Multi-network element structure big data processing system

Abstract

The present invention relates to a multi-network element structure big data processing system, comprising: a second big data processing network element, which determines the image block that best matches the content of the current image block to be encoded of the frame to be encoded from each image block of the reference image block set as the target image block, and uses the target image block to perform the image block selected when performing the inter-frame encoding of the first color component as the image block used for the inter-frame encoding of the second color component; a third big data processing network element, which obtains the binary data stream of the inter-frame encoding of the second color component of the frame to be encoded. The multi-network element structure big data processing system of the present invention has compact logic and intelligent design. Because the dynamic block inter-frame encoding operation based on the number of edge pixels of the image block to be encoded is completed by adopting the big data analysis mechanism of the multi-network element structure, and the reference image block of the encoded color component is used to perform the inter-frame encoding of other color components, the speed and efficiency of the inter-frame encoding are improved.

Description

Technical Field

[0001] The present invention relates to the field of big data applications, and in particular to a multi-network element structure big data processing system. Background Art

[0002] Big data application means that the key to creating the value of big data lies in the application of big data. With the rapid development of big data technology, big data application has been integrated into all walks of life. The key to creating the value of big data lies in the application of big data. With the rapid development of big data technology, big data application has been integrated into all walks of life. The big data industry is rapidly developing into a new generation of information technology and service formats, that is, collecting, storing and analyzing the association of huge amounts of data with scattered sources and diverse formats, and discovering new knowledge, creating new value and improving new capabilities. The development of big data application technology in my country will involve fields such as machine learning, multidisciplinary integration, and large-scale application of open source technology.

[0003] As one of the carriers with huge data volume and huge computational load, image coding is an important field of big data application, especially the typical high-complexity inter-frame coding. Generally, in the inter-frame coding process, the image blocks closest to the content of the current image block to be coded are selected from the image blocks of the coded reference frame and used as the reference data for the current image block to be coded to perform inter-frame coding. However, when performing inter-frame coding of various color components, different color components correspond to different inter-frame coding processes respectively, and the necessary simplification mechanism is lacking, resulting in low speed and efficiency of inter-frame coding. Summary of the invention

[0004] In order to solve the technical problems in the prior art, the present invention provides a multi-network element structure big data processing system, which completes the dynamic block inter-frame coding operation based on the number of edge pixel points of the image block to be encoded by adopting the big data analysis mechanism of the multi-network element structure. The more edge pixel points of the image block to be encoded, the more encoded frames are used as reference when performing inter-frame coding, so that it is suitable for inter-frame coding processing with various content complexities, and selects the image block that best matches the content of the image block to be encoded from the multiple image blocks obtained by segmenting the encoded frames used for reference as the target image block, and uses the reference image block used when the target image block performs inter-frame coding of a certain color component as the reference image block used when the image block to be encoded performs inter-frame coding of another color component, thereby improving the speed and efficiency of inter-frame coding of image blocks.

[0005] According to the present invention, a multi-network element structure big data processing system is provided, the system comprising:

[0006] a first data processing network element, configured to select a number of multiple encoded frames for uniform segmentation processing respectively to obtain a group of image blocks corresponding to each encoded frame, and place the multiple groups of image blocks respectively corresponding to the multiple encoded frames into the same image block set to obtain and output a reference image block set, wherein the multiple encoded frames and the frame to be encoded are in the same video segment and are before the frame to be encoded;

[0007] a second large data processing network element, connected to the first large data processing network element, and configured to determine, from the image blocks in the reference image block set, an image block that best matches the content of the current image block to be encoded of the frame to be encoded as a target image block, and to use the target image block as the image block used when performing inter-frame encoding of the first color component as the image block used when the current image block to be encoded performs inter-frame encoding of the second color component;

[0008] a third data processing network element, connected to the second data processing network element, and configured to merge binary coded data obtained after completing inter-frame coding of the second color component for each image block in the frame to be coded, to obtain a binary data stream obtained after completing inter-frame coding of the second color component for the frame to be coded;

[0009] A wireless transmission interface, connected to the third data processing network element, for merging the binary data streams corresponding to the color components of the frame to be encoded to obtain a binary data stream sequence obtained after the frame to be encoded completes inter-frame encoding, and wirelessly transmitting the sequence to a remote video receiving terminal via a wireless transmission link;

[0010] a fourth data processing network element, connected to the first data processing network element, for determining, based on the number of edge pixels in the target image block, a specific value of the selected number that is proportional to the number of edge pixels in the target image block, and sending the selected number to the first data processing network element;

[0011] Among them, determining the image block that best matches the content of the current image block to be encoded of the frame to be encoded from each image block in the reference image block set as the target image block, and using the image block selected when performing inter-frame encoding of the first color component by the target image block as the image block used when performing inter-frame encoding of the second color component by the current image block to be encoded includes: for two image blocks, the more pairs of pixels with the same pixel value at the same position of the two image blocks, the more the two image blocks match;

[0012] Among them, an image block that best matches the content of the current image block to be encoded of the frame to be encoded is determined from the respective image blocks in the reference image block set as the target image block, and the image block selected when the target image block is used to perform inter-frame encoding of the first color component is used as the image block used when the current image block to be encoded performs inter-frame encoding of the second color component, and also includes: the first color component and the second color component are in the same color space.

