A multimodal big data transmission method based on the Internet

Abstract

The present invention relates to the field of image communication technology, and more particularly to an internet-based multimodal big data transmission method, comprising: obtaining teaching video image information data to be transmitted; obtaining the importance of the image information of each frame of image based on the grayscale distribution of each frame of image and the grayscale difference between each frame of image and adjacent frames of image; obtaining the transmission importance of each frame of image based on the image information importance of each frame of image and the text changes between each frame of image and adjacent frames of image; obtaining the compression level of each frame of image based on the transmission importance; compressing the teaching video image information data to be transmitted based on the compression level to obtain compressed teaching video image information data; and transmitting the compressed teaching video image information data. The present invention improves the transmission efficiency of teaching video image information data.

Description

Technical Field

[0001] The present invention relates to the field of image communication technology, and in particular to an Internet-based multimodal big data transmission method. Background Art

[0002] The construction of smart campuses has become an important part of educational informatization. Among them, video technology can be used for remote teaching and the implementation of smart classrooms. Through high-definition cameras and video conferencing systems, teachers and students can interact in real time across regions. In the process of transmitting teaching video image information data, the existing transmission technology only transmits data according to the order in which the data is generated. However, due to network fluctuations, if the data is transmitted directly according to the order in which it is generated, it will cause the teaching screen to freeze, resulting in low efficiency in the transmission of teaching video image information data. Summary of the Invention

[0003] In order to solve the above problems, the present invention provides an Internet-based multimodal big data transmission method, which includes:

[0004] Acquire teaching video image information data to be transmitted, wherein the teaching video image information data includes a plurality of frames of images;

[0005] The importance of the image information of each frame is obtained based on the grayscale distribution of each frame image and the grayscale difference between the adjacent frames; the transmission importance of each frame image is obtained based on the importance of the image information of each frame image and the text changes between the adjacent frames;

[0006] Obtain the compression level of each frame of image according to its transmission importance;

[0007] The teaching video image information data to be transmitted is compressed according to the compression degree to obtain compressed teaching video image information data; and the compressed teaching video image information data is transmitted.

[0008] Preferably, the method of obtaining the importance of the picture information of each frame of image according to the grayscale distribution of each frame of image and the grayscale difference between each frame of image and adjacent frames of image includes the following specific methods:

[0009] For the video image information data Frame image, according to Grayscale distribution in the frame image, get the The image expressiveness of the frame image;

[0010] According to Frame image and Grayscale difference between frame images, get the Frame image and The difference in image performance between frame images;

[0011] In the Frame image and The image performance difference between the frames and the Frame image and Among the image performance differences between frame images, the largest image performance difference is taken as the The target image of the frame image shows the difference; The difference between the target image performance of the frame image and the The product of the image expression of the frame image is recorded as the first product; the normalized value of the first product is recorded as the second product. The importance of the frame information.

[0012] Preferably, the obtaining The specific methods for the expressiveness of the frame image include:

[0013] The first The total number of grayscale value types in the frame image is the same as the The product of the mean values ​​of the gradient values ​​of all pixels in the frame image is recorded as the second product; The absolute value of the difference between the mean of the grayscale values ​​of all pixels in the frame image and 128 is recorded as the first absolute value of the difference; the ratio of the second product to the first absolute value of the difference is recorded as the second absolute value of the difference. The picture expressiveness of the frame image.

[0014] Preferably, the obtaining Frame image and The difference in image performance between frame images includes the following specific methods:

[0015] The first The total number of grayscale value types in the frame image is the same as the The absolute value of the difference between the total number of gray value types in the frame image is recorded as the gray level difference value; The mean of the gradient values ​​of all pixels in the frame image is The absolute value of the difference between the mean values ​​of the gradient values ​​of all pixels in the frame image is recorded as the gradient mean difference value; The mean gray value of all pixels in the frame image is The absolute value of the difference between the mean values ​​of the gray values ​​of all pixels in the frame image is recorded as the gray mean difference value; the product of the gray level difference value, the gradient mean difference value and the gray mean difference value is taken as the first Frame image and The difference in image performance between frame images.

