CN111476730B - Image restoration processing method and device - Google Patents
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Abstract
The embodiment of the application provides a processing method and a device for image restoration, wherein the method comprises the following steps: acquiring original image information to be transmitted in a communication way; generating first image signal data according to the original image information; determining a data restoration model which corresponds to the communication equipment and is obtained through pre-training; obtaining repair data corresponding to the first image signal data through a data repair model; compensating the first image signal data by the repair data to obtain second image signal data; and obtaining repaired image information according to the second image signal data. By adopting the method in the embodiment, the difference of specific types of communication equipment in communication transmission is not needed to be considered, and the data loss caused by the communication equipment can be repaired only by acquiring a trained data repair model corresponding to the communication equipment; the problem of image distortion caused by unstable noise and data compression in communication transmission can be solved; and further, the communication transmission quality of the image can be effectively improved.
Description
Technical Field
The present disclosure relates to the field of image processing technologies, and in particular, to a method and an apparatus for processing image restoration.
Background
Image restoration refers to a technique of recovering a lost portion of an image and reconstructing the image based on background information. In image processing techniques, complex application algorithms are used to replace missing or corrupted portions of image data.
The existing image restoration technology is mainly divided into: the restoration is carried out based on the methods of structure information diffusion and texture block replication, and the main answer is the restoration of the missing part of the image. Such methods do not produce good repair results when the lost portion is large. In addition, with the development of technology, high-resolution and high-quality image acquisition becomes a necessary trend; however, in the process of uploading information of a large amount of image data, the image data is excessively large, so that the image data needs to be uploaded through image compression. In this process, high-quality image data is more likely to be lost by noise or interference signals generated in the communication device due to compression or the like.
Aiming at a plurality of technical problems existing in the related art, no effective solution is provided at present.
Disclosure of Invention
In order to solve the above technical problems or at least partially solve the above technical problems, the present application provides a method and an apparatus for processing image restoration.
In a first aspect, the present application provides a method for processing image restoration, including:
acquiring original image information to be transmitted in a communication way;
generating first image signal data according to the original image information, wherein the first image signal data is data capable of being transmitted by communication equipment;
determining a data restoration model which corresponds to the communication equipment and is obtained through pre-training;
obtaining repair data corresponding to the first image signal data through the data repair model, wherein the repair data is used for compensating data lost when the first image signal data is transmitted in the communication equipment;
compensating the first image signal data through the repair data so that the communication equipment outputs second image signal data according to the first image signal data and the repair data;
and obtaining repaired image information according to the second image signal data.
Optionally, in the foregoing processing method, the obtaining, by the data repair model, repair data corresponding to the first image signal data includes:
determining distortion data of the first image signal data after transmission in the communication device;
and inputting the distorted data into the data restoration model to obtain the restoration data for compensating the distorted data.
Optionally, in the foregoing processing method, the method for establishing a data repair model includes:
acquiring sample distortion data collected in advance, wherein the sample distortion data is obtained according to sample image information and distortion image information of the sample image information after transmission in communication equipment;
inputting the sample distortion data into a preset neural network model for training to obtain a trained neural network model;
and verifying the trained neural network model through the sample image information and the distorted image information, and obtaining the data restoration model after the verification result meets the preset requirement.
Optionally, the acquiring pre-collected sample distortion data according to the foregoing processing method includes:
determining two-dimensional digital matrix data of the sample image information;
converting the two-dimensional digital matrix data into one-dimensional sequence data;
performing Fourier transform on the one-dimensional sequence data to obtain corresponding spectrum information;
obtaining distorted sample image information obtained after the sample image information is transmitted through the communication equipment;
obtaining corresponding distorted spectrum information according to the distorted sample image information;
and obtaining the sample distortion data according to the spectrum information and the spectrum information after distortion.
Optionally, the acquiring pre-collected sample distortion data according to the foregoing processing method includes:
converting the sample image information into first color distribution energy spectrum information;
obtaining distorted sample image information obtained after the sample image information is transmitted through the communication equipment;
converting the distorted sample image information into second color distribution energy spectrum information;
and obtaining the sample distortion data according to the first color distribution energy spectrum information and the second color distribution energy spectrum information.
