CN110287388B - Data visualization method and device - Google Patents
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Abstract
The application provides a data visualization method and a data visualization device, wherein the method comprises the following steps: the method comprises the steps of obtaining original volume data to be processed, compressing the original volume data in a layering compression mode to form compressed data, and transmitting the compressed data to client equipment to enable the client equipment to visually display the compressed data. By adopting the scheme, the problem that the adaptability of a remote visualization technology to different scenes in the related technology is poor is solved, the original volume data to be processed is compressed in a layering manner and then is transmitted to the client device, the data volume of the visualization data is greatly reduced, the data of different layers adapt to different display scenes, the real-time performance of interaction between two parties is ensured, and the display effect is improved.
Description
Technical Field
The present application relates to, but not limited to, the field of remote visualization, and in particular, to a data visualization method and apparatus.
Background
In the related art, a remote visualization system is a tool system for rapidly and remotely viewing large-scale data through a network. In recent years, with the development of various imaging devices in the biomedical field, a large amount of volume data with a large scale can be acquired through electron microscope acquisition, tomography or other three-dimensional reconstruction technologies. Since the data volume is large, it is not easy to transmit or transfer the data directly through the network, and for the visualization of the data, a local data visualization system or method is often adopted, such as software using visualization tools including slicing, iso-surface or volume rendering. However, if a remote browsing service or web distribution is to be provided based on such data, only visualization or quick preview of the data can be achieved by means of a remote visualization system.
Aiming at the problem that the remote visualization technology in the related technology has poor adaptability to different scenes, no effective solution is available at present.
Disclosure of Invention
The embodiment of the application provides a data visualization method and device, and aims to at least solve the problem that a remote visualization technology in the related technology is poor in adaptability to different scenes.
There is also provided, in accordance with an embodiment of the present application, a data visualization method, including: acquiring original volume data to be processed; compressing the original volume data in a layering compression mode to form compressed data; and transmitting the compressed data to client equipment so that the client equipment can visually display the compressed data.
There is also provided, in accordance with another embodiment of the present application, a data visualization method, including: receiving compressed data transmitted by a server, wherein the compressed data is formed by compressing original volume data in a layering manner; and loading the compressed data packet by packet according to the hierarchy, and visually displaying the compressed data.
There is also provided, in accordance with another embodiment of the present application, apparatus for data visualization, including: the acquisition module is used for acquiring original volume data to be processed; the compression module is used for compressing the original volume data in a layering compression mode to form compressed data; and the transmission module is used for transmitting the compressed data to client equipment so as to enable the client equipment to visually display the compressed data.
There is also provided, in accordance with another embodiment of the present application, apparatus for data visualization, including: the receiving module is used for receiving compressed data transmitted by the server, wherein the compressed data is formed by compressing original volume data in a layering manner; and the display module is used for loading the compressed data packet by packet according to the hierarchy and visually displaying the compressed data.
There is also provided, in accordance with another embodiment of the present application, a data visualization system, including: the server is used for acquiring original volume data to be processed and compressing the original volume data in a layering compression mode to form compressed data; the server is also used for transmitting the compressed data to the client device; and the client equipment is used for receiving the compressed data, loading the compressed data packet by packet according to the layers and visually displaying the compressed data.
According to a further embodiment of the present application, there is also provided a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
According to yet another embodiment of the present application, there is also provided an electronic device, comprising a memory in which a computer program is stored and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
According to the method and the device, original volume data to be processed are obtained, the original volume data are compressed in a layering compression mode to form compressed data, and the compressed data are transmitted to client equipment so that the client equipment can visually display the compressed data. By adopting the scheme, the problem that the adaptability of a remote visualization technology to different scenes in the related technology is poor is solved, the original volume data to be processed is compressed in a layering manner and then is transmitted to the client device, the data volume of the visualization data is greatly reduced, the data of different layers adapt to different display scenes, the real-time performance of interaction between two parties is ensured, and the display effect is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a block diagram of a hardware structure of a terminal of a data visualization method according to an embodiment of the present application;
FIG. 2 is a flow chart of a method of data visualization according to an embodiment of the present application;
FIG. 3 is a block diagram of an asymptotic data remote visualization system according to another embodiment of the present application;
FIG. 4 is a functional flow diagram of a volumetric data organization compression storage module according to another embodiment of the present application;
FIG. 5 is a functional flow diagram of a raw data verification update module according to another embodiment of the present application;
FIG. 6 is a functional flow diagram of an asymptotic data visualization interaction module according to another embodiment of the present application;
FIG. 7 is a schematic diagram of compression ratios of data in each layer of electron microscope reconstructed three-dimensional volume data according to another embodiment of the present application;
fig. 8 is an effect diagram for remote visualization of electron microscope reconstructed data according to another embodiment of the present application.