[0013] Therefore, the present invention has the following outstanding technical effects:

[0014] Technical effect A: A big data analysis mechanism with a multi-network element structure is used to complete dynamic block inter-frame coding operations based on the number of edge pixels of the image block to be coded. The more edge pixels of the image block to be coded, the more coded frames are used as references when performing inter-frame coding, thus being suitable for inter-frame coding processing with different content complexities.

[0015] Technical effect B: An image block that best matches the content of the image block to be encoded is selected from multiple image blocks obtained by segmenting each encoded frame used as a reference image block, and a reference image block used when the target image block performs inter-frame encoding of a certain color component is used as a reference image block when the image block to be encoded performs inter-frame encoding of another color component, thereby improving the speed and efficiency of image block inter-frame encoding;

[0016] Technical effect C: After the inter-frame coding of the color components of each image block of the frame to be encoded is completed, the binary data streams corresponding to the various color components of the frame to be encoded are merged to obtain a binary data stream sequence obtained after the inter-frame coding of the frame to be encoded is completed, and the sequence is wirelessly transmitted to a remote video receiving terminal through a wireless transmission link, thereby completing the inter-frame coding process of the entire frame content of the frame to be encoded.

[0017] The multi-network element structure big data processing system of the present invention has compact logic and intelligent design. Since the dynamic block inter-frame coding operation based on the number of edge pixels of the image block to be coded is completed by adopting the big data analysis mechanism of the multi-network element structure, and the reference image block of the coded color component is used to perform the inter-frame coding of other color components, the speed and efficiency of the inter-frame coding are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The embodiments of the present invention will be described below with reference to the accompanying drawings, wherein:

[0019] Figure 1 The structure block diagram of a multi-network element structure big data processing system according to the first embodiment of the present invention is shown.

[0020] Figure 2It is a structural block diagram of a multi-network element structure big data processing system according to the second embodiment of the present invention.

[0021] Figure 3 1 is a structural block diagram of a multi-network element structure big data processing system according to Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0022] The following is a detailed description of an embodiment of the multi-network element structure big data processing system of the present invention with reference to the accompanying drawings.

[0023] Figure 1 This is a structural block diagram of a multi-network element structure big data processing system according to Embodiment 1 of the present invention, wherein the system includes:

[0024] a first data processing network element, configured to select a number of multiple encoded frames for uniform segmentation processing respectively to obtain a group of image blocks corresponding to each encoded frame, and place the multiple groups of image blocks respectively corresponding to the multiple encoded frames into the same image block set to obtain and output a reference image block set, wherein the multiple encoded frames and the frame to be encoded are in the same video segment and are before the frame to be encoded;

[0025] For example, a first large data processing network element is used to select a number of multiple encoded frames and perform uniform segmentation processing respectively to obtain a group of image blocks corresponding to each encoded frame, and place the multiple groups of image blocks corresponding to the multiple encoded frames into the same image block set to obtain and output a reference image block set, wherein the multiple encoded frames are in the same video segment as the frame to be encoded and are before the frame to be encoded. The first large data processing network element has a built-in big data service node, which is used to select a number of multiple encoded frames and perform uniform segmentation processing respectively to obtain a group of image blocks corresponding to each encoded frame;

[0026] a second large data processing network element, connected to the first large data processing network element, and configured to determine, from the image blocks in the reference image block set, an image block that best matches the content of the current image block to be encoded of the frame to be encoded as a target image block, and to use the target image block as the image block used when performing inter-frame encoding of the first color component as the image block used when the current image block to be encoded performs inter-frame encoding of the second color component;

[0027] a third data processing network element, connected to the second data processing network element, and configured to merge binary coded data obtained after completing inter-frame coding of the second color component for each image block in the frame to be coded, to obtain a binary data stream obtained after completing inter-frame coding of the second color component for the frame to be coded;

[0028] A wireless transmission interface, connected to the third data processing network element, for merging the binary data streams corresponding to the color components of the frame to be encoded to obtain a binary data stream sequence obtained after the frame to be encoded completes inter-frame encoding, and wirelessly transmitting the sequence to a remote video receiving terminal via a wireless transmission link;