Optionally, in the foregoing processing method, the determining a pre-trained data repair model corresponding to the communication device includes:
determining preset corresponding relations between different preset communication devices and a preset data restoration model;
and according to the preset corresponding relation, matching to obtain the data restoration model corresponding to the communication equipment.
Optionally, the processing method, in which the compensating the first image signal data by the repair data includes:
determining minimum unit signal data which needs to be compensated in the first image signal data;
determining minimum unit repair signal data corresponding to each minimum unit signal data in the repair data, and obtaining a data corresponding relation;
and loading each minimum unit repair signal data into the corresponding minimum unit signal data according to the data corresponding relation.
In a second aspect, the present application provides a processing apparatus for image restoration, including:
the acquisition module is used for acquiring the original image information needing communication transmission;
the first conversion module is used for generating first image signal data according to the original image information, wherein the first image signal data is data which can be transmitted through communication equipment;
the determining module is used for determining a data restoration model which is obtained by training and corresponds to the communication equipment;
the data restoration module is used for obtaining restoration data corresponding to the first image signal data through the data restoration model, and the restoration data is used for compensating data lost when the first image signal data is transmitted in the communication equipment;
a compensation module for compensating the first image signal data by the repair data so that the communication device outputs second image signal data according to the first image signal data and the repair data;
and the second conversion module is used for obtaining the repaired image information according to the second image signal data.
In a third aspect, the present application provides an electronic device, including: the device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
the memory is used for storing a computer program;
the processor is configured to implement a processing method according to any one of the preceding claims when executing the computer program.
In a fourth aspect, the present application provides a non-transitory computer readable storage medium storing computer instructions that cause a computer to perform the processing method of any preceding claim.
The embodiment of the application provides a processing method and device for image restoration, wherein the method comprises the following steps: acquiring original image information to be transmitted in a communication way; generating first image signal data according to the original image information, wherein the first image signal data is data capable of being transmitted by communication equipment; determining a data restoration model which corresponds to the communication equipment and is obtained through pre-training; obtaining repair data corresponding to the first image signal data through the data repair model, wherein the repair data is used for compensating data lost when the first image signal data is transmitted in the communication equipment; compensating the first image signal data through the repair data so that the communication equipment outputs second image signal data according to the first image signal data and the repair data; and obtaining repaired image information according to the second image signal data. By adopting the method in the embodiment, the difference of specific types of communication equipment in communication transmission is not needed to be considered, and the data loss caused by the communication equipment can be repaired only by acquiring a trained data repair model corresponding to the communication equipment; the problem of image distortion caused by unstable noise and data compression in communication transmission can be solved; and further, the communication transmission quality of various images can be effectively improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.
Fig. 1 is a flowchart of a processing method of image restoration according to an embodiment of the present application;
FIG. 2 is a flowchart of a method for processing image restoration according to another embodiment of the present disclosure;
FIG. 3 is a flowchart of a method for processing image restoration according to another embodiment of the present disclosure;
FIG. 4 is a block diagram of an image restoration processing device according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present application based on the embodiments herein.
Fig. 1 is a first aspect provided in an embodiment of the present application, where the present application provides a processing method for image restoration, including steps S1 to S6 as follows:
s1, acquiring original image information to be transmitted in a communication mode.
Specifically, the original image information is: image information before communication transmission is performed; and the data format of the original image information may be bmp, jpg, png, tif, gif, pcx, tga, exif, fpx, svg, psd, cdr, pcd, dxf, ufo, eps, ai, raw, wmf, webp or the like.
The communication may be carried out by bluetooth, wiFi, mobile communication network, etc.
And S2, generating first image signal data according to the original image information, wherein the first image signal data are data which can be transmitted through the communication equipment.
Specifically, when communication transmission is performed, original image information cannot be transmitted according to the original format, so that the original image information needs to be converted into a data format which can be transmitted by communication equipment; therefore, the first image signal data is the data corresponding to the data format that can be transmitted by the communication device. And the communication device may include a wired communication device and a wireless communication device; as long as data transmission is enabled.
