CN117354467A - Intelligent optimized transmission system for image data - Google Patents
Intelligent optimized transmission system for image data Download PDFInfo
- Publication number
- CN117354467A CN117354467A CN202311477486.3A CN202311477486A CN117354467A CN 117354467 A CN117354467 A CN 117354467A CN 202311477486 A CN202311477486 A CN 202311477486A CN 117354467 A CN117354467 A CN 117354467A
- Authority
- CN
- China
- Prior art keywords
- image
- enhancement device
- data
- signal
- filtering
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 230000005540 biological transmission Effects 0.000 title claims abstract description 29
- 238000001914 filtration Methods 0.000 claims abstract description 86
- 238000012544 monitoring process Methods 0.000 claims abstract description 37
- 230000007246 mechanism Effects 0.000 claims abstract description 21
- 230000005855 radiation Effects 0.000 claims description 22
- 238000003062 neural network model Methods 0.000 claims description 19
- 230000006835 compression Effects 0.000 claims description 14
- 238000007906 compression Methods 0.000 claims description 14
- 238000000034 method Methods 0.000 claims description 13
- 230000005670 electromagnetic radiation Effects 0.000 claims description 10
- 238000005315 distribution function Methods 0.000 claims description 3
- 235000020061 kirsch Nutrition 0.000 claims description 3
- 238000005457 optimization Methods 0.000 abstract description 6
- 238000010586 diagram Methods 0.000 description 6
- 230000008569 process Effects 0.000 description 6
- 125000004122 cyclic group Chemical group 0.000 description 2
- 230000008901 benefit Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0499—Feedforward networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/70—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by syntax aspects related to video coding, e.g. related to compression standards
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/95—Computational photography systems, e.g. light-field imaging systems
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Computing Systems (AREA)
- Biophysics (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Biomedical Technology (AREA)
- Health & Medical Sciences (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Image Processing (AREA)
Abstract
The invention relates to an intelligent optimized transmission system for image data, which comprises the following components: the monitoring camera shooting mechanism is used for executing camera shooting operation on a monitoring scene so as to obtain each camera shooting acquisition frame at each acquisition moment; the filtering prediction device is used for intelligently analyzing and equalizing each image information of the image based on binary identification of the set filtering algorithm and resolution and completing image signal-to-noise ratio of the set filtering algorithm, and outputting the filtering algorithm corresponding to the image signal-to-noise ratio with the largest value in each image signal-to-noise ratio corresponding to each filtering algorithm as a preferable filtering algorithm. According to the invention, when the equalization processing image with the pertinently optimized monitoring picture is obtained, the signal to noise ratio of the image after the equalization processing image is set up by the intelligent analysis of the binary identification of the set filtering algorithm, each image information of the equalization processing image and the resolution, so that a plurality of reliable basic data are provided for optimization of the filtering algorithm.
Description
Technical Field
The invention relates to the field of image processing, in particular to an intelligent optimized transmission system for image data.
Background
The existing image filtering modes include: the invention of application publication number CN116843586A provides an image filtering method and system based on FPGA, and the image filtering processing is carried out based on a median filtering IP core in an FPGA development board, and the method comprises the following steps: converting the acquired RGB format image into a gray image; and filtering the gray level image through a median filter of 3*3 to obtain a processed digital image. The median filtering IP core is written through Vivado, the whole system framework is generated by utilizing the cores in the Xilinx IP core library, and the output of the bit stream is generated through Generation Bitstream command of Vivado. The method is downloaded to an FPGA development board through a serial port, and the Jupyter Notebook in a computer is utilized to call the internal logic resources of the FPGA, so that the aim of combining the median filtering algorithm and the parallel advantage of the FPGA is fulfilled, and the efficiency of image filtering operation is effectively improved. The invention of application publication number CN115482161A provides an image filtering method and system based on cyclic sampling, wherein the method comprises the following steps: sequentially performing downsampling processing and upsampling processing of at least 2 loop iterations on a target image to be processed; in the cyclic iteration process, the image after the downsampling process is subjected to the upsampling process, and the image after the upsampling process is subjected to the downsampling process. The invention can filter large-area noise by circularly downsampling and upsampling the image, and can well protect the shape and size of the image target feature and specific geometric and topological structure features.