Detailed Description
The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
The traditional remote visualization system has a simple structure, and often realizes server-side data visualization through direct data transmission or image transmission, and the method causes great pressure on a server, a network and a client. The visualization system is also optimized by data reduction methods such as data extraction, but the problems of low interaction real-time performance, poor visualization effect, complex client and the like exist in the aspect of remote visualization of volume data.
Example one
The method provided by the first embodiment of the present application may be executed in a computer terminal or a similar computing device. Taking a terminal as an example, fig. 1 is a hardware structure block diagram of a terminal of a data visualization method according to an embodiment of the present application, and as shown in fig. 1, the terminal may include one or more processors 102 (only one is shown in fig. 1) (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA, etc.), and a memory 104 for storing data, and optionally, the terminal may further include a transmission device 106 for a communication function and an input/output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration and is not intended to limit the structure of the terminal. For example, the terminal may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
The memory 104 may be used to store software programs and modules of application software, such as program instructions/modules corresponding to the data visualization method in the embodiment of the present application, and the processor 102 executes various functional applications and data processing by executing the software programs and modules stored in the memory 104, so as to implement the method described above. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the terminal. In one example, the transmission device 106 includes a Network adapter (NIC) that can be connected to other Network devices through a base station to communicate with the internet. In one example, the transmission device 106 can be a Radio Frequency (RF) module, which is used to communicate with the internet in a wireless manner.
In the present embodiment, a data visualization method operating in a server is provided, and fig. 2 is a flowchart of a data visualization method according to an embodiment of the present application, and as shown in fig. 2, the flowchart includes the following steps:
step S202, acquiring original volume data to be processed;
this step may be run on the server.
Step S204, compressing the original volume data by adopting a layering compression mode to form compressed data;
the hierarchical compression, i.e. compressing the original volume data according to different data resolutions, e.g. compressing according to different resolution requirements, compressing according to different sizes, etc., may be referred to as hierarchical compression.
Optionally, the original volume data can be organized and compressed hierarchically, so that the network transmission pressure is effectively reduced.
Step S206, transmitting the compressed data to a client device so that the client device can visually display the compressed data.
By adopting the scheme, the problem that the adaptability of a remote visualization technology to different scenes in the related technology is poor is solved, the original volume data to be processed is compressed in a layering manner and then is transmitted to the client device, the data volume of the visualization data is greatly reduced, the data of different layers adapt to different display scenes, the real-time performance of interaction between two parties is ensured, and the display effect is improved.
Optionally, compressing the original volume data in a hierarchical compression manner to form compressed data, including: sampling the original volume data according to different sampling step lengths to form sampling data corresponding to different resolutions; sorting according to the resolution, and organizing the sampling data to form hierarchical data; and performing block compression on the hierarchical data by adopting a block-based compression mode, and establishing compressed data which can be randomly indexed according to blocks. By adopting the scheme, compressed data with different resolutions is formed, so that different resolutions can be selected conveniently according to network transmission conditions, and the method is suitable for various visual scenes.
Optionally, before sampling the original volume data according to different sampling step sizes and forming sampling data corresponding to different resolutions, determining a value of the sampling step size I by the following method:
I＝2twherein t satisfies the following condition:
wherein t is a non-negative integer, (N)x,Ny,Nz) For the original volume data resolution, Nx，Ny，NzNumber of pixel points similar to three dimensions of an image, BlowAnd BhighIs a preset value; when there is no parameter t satisfying the condition, the t is set to 0.
