CN111524077B - Method and system for repairing image data - Google Patents
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Abstract
The invention relates to a method and a system for repairing image data, wherein the method comprises the following steps: acquiring image data to be repaired, and storing the image data to be repaired into a central memory; transcoding the image data to be restored through a transcoding workstation to obtain intermediate image data in a target format; the intermediate image data is repaired by the video repair workstation to obtain a standard image data file, so that the problem of low manual repair efficiency is effectively solved, and the high efficiency of repairing the image data is greatly ensured.
Description
Technical Field
The invention belongs to the technical field of image restoration, and particularly relates to a restoration method and system for image data.
Background
Film and television data are accumulation and witnessing of technological development, crystallization of modern technology and culture, reduction of economic development of times progress, most of carriers of images are films before digitization, film instability leads to a time period for film copying in storage, and poor storage conditions of early films are a main cause of serious damage of a large number of early films. In recent years, with the death of film movies, the preservation and repair of old films have become a problem faced by the industry, and if the old films cannot be repaired in time, some old films are likely to be unable to meet the audience.
Therefore, how to ensure that the restoration of the image data such as the old movie is efficiently completed becomes a technical problem to be solved by those skilled in the art.
Disclosure of Invention
In order to solve at least the above problems in the prior art, the present invention provides a method and a system for repairing image data, so as to realize efficient repair of old image data.
The technical scheme provided by the invention is as follows:
in one aspect, a method for repairing image data includes:
acquiring image data to be repaired, and storing the image data to be repaired into a central memory;
transcoding the image data to be repaired through a transcoding workstation to obtain intermediate image data in a target format;
and repairing the intermediate image data through a video repairing workstation to obtain a standard image data file.
Optionally, the acquiring the image data to be repaired and storing the image data to be repaired in the central storage includes:
the image data to be repaired is digitized into digital format image data to be repaired through a video acquisition workstation, and the digital format image data to be repaired is imported into a central memory; and/or;
and acquiring the image data to be repaired through a media library, and importing the image data to be repaired in the media library into a central storage.
Optionally, the digitizing the image data to be repaired by the video acquisition workstation includes:
scanning the image data to be repaired after physical cleaning by a film scanner to obtain preliminary image data to be repaired;
and automatically rendering the preliminary image data to be repaired based on a preset numerical value to obtain the image data to be repaired in a digital format.
Optionally, the transcoding processing is performed on the image data to be repaired by the transcoding workstation to obtain intermediate image data in a target format, including:
at a transcoding workstation, converting an interlaced file of the image data to be repaired into a progressive file by using a field removing algorithm;
and converting the format of the progressive file into a target format file supported by repair software, and taking the target format file as the intermediate image data.
Optionally, the repairing the intermediate image data by the video repairing workstation to obtain a standard image data file includes:
using DRS TM The NOVA tool automatically or manually repairs video noise, magnetic powder falling, dirty blocks, spots, scratches, color flickering, unstable pictures, color cast, jitter, signal fading, line synchronization jitter and frame loss to obtain a standard image data file.
Optionally, after the repairing the intermediate image data by the video repairing workstation, the method further includes:
performing sound-picture synchronization, editing, color mixing, synthesis and encapsulation processing on the repaired intermediate image data through a workflow workstation to obtain a primary image data file;
and rendering the preliminary image data file by using an up-conversion algorithm to obtain the standard image data file.
Optionally, before the rendering the preliminary image data file by using the up-conversion algorithm, the method further includes:
performing quality detection on the preliminary image data;
and adjusting the preliminary image data according to the quality detection result.
Optionally, the repairing the intermediate image data by the video repairing workstation further includes:
transmitting the intermediate image data to an online cloud;
and performing online cloud restoration on the intermediate image data through cloud deployment.
Optionally, after the obtaining the standard image data file, the method further includes:
and storing the standard image data file on line or storing the standard image data file to a media resource archiving server.