In the prior art, when a monitoring camera shooting operation is performed on a monitoring environment, a monitoring camera shooting mechanism is generally used to obtain each camera shooting acquisition frame corresponding to each acquisition time, the acquisition times are uniformly distributed at intervals on a time axis, each camera shooting acquisition frame corresponding to each acquisition time respectively comprises a current camera shooting acquisition frame corresponding to the current acquisition time, and meanwhile, in order to improve the image quality of an acquired image, the same filtering algorithm is adopted to perform the same filtering processing on each camera shooting acquisition frame.
However, for the monitoring end of the monitoring environment, due to the frequent actions of each object in the environment, the content of each monitoring environment monitoring picture obtained in a time-sharing manner is different, the filtering processing algorithms suitable for each monitoring environment monitoring picture content are also different, and how to obtain each filtering processing algorithm suitable for each monitoring environment monitoring picture content is a technical problem to be solved when the image filtering field is applied to monitoring environment monitoring.
Disclosure of Invention
In order to solve the technical problems in the related art, the invention provides an intelligent optimized transmission system for image data, which comprises:
the monitoring camera shooting mechanism is used for executing camera shooting operation on a monitoring scene so as to obtain each camera shooting acquisition frame corresponding to each acquisition time, wherein each acquisition time is uniformly distributed at intervals on a time axis, and each camera shooting acquisition frame corresponding to each acquisition time comprises a current camera shooting acquisition frame corresponding to the current acquisition time;
the content sharpening device is connected with the monitoring camera mechanism and is used for executing sharpening processing based on a Kirsch operator on the received current camera acquisition frame corresponding to the current acquisition time so as to obtain and output a corresponding content sharpening image;
the data enhancement device is connected with the content sharpening device and is used for executing image airspace enhancement processing on the received content sharpening image so as to obtain and output a corresponding airspace enhancement image;
the equalization processing equipment is connected with the data enhancement equipment and is used for performing histogram equalization processing based on a distribution function on the received airspace enhanced image so as to obtain and output a corresponding equalization processed image;
the filter prediction device is connected with the equalization processing equipment to receive an equalization processing image, acquire various image information of the equalization processing image, wherein the various image information of the equalization processing image comprises signal-to-noise ratio, maximum noise amplitude, noise type number and contrast of the equalization processing image, input binary identification of a set filter algorithm, various image information of the equalization processing image and resolution of the equalization processing image into a feedforward neural network model after repeated learning is finished, execute the feedforward neural network model after repeated learning to obtain an image signal-to-noise ratio of the equalization processing image output by the feedforward neural network model after repeated learning, and output a filter algorithm corresponding to the image signal-to-noise ratio with the largest value in various image signal-to-noise ratios corresponding to various filter algorithms respectively as a preferable filter algorithm;
and the wireless transmission mechanism is connected with the filtering prediction device and is used for carrying out compression encoding on the balanced processing image processed by adopting the optimal filtering algorithm and then wirelessly transmitting the balanced processing image to a remote monitoring server.
When the image data intelligent optimization transmission system provided by the invention obtains the equalization processing image with pertinence optimized monitoring picture, the binary identification of the set filtering algorithm, various image information of the equalization processing image and the resolution of the equalization processing image are input into the feedforward neural network model after the repeated learning is finished, and the feedforward neural network model after the repeated learning is finished is executed to obtain the signal to noise ratio of the image after the equalization processing image output by the feedforward neural network model after the repeated learning is finished and the set filtering algorithm is finished, so that reliable multiple basic data are provided for optimization of the filtering algorithm.
Drawings
Embodiments of the present invention will be described below with reference to the accompanying drawings.
Fig. 1 is a schematic diagram of an internal structure of an intelligent optimized transmission system for image data according to embodiment a of the present invention.
Fig. 2 is a schematic diagram of an internal structure of an intelligent optimized transmission system for image data according to embodiment B of the present invention.
Fig. 3 is a schematic diagram of an internal structure of an intelligent optimized transmission system for image data according to embodiment C of the present invention.
Detailed Description
Embodiments of the intelligent optimized transmission system for image data according to the present invention will be described in detail with reference to the accompanying drawings.