Optionally, after the sample data is organized according to the resolution order to form hierarchical data, a hash check algorithm is used to calculate a hash check code of each block of data, and the hash check code is stored. By adopting the scheme, the Hash check code of the original block data is calculated through a Hash check algorithm, and a basis is provided for detecting whether the original block data is transformed or not by comparing the Hash check code subsequently.
Optionally, compressing the original volume data in a layered compression manner to form compressed data, and periodically detecting whether the original volume data has data change; and when the original volume data has data change, performing hierarchical compression on the changed original volume data, and updating the compressed data.
Optionally, the method comprises at least one of: detecting whether the resolution of data in the original volume data changes or not, and if so, integrally updating the compressed data; and verifying and comparing the original volume data by adopting a Hash verification algorithm, and when the Hash verification code of the block data is changed when the original volume data is compared with the original volume data, performing hierarchical compression on the block data again. In the above scheme, the data resolution may be data at different positions, data at different resolutions, and data at different sizes, and when it is determined that the currently required data resolution changes in the interaction, the compressed data to be visualized needs to be updated integrally, for example, the data with clearer resolution is transmitted to the client. For block data updating, namely when the block data is detected to be transformed, the block data is independently recompressed and transmitted.
There is also provided, in accordance with another embodiment of the present application, a data visualization method, including the steps of:
receiving compressed data transmitted by a server, wherein the compressed data is formed by compressing original volume data in a layering manner;
and step two, loading the compressed data packet by packet according to the hierarchy, and visually displaying the compressed data.
By adopting the scheme, the layered compressed data is loaded packet by packet, and the compressed data of different layers is loaded according to different display requirements so as to meet the current transmission scene and the current display scene, the data of different layers is suitable for different display scenes and different transmission scenes, the real-time performance of interaction between the two parties is ensured, and the display effect is improved. The problem that the remote visualization technology in the related technology is poor in adaptability to different scenes is solved.
Optionally, receiving compressed data transmitted by the server includes: requesting the server to obtain a hierarchical compressed data list; sorting the data packets according to the parameter information of the data packets in the hierarchical compressed data list, and downloading the data packets according to the sorting result; optionally, the packet parameter information includes: image size, image position, image resolution, etc.
Loading the compressed data packet by packet according to the hierarchy, and visually displaying the compressed data, wherein the method comprises the following steps: and decompressing the highest-resolution compressed data in the currently downloaded data and generating a visual result.
Alternatively, the data packets may be downloaded sequentially according to the sorting result, for example, downloading the data packets sequentially from low resolution to high resolution, so as to preferentially ensure the integrity of the image. It is also possible to directly accept an input signal of a user, where the input signal includes a data resolution desired by the user, for example, an input signal displayed according to a 1080p display effect, and the client directly downloads the compressed data of the resolution from the server, and ignores the compressed data of other resolutions.
Optionally, after the compressed data is loaded packet by packet according to a hierarchy and visually displayed, the method includes at least one of:
taking compressed data displayed in a current visualization mode as first compressed data, downloading second compressed data from the server when detecting that second compressed data with higher resolution than the first compressed data exists in the server and a current visualization result meets the minimum requirement of real-time interaction, and generating a visualization result;
receiving an input signal, determining a visualization requirement according to the input signal, and downloading compressed data corresponding to the resolution ratio meeting the visualization requirement from the server.
By adopting the scheme, the client automatically changes the data resolution of the current display data, for example, automatically changes from high definition to ultra-definition, and can also change according to the input signal of the user so as to better meet the requirement of the user. When the two conflict, for example, the current network bandwidth allows upgrading from high definition to ultra-definition, but after receiving a signal that the user saves data traffic, the data resolution is not changed, and the image display effect of high definition is continuously maintained.
The following description is made in conjunction with another embodiment of the present application.