In another aspect, a system for repairing image data includes:
the acquisition module is used for acquiring the image data to be repaired and storing the image data to be repaired into the central memory;
the transcoding module is used for carrying out transcoding processing on the image data to be repaired through a transcoding workstation to obtain intermediate image data in a target format;
and the restoration module is used for restoring the intermediate image data through a video restoration workstation to obtain a standard image data file.
The beneficial effects of the invention are as follows:
according to the method and the system for repairing the image data, the image data to be repaired is obtained and stored in the central memory, the transcoding workstation is used for transcoding the image data to be repaired to obtain the intermediate image data in the target format, and finally the intermediate image data is repaired by the video repairing workstation to obtain the standard image data file, so that the manual repairing pressure is effectively relieved in the manners of obtaining, transcoding and repairing, the repairing efficiency is greatly improved, and the image data can be repaired efficiently.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of an image data restoration method according to an embodiment of the present invention;
FIG. 2 is a flowchart of an embodiment of a method for repairing image data;
FIG. 3 is a schematic diagram of an embodiment of an image data restoration system according to the present invention;
fig. 4 is a schematic structural diagram of an image data restoration device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, based on the examples herein, which are within the scope of the invention as defined by the claims, will be within the scope of the invention as defined by the claims.
Fig. 1 is a flowchart of an image data restoration method according to an embodiment of the present invention shown in fig. 1.
As shown in fig. 1, a method for repairing image data according to an embodiment of the present invention may include the following steps:
s11, obtaining the image data to be repaired, and storing the image data to be repaired into a central storage.
Specifically, there are two ways to obtain the image data to be repaired, which are classified into acquisition and import.
The acquisition is to digitize the image data to be repaired into digital format image data to be repaired by a video acquisition workstation and to guide the digital format image data to be repaired into a central memory. Firstly, before digitizing a film, performing physical cleaning to remove impurities such as dust, and then using a Filmfabriek HDS+scanner to perform clear and sharp scanning on old film materials, wherein the old film can be easily digitized by advanced wet gate technology, matched FRS can automatically render the scanned film, the operation is very simple, the scanned film is processed by using a set value to obtain image data to be repaired in a digital format, the effects of reducing dirty points and noise reduction are achieved, the workload of later manual repair is greatly reduced, and naturally, the set preset value can be manually adjusted according to specific conditions so as to meet different requirements of different situations. After digitization, the digital data can be imported into a central memory for the next operation.
The image data to be repaired in the media library is imported into the central storage through the media library, and the image data in the media library and the data in a digital format are imported into the central storage through the workflow workstation.
S12, transcoding the image data to be restored through a transcoding workstation to obtain intermediate image data in a target format.
Before transcoding, the damage degree of the image data to be repaired can be checked through playback of the material, the subsequent field-removing operation can be known through playback, the color condition of the image data to be repaired can be checked through playback, and the preparation work before the better repair is ensured. Playback can be performed by Cortex software, which includes various review and field-view modules including dead pixel detection, dead pixel correction, HDR and SDR gamut mapping, playback of IMF and DCP, verification of IMF and Dolby Vision, loudness monitoring, and photosensitive epilepsy detection. The matched OBM U series supports the wide color gamut of DCI-P3 and ITU-R BT.2020, and the wide color gamut and the advanced 3D LUT function enable the OBM series to accurately reproduce various color spaces and have excellent gray scales, so that the problems of the image data to be repaired can be accurately detected.
After knowing the problems of the image data to be repaired, in particular, at the transcoding workstation, converting the interlaced file of the image data to be repaired into the progressive file by using a field-removing algorithm, and converting the format of the progressive file into a target format file supported by the repair software as the intermediate image data. While the CORTEX product family includes fully functional everyday applications, IMF, DCP, AS-02 and Dolby Vision TM Packaging field packaging and release solutions, world-first media upload and MTI and Samsung advanced algorithm, and have stronger editing function, can perform high-speed rendering work, support Apple ProRes, apple ProRes XQ, AS02, avid DNxHD, avid DNxHR, avid MXF 1-to-1, blu-Ray-Automatically Authored, DPX, DVD-Automatically Authored, EXR, H.264, HEVC, IMF, JPEG (Quicktime/JPG), JPEG 2000,MPEG 1,MPEG 2,TIFF,XAVC,XDCAM, etc., can complete the conversion of various formats due to the strong encoding and decoding capabilities of the CORTEX products so as to meet the requirements of repair software and quickly complete the subsequent repair work.