[0016] Preferably, the transmission importance of each frame of image is obtained according to the importance of the picture information of each frame of image and the text changes between adjacent frames of image, including the specific method of:

[0017] For the video image information data Frame image, using optical character recognition technology to obtain the first The number of characters in the frame image; The difference in the number of characters between the frame image and the adjacent frame image is used to obtain the first The text change degree of the frame image; The text change degree and image information importance of the frame image are used to obtain the The importance preference of the frame image; according to the importance preference, obtain the first The transmission importance of the frame image.

[0018] Preferably, the obtaining The text change degree of the frame image includes the following specific methods:

[0019] The first The number of characters in the frame image is the same as the The absolute value of the difference in the number of characters in the frame image is recorded as the text quantity difference value; the text quantity difference value is compared with the first The ratio of the number of characters in the frame image is used as the The text variation of the frame image.

[0020] Preferably, the obtaining The importance preference of the frame image includes the following specific methods:

[0021] The first The text change degree of the frame image is the same as that of the The ratio of the importance of the frame information is recorded as the first priority; The text change degree of the frame image is the same as that of the The ratio of the importance of the frame information is recorded as the second priority; the maximum value between the first priority and the second priority is taken as the first priority. The importance preference of the frame image.

[0022] Preferably, the obtaining The importance of frame image transmission, including the following specific methods:

[0023] Preset a threshold parameter , if The importance of the frame image is preferably greater than the threshold parameter , will The importance of the frame information is taken as the first The importance of frame image transmission; if The importance of the frame image is preferably less than or equal to the threshold parameter , will The text change degree of the frame image is taken as the The transmission importance of the frame image.

[0024] Preferably, the method of obtaining the compression level of each frame of image according to the transmission importance level includes:

[0025] For any frame image in the video image information data, the reciprocal of the product of the transmission importance of the frame image and the network bandwidth size is recorded as the first reciprocal; the normalized value of the first reciprocal is used as the compression degree of the frame image.

[0026] Preferably, the method of compressing the teaching video image information data to be transmitted according to the compression degree to obtain the compressed teaching video image information data includes the following specific methods:

[0027] Preset a threshold parameter For any frame of video image information data, if the compression degree of the frame is greater than or equal to the threshold parameter , compress the frame image; if the compression degree of the frame image is less than the threshold parameter , the frame image is not compressed; and compressed video image information data is obtained.

[0028] The beneficial effects of the technical solution of the present invention are: the present invention obtains the importance of the picture information of each frame image according to the grayscale distribution of each frame image and the grayscale difference between adjacent frame images; obtains the transmission importance of each frame image according to the picture information importance of each frame image and the text change between adjacent frame images; obtains the compression degree of each frame image according to the transmission importance; compresses the teaching video image information data to be transmitted according to the compression degree to obtain compressed teaching video image information data; selectively compresses the teaching video image information data according to the compression degree, and can avoid the jamming phenomenon of the teaching picture by reducing the quality of images with low transmission importance; and transmits the compressed teaching video image information data to improve the transmission efficiency of the teaching video image information data. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0030] Figure 1 This is a flowchart of the steps of a multimodal big data transmission method based on the Internet of the present invention;

[0031] Figure 2 This is a characteristic relationship flow chart of a multimodal big data transmission method based on the Internet of the present invention. DETAILED DESCRIPTION

[0032] To further illustrate the technical means and effects employed by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effects of a multimodal big data transmission method based on the Internet proposed by the present invention. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0033] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0034] The following describes in detail a specific solution of an Internet-based multimodal big data transmission method provided by the present invention with reference to the accompanying drawings.

[0035] See also Figure 1 , which shows a flowchart of a method for transmitting multimodal big data over the Internet provided by one embodiment of the present invention, the method comprising the following steps:

[0036] Step S001: Acquire teaching video image information data to be transmitted.

[0037] It should be noted that with the in-depth popularization of smart campuses, smart classrooms and distance learning have become a part of students' normal learning life. However, for classroom teaching, network fluctuations will inevitably occur, which may cause problems such as picture freezes and sound delays, thereby making the teaching effect fail to meet the expected requirements; therefore, the importance of the image in the video image information data can be obtained based on the image performance in the teaching video image information data; the image is selectively compressed according to the importance, and then transmitted, thereby reducing the image freeze during the teaching process.