And S3, determining a data restoration model which corresponds to the communication equipment and is obtained through pre-training.
Specifically, when different communication devices transmit image signal data, the first image signal data is distorted due to signal interference or transmission stability; the data repair model is used for compensating and repairing distorted data, so that the data output by the communication equipment and the input data are kept as true as possible.
In addition, since the interference susceptibility and the transmission stability of different communication devices are different, the communication devices need to have corresponding data repair models.
Generally, since the data repair model is obtained based on a deep neural network model, training is required, and after a preset accuracy is achieved, the expected use effect can be achieved.
And S4, obtaining repair data corresponding to the first image signal data through a data repair model, wherein the repair data are used for compensating the data lost when the first image signal data are transmitted in the communication equipment.
Specifically, when data is transmitted through the communication device, the nature is that the electronic signal is transmitted, so that the electronic signal is lost during transmission, and the electronic signal is a specific expression form of data transmission, so that the electronic signal can be repaired by repairing data, and the lost data can be compensated: when the electronic signal is lower than the normal value, lifting the signal to enable the signal to be lifted to the normal value; when the electronic signal is higher than the normal value, the signal is reduced to the normal value.
And S5, compensating the first image signal data through the repair data so that the communication equipment outputs second image signal data according to the first image signal data and the repair data.
Specifically, after the first image signal data is compensated by the repair data, the data lost in the communication device by the first image signal data can be compensated, so that the second image signal data output by the communication device can be obtained by repairing the first image data by the repair data.
Alternatively, the compensation of the first image signal data by the repair data may be performed before or after the loss occurs.
And S6, obtaining repaired image information according to the second image signal data.
In particular, the data type of the second image signal data is generally identical to that of the first image signal data, so that the frame is not in a normal image format and needs to be converted to obtain the corresponding repaired image information.
By adopting the method in the embodiment, the difference of specific types of communication equipment in communication transmission is not needed to be considered, and the data loss caused by the communication equipment can be repaired only by acquiring a trained data repair model corresponding to the communication equipment; the problem of image distortion caused by unstable noise and data compression in communication transmission can be solved; and further, the communication transmission quality of various images can be effectively improved.
In some embodiments, as the foregoing processing method, step S4 obtains repair data corresponding to the first image signal data through the data repair model, including steps S41 and S42 as follows:
step S41, determining distortion data of the first image signal data after transmission in the communication device.
Specifically, since the present application repairs a transmission image of a fixed communication device, the positions where distortion occurs when the communication device transmits signal data are relatively fixed, for example: when a communication device is used to transmit a spectrum information I (including, in turn, signal data A, B, C, D, E), distortion is D; the communication device distorts the signal data D 'when transmitting another spectral information II (comprising in sequence: signal data a', B ', C', D ', E'); the distortion data may be original data in which distortion occurs in the first image signal data; the first image signal data may be distorted data after transmission; but also the original data and the distorted data which are distorted.
S42, inputting the distorted data into a data restoration model to obtain restoration data for compensating the distorted data.
Specifically, the data repair model is obtained by training sample distortion data before training, so that corresponding repair data can be obtained through the input distortion data.
As shown in fig. 2, in some embodiments, the method for creating a data repair model, such as the foregoing processing method, includes steps A1 to A3 as follows:
step A1. Sample distortion data collected in advance is acquired, wherein the sample distortion data is obtained from sample image information and distorted image information after the sample image information is transmitted in the communication device.
Specifically, the sample distortion data is obtained by data comparison, and is obtained by comparing distorted image information after transmission of sample image information in the communication device with sample image information before transmission. Typically, the sample distortion data will include multiple sets.
And step A2, inputting the sample distortion data into a preset neural network model for training, and obtaining a trained neural network model.
And step A3, verifying the trained neural network model through the sample image information and the distorted image information, and obtaining a data restoration model after the verification result meets the preset requirement.