S13, repairing the intermediate image data through a video repairing work station to obtain a standard image data file.
In particular, DRS can be adopted TM The NOVA tool automatically or manually repairs video noise, magnetic powder falling, dirty blocks, spots, scratches, color flickering, unstable pictures, color cast, jitter, signal fading, line synchronization jitter and frame loss to obtain a standard image data file. DRS (data transfer system) TM NOVA as a specialized repair software can be used to repair various defects caused by magnetic tracking instability, tape dust, breaks, head defects, and all problems ranging from common dust and dirt to catastrophic tearing and curling. The system can be automatically repaired or manually repaired, and comprises powerful tools with stable color, intelligent repair, anti-distortion, flicker removal, picture particle management, picture layer alignment and the like, and the tools can simply and effectively meet the requirement for ultrahigh definition film repair. The following functions may also be implemented: the tool can simply and effectively meet the requirements for repairing ultra-high definition movies. The GPU rendering is supported, the repairing efficiency is greatly improved, and the repairing technology is matched with the transcoding software from standard definition to high definition and 4K field-removing and up-converting technology, so that various analog standard definition programs can be repaired, various original defects of digital high definition program original sheets and various defects caused by unstable track tracking, tape powder falling, breakage and magnetic head defects in the digitizing process can be repaired. The method can also be combined with artificial intelligence calculation to carry out intelligent repair, further liberate manpower and improve the high efficiency of repair.
In addition, repair the middle image data through the video repair workstation, still include: transmitting the intermediate image data to an online cloud; and performing online cloud restoration on the intermediate image data through cloud deployment. Specifically, the online repair method can be realized by deploying the tools such as Cortex transcoding, field removal, DRS repair, cortex field removal, transcoding output and the like in a cloud, HCSO or video industry park, combining the image quality enhancement and super-resolution capability of the cloud to form an online integral solution for digitalization +4K repair of video files, and directly storing the online repair on the cloud or HCSO platform after the repair is finished. The off-line repair can be realized, and particularly, the off-line repair can be realized by deploying software and hardware systems such as acquisition equipment, repair, transcoding work stations, high-performance storage, fusion cube HCI virtualization resource pools, AI enhancement and superdivision systems, optical disc libraries, cortex software, DRS software and the like in a client machine room, and meanwhile, the AI enhancement and superdivision systems need to be linked with a cloud end to acquire cloud algorithms and operators in real time. The method can realize the efficient restoration of the image data no matter in an on-line restoration or off-line restoration mode.
To ensure the integrity of the repair, after the intermediate image data is repaired by the video repair workstation, the method may further include: and carrying out sound-picture synchronization, editing, color matching, synthesis and encapsulation processing on the repaired intermediate image data through a workflow workstation to obtain a preliminary image data file, rendering the preliminary image data file by using an up-conversion algorithm to obtain a standard image data file, and obtaining a good standard image data file after the encapsulation processing is completed to complete the whole repair work.
In order to ensure better quality, before the primary image data file is rendered by using the up-conversion algorithm, the method further comprises: performing quality detection on the preliminary image data; and adjusting the preliminary image data according to the quality detection result. For example, quality inspection of preliminary image material may include playback viewing and the like. If the detection result has no problem, the standard media file can be directly output and stored, and if the detection result has a problem, the detail adjustment can be carried out according to the specific condition of the specific problem, so that the standard image data file with quality overstretched is ensured to be obtained.
According to the method for repairing the image data, provided by the embodiment of the invention, the image data to be repaired is obtained and stored in the central memory, then the transcoding workstation is utilized to transcode the image data to be repaired to obtain the intermediate image data in the target format, and finally the intermediate image data is repaired by the video repairing workstation to obtain the standard image data file, so that the manual repairing pressure is effectively relieved in the manners of obtaining, transcoding and repairing, the repairing efficiency is greatly improved, and the repairing of the image data can be efficiently completed.