[0038] Specifically, first, it is necessary to collect the video image information data to be transmitted. The specific process is as follows:

[0039] The video image information data of the latest three minutes in the remote teaching process of the smart campus is collected as the teaching video image information data to be transmitted, and the teaching video image information data includes several frames of images.

[0040] So far, the video image information data to be transmitted is obtained through the above method.

[0041] Step S002: Obtain the importance of the picture information of each frame of image based on the grayscale distribution of each frame of image and the grayscale difference between adjacent frame images; obtain the transmission importance of each frame of image based on the importance of the picture information of each frame of image and the text changes between adjacent frame images.

[0042] It should be noted that since the video image information data in the remote video teaching process mainly includes teaching video image information data, in order to reduce the impact of network fluctuations on the quality of remote video teaching, the teaching video image information data can be analyzed to obtain the transmission importance of each frame of the teaching video image information data; the image is compressed to different degrees according to the transmission importance, so as to reduce the impact of network fluctuations on the quality of remote video teaching; in the teaching process, if the teaching teacher needs to use the picture as the main explanation, the video picture will show more obvious continuous changes at this time; when the teaching teacher does not need to use the picture much, the video picture may have a very small degree of change; therefore, the transmission importance of each frame of the teaching video image information data can be obtained based on the picture performance information of the single frame image, the difference in picture performance between adjacent frames, and the text change degree.

[0043] 1. Obtain the importance of the picture information of each frame in the video image information data.

[0044] It should be noted that for a single-frame image, it is necessary to pay attention to the key information displayed by the image, that is, the degree of detail and degree of expression of the image; it is inaccurate to judge the importance of the picture information of the current image only by a single-frame image. For video image information data, the performance between consecutive video frames also has certain influencing factors on the importance of the picture information of the current image. Therefore, it is necessary to further analyze the differences in picture performance between adjacent frame images to obtain the importance of the picture information of each frame image.

[0045] Preferably, in some implementations of the embodiments of the present invention, the calculation method for obtaining the importance of the picture information of each frame of image is:

[0046] For the video image information data Frame image, according to Grayscale distribution in the frame image, get the The image expressiveness of the frame image;

[0047] According to Frame image and Grayscale difference between frame images, get the Frame image and The difference in image performance between frame images;

[0048] In the Frame image and The image performance difference between the frames and the Frame image and Among the image performance differences between frame images, the largest image performance difference is taken as the The target image of the frame image shows the difference; The difference between the target image performance of the frame image and the The product of the image expression of the frame image is recorded as the first product; the normalized value of the first product is recorded as the second product. The importance of the frame information.

[0049] The specific formula is:

[0050]

[0051] Where, Indicates the The importance of the picture information of the frame image; Indicates the The image expressiveness of the frame image; Indicates the Frame image and The difference in image performance between frame images; Indicates the Frame image and The difference in image performance between frame images; Indicates taking the maximum value; represents the linear normalization function.

[0052] Preferably, in some implementations of the embodiments of the present invention, The method for obtaining the picture expressiveness of the frame image includes:

[0053] The first The total number of grayscale value types in the frame image is the same as the The product of the mean values ​​of the gradient values ​​of all pixels in the frame image is recorded as the second product; The absolute value of the difference between the mean of the grayscale values ​​of all pixels in the frame image and 128 is recorded as the first absolute value of the difference; the ratio of the second product to the first absolute value of the difference is recorded as the second absolute value of the difference. The picture expressiveness of the frame image.

[0054] The specific formula is:

[0055]

[0056] Where, Indicates the The image expressiveness of the frame image; Indicates the The total number of grayscale value types in the frame image; Indicates the The mean of the gradient values ​​of all pixels in the frame image; Indicates the The mean grayscale value of all pixels in the frame image; Indicates taking the absolute value; Represents the preset hyperparameters. This implementation presets , used to prevent the denominator from being 0.