Specifically, the neural network model herein may be a DNN model (deep neural network model), and in general, the DNN model may include an input layer, after which a plurality of network layers may be connected in series, and finally an output layer is connected; after the sample distortion data is input into the neural network model, the data compensation repair data is obtained through the output layer output; meeting the preset requirements may be: when the neural network model after training is subjected to the repair data obtained by verifying the data, and the distortion image information is consistent with the sample image information or the distortion rate is within a preset range after being repaired by the repair data, the neural network model after training can be judged to meet the performance requirements and can be used.
In some embodiments, as in the previous processing method, step A1 acquires pre-collected sample distortion data, including steps a111 to a116 as follows:
a111, determining two-dimensional digital matrix data of sample image information;
a112, converting the two-dimensional digital matrix data into one-dimensional sequence data;
a113, performing Fourier transform on the one-dimensional sequence data to obtain corresponding frequency spectrum information;
a114, obtaining distorted sample image information obtained after the sample image information is transmitted by the communication equipment;
a115, obtaining corresponding distorted frequency spectrum information according to the distorted sample image information;
step A116, sample distortion data is obtained according to the spectrum information and the spectrum information after distortion.
Specifically, one of the alternative implementation methods may be:
1) N original images with high resolution and high quality are obtained, and as the digital image data can be represented by a matrix, the digital image can be analyzed and processed by adopting a matrix theory and a matrix algorithm. Since digital images can be represented in the form of a matrix, in a computer digital image processing program, two-dimensional matrix data is generally used to store image data. Respectively converting the two-dimensional matrix data of each original image to obtain corresponding data S i Then by each S i Concatenated into one-dimensional sequence data S:
S＝S 0 ∪S 1 ∪S 2 ∪....∪S n ；
2) Taking the one-dimensional sequence data S of each image as signal data, performing Fourier transformation by using a signal processing mode, and according to each S i Obtaining spectral data M i Based on the spectrum data M i The spectrum information M is obtained by sequencing, and is used for carrying out spectrum information analysis:
M＝M 0 ∪M 1 ∪M 2 ∪....∪M n ；
3) After each image data is transmitted by the fixed communication equipment, the image data is processed by a signal processing mode again to carry out Fourier transformation, and the distorted frequency spectrum data is recorded as N i Then according to each frequency spectrum data N i The distorted spectrum information N is obtained by sequential arrangement and is used for carrying out spectrum information analysis:
N＝N 0 ∪N 1 ∪N 2 ∪....∪N n ；
4) And obtaining sample distortion data according to the spectrum information M and the distorted spectrum information N of each piece of image data, and taking the sample distortion data as input=M-N of the neural network model to be trained.
In some embodiments, as the aforementioned processing method, step A1 acquires pre-collected sample distortion data, including steps a121 to a123 as follows:
a121, converting the sample image information into first color distribution energy spectrum information;
a122, obtaining distorted sample image information obtained after the sample image information is transmitted by the communication equipment;
a123 converting the distorted sample image information into second color distribution energy spectrum information;
step A124, obtaining sample distortion data according to the first color distribution energy spectrum information and the second color distribution energy spectrum information.
Specifically, the conversion of the sample image information into the first color distribution energy spectrum information may be: converting the sample image information into energy spectrum information with different color distribution, for example, when the image is a black-and-white image, the first color distribution energy spectrum information can be obtained according to the change of gray values corresponding to the pixels; in the case of a color image, the distributed energy spectrum information of three colors of RGB can be used as the distributed energy spectrum information of the first color, and optionally, the energy spectrums of the colors can be linearly connected to obtain one-dimensional energy spectrum information.
And after the second color distribution energy spectrum information is obtained, sample distortion data can be obtained according to the first color distribution energy spectrum information and the second color distribution energy spectrum information.
In some embodiments, as the foregoing processing method, step S3 determines a pre-trained data repair model corresponding to the communication device, including steps S31 and S32 as follows:
s31, determining preset corresponding relations between different preset communication devices and a preset data restoration model.
And S32, matching to obtain a data restoration model corresponding to the communication equipment according to a preset corresponding relation.