FIG. 2 is a flowchart of an embodiment of a method for repairing image data.
Further, as shown in fig. 2, on the basis of the above embodiment, the method for repairing image data in this embodiment may further include the following steps:
s21, obtaining the image data to be repaired, and storing the image data to be repaired into a central storage.
S22, transcoding the image data to be restored through a transcoding workstation to obtain intermediate image data in a target format.
S23, repairing the intermediate image data through a video repairing work station to obtain a standard image data file.
The steps S21, S22, and S23 have been clearly and clearly explained in the above embodiments, and are not explained in detail in the present embodiment, and are understood by reference to each other.
S24, the standard image data file is stored on line or stored in a media resource archiving server.
For example, the standard image data file may be directly stored in the central storage, or may be stored in other online manners, such as ocean stor 9000 V5, which may implement a laterally-expanded file storage, and use a fully-symmetric distributed architecture to provide unstructured data sharing resource storage for users with its excellent performance, large-scale laterally-expanded capability, and ultra-large single file system. The method can be applied to the fields of various business applications such as broadcast and television media, satellite mapping, gene sequencing, energy exploration, scientific research education, video monitoring, archiving backup and the like and storage resource sharing. In addition, the OceanStor distributed storage has a single-node bandwidth of up to 2.8GB/s, and the single-node bandwidth of up to 5.0GB/s in the full flash memory configuration, leading the single-disk performance industry. Supporting multiple networking forms of 10GE, 25GE, 40GE, 100G InfiniBand and the like, supporting RDMA mode transmission and TOE unloading, and improving the transmission performance of the system. The system performance increases linearly with the increase of the nodes, and the highest bandwidth can reach 700 GB/s; the system bandwidth can reach 1.4TB/s at the highest when the flash memory is configured. In a video editing scene, by taking the model of a P36A product as an example, a single storage node can realize stable playback of 27 layers of 500Mbps and 10 layers of 1500Mbps 4K materials in a 25GE networking environment, and can meet the bandwidth requirement of a 4K image restoration scene. Thereby meeting the storage requirements.
Meanwhile, a specialized media asset library management system and a high-reliability storage medium for persistent storage can be adopted for supporting, wherein a plurality of main stream archiving systems including an ODA mass optical disc library are integrated on the basis of Navigator X media asset management software, and the media asset management solution can be tightly matched with the front-end online storage. The mass optical disk data storage system is based on an optical disk box which has high firmness and reliability and stores a plurality of commercial optical disks, and an optical disk storage system of a high-speed optical disk drive which controls the optical disk box. Since the release of the system in 2012, the system has been adopted by users in various industries who need to store digital data for a long period of time, and the 3 rd generation optical disc (5.5 TB) product line has been updated in 2020. Compared with the storage mode of the magnetic tape, the ODA optical disk storage system can provide a near-line reading mode for video files, and can randomly read at an average 375MB/s reading rate after the optical disk is loaded into a drive. Meanwhile, data transmission is realized through the latest USB3.2/USB3.0 compatible connection, and the desktop reading requirement of a media scene can be flexibly met, so that the safe storage of standard image data files is ensured.
Based on a general inventive concept, the embodiment of the invention also provides an image data restoration system.
FIG. 3 is a schematic diagram of an embodiment of an image data restoration system.
Referring to fig. 3, an image data restoration system provided in an embodiment of the invention may include:
the acquisition module 10 is used for acquiring the image data to be repaired and storing the image data to be repaired into the central memory;
the transcoding module 20 is used for performing transcoding processing on the image data to be restored through the transcoding workstation to obtain intermediate image data in a target format;
and the repair module 30 is used for repairing the intermediate image data through the video repair workstation to obtain a standard image data file.