Embodiment A
Fig. 1 is a schematic diagram of an internal structure of an intelligent optimized transmission system for image data according to an embodiment a of the present invention, where the system includes:
the monitoring camera shooting mechanism is used for executing camera shooting operation on a monitoring scene so as to obtain each camera shooting acquisition frame corresponding to each acquisition time, wherein each acquisition time is uniformly distributed at intervals on a time axis, and each camera shooting acquisition frame corresponding to each acquisition time comprises a current camera shooting acquisition frame corresponding to the current acquisition time;
the content sharpening device is connected with the monitoring camera mechanism and is used for executing sharpening processing based on a Kirsch operator on the received current camera acquisition frame corresponding to the current acquisition time so as to obtain and output a corresponding content sharpening image;
the data enhancement device is connected with the content sharpening device and is used for executing image airspace enhancement processing on the received content sharpening image so as to obtain and output a corresponding airspace enhancement image;
the equalization processing equipment is connected with the data enhancement equipment and is used for performing histogram equalization processing based on a distribution function on the received airspace enhanced image so as to obtain and output a corresponding equalization processed image;
the filter prediction device is connected with the equalization processing equipment to receive an equalization processing image, acquire various image information of the equalization processing image, wherein the various image information of the equalization processing image comprises signal-to-noise ratio, maximum noise amplitude, noise type number and contrast of the equalization processing image, input binary identification of a set filter algorithm, various image information of the equalization processing image and resolution of the equalization processing image into a feedforward neural network model after repeated learning is finished, execute the feedforward neural network model after repeated learning to obtain an image signal-to-noise ratio of the equalization processing image output by the feedforward neural network model after repeated learning, and output a filter algorithm corresponding to the image signal-to-noise ratio with the largest value in various image signal-to-noise ratios corresponding to various filter algorithms respectively as a preferable filter algorithm;
specifically, a MATLAB tool box can be selected to complete inputting binary identification of a set filtering algorithm, various image information of the balanced processing image and the resolution of the balanced processing image into a feedforward neural network model after multiple times of learning are completed, the feedforward neural network model after multiple times of learning is executed to obtain an image signal-to-noise ratio of the balanced processing image after the balanced processing image is output and the image signal-to-noise ratio of the balanced processing image after the set filtering algorithm is completed, and a filtering algorithm corresponding to the image signal-to-noise ratio with the largest value in various image signal-to-noise ratios respectively corresponding to various filtering algorithms is used as simulation operation of a data processing process of the optimized filtering algorithm output;
the wireless transmission mechanism is connected with the filtering prediction device and is used for carrying out compression encoding on the balanced processing image processed by adopting the optimal filtering algorithm and then wirelessly transmitting the balanced processing image to a remote monitoring server;
the method for wirelessly transmitting the equalization processing image processed by the optimized filtering algorithm to a remote monitoring server after compression encoding comprises the following steps: and performing HEVC standard compression coding processing on the equalization processed image processed by the optimized filtering algorithm to obtain a compression coding code stream, and wirelessly transmitting the compression coding code stream to a remote monitoring server.
Embodiment B
Fig. 2 is a schematic diagram of an internal structure of an intelligent optimized transmission system for image data according to embodiment B of the present invention.
Compared to embodiment a, the intelligent optimized transmission system for image data shown in embodiment B may further include the following components:
the voltage supply interface is respectively connected with the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device and is used for respectively providing respectively required working voltages for the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device;
the voltage supply interface is respectively connected with the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device, and is used for respectively providing the required working voltages for the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device, and comprises the following steps: the operating voltages required by each of the content sharpening device, the data enhancement device, the signal enhancement device, and the filtering prediction device include 3.3 volts and 5 volts;
the voltage supply interface is respectively connected with the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device, and is used for respectively providing the required working voltages for the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device, and further comprises: the content sharpening device, the data enhancement device, the signal enhancement device, and the filtering prediction device are configured around the voltage supply interface and isolated from the voltage supply interface with different electromagnetic shielding mechanisms, respectively;
wherein the content sharpening device, the data enhancement device, the signal enhancement device, and the filtering prediction device are configured around the voltage supply interface and isolated from the voltage supply interface with different electromagnetic shielding mechanisms, respectively, comprises: the distances from the different electromagnetic shielding mechanisms adopted by the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device to the voltage supply interface are equal;
wherein the content sharpening device, the data enhancement device, the signal enhancement device, and the filtering prediction device are configured around the voltage supply interface and isolated from the voltage supply interface with different electromagnetic shielding mechanisms, respectively, further comprises: the internal structures of different electromagnetic shielding mechanisms adopted by the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device are the same.
