect of the smoothing algorithm.

[0048] Thirdly: The binary values ​​of multiple information parameters of each foreground imaging region, the contrast of the spatial domain enhanced image, the number of noise-invaded pixels, and the code corresponding to the current smoothing algorithm are synchronously input into the artificial intelligence model and run the artificial intelligence model to obtain the signal-to-noise ratio of the image content obtained after the current smoothing algorithm is applied to the spatial domain enhanced image. The artificial intelligence model is a radial basis neural network after each training iteration, and the number of training iterations is proportional to the total number of pixels in each foreground imaging region.

[0049] Fourthly, based on the customized artificial intelligence model, the smoothing algorithm with the largest signal-to-noise ratio in each smoothing algorithm is selected as the preferred smoothing algorithm. This algorithm is used to perform corresponding smoothing processing on the spatial enhancement image after targeted sharpening of the aerial view of the industrial park, thereby obtaining and outputting the corresponding optimal smoothed image, thus improving the visual monitoring effect of the industrial park.

[0050] The image content conversion system based on the artificial intelligence model of this invention addresses the technical problem in the prior art that it is difficult to obtain the best matching smoothing algorithm for different aerial images of industrial parks. Based on a customized artificial intelligence model, it can select the smoothing algorithm with the largest signal-to-noise ratio in each set of smoothing algorithms as the preferred smoothing algorithm. This algorithm is then used to perform corresponding smoothing processing on the spatial enhancement image after targeted sharpening of the aerial image of the industrial park, thereby obtaining and outputting the corresponding optimal smoothed image, thus improving the visual monitoring effect of the industrial park.

[0051] Furthermore, the present invention is not limited to the embodiments described above, and can be embodied by modifying its constituent elements during implementation without departing from its spirit. Moreover, various inventions can be formed by appropriately combining the multiple constituent elements disclosed in the above embodiments. For example, several constituent elements can be deleted from all the constituent elements shown in this embodiment. Furthermore, constituent elements of different embodiments can also be appropriately combined.

Claims

1. A screen content conversion system based on an artificial intelligence model, characterized in that, The system includes: A mode switching device is installed in the control room of the industrial park to turn off the visible light camera during nighttime hours and turn it on during daytime hours. A visible light camera is positioned directly above the center of the industrial park and is used to perform bird's-eye view photography of the industrial park during the daytime period, driven by the mode switching device, to obtain bird's-eye view images. A filtering and sharpening device is installed in the control room of the industrial park and connected to the visible light camera. It is used to perform high-pass filtering and sharpening processing on the received bird's-eye view video to obtain and output the corresponding filtered and sharpened image. A signal conversion device, connected to the filtering and sharpening device, is used to perform USM filter-based sharpening processing on the received filtered and sharpened image to obtain and output the corresponding real-time sharpened image. The content enhancement device, connected to the signal conversion device, is used to perform image spatial enhancement processing on the received real-time sharpened image to obtain and output the corresponding spatial enhancement image; A numerical detection device, located in the control room of an industrial park, is connected to the content enhancement equipment and includes a region resolution unit, a content processing unit, and a signal-to-noise ratio (SNR) identification unit. The content processing unit is connected to both the region resolution unit and the SNR identification unit. The numerical detection device is used to identify each foreground imaging region in the received spatial domain enhancement image, and to detect multiple information parameters of each foreground imaging region to obtain multiple information parameters of each foreground imaging region. The multiple information parameters of each foreground imaging region are the grayscale value, horizontal coordinate value, and vertical coordinate value of each pixel in the foreground imaging region. The multiple information parameters of each foreground imaging region, the contrast of the spatial domain enhancement image, the number of noise-invaded pixels, and the binary value of the code corresponding to the current smoothing algorithm are synchronously input into an artificial intelligence model and the artificial intelligence model is run to obtain the SNR of the image content obtained after the current smoothing algorithm is applied to the spatial domain enhancement image. The artificial intelligence model is a radial basis function neural network that has undergone multiple training iterations, and the number of training iterations is proportional to the total number of pixels in the foreground imaging region. A smoothing device is selected and connected to the numerical detection device. It is used to select the smoothing algorithm with the largest signal-to-noise ratio among the various smoothing algorithms as the preferred smoothing algorithm to perform corresponding smoothing processing on the spatial domain enhanced image, thereby obtaining and outputting the corresponding optimal smoothed image.

2. The image content conversion system based on an artificial intelligence model as described in claim 1, characterized in that: A mode switching device, installed in the control room of an industrial park, is used to turn off the visible light camera during nighttime and turn it on during daytime. The mode switching device includes a data storage unit and a time judgment unit. The data storage unit is used to store the time distribution interval of the nighttime period in the area where the industrial park is located.

3. The image content conversion system based on an artificial intelligence model as described in claim 2, characterized in that, The system also includes: A parameter configuration device is connected to the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively, and is used to provide the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device with their respective required parameter configuration services; The parameter configuration device is connected to the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively, and is used to provide the parameter configuration services required by each of the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device. The parameter configuration device uses the IIC configuration bus to provide the parameter configuration services required by each of the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device.

4. The image content conversion system based on an artificial intelligence model as described in claim 3, characterized in that: The parameter configuration device uses the IIC configuration bus to provide the required parameter configuration services for the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively. The filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device each have different IIC configuration addresses.

5. The image content conversion system based on an artificial intelligence model as described in claim 4, characterized in that: The filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device each have different IIC configuration addresses, including: the different IIC configuration addresses of the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device are in binary numerical representation mode.

6. The image content conversion system based on an artificial intelligence model as described in claim 5, characterized in that: The different IIC configuration addresses of the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device are represented in binary numerical mode, including that the byte lengths of the different IIC configuration addresses of the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device are equal.

7. The image content conversion system based on an artificial intelligence model as described in claim 2, characterized in that, The system also includes: A positioning operation device is connected to the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively, and is used to provide positioning services for the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device, respectively.

8. The image content conversion system based on an artificial intelligence model as described in claim 7, characterized in that: A positioning operation device, connected to the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device respectively, is used to provide positioning services for the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device respectively, including: the positioning operation device using a GPS positioning mechanism to provide GPS positioning services for the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device respectively.

9. The image content conversion system based on an artificial intelligence model as described in claim 7, characterized in that: A positioning operation device, connected to the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device respectively, is used to provide positioning services for the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device respectively, including: the positioning operation device uses the BeiDou positioning mechanism to provide BeiDou positioning services for the filtering and sharpening device, the signal conversion device, the content enhancement device, and the numerical detection device respectively.

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