Another embodiment of the present application provides a progressive volume data remote visualization system, which implements data reduction based on hierarchical detail and block transform compression technology, thereby reducing server and network bandwidth pressure, and simultaneously provides remote visualization service based on progressive visualization technology, and improves client interaction real-time performance.
In order to achieve the purpose, the technical scheme of the application is as follows:
a volume data remote visualization system is adopted, hierarchical organization is completed after data sampling is conducted on original data, meanwhile block transformation compression algorithm is utilized to conduct block compression on the hierarchical data, data reduction is completed on the premise that information quantity is reserved as much as possible, and meanwhile asymptotic remote visualization service is provided based on the pre-organized data.
The system comprises the following modules:
the system comprises an M1 volume data organization compression storage module, a data compression module and a data compression module, wherein the volume data organization compression storage module is used for realizing original volume data organization and hierarchical compression and effectively reducing network transmission pressure;
m2, an original data checking and updating module for regularly checking the state of original data to adapt to the irregular change of the content of the original data and realize the original data checking and the layered compressed data updating;
and M3, an asymptotic data visualization interaction module, which is used for loading the layered compressed data packet by packet and providing good real-time interaction experience for the user.
The module M1 is specifically implemented by the following steps:
s11, adopting a series of sampling step length I in a specific range to be 2tThe method comprises the following steps of carrying out downsampling on original data to form downsampled data with different resolutions, sequencing and organizing according to the resolution to form hierarchical data, and selecting a parameter t according to the following criteria:
wherein t is a non-negative integer, (N)x,Ny,Nz) For the resolution of the raw data, BlowLower bound for customizable data size, BhighAn upper bound for customizable data size. If the sampling step length meeting the condition does not exist, directly adopting a parameter t which is 0;
s12, calculating hash check codes of the data by adopting hash check algorithms such as cyclic redundancy check CRC32, a secure hash algorithm SHA1, a message digest algorithm MD5 and the like, and storing the hash check codes for data change detection;
and S13, performing block-based compression on the downsampled data by adopting a data compression method based on block Transform (DCT), HWT, ZFP and the like, such as Discrete Cosine Transform (DCT), HWT and ZFP, and establishing hierarchical compressed data which can be randomly indexed according to blocks.
The original data content may change irregularly, and the module M2 checks the data change regularly, and performs data verification and update by using the following strategies:
s21, checking whether the data resolution is changed or not, if so, updating the original data compression state into overall update, and informing an M1 module to perform overall update on the layered data, otherwise, performing the next step;
s22, carrying out verification comparison on the whole original data by adopting a Hash verification algorithm, updating the data compression state into block updating when the original data is detected to be changed, and carrying out the next step, or updating the data compression state into a state without updating, and quitting the corresponding original data check;
s23, checking and comparing each data block of the original data by adopting a Hash check algorithm, when the block data change is detected, updating the compression state of the block data into block updating, informing the M1 module to perform data compression and layering processing on the corresponding data block again, otherwise, updating the data compression state of the block into a state of not needing updating, and quitting the check of the corresponding block data.
The module M3 operates on the client side and operates according to the following steps:
s31, requesting a server to obtain a hierarchical compressed data list;
s32, sorting the data packets according to the size, position, resolution ratio and other information of the data packets in the obtained hierarchical compressed data list, and sequentially downloading the data packets according to priority through network communication;
s33, decompressing and generating a visual result by using the currently downloaded data with the highest resolution and adopting an isosurface or volume rendering method;
s34, if higher resolution data exist and the current visualization result can meet the minimum interactive real-time performance, downloading the higher-level resolution data, and returning to S33, otherwise, performing the next step;
s35, the user adjusts the data resolution ratio level according to the current interaction real-time performance and the visualization requirement, loads corresponding data and generates a visualization result.
Fig. 3 is a structural diagram of an asymptotic data remote visualization system according to another embodiment of the present application, and as shown in fig. 3, in another embodiment of the present application, the asymptotic volume data remote visualization system includes a client and a server, the client includes a progressive data visualization interaction module, and the functions of the module include: data request, priority ordering, data decompression, isosurface calculation, color mapping and visual display.