[0057] It should be noted that the The more the total number of gray value types in the frame image, the greater the mean of the gradient values ​​of all pixels. The higher the detail level and clarity of the frame image, the better the picture performance. When the average grayscale value is too large or too small, the image will appear very bright or very dark, that is, the picture is relatively monotonous, and the picture performance is low. Therefore, the brightness and darkness of the picture are expressed by the absolute value of the first difference.

[0058] Preferably, in some implementations of the embodiments of the present invention, Frame image and The method for obtaining the image performance difference between frame images includes:

[0059] The first The total number of grayscale value types in the frame image is the same as the The absolute value of the difference between the total number of gray value types in the frame image is recorded as the gray level difference value; The mean of the gradient values ​​of all pixels in the frame image is The absolute value of the difference between the mean values ​​of the gradient values ​​of all pixels in the frame image is recorded as the gradient mean difference value; The mean gray value of all pixels in the frame image is The absolute value of the difference between the mean values ​​of the gray values ​​of all pixels in the frame image is recorded as the gray mean difference value; the product of the gray level difference value, the gradient mean difference value and the gray mean difference value is taken as the first Frame image and The difference in image performance between frame images.

[0060] The specific formula is:

[0061]

[0062] Where, Indicates the Frame image and The difference in image performance between frame images; Indicates the The total number of grayscale value types in the frame image; Indicates the The total number of grayscale value types in the frame image; Indicates the The mean of the gradient values ​​of all pixels in the frame image; Indicates the The mean grayscale value of all pixels in the frame image; Indicates the The mean of the gradient values ​​of all pixels in the frame image; Indicates the The mean grayscale value of all pixels in the frame image; Indicates taking the absolute value.

[0063] It should be noted that when rapid changes occur between continuous video images during remote video teaching, it means that the video image currently provided by the teacher is in a rapidly changing process. Compared with stable video images, rapidly changing video images obviously show that they contain more critical information. That is, if there is a large difference in image performance, it means that there is a large change between the current image and the previous and next images, and therefore the image information is more important.

[0064] At this point, the importance of the picture information of each frame of the video image information data is obtained.

[0065] 2. The importance of transmitting each frame of image in the video image information data.

[0066] It should be noted that, due to the special situations such as screen distortion and video freeze that may occur during the transmission of video image information data, the above calculation may determine that the importance of the picture information is relatively high. If the transmission importance is obtained only based on the importance of the picture information of each frame of the image, the judgment result will be inaccurate. Therefore, it is necessary to verify the importance of the judgment result in combination with the actual situation in the remote video teaching process; in the process of teachers teaching through remote video, combined with the actual situation, the teacher will use the whiteboard to show the teaching information to the students to impart knowledge; accordingly, the importance of the picture information can be corrected through the text data in each frame of the image to obtain the transmission importance.

[0067] Preferably, in some implementations of the embodiments of the present invention, the calculation method for obtaining the transmission importance of each frame of image is:

[0068] For the video image information data Frame image, using optical character recognition technology to obtain the first The number of characters in the frame image;

[0069] According to The difference in the number of characters between the frame image and the adjacent frame image is used to obtain the first The text change degree of the frame image;

[0070] According to The text change degree and the importance of the picture information of the frame image are used to obtain the The priority of the importance of the frame image;

[0071] According to the priority, get the The transmission importance of the frame image.

[0072] Among them, optical character recognition technology is an existing technology and will not be described in detail in this embodiment.

[0073] Preferably, in some implementations of the embodiments of the present invention, The method for obtaining the text change degree of the frame image includes:

[0074] The first The number of characters in the frame image is the same as the The absolute value of the difference in the number of characters in the frame image is recorded as the text quantity difference value; the text quantity difference value is compared with the first The ratio of the number of characters in the frame image is used as the The text change degree of the frame image.

[0075] Preferably, in some implementations of the embodiments of the present invention, The method for obtaining the priority of the importance of the frame image includes:

[0076] The first The text change degree of the frame image is the same as that of the The ratio of the importance of the frame information is recorded as the first priority; The text change degree of the frame image is the same as that of the The ratio of the importance of the frame information is recorded as the second priority; the maximum value between the first priority and the second priority is taken as the first priority. The importance preference of the frame image.