According to the system for repairing the image data, provided by the embodiment of the invention, the image data to be repaired is obtained and stored in the central memory, the transcoding workstation is used for transcoding the image data to be repaired to obtain the intermediate image data in a target format, and finally the intermediate image data in a target format is repaired by the video repairing workstation to obtain a standard image data file, so that the pressure of manual repair is effectively relieved in the manners of obtaining, transcoding and repairing, the repairing efficiency is greatly improved, and the repairing of the image data can be efficiently completed.
Further, the acquiring module 10 in this embodiment is specifically configured to:
scanning the image data to be repaired after physical cleaning by a film scanner to obtain preliminary image data to be repaired;
automatically rendering the preliminary image data to be repaired based on a preset value to obtain digital format image data to be repaired, and importing the digital format image data to be repaired into a central memory; and, or;
and acquiring the image data to be repaired through the media library, and importing the image data to be repaired in the media library into the central storage.
Further, the transcoding module 20 in this embodiment is specifically configured to:
at a transcoding workstation, converting an interlaced file of the image data to be repaired into a progressive file by using a field removing algorithm;
converting the format of the progressive file into a target format file supported by the repair software as intermediate image data.
Further, the repair module 30 in this embodiment is specifically configured to include:
using DRS TM The NOVA tool automatically or manually repairs video noise, magnetic powder falling, dirty blocks, spots, scratches, color flickering, unstable pictures, color cast, jitter, signal fading, line synchronization jitter and frame loss to obtain a standard image data file.
Further, the image data restoration system in this embodiment further includes:
the output module is used for carrying out sound-picture synchronization, editing, color mixing, synthesis and packaging treatment on the repaired intermediate image data through the workflow workstation to obtain a primary image data file; rendering the preliminary image data file by using an up-conversion algorithm to obtain a standard image data file.
Further, the image data restoration system in this embodiment further includes:
the quality inspection module is used for detecting the quality of the preliminary image data; and adjusting the preliminary image data according to the quality detection result.
Further, in the image data restoration system of the present embodiment, the restoration module 30 is specifically further configured to:
transmitting the intermediate image data to an online cloud;
and performing online cloud restoration on the intermediate image data through cloud deployment.
Further, the image data restoration system in this embodiment further includes:
and the storage module is used for carrying out online storage on the standard image data file or storing the standard image data file to the media resource archiving server.
The specific manner in which the various modules perform the operations in relation to the systems of the above embodiments have been described in detail in relation to the embodiments of the method and will not be described in detail herein.
Based on a general inventive concept, the embodiment of the invention also provides an image data restoration device.
Fig. 4 is a schematic structural diagram of an image data restoration device according to an embodiment of the present invention, referring to fig. 4, the image data restoration device according to an embodiment of the present invention includes: a processor 41, and a memory 42 connected to the processor.
The memory 42 is used for storing a computer program, and the computer program is at least used for the image data restoration method described in any of the above embodiments;
the processor 31 is used to call and execute the computer program in memory.
In order to better meet the requirement of the digital restoration scene of the offline video data, the intelligent data and storage product line is based on the fusion cube HCI super-fusion product capability, and the AI video restoration integrated machine equipment based on the digital restoration scene of the offline video data is provided. The overall architecture of fusion cube HCI is mainly composed of: the system comprises a hardware platform, distributed storage software, an installation deployment and operation management platform, a virtualization platform and a corresponding backup disaster recovery scheme, wherein the virtualization platform supports a fusion sphere virtualization platform and a Vmware virtualization platform which are self-developed. In addition, under the fusion speed scene, the fusion cube HCI supports a hybrid deployment scheme, and can support physical node deployment besides a fusion sphere virtualization platform, so that corresponding computing, storage and network resources are provided for a system database. In the deployment of fusion sphere virtualization, fusion cube distributed storage software is directly deployed in a Hypervisor kernel, the HDD and SSD Cache storage media of the node are configured into storage pool resources shared by the system through the fusion cube distributed storage software, and meanwhile, a fusion sphere virtualization platform virtually provides computing resources of the node for service virtual machines on the node to use. According to the functional characteristic difference provided by the nodes, the method is divided into a management fusion node, a storage fusion node, a calculation node and a physical database node.