Embodiment C
Fig. 3 is a schematic diagram of an internal structure of an intelligent optimized transmission system for image data according to embodiment C of the present invention.
Compared to embodiment a, the intelligent optimized transmission system for image data shown in embodiment C may further include the following components:
a radiation sensing device connected with the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device respectively, and used for providing numerical sensing operation of respective real-time electromagnetic radiation amounts for the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device;
wherein the radiation sensing device is respectively connected with the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device, and is used for providing respective numerical sensing operations of real-time electromagnetic radiation amounts for the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device, and the numerical sensing operations comprise: the radiation sensing device comprises a plurality of radiation sensing units for respectively providing numerical sensing operations of respective real-time electromagnetic radiation amounts for the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device;
wherein the radiation sensing device comprises a plurality of radiation sensing units for providing respective numerical sensing operations of real-time electromagnetic radiation amounts for the content sharpening device, the data enhancement device, the signal enhancement device, and the filtering prediction device, respectively, comprising: the internal structures of the plurality of radiation sensing units are the same;
and wherein the radiation sensing device comprises a plurality of radiation sensing units for providing respective numerical sensing operations of real-time electromagnetic radiation amounts to the content sharpening device, the data enhancement device, the signal enhancement device, and the filtering prediction device, respectively, comprising: the radiation sensing units are respectively internally provided with respective radiation alarm components.
In addition, in the image data intelligent optimization transmission system, performing HEVC standard compression coding processing on the equalization processed image processed by the optimized filtering algorithm to obtain a compression coded code stream, and wirelessly transmitting the compression coded code stream to a remote monitoring server comprises: the monitoring server is a big data server, a cloud computing server or a block chain server.
The technical innovation of the invention is as follows:
first: receiving an equalization processing image, and acquiring various image information of the equalization processing image, wherein the various image information of the equalization processing image comprises signal-to-noise ratio, maximum noise amplitude, noise type number and contrast of the equalization processing image, so that reliable multiple basic data are provided for optimization of a filtering algorithm;
second,: inputting binary identification of a set filtering algorithm, various image information of an equalization processing image and the resolution of the equalization processing image into a feedforward neural network model after multiple times of learning are completed, and executing the feedforward neural network model after multiple times of learning to obtain the signal-to-noise ratio of the image after the equalization processing image is output and the set filtering algorithm is completed;
third,: and outputting a filter algorithm corresponding to the image signal-to-noise ratio with the largest value in the image signal-to-noise ratios respectively corresponding to the various filter algorithms as a preferable filter algorithm.
By adopting the intelligent optimized transmission system for the image data, aiming at the technical problem that different filtering algorithms are needed for time-sharing monitoring pictures in the prior art, when the balanced processing image with pertinently optimized monitoring pictures is obtained, the binary identification of the set filtering algorithm, various image information of the balanced processing image and the resolution of the balanced processing image are input into a feedforward neural network model after multiple times of learning are completed, and the feedforward neural network model after multiple times of learning is executed to obtain the balanced processing image output by the feedforward neural network model after multiple times of learning so as to complete the image signal to noise ratio after the set filtering algorithm, thereby providing reliable multiple basic data for optimization of the filtering algorithm.
While the preferred embodiment of the invention has been illustrated and described, it will be appreciated that various changes can be made therein without departing from the spirit and scope of the invention.