The server side comprises original volume data, a data organization compression storage module and a data verification updating module. The functions of the data organization compression storage module comprise: data downsampling, Hash check code generation and block conversion compression. The data checking and updating module comprises the following functions: database retrieval, hash check and data state update.
Fig. 4 is a functional flowchart of a volume data organization and compression storage module according to another embodiment of the present application, and as shown in fig. 4, the volume data organization and compression storage module operates on a server side and is responsible for hierarchical organization and block compression storage of volume data, including the following steps:
s11, inquiring the state of the original data, and jumping to S12 if the state is wholly updated; if the status is block update, go to S14; if the state is not required to be updated, the data organization compression process is exited;
s12, detecting whether a compression condition is met? Customizable upper and lower bounds B according to set data sizelowAnd BhighCalculating upper and lower limits t of sampling step length parameterminAnd tmaxIf the sampling step length meeting the conditions does not exist, the original data is directly stored, and the data organization compression process is exited; otherwise, jumping to S13;
and S13, data block compression queue. Recording information such as sampling step length, dimensionality, position, data type and the like of the data block, pressing the information into a data block compression queue, and jumping to S15;
s14, inquiring the block data compression state. Inquiring the compression state of all recorded data blocks, if the state is block updating, recording the information of sampling step length, dimensionality, position, data type and the like of the corresponding data block, and pressing the information into a data block compression queue; and if the state is not required to be updated, not recording the data block information. Waiting for the completion of the query of the compression states of all the data blocks, and jumping to S15;
and S15, compressing block data. According to the data block compression queue, parallel compression is carried out on each block of data, and the specific block of data compression flow is as follows:
(1) according to the recorded information of the sampling step length, dimensionality, position, data type and the like of the data block, down-sampling is carried out on the original data;
(2) updating and storing the block data hash check code by adopting hash check algorithms such as CRC32, SHA1, MD5 and the like;
(3) and compressing the block data by adopting a data compression method based on block transformation, such as DCT, HWT, ZFP and the like.
After all the block data are compressed, jumping to S16;
and S16, storing hierarchical data information. And establishing layered compressed data which can be randomly indexed according to the blocks by combining the block data compressed by the S15 according to the recorded information of the sampling step length, the dimensionality, the position, the data type and the like of the data block, and exiting the data organization and compression process.
Fig. 5 is a functional flowchart of an original data verification update module according to another embodiment of the present application, and as shown in fig. 5, the original data verification update module is executed on a server side and is responsible for original data verification and hierarchical data update. The processing flow is shown in fig. 5, and comprises the following steps:
s21, analyzing the original data, checking whether the resolution of the data is changed or not, if so, updating the compression state of the original data into an overall update, and quitting the original data check; otherwise jump to S22;
s22. detect if the data dimensions match? The data dimension may be equivalent to the data resolution. If the data match, a hash check code is generated according to the current data, check code query is performed, and it is detected whether the check codes match? And when the verification is not matched, setting the original data compression state as block updating, jumping to S23, otherwise, confirming that the data compression state is not required to be updated, and exiting the original data check.
And when the data dimensions are not matched, integrally updating the original data.
S23, partitioning the original data, verifying and comparing each data block of the original data by adopting a Hash verification algorithm, and updating the compression state of the corresponding block data into block updating if the block verification codes are successfully matched; otherwise, updating the compression state of the corresponding block data to be unnecessary to update, and quitting the check of the corresponding block data.