[0029] a fourth data processing network element, connected to the first data processing network element, for determining, based on the number of edge pixels in the target image block, a specific value of the selected number that is proportional to the number of edge pixels in the target image block, and sending the selected number to the first data processing network element;

[0030] Among them, determining the image block that best matches the content of the current image block to be encoded of the frame to be encoded from each image block in the reference image block set as the target image block, and using the image block selected when performing inter-frame encoding of the first color component by the target image block as the image block used when performing inter-frame encoding of the second color component by the current image block to be encoded includes: for two image blocks, the more pairs of pixels with the same pixel value at the same position of the two image blocks, the more the two image blocks match;

[0031] Among them, determining the image block that best matches the content of the current image block to be encoded of the frame to be encoded from each image block in the reference image block set as the target image block, and using the image block selected when performing inter-frame encoding of the first color component by the target image block as the image block used when performing inter-frame encoding of the second color component by the current image block to be encoded further includes: the first color component and the second color component are in the same color space;

[0032] wherein, a plurality of coded frames of a selected number are respectively subjected to uniform segmentation processing to obtain a group of image blocks corresponding to each coded frame, and the plurality of groups of image blocks respectively corresponding to the plurality of coded frames are placed into the same image block set to obtain and output a reference image block set, wherein the plurality of coded frames and the frame to be coded are in the same video segment and before the frame to be coded, the group of image blocks corresponding to each coded frame includes a plurality of image blocks and the size of each image block is the same as the size of the target image block;

[0033] The first color component and the second color component being in the same color space includes: the first color component is a saturation component in an HSL color space, and the second color component is a hue component or a brightness component in an HSL color space.

[0034] Figure 2 It is a structural block diagram of a multi-network element structure big data processing system according to the second embodiment of the present invention.

[0035] Compared to Figure 1 , Figure 2 The multi-network element structure big data processing system may also include:

[0036] An instant display device is arranged near the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element and is connected to the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element respectively;

[0037] Among them, the real-time display device is arranged near the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element and is respectively connected to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element, including: the real-time display device is used to respectively display the current output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element.

[0038] Figure 3 1 is a structural block diagram of a multi-network element structure big data processing system according to Embodiment 3 of the present invention.

[0039] Compared to Figure 1 , Figure 3 The multi-network element structure big data processing system may also include:

[0040] a single-chip processor, arranged near the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element and connected to the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element respectively;

[0041] Among them, the single-chip microcomputer processor is arranged near the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element and is respectively connected to the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element, including: the single-chip microcomputer processor is used to provide data connection channels between two of the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element respectively and instruction interaction channels between two of the two.

[0042] Next, the specific structure of the multi-network element structure big data processing system of the present invention is further explained.

[0043] In the multi-network element structure big data processing system according to various embodiments of the present invention:

[0044] Using a signal enhancement component to perform image data processing on the output data of the first large data processing network element, the second large data processing network element, the third large data processing network element, and the fourth large data processing network element to obtain output processing data corresponding to the first large data processing network element, the second large data processing network element, the third large data processing network element, and the fourth large data processing network element respectively;

[0045] Among them, using a signal enhancement component to perform image data processing on the output data of the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element to obtain the output processing data corresponding to the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element respectively includes: performing adaptive recursive filtering processing on the output data of the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element to obtain the output processing data corresponding to the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element respectively;

[0046] Among them, using a signal enhancement component to perform image data processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain the output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively includes: performing salt and pepper noise elimination processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain the output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively;

[0047] Among them, using a signal enhancement component to perform image data processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain the output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively includes: performing Gaussian white noise elimination processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain the output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively;

[0048] And wherein, a signal enhancement component is used to perform image data processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain the output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively, including: performing inverse harmonic mean filtering processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain the output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively.

[0049] In addition, in the multi-network element structure big data processing system, a plurality of coded frames are selected to be evenly divided to obtain a group of image blocks corresponding to each coded frame, and the plurality of groups of image blocks corresponding to the plurality of coded frames are placed into the same image block set to obtain and output a reference image block set, wherein the plurality of coded frames are in the same video segment as the frame to be coded and are before the frame to be coded, and further comprises: the plurality of timestamps corresponding to the plurality of coded frames are continuous and are all before the timestamp of the frame to be coded;

[0050] Among them, in the multi-network element structure big data processing system, a selected number of multiple encoded frames are respectively uniformly divided and processed to obtain a group of image blocks corresponding to each encoded frame, and the multiple groups of image blocks corresponding to the multiple encoded frames are placed in the same image block set to obtain and output a reference image block set, and the multiple encoded frames are in the same video segment as the frames to be encoded and before the frames to be encoded. It also includes: selecting and adopting MATLAB simulation mode to implement a selected number of multiple encoded frames. Uniform division processing is performed to obtain a group of image blocks corresponding to each encoded frame, and the multiple groups of image blocks corresponding to the multiple encoded frames are placed in the same image block set to obtain and output a reference image block set, and the multiple encoded frames are in the same video segment as the frames to be encoded and before the frames to be encoded. Data processing process simulation and testing.