In a digital video data restoration scene, a management fusion node and a storage fusion node provide virtual machine running environments meeting restoration application software deployment, and a computing node provides image quality enhancement, 4K super and other AI-based computing power support through installing a GPU display card. The 2U rack server based on 2288H V5 is recommended to be deployed, and is characterized by being the most flexible, supporting various hard disk types, reserving a plurality of PCIE slots and supporting GPU cards. The integrated machine equipment scheme preinstalls repair application software, AI image quality enhancement and 4K super-distribution sleeve algorithm and drive in a mode of a virtual machine template, and the minimum configuration is 3 nodes 2288H V5 calculation, storage and fusion deployment. The number of GPU graphics cards (up to 3 NVIDIA Tesla M60 graphics cards) can be flexibly selected according to service requirements. The device can be used with online cloud storage, provides virtualized desktop deployment with GPU virtualization and through functions, and meets the requirements of daily office and video content production environments of media scenes.
The invention has the technical advantages that:
the technical scheme is as follows:
1) The architecture is flexible, and the deployment is flexible based on the requirements of clients;
2) The public cloud business mode is supported, and the initial investment is low;
advantageous properties:
1) Support multiple film/video formats: (super) 8mm,16mm,35mm; inch bands, 3/4, VHS, beta-Cam, etc., analog bands, HDCAM, SR, etc.
2) Automatic repair based on AI technology, supporting repair of jitter, dirty points, scratches and flicker;
3) The transcoding efficiency is ultra-real-time, and the support format is wide;
4) Supporting HDR, dolby Vision, IMF, DCP, XAVC and other multi-format packages.
Historical value:
1) Digitally protecting and repairing the historical image file;
2) Solves the problem of lack of ultra-high definition tablet sources;
3) The secondary distribution capability of the history image data is improved, and the technology and the E2E distribution service are provided.
The scheme can solve the problems of most existing image data and the problem of difficult format conversion in the manufacturing process, and provides one-stop full-process service for a data hall, a television station and the like.
The packaging speed of the media material is high, the picture quality exceeding 60% in the same field can be obtained by using the solution, the effect on picture up-conversion and image enhancement is improved by about 50% compared with most of the solutions, and even the effect of three times of super real time can be achieved under the specific condition of transcoding efficiency.
The digital video processing tool software used in the scheme can complete the functions of process flow establishment, video project management, data input and output, verification, sound and picture synchronization, color matching, editing synthesis, transcoding rendering, quality management, multi-stage cluster multi-task parallel processing, and the specific functions can be completed as follows:
(1) the end-to-end 4K/8K manufacturing tool is complete and can meet the requirements of the complete manufacturing process from the lens to the screen;
(2) the method can realize automatic intelligent judgment, import and playback of various common professional film and television material files;
(3) MD5 and other HASH verification modes are supported, and the integrity and safety of data are ensured;
(4) multiple sources, multiple destinations, multiple data media (HD, RAID, LTO, etc.) are supported. Intelligent sound-picture synchronization and metadata extraction and management;
(5) tools such as color mixing, drawing templates, various oscilloscopes and the like ensure the manufacturing efficiency;
(6) clip composition supports various common delivery formats and supports HDR10/DOLBY VISION metadata management on the timeline;
(7) optimizing a field removing algorithm, and ensuring that interlaced video materials are subjected to field removing to be changed into progressive;
(8) the up/down conversion algorithms are combined with a plurality of optimization modes, so that various requirements of various manufacturing processes are fully met and considered;
(9) the multi-workstation cluster rendering structure is supported, and the transcoding efficiency is improved by a parallel mode through a flexible task allocation algorithm.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
It is to be understood that the same or similar parts in the above embodiments may be referred to each other, and that in some embodiments, the same or similar parts in other embodiments may be referred to.
It should be noted that in the description of the present invention, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Furthermore, in the description of the present invention, unless otherwise indicated, the meaning of "plurality" means at least two.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and further implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
It is to be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.
The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.