Fig. 6 is a functional flowchart of an asymptotic data visualization interaction module according to another embodiment of the present application, as shown in fig. 6, the asymptotic data visualization interaction module runs on a client and is responsible for asymptotic data request and interaction, and the interaction flow is shown in fig. 6, and includes the following steps:
s31, request of layering compressed data list. The module requests the server to obtain a hierarchical compressed data list, and if the request is successful, the module jumps to S32; otherwise, quitting the asymptotic data visualization interaction;
and S32, setting data priority. Setting the priority of the data packet according to the dimension, position, resolution and other information of the data packet in the obtained hierarchical compressed data list, and jumping to S33;
s33, single data packet request. According to the priority sequence set in the S32, requesting single-packet data from the server, judging whether the currently downloaded data can meet the minimum interactive requirement, if not, updating the priority of the data packet, repeatedly executing the S33, and simultaneously jumping to the S34; if yes, go to S34;
and S34, data packet decompression. Decompressing and generating a visual result by using the currently downloaded highest resolution data and adopting an isosurface method, and jumping to S35;
s35, waiting for user interaction input. And the user adjusts the resolution level of the data according to the current interaction real-time performance and visualization requirements, loads corresponding data and generates a visualization result.
By way of example, with the progressive volume data remote visualization system provided by the present application, the present example uses cryo-electron microscope three-dimensional reconstruction data as the original volume data, the resolution of the volume data is (480, 480, 480), the voxel type is Float32, and the storage occupancy size is 421MB (442,368,000 bytes). The schematic diagram of the compression ratio of each layer of the electron microscope reconstructed three-dimensional data and the remote visualization effect diagram of the electron microscope reconstructed data are respectively shown in fig. 7 and fig. 8.
Fig. 7 is a schematic diagram of data compression ratios of each layer of the electron microscope reconstructed three-dimensional volume data according to another embodiment of the present application, as shown in fig. 7, showing data compression ratios at different resolution layers. Abscissa of the graphDimension information (N) representing hierarchical datax＝Ny＝Nz) Dimension information, i.e., data resolution, or the number of grid points. The data downsampling of the original data at different sampling rates can generate data of different levels, and the downsampled result data respectively have different resolutions.
Fig. 8 is a diagram illustrating the remote visualization effect of the reconstructed data from the electron microscope according to another embodiment of the present application, which shows the visualization effect presented by the asymptotic data visualization interaction module at different resolution levels. Fig. 8(a) (b) (c) (d) correspond in sequence to the hierarchical data resolutions 480, 240, 120 and 60 in fig. 7. As can be seen from the figure, under the low resolution, the layering data completely reserves the whole structure of the original data; at high resolution, the hierarchical data may also present rich detailed information. And the user adjusts the data resolution level according to the current interaction real-time performance and the visualization requirement so as to obtain a satisfactory visualization effect.
By adopting the scheme, the following technical effects are realized:
(1) according to the method and the device, the data organization and the layering compression are carried out on the original data through the data organization compression storage module in the system, so that the network bandwidth occupation can be greatly reduced, and the service concurrency capability is improved.
(2) According to the method and the system, the original data are verified and updated through the data verification and updating module in the system, the irregular change of the content of the original data is adapted, and the daily operation and maintenance pressure of the server can be effectively reduced.
(3) The application provides asymptotic remote visual service for the pre-organized data through the asymptotic data visual interaction module in the system, so that the real-time interaction of the client can be obviously improved, and the user experience is optimized.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present application.
Example two
In this embodiment, a data visualization device is further provided, and the data visualization device is used to implement the foregoing embodiments and preferred embodiments, which have already been described and will not be described again. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
According to another embodiment of the present application, there is provided a data visualization apparatus including:
the acquisition module is used for acquiring original volume data to be processed;
the compression module is used for compressing the original volume data in a layering compression mode to form compressed data;
and the transmission module is used for transmitting the compressed data to client equipment so as to enable the client equipment to visually display the compressed data.
By adopting the scheme, the problem that the adaptability of a remote visualization technology to different scenes in the related technology is poor is solved, the original volume data to be processed is compressed in a layering manner and then is transmitted to the client device, the data volume of the visualization data is greatly reduced, the data of different layers adapt to different display scenes, the real-time performance of interaction between two parties is ensured, and the display effect is improved.
There is also provided, in accordance with another embodiment of the present application, apparatus for data visualization, including:
the receiving module is used for receiving compressed data transmitted by the server, wherein the compressed data is formed by compressing original volume data in a layering manner;
and the display module is used for loading the compressed data packet by packet according to the hierarchy and visually displaying the compressed data.