[0077] Preferably, in some implementations of the embodiments of the present invention, The method for obtaining the transmission importance of the frame image includes:

[0078] Preset a threshold parameter , wherein this embodiment is based on This example is described as an example, and this embodiment is not specifically limited. Depends on the specific implementation situation;

[0079] Jordi The importance of the frame image is preferably greater than the threshold parameter , will The importance of the frame information is taken as the first The importance of frame image transmission; if The importance of the frame image is preferably less than or equal to the threshold parameter , will The text change degree of the frame image is taken as the The transmission importance of the frame image.

[0080] It should be noted that the transmission importance of the image is verified by combining the difference in the number of characters between consecutive frame images with the importance of the image's picture information; when the difference in the number of characters between consecutive frame images is large, and the obtained picture information importance is also large, and the two are close, it indicates that the accuracy of the transmission importance obtained by the image's picture information importance is high.

[0081] So far, the transmission importance of each frame of image in the video image information data is obtained through the above method.

[0082] Step S003: Obtain the compression level of each frame of image according to the transmission importance.

[0083] It should be noted that when the network bandwidth fluctuates, it will have a certain impact on the transmission process of data generated by remote video teaching. In combination with actual conditions, it is necessary to sacrifice a certain amount of picture information while ensuring the quality of teaching. Under different network bandwidth conditions, the degree of sacrificed picture information is also different, and for images with different transmission importance, the acceptable degree of sacrifice is also different. Therefore, the compression degree of each frame of the image can be obtained based on the transmission importance of the image and the current network bandwidth.

[0084] Preferably, in some implementations of the embodiments of the present invention, the calculation method for obtaining the compression degree of each frame of image is:

[0085] For any frame image in the video image information data, the reciprocal of the product of the transmission importance of the frame image and the network bandwidth size is recorded as the first reciprocal; the normalized value of the first reciprocal is used as the compression degree of the frame image.

[0086] It should be noted that in the process of remote video teaching, if the image carries more key information, the higher the importance of image transmission, and the larger the network bandwidth, the smaller the image compression degree; a larger network bandwidth indicates that the current data transmission capacity is stronger, and the image compression degree can be smaller, so that the overall image can retain more original information as much as possible.

[0087] So far, the compression degree of each frame image is obtained through the above method.

[0088] Step S004: compressing the teaching video image information data to be transmitted according to the compression degree to obtain compressed teaching video image information data; and transmitting the compressed teaching video image information data.

[0089] Specifically, a threshold parameter is preset , wherein this embodiment is based on This example is described as an example, and this embodiment is not specifically limited. Depends on the specific implementation situation;

[0090] For any frame of video image information data, if the compression degree of the frame is greater than or equal to the threshold parameter , compress the frame image; if the compression degree of the frame image is less than the threshold parameter , the frame image is not compressed; compressed video image information data is obtained, and the compressed video image information data is transmitted.

[0091] The image compression method is the LZW compression algorithm, which is a prior art and will not be described in detail in this embodiment.

[0092] See also Figure 2 , which shows a characteristic relationship flow chart of a multimodal big data transmission method based on the Internet.

[0093] At this point, this embodiment is completed.

[0094] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A multimodal big data transmission method based on the Internet, characterized in that: The method comprises the following steps: Acquire teaching video image information data to be transmitted, wherein the teaching video image information data includes a plurality of frames of images; The importance of the image information of each frame is obtained based on the grayscale distribution of each frame image and the grayscale difference between the adjacent frames; the transmission importance of each frame image is obtained based on the importance of the image information of each frame image and the text changes between the adjacent frames; Obtain the compression level of each frame of image according to its transmission importance; Compressing the teaching video image information data to be transmitted according to the compression degree to obtain compressed teaching video image information data; transmitting the compressed teaching video image information data; The method of obtaining the importance of the image information of each frame of image according to the grayscale distribution of each frame of image and the grayscale difference between each frame of image and adjacent frames of image includes the following specific methods: For the video image information data Frame image, according to Grayscale distribution in the frame image, get the The image expressiveness of the frame image; According to Frame image and Grayscale difference between frame images, get the Frame image and The difference in image performance between frame images; In the Frame image and The difference in image performance between frames and the Frame image and Among the image performance differences between frame images, the largest image performance difference is taken as the The target image of the frame image shows the difference; The difference between the target image performance of the frame image and the The product of the image expression of the frame image is recorded as the first product; the normalized value of the first product is recorded as the second product. The importance of the picture information of the frame image; The specific method of obtaining the compression degree of each frame of image according to the transmission importance is as follows: For any frame image in the video image information data, the reciprocal of the product of the transmission importance of the frame image and the network bandwidth size is recorded as the first reciprocal; the normalized value of the first reciprocal is used as the compression degree of the frame image.