Specifically, the degree and frequency of loss of different communication devices are different, so that it is difficult to compensate the loss of all communication devices through one data restoration model; in the embodiment, a preset data restoration model corresponding to different preset communication devices is pre-established, and the corresponding relation between the preset data restoration model and the different preset communication devices is determined; the preset corresponding relation can be realized in a data table, and the data table can record the links of the serial numbers of all preset communication devices and all preset data restoration models, so that the data restoration models corresponding to the communication devices can be quickly obtained when the specific data restoration models are required to be used.
As shown in fig. 3, in some embodiments, as the foregoing processing method, step S5 compensates the first image signal data by the repair data, including steps S51 to S53 as follows:
step S51, determining minimum unit signal data which needs to be compensated in the first image signal data.
Specifically, the minimum unit signal data is signal data to be compensated, and the minimum unit signal data is data of the minimum unit of the first image signal data, that is, the minimum unit signal data cannot be decomposed again.
S52, determining the minimum unit repair signal data corresponding to each minimum unit signal data in the repair data, and obtaining a data corresponding relation.
Specifically, the minimum unit repair signal data is data of the minimum unit constituting the repair data.
The repair data is data for compensating the first image signal data which is not lost or the first image signal data after the loss, but the first image signal data which is not lost or the first image signal data after the loss does not need to be repaired for each minimum unit of signal data, so if the data correspondence relationship between each minimum unit of signal data and the minimum unit repair signal data is not determined, there is a case that the repair cannot be performed, even the loss is increased because the non-corresponding minimum unit of signal data is repaired.
The data corresponding relation obtaining method can be as follows:
when generating the repair data, the characteristic information of each minimum unit signal data is determined first (the characteristic information can be obtained from the minimum unit signal data or obtained by marking the minimum unit signal data), and when generating the minimum unit repair signal data, the characteristic information is also used for marking each minimum unit repair signal data, so that the data corresponding relation can be established.
And S53, loading each minimum unit repair signal data into the corresponding minimum unit signal data according to the data corresponding relation.
Specifically, since each minimum unit signal data is generally transmitted in the form of a wave, the minimum unit repair signal data is also data of a corresponding form, and can be realized by superposition when loaded.
As shown in fig. 4, in a second aspect, the present application provides an image restoration processing apparatus, including:
the acquisition module 1 is used for acquiring original image information needing communication transmission;
a first conversion module 2 for generating first image signal data based on the original image information, the first image signal data being data that can be transmitted by the communication device;
a determining module 3, configured to determine a data repair model obtained by training in advance and corresponding to the communication device;
a repair data generating module 4, configured to obtain repair data corresponding to the first image signal data through a data repair model, where the repair data is used to compensate for data lost when the first image signal data is transmitted in the communication device;
a compensation module 5 for compensating the first image signal data by the repair data so that the communication device outputs the second image signal data according to the first image signal data and the repair data;
and the second conversion module 6 is used for obtaining the repaired image information according to the second image signal data.
In particular, the specific process of implementing the functions of each module in the apparatus of the embodiment of the present invention may be referred to the related description in the method embodiment, which is not repeated herein.
According to another embodiment of the present application, there is also provided an electronic apparatus including: as shown in fig. 5, the electronic device may include: the device comprises a processor 1501, a communication interface 1502, a memory 1503 and a communication bus 1504, wherein the processor 1501, the communication interface 1502 and the memory 1503 are in communication with each other through the communication bus 1504.
A memory 1503 for storing a computer program;
the processor 1501 is configured to execute the program stored in the memory 1503, thereby implementing the steps of the method embodiment described above.
The buses mentioned for the above electronic devices may be peripheral component interconnect standard (Peripheral Component Interconnect, PCI) buses or extended industry standard architecture (Extended Industry Standard Architecture, EISA) buses, etc. The bus may be classified as an address bus, a data bus, a control bus, etc. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.
The communication interface is used for communication between the electronic device and other devices.
The Memory may include random access Memory (Random Access Memory, RAM) or may include Non-Volatile Memory (NVM), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the aforementioned processor.