[0051] Although some embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the claims and their equivalents.

Claims

1. A multi-network element structure big data processing system, characterized in that: The system comprises: a first data processing network element, configured to evenly divide a selected number of coded frames respectively to obtain a group of image blocks corresponding to each coded frame, and place the groups of image blocks respectively corresponding to the coded frames into the same image block set to obtain and output a reference image block set, wherein the coded frames and the frame to be coded are in the same video segment and are before the frame to be coded; a second large data processing network element, connected to the first large data processing network element, and configured to determine, from the image blocks in the reference image block set, an image block that best matches the content of the current image block to be encoded of the frame to be encoded as a target image block, and to use the target image block as the image block used when performing inter-frame encoding of the first color component as the image block used when the current image block to be encoded performs inter-frame encoding of the second color component; Among them, for two image blocks, the more pairs of pixels with the same pixel values ​​at the same position of the two images, the better the match between the two images; wherein the first color component and the second color component are in the same color space; a third data processing network element, connected to the second data processing network element, and configured to merge binary coded data obtained after completing inter-frame coding of the second color component for each image block in the frame to be coded, to obtain a binary data stream obtained after completing inter-frame coding of the second color component for the frame to be coded; A wireless transmission interface, connected to the third data processing network element, for merging the binary data streams corresponding to the color components of the frame to be encoded to obtain a binary data stream sequence obtained after the frame to be encoded completes inter-frame encoding, and wirelessly transmitting the sequence to a remote video receiving terminal via a wireless transmission link; A fourth data processing network element is connected to the first data processing network element, and is used to determine the specific value of the selected number that is proportional to the number of edge pixels in the target image block based on the number of edge pixels in the target image block, and send the selected number to the first data processing network element.

2. The multi-network element structure big data processing system according to claim 1, characterized in that: A plurality of encoded frames are selected to be evenly divided respectively to obtain a group of image blocks corresponding to each encoded frame, and the plurality of groups of image blocks respectively corresponding to the plurality of encoded frames are placed into the same image block set to obtain and output a reference image block set, wherein the plurality of encoded frames are in the same video segment as the frame to be encoded and are before the frame to be encoded: the group of image blocks corresponding to each encoded frame includes a plurality of image blocks and the size of each image block is the same as the size of the target image block; The first color component and the second color component being in the same color space includes: the first color component is a saturation component in an HSL color space, and the second color component is a hue component or a brightness component in an HSL color space.

3. The multi-network element structure big data processing system according to claim 2, characterized in that: The system further comprises: An instant display device is arranged near the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element and is connected to the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element respectively; Among them, the real-time display device is arranged near the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element and is respectively connected to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element, including: the real-time display device is used to respectively display the current output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element.

4. The multi-network element structure big data processing system according to claim 2, characterized in that: The system further comprises: a single-chip processor, arranged near the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element and connected to the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element respectively; Among them, the single-chip microcomputer processor is arranged near the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element and is respectively connected to the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element, including: the single-chip microcomputer processor is used to provide data connection channels between two of the first large data processing network element, the second large data processing network element, the third large data processing network element and the fourth large data processing network element respectively and instruction interaction channels between two of the two.

5. The multi-network element structure big data processing system according to any one of claims 2 to 4, characterized in that: A signal enhancement component is used to perform image data processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively.

6. The multi-network element structure big data processing system according to claim 5, characterized in that: The signal enhancement component is used to perform image data processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain the output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively, including: performing adaptive recursive filtering processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain the output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively.

7. The multi-network element structure big data processing system according to claim 5, characterized in that: A signal enhancement component is used to perform image data processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain the output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively, including: performing salt and pepper noise elimination processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain the output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively.

8. The multi-network element structure big data processing system according to claim 5, characterized in that: The signal enhancement component is used to perform image data processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain the output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively, including: performing Gaussian white noise elimination processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain the output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively.

9. The multi-network element structure big data processing system according to claim 5, characterized in that: The signal enhancement component is used to perform image data processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain the output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively, including: performing inverse harmonic mean filtering processing on the output data of the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element to obtain the output processing data corresponding to the first big data processing network element, the second big data processing network element, the third big data processing network element and the fourth big data processing network element respectively.

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