2. The method for transmitting multimodal big data based on the Internet according to claim 1, characterized in that: The acquisition The specific methods for the expressiveness of the frame image include: The first The total number of grayscale value types in the frame image is the same as the The product of the mean values ​​of the gradient values ​​of all pixels in the frame image is recorded as the second product; The absolute value of the difference between the mean of the grayscale values ​​of all pixels in the frame image and 128 is recorded as the first absolute value of the difference; the ratio of the second product to the first absolute value of the difference is recorded as the second absolute value of the difference. The picture expressiveness of the frame image.

3. The method for transmitting multimodal big data based on the Internet according to claim 1, characterized in that: The acquisition Frame image and The difference in image performance between frame images includes the following specific methods: The first The total number of grayscale value types in the frame image is the same as the The absolute value of the difference between the total number of gray value types in the frame image is recorded as the gray level difference value; The mean of the gradient values ​​of all pixels in the frame image is The absolute value of the difference between the mean values ​​of the gradient values ​​of all pixels in the frame image is recorded as the gradient mean difference value; The mean gray value of all pixels in the frame image is The absolute value of the difference between the mean values ​​of the gray values ​​of all pixels in the frame image is recorded as the gray mean difference value; the product of the gray level difference value, the gradient mean difference value and the gray mean difference value is taken as the first Frame image and The difference in image performance between frame images.

4. The method for transmitting multimodal big data based on the Internet according to claim 1, characterized in that: The specific method of obtaining the transmission importance of each frame of image according to the importance of the picture information of each frame of image and the text changes between adjacent frames of image includes: For the video image information data Frame image, using optical character recognition technology to obtain the first The number of characters in the frame image; The difference in the number of characters between the frame image and the adjacent frame image is used to obtain the first The text change degree of the frame image; The text change degree and image information importance of the frame image are used to obtain the The importance preference of the frame image; according to the importance preference, obtain the first The transmission importance of the frame image.

5. The method for transmitting multimodal big data based on the Internet according to claim 4, characterized in that: The acquisition The text change degree of the frame image includes the following specific methods: The first The number of characters in the frame image is the same as the The absolute value of the difference in the number of characters in the frame image is recorded as the text quantity difference value; the text quantity difference value is compared with the first The ratio of the number of characters in the frame image is used as the The text change degree of the frame image.

6. The method for transmitting multimodal big data based on the Internet according to claim 4, characterized in that: The acquisition The importance preference of the frame image includes the following specific methods: The first The text change degree of the frame image is the same as that of the The ratio of the importance of the frame information is recorded as the first priority; The text change degree of the frame image is the same as that of the The ratio of the importance of the frame information is recorded as the second priority; the maximum value between the first priority and the second priority is taken as the first priority. The importance preference of the frame image.

7. The method for transmitting multimodal big data based on the Internet according to claim 4, characterized in that: The acquisition The importance of frame image transmission, including the following specific methods: Preset a threshold parameter , if The importance of the frame image is preferably greater than the threshold parameter , will The importance of the frame information is taken as the first The importance of frame image transmission; if The importance of the frame image is preferably less than or equal to the threshold parameter , will The text change degree of the frame image is taken as the The transmission importance of the frame image.

8. The method for transmitting multimodal big data based on the Internet according to claim 1, characterized in that: The specific method of compressing the teaching video image information data to be transmitted according to the compression degree to obtain the compressed teaching video image information data includes: Preset a threshold parameter For any frame of video image information data, if the compression degree of the frame is greater than or equal to the threshold parameter , compress the frame image; if the compression degree of the frame image is less than the threshold parameter , the frame image is not compressed; and compressed video image information data is obtained.

Images