By adopting the scheme, the layered compressed data is loaded packet by packet, and the compressed data of different layers is loaded according to different display requirements so as to meet the current transmission scene and the current display scene, the data of different layers is suitable for different display scenes and different transmission scenes, the real-time performance of interaction between the two parties is ensured, and the display effect is improved. The problem that the remote visualization technology in the related technology is poor in adaptability to different scenes is solved.
It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.
EXAMPLE III
There is also provided, in accordance with an embodiment of the present application, a data visualization system, including:
the server is used for acquiring original volume data to be processed and compressing the original volume data in a layering compression mode to form compressed data;
the server is also used for transmitting the compressed data to the client device;
and the client equipment is used for receiving the compressed data, loading the compressed data packet by packet according to the layers and visually displaying the compressed data.
Example four
Embodiments of the present application also provide a storage medium. Alternatively, in the present embodiment, the storage medium may be configured to store program codes for performing the following steps:
s1, acquiring original volume data to be processed;
s2, compressing the original volume data by adopting a layering compression mode to form compressed data;
s3, transmitting the compressed data to a client device so that the client device can visually display the compressed data.
Optionally, in this embodiment, the storage medium may include, but is not limited to: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Embodiments of the present application further provide an electronic device comprising a memory having a computer program stored therein and a processor configured to execute the computer program to perform the steps of any of the above method embodiments.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:
s1, acquiring original volume data to be processed;
s2, compressing the original volume data by adopting a layering compression mode to form compressed data;
s3, transmitting the compressed data to a client device so that the client device can visually display the compressed data.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and this embodiment is not described herein again.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and this embodiment is not described herein again.
It will be apparent to those skilled in the art that the modules or steps of the present application described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present application is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (11)
1. A method of data visualization, comprising:
acquiring original volume data to be processed;
sampling the original volume data according to different sampling step lengths to form sampling data corresponding to different resolutions;
sorting according to the resolution, and organizing the sampling data to form hierarchical data;
performing block compression on the hierarchical data by adopting a block-based compression mode, and establishing compressed data which can be randomly indexed according to blocks;
transmitting the compressed data to a client device so that the client device can visually display the compressed data;
periodically detecting whether the original volume data has data change;
when the original volume data is changed, performing hierarchical compression on the changed original volume data, and updating the compressed data;
and verifying and comparing the original volume data by adopting a Hash verification algorithm, and when the Hash verification code of the block data is changed when the original volume data is compared with the original volume data, performing hierarchical compression on the block data again.
2. The method according to claim 1, wherein before sampling the original volume data according to different sampling step sizes and forming sampling data corresponding to different resolutions, a value of a sampling step size I is determined by:
wherein the content of the first and second substances,
is a non-negative integer: (
, 
, 
) For the resolution of the original volume data,
and
is a preset value; when there is no parameter t satisfying the condition, the parameter is set
。
3. The method of claim 1, wherein after organizing the sampled data into hierarchical data in a resolution size order, the method further comprises:
and calculating the hash check code of each block of data by adopting a hash check algorithm, and storing the hash check code.
4. A method of data visualization, comprising:
receiving compressed data transmitted by a server, wherein the compressed data is formed by compressing original volume data in a layering manner;
loading the compressed data packet by packet according to the hierarchy, and visually displaying the compressed data;
the server is used for periodically detecting whether the original volume data has data change; when the original volume data is changed, performing hierarchical compression on the changed original volume data, and updating the compressed data;
wherein the server is further configured to implement the hierarchical compression of the original volume data into the compressed data by: sampling the original volume data according to different sampling step lengths to form sampling data corresponding to different resolutions; sorting according to the resolution, and organizing the sampling data to form hierarchical data; performing block compression on the hierarchical data by adopting a block-based compression mode, and establishing compressed data which can be randomly indexed according to blocks;
the server is further configured to perform verification comparison on the original volume data by using a hash verification algorithm, and perform hierarchical compression on the block data again when the hash verification code of the block data changes when the original volume data is compared with the original volume data.