Claims (9)
1. An intelligent optimized transmission system for image data, the system comprising:
the monitoring camera shooting mechanism is used for executing camera shooting operation on a monitoring scene so as to obtain each camera shooting acquisition frame corresponding to each acquisition time, wherein each acquisition time is uniformly distributed at intervals on a time axis, and each camera shooting acquisition frame corresponding to each acquisition time comprises a current camera shooting acquisition frame corresponding to the current acquisition time;
the content sharpening device is connected with the monitoring camera mechanism and is used for executing sharpening processing based on a Kirsch operator on the received current camera acquisition frame corresponding to the current acquisition time so as to obtain and output a corresponding content sharpening image;
the data enhancement device is connected with the content sharpening device and is used for executing image airspace enhancement processing on the received content sharpening image so as to obtain and output a corresponding airspace enhancement image;
the equalization processing equipment is connected with the data enhancement equipment and is used for performing histogram equalization processing based on a distribution function on the received airspace enhanced image so as to obtain and output a corresponding equalization processed image;
the filter prediction device is connected with the equalization processing equipment to receive an equalization processing image, acquire various image information of the equalization processing image, wherein the various image information of the equalization processing image comprises signal-to-noise ratio, maximum noise amplitude, noise type number and contrast of the equalization processing image, input binary identification of a set filter algorithm, various image information of the equalization processing image and resolution of the equalization processing image into a feedforward neural network model after repeated learning is finished, execute the feedforward neural network model after repeated learning to obtain an image signal-to-noise ratio of the equalization processing image output by the feedforward neural network model after repeated learning, and output a filter algorithm corresponding to the image signal-to-noise ratio with the largest value in various image signal-to-noise ratios corresponding to various filter algorithms respectively as a preferable filter algorithm;
and the wireless transmission mechanism is connected with the filtering prediction device and is used for carrying out compression encoding on the balanced processing image processed by adopting the optimal filtering algorithm and then wirelessly transmitting the balanced processing image to a remote monitoring server.
2. The intelligent optimized transmission system for image data as claimed in claim 1, wherein:
the method for wirelessly transmitting the equalization processed image processed by the optimized filtering algorithm to a remote monitoring server after compression encoding comprises the following steps: and performing HEVC standard compression coding processing on the equalization processed image processed by the optimized filtering algorithm to obtain a compression coding code stream, and wirelessly transmitting the compression coding code stream to a remote monitoring server.
3. The intelligent optimized transmission system for image data as claimed in claim 2, wherein said system further comprises:
the voltage supply interface is respectively connected with the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device and is used for respectively providing respectively required working voltages for the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device;
the voltage supply interface is respectively connected with the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device, and is used for respectively providing the required working voltages for the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device, and comprises the following steps: the operating voltages required by each of the content sharpening device, the data enhancement device, the signal enhancement device, and the filtering prediction device include 3.3 volts and 5 volts.
4. The intelligent optimized transmission system for image data as claimed in claim 3, wherein:
the voltage supply interface is respectively connected with the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device, and is used for respectively providing respectively required working voltages for the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device, and further comprises: the content sharpening device, the data enhancement device, the signal enhancement device, and the filtering prediction device are configured around the voltage supply interface and isolated from the voltage supply interface with different electromagnetic shielding mechanisms, respectively.
5. The intelligent optimized transmission system for image data as claimed in claim 4, wherein:
the content sharpening device, the data enhancement device, the signal enhancement device, and the filtering prediction device being configured around the voltage supply interface and separately isolated from the voltage supply interface using different electromagnetic shielding mechanisms includes: the distances from the different electromagnetic shielding mechanisms adopted by the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device to the voltage supply interface are equal.
6. The intelligent optimized transmission system for image data as claimed in claim 4, wherein:
the content sharpening device, the data enhancement device, the signal enhancement device, and the filtering prediction device being configured around the voltage supply interface and isolated from the voltage supply interface with different electromagnetic shielding mechanisms, respectively, further comprising: the internal structures of different electromagnetic shielding mechanisms adopted by the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device are the same.
7. The intelligent optimized transmission system for image data as claimed in claim 2, wherein said system further comprises:
a radiation sensing device connected with the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device respectively, and used for providing numerical sensing operation of respective real-time electromagnetic radiation amounts for the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device;
wherein the radiation sensing device is respectively connected with the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device, and is used for providing respective numerical sensing operations of real-time electromagnetic radiation amounts for the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device, and the numerical sensing operations comprise: the radiation sensing device comprises a plurality of radiation sensing units for providing respective numerical sensing operations of the amount of real-time electromagnetic radiation for the content sharpening device, the data enhancement device, the signal enhancement device and the filtering prediction device, respectively.