Claims (8)
1. A method for repairing image data, comprising:
acquiring image data to be repaired, and storing the image data to be repaired into a central memory;
transcoding the image data to be repaired through a transcoding workstation to obtain intermediate image data in a target format;
repairing the intermediate image data through a video repairing workstation to obtain a standard image data file;
the transcoding processing is carried out on the image data to be repaired through a transcoding workstation to obtain intermediate image data in a target format, and the method comprises the following steps:
at a transcoding workstation, converting an interlaced file of the image data to be repaired into a progressive file by using a field removing algorithm;
converting the format of the progressive file into a target format file supported by repair software as the intermediate image data;
the repairing of the intermediate image data by the video repairing workstation further comprises: transmitting the intermediate image data to an online cloud; performing online cloud restoration on the intermediate image data through cloud deployment;
specifically, through public cloud deployment, cortex transcoding, field removal, DRS repair, cortex field removal and transcoding output tools are deployed in a cloud, HCSO or video industry park, and meanwhile, image quality enhancement and super-resolution capability of the cloud are combined into an on-line overall solution for digital +4K repair of video files, so that on-line repair is performed on intermediate image data.
2. The method for restoring image data according to claim 1, wherein said acquiring image data to be restored and storing said image data to be restored in a central storage comprises:
the image data to be repaired is digitized into digital format image data to be repaired through a video acquisition workstation, and the digital format image data to be repaired is imported into a central memory; and/or;
and acquiring the image data to be repaired through a media library, and importing the image data to be repaired in the media library into a central storage.
3. The method of claim 2, wherein digitizing the image data to be repaired by a video capture workstation comprises:
scanning the image data to be repaired after physical cleaning by a film scanner to obtain preliminary image data to be repaired;
and automatically rendering the preliminary image data to be repaired based on a preset numerical value to obtain the image data to be repaired in a digital format.
4. The method for restoring image data according to claim 1, wherein said restoring said intermediate image data by means of a video restoration workstation to obtain a standard image data file comprises:
and (3) automatically or manually repairing video noise, magnetic powder falling, dirty blocks, spots, scratches, color flickering, unstable pictures, color cast, jitter, signal fading, line synchronization jitter and frame loss by adopting a DRS ™ NOVA tool to obtain a standard image data file.
5. The method of claim 1, wherein after the repairing the intermediate image data by the video repairing workstation, further comprising:
performing sound-picture synchronization, editing, color mixing, synthesis and encapsulation processing on the repaired intermediate image data through a workflow workstation to obtain a primary image data file;
and rendering the preliminary image data file by using an up-conversion algorithm to obtain the standard image data file.
6. The method of claim 5, wherein before the primary image data file is rendered by the up-conversion algorithm, further comprising:
performing quality detection on the preliminary image data;
and adjusting the preliminary image data according to the quality detection result.
7. The method for restoring image data according to claim 1, further comprising, after the obtaining the standard image data file:
and storing the standard image data file on line or storing the standard image data file to a media resource archiving server.
8. A system for repairing image data, comprising:
the acquisition module is used for acquiring the image data to be repaired and storing the image data to be repaired into the central memory;
the transcoding module is used for carrying out transcoding processing on the image data to be repaired through a transcoding workstation to obtain intermediate image data in a target format; the transcoding processing is carried out on the image data to be repaired through a transcoding workstation to obtain intermediate image data in a target format, and the method comprises the following steps:
at a transcoding workstation, converting an interlaced file of the image data to be repaired into a progressive file by using a field removing algorithm; converting the format of the progressive file into a target format file supported by repair software as the intermediate image data;
the restoration module is used for restoring the intermediate image data through a video restoration workstation to obtain a standard image data file;
the repair module is also used for sending the intermediate image data to an online cloud; and carrying out online cloud restoration on the intermediate image data through cloud deployment, specifically, carrying out online restoration on the intermediate image data through public cloud deployment by disposing Cortex transcoding, field removal and DRS restoration, wherein Cortex field removal and transcoding output tools are deployed in a cloud, HCSO or video industry park, and meanwhile, combining image quality enhancement and superdivision capability of the cloud into an online integral solution of digital +4K restoration of the video file.
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