The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but also Digital signal processors (Digital SignalProcessing, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field-programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
The embodiments of the present application also provide a non-transitory computer readable storage medium storing computer instructions that cause a computer to perform the steps of the method embodiments described above.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (9)
1. A method for processing image restoration, comprising:
acquiring original image information to be transmitted in a communication way;
generating first image signal data according to the original image information, wherein the first image signal data is data capable of being transmitted by communication equipment;
determining a data restoration model which corresponds to the communication equipment and is obtained through pre-training;
determining distortion data of the first image signal data after transmission in the communication equipment, and inputting the distortion data into the data restoration model to obtain restoration data for compensating the distortion data, wherein the restoration data is used for compensating data lost when the first image signal data is transmitted in the communication equipment;
compensating the first image signal data by the repair data so that the communication device outputs second image signal data according to the first image signal data and the repair data;
and obtaining repaired image information according to the second image signal data.
2. The processing method according to claim 1, wherein the method for creating the data repair model includes:
acquiring sample distortion data collected in advance, wherein the sample distortion data is obtained according to sample image information and distortion image information of the sample image information after transmission in communication equipment;
inputting the sample distortion data into a preset neural network model for training to obtain a trained neural network model;
and verifying the trained neural network model through the sample image information and the distorted image information, and obtaining the data restoration model after the verification result meets the preset requirement.
3. The method of processing according to claim 2, wherein the acquiring pre-collected sample distortion data comprises:
determining two-dimensional digital matrix data of the sample image information;
converting the two-dimensional digital matrix data into one-dimensional sequence data;
performing Fourier transform on the one-dimensional sequence data to obtain corresponding spectrum information;
obtaining distorted sample image information obtained after the sample image information is transmitted through the communication equipment;
obtaining corresponding distorted spectrum information according to the distorted sample image information;
and obtaining the sample distortion data according to the spectrum information and the spectrum information after distortion.
4. The method of processing according to claim 2, wherein the acquiring pre-collected sample distortion data comprises:
converting the sample image information into first color distribution energy spectrum information;
obtaining distorted sample image information obtained after the sample image information is transmitted through the communication equipment;
converting the distorted sample image information into second color distribution energy spectrum information;
and obtaining the sample distortion data according to the first color distribution energy spectrum information and the second color distribution energy spectrum information.
5. The processing method according to claim 1, wherein the determining a pre-trained data repair model corresponding to the communication device includes:
determining preset corresponding relations between different preset communication devices and a preset data restoration model;
and according to the preset corresponding relation, matching to obtain the data restoration model corresponding to the communication equipment.
6. A processing method according to claim 1, wherein said compensating the first image signal data by the repair data includes:
determining minimum unit signal data which needs to be compensated in the first image signal data;
determining minimum unit repair signal data corresponding to each minimum unit signal data in the repair data, and obtaining a data corresponding relation;
and loading each minimum unit repair signal data into the corresponding minimum unit signal data according to the data corresponding relation.
7. An image restoration processing apparatus, comprising:
the acquisition module is used for acquiring the original image information needing communication transmission;
the first conversion module is used for generating first image signal data according to the original image information, wherein the first image signal data is data which can be transmitted through communication equipment;
the determining module is used for determining a data restoration model which is obtained by training and corresponds to the communication equipment;
a repair data generating module, configured to obtain repair data corresponding to the first image signal data through the data repair model, where the repair data is used to compensate for data lost when the first image signal data is transmitted in the communication device, and the obtaining, through the data repair model, repair data corresponding to the first image signal data includes: determining distortion data of the first image signal data after transmission in the communication device; inputting the distorted data into the data repair model to obtain the repair data for compensating the distorted data;
a compensation module for compensating the first image signal data by the repair data so that the communication device outputs second image signal data according to the first image signal data and the repair data;
and the second conversion module is used for obtaining the repaired image information according to the second image signal data.
8. An electronic device, comprising: the device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
the memory is used for storing a computer program;
the processor being adapted to implement the processing method of any of claims 1-6 when executing the computer program.
9. A non-transitory computer readable storage medium storing computer instructions that cause a computer to perform the processing method of any of claims 1-6.
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