8. The intelligent optimized transmission system for image data as claimed in claim 7, wherein:
the radiation sensing device comprises a plurality of radiation sensing units for providing respective numerical sensing operations of real-time electromagnetic radiation amounts for the content sharpening device, the data enhancement device, the signal enhancement device, and the filtering prediction device, respectively, comprising: the internal structures of the plurality of radiation sensing units are identical.
9. The intelligent optimized transmission system for image data as claimed in claim 7, wherein:
the radiation sensing device comprises a plurality of radiation sensing units for providing respective numerical sensing operations of real-time electromagnetic radiation amounts for the content sharpening device, the data enhancement device, the signal enhancement device, and the filtering prediction device, respectively, comprising: the radiation sensing units are respectively internally provided with respective radiation alarm components.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311477486.3A CN117354467A (en) | 2023-11-08 | 2023-11-08 | Intelligent optimized transmission system for image data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311477486.3A CN117354467A (en) | 2023-11-08 | 2023-11-08 | Intelligent optimized transmission system for image data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117354467A true CN117354467A (en) | 2024-01-05 |
Family
ID=89371035
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311477486.3A Withdrawn CN117354467A (en) | 2023-11-08 | 2023-11-08 | Intelligent optimized transmission system for image data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117354467A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117734510A (en) * | 2024-02-21 | 2024-03-22 | 南京优芮智能科技有限公司 | Intelligent emergency power-off control system for charging pile |
-
2023
- 2023-11-08 CN CN202311477486.3A patent/CN117354467A/en not_active Withdrawn
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117734510A (en) * | 2024-02-21 | 2024-03-22 | 南京优芮智能科技有限公司 | Intelligent emergency power-off control system for charging pile |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP2020527001A (en) | Point group encoder | |
| KR20230074137A (en) | Instance adaptive image and video compression using machine learning systems | |
| Nguyen et al. | Multiscale deep context modeling for lossless point cloud geometry compression | |
| CN110210378B (en) | Embedded video image analysis method and device based on edge calculation | |
| CN117354467A (en) | Intelligent optimized transmission system for image data | |
| CN112565777B (en) | Deep learning model-based video data transmission method, system, medium and device | |
| CN108028945A (en) | The apparatus and method of conversion are performed by using singleton coefficient update | |
| CN112733824A (en) | Transformer equipment defect diagnosis method and system based on video image intelligent front end | |
| CN116189172B (en) | 3D target detection method, device, storage medium and chip | |
| CN116205962A (en) | Monocular depth estimation method and system based on complete context information | |
| CN112399177B (en) | Video coding method, device, computer equipment and storage medium | |
| CN116342884A (en) | Image segmentation and model training method and server | |
| Ranjbar Alvar et al. | Joint image compression and denoising via latent-space scalability | |
| Mei et al. | Learn a compression for objection detection-vae with a bridge | |
| CN113010469A (en) | Image feature extraction method, device and computer-readable storage medium | |
| CN116250008A (en) | Encoding and decoding methods, encoder, decoder and encoding and decoding system of point cloud | |
| Wang et al. | Dynamic kernel-based adaptive spatial aggregation for learned image compression | |
| CN115086660B (en) | Decoding and encoding method based on point cloud attribute prediction, decoder and encoder | |
| CN116644783A (en) | Model training method, object processing method and device, electronic equipment and medium | |
| WO2022067776A1 (en) | Point cloud decoding and encoding method, and decoder, encoder and encoding and decoding system | |
| WO2022226850A1 (en) | Point cloud quality enhancement method, encoding and decoding methods, apparatuses, and storage medium | |
| CN110958449B (en) | Three-dimensional video subjective perception quality prediction method | |
| CN113902992A (en) | Video quality evaluation method and device and storage medium | |
| CN117239930B (en) | Intelligent inspection system and method for power distribution network | |
| CN105488510B (en) | The construction method and its system of the color histogram of static images |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20240105 |
|
| WW01 | Invention patent application withdrawn after publication |