5. The method of claim 4,
receiving compressed data transmitted by a server, comprising: requesting the server to obtain a hierarchical compressed data list; sorting the data packets according to the parameter information of the data packets in the hierarchical compressed data list, and downloading the data packets according to the sorting result;
loading the compressed data packet by packet according to the hierarchy, and visually displaying the compressed data, wherein the method comprises the following steps: and decompressing the highest-resolution compressed data in the currently downloaded data and generating a visual result.
6. The method of claim 4, wherein after the compressed data is loaded packet by packet in a hierarchy and visually displayed, the method comprises at least one of:
taking compressed data displayed in a current visualization mode as first compressed data, downloading second compressed data from the server when detecting that second compressed data with higher resolution than the first compressed data exists in the server and a current visualization result meets the minimum requirement of real-time interaction, and generating a visualization result;
receiving an input signal, determining a visualization requirement according to the input signal, and downloading compressed data corresponding to the resolution ratio meeting the visualization requirement from the server.
7. A data visualization device, comprising:
the acquisition module is used for acquiring original volume data to be processed;
the compression module is used for compressing the original volume data in a layering compression mode to form compressed data;
the transmission module is used for transmitting the compressed data to client equipment so as to enable the client equipment to visually display the compressed data;
the device is also used for periodically detecting whether the original volume data has data change; when the original volume data is changed, performing hierarchical compression on the changed original volume data, and updating the compressed data;
the compression module is further configured to sample the original volume data according to different sampling step lengths to form sampling data corresponding to different resolutions; sorting according to the resolution, and organizing the sampling data to form hierarchical data; performing block compression on the hierarchical data by adopting a block-based compression mode, and establishing compressed data which can be randomly indexed according to blocks;
the device is also used for verifying and comparing the original volume data by adopting a Hash verification algorithm, and when the Hash verification code of the block data is changed when the original volume data is compared with the original volume data, the block data is compressed hierarchically again.
8. A data visualization device, comprising:
the receiving module is used for receiving compressed data transmitted by the server, wherein the compressed data is formed by compressing original volume data in a layering manner;
the display module is used for loading the compressed data packet by packet according to the hierarchy and visually displaying the compressed data;
the server is used for periodically detecting whether the original volume data has data change; when the original volume data is changed, performing hierarchical compression on the changed original volume data, and updating the compressed data;
the server is further used for sampling the original volume data according to different sampling step lengths to form sampling data corresponding to different resolutions; sorting according to the resolution, and organizing the sampling data to form hierarchical data; performing block compression on the hierarchical data by adopting a block-based compression mode, and establishing compressed data which can be randomly indexed according to blocks;
the server is further configured to perform verification comparison on the original volume data by using a hash verification algorithm, and perform hierarchical compression on the block data again when the hash verification code of the block data changes when the original volume data is compared with the original volume data.
9. A data visualization system, comprising:
the server is used for acquiring original volume data to be processed and compressing the original volume data in a layering compression mode to form compressed data;
the server is also used for transmitting the compressed data to the client device;
the client device is used for receiving the compressed data, loading the compressed data packet by packet according to the layers and visually displaying the compressed data;
the server is also used for periodically detecting whether the original volume data has data change; when the original volume data is changed, performing hierarchical compression on the changed original volume data, and updating the compressed data;
the server is further used for sampling the original volume data according to different sampling step lengths to form sampling data corresponding to different resolutions; sorting according to the resolution, and organizing the sampling data to form hierarchical data; performing block compression on the hierarchical data by adopting a block-based compression mode, and establishing compressed data which can be randomly indexed according to blocks;
the server is further configured to perform verification comparison on the original volume data by using a hash verification algorithm, and perform hierarchical compression on the block data again when the hash verification code of the block data changes when the original volume data is compared with the original volume data.
10. A storage medium, in which a computer program is stored, wherein the computer program is arranged to perform the method of any of claims 1 to 6 when executed.
11. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and wherein the processor is arranged to execute the computer program to perform the method of any of claims 1 to 6.
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