CN109936752A - A kind of image layered processing method and processing device - Google Patents
A kind of image layered processing method and processing device Download PDFInfo
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Abstract
The embodiment of the present invention provides a kind of image layered processing method and processing device.The described method includes: calculating the resource metric of each service node according to the resource utilization parameters of multiple service nodes；Destination service node is determined according to the resource metric, and initial resolution multiplying power and initial pictures level quantity are determined according to the resource metric of the destination service node；According to the image parameter of the initial resolution multiplying power, the initial pictures level quantity and image to be processed, layered shaping is carried out to the image to be processed.Described device is for executing the above method.Method and device provided in an embodiment of the present invention improves the image-capable of cloud computing platform.
Description
Technical field
The present embodiments relate to field of communication technology more particularly to a kind of image layered processing method and processing devices.
Background technique
Cloud computing was achieving rapid development in recent years, using cloud computing platform carry various extensive services oneself through at
For the trend of the times of the information industry development, and with the progress of multimedia technology, also emerged on internet a large amount of new
Type multimedia service is simultaneously popularized in users, under such two overall background, how to improve the image of cloud computing platform
Processing capacity also has been to be concerned by more and more people as the key problem for using cloud computing platform bearing multimedia business.
Cloud computing not only includes passing to the application of user on internet with service form, is also included in data center
It is middle that the hardware and software of these services is provided, and include that the data centers of these soft and hardwares is then referred to as " cloud ", in cloud, institute
Resource (including framework, platform and software) be all to be passed as service.At present the cloud computing platform of mainstream be all for
General cloud calculation service and establish, as shown in Figure 1, including former site server, Core server group, Edge Server group three
Layer architecture provides service；Wherein, former site server provides information source, and Core server group mainly provides the processing of information, place
Reason, safety, distribution policy work, the Edge Server group such as formulation specifically execute the distribution of data, what their resource was dominant
It is CPU ability and storage capacity (such as central server and Edge Server), but for occupying carrier data flow at present
87% video class multimedia is but difficult to meet.In the prior art, the way compromised at present is right on the mobile terminal of isomery
Multimedia image data carries out dimension-reduction treatment to adapt to the mobile terminal of user, and such way is only realized reluctantly in movement
Multimedia image data is shown in terminal, still, since the ability of mobile terminal processing multimedia image data is wretched insufficiency
It will affect multi-media image and effect be presented, and in mobile terminal processing figure multimedia as data can occupy mobile terminal significantly
Resource consumes more electricity simultaneously.
It is therefore proposed that the image-capable that a kind of method improves cloud computing platform is urgently to be resolved important of current industry
Project.
Summary of the invention
For the defects in the prior art, the embodiment of the present invention provides a kind of image layered processing method and processing device.
On the one hand, the embodiment of the present invention provides a kind of image layered processing method, comprising:
The resource metric of each service node is calculated according to the resource utilization parameters of multiple service nodes；
Destination service node is determined according to the resource metric, and according to the resource metric of the destination service node
Determine initial resolution multiplying power and initial pictures level quantity；
According to the image parameter of the initial resolution multiplying power, the initial pictures level quantity and image to be processed,
Layered shaping is carried out to the image to be processed.
On the other hand, the embodiment of the present invention provides a kind of image layered processing unit, comprising:
Computing unit, for calculating the resource degree of each service node according to the resource utilization parameters of multiple service nodes
Magnitude；
Processing unit, for determining destination service node according to the resource metric, and according to the destination service section
The resource metric of point determines initial resolution multiplying power and initial pictures level quantity；
Delaminating units, for according to the initial resolution multiplying power, the initial pictures level quantity and figure to be processed
The image parameter of picture carries out layered shaping to the image to be processed.
Another aspect, the embodiment of the present invention provide a kind of electronic equipment, including processor, memory and bus, in which:
The processor, the memory complete mutual communication by bus；
The processor can call the computer program in memory, the step of to execute the above method.
In another aspect, the embodiment of the present invention provides a kind of computer readable storage medium, it is stored thereon with computer program,
The step of above method is realized when the program is executed by processor.
Image layered processing method and processing device provided in an embodiment of the present invention passes through the resource benefit according to multiple service nodes
Destination service node is determined with the resource measurement that parameter calculates each service node obtained, and according to by the destination service
The resource metric of node determines the image parameter of initial resolution multiplying power, initial pictures level quantity and image to be processed,
Layered shaping is carried out to image to be processed, improves cloud computing platform image-capable.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is this hair
Bright some embodiments for those of ordinary skill in the art without creative efforts, can be with root
Other attached drawings are obtained according to these attached drawings.
Fig. 1 is cloud computing platform structural schematic diagram；
Fig. 2 is the flow diagram of image layered processing method provided in an embodiment of the present invention；
Fig. 3 is the structural schematic diagram of image layered processing unit provided in an embodiment of the present invention；
Fig. 4 is electronic equipment entity apparatus structural schematic diagram provided in an embodiment of the present invention.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical solution in the embodiment of the present invention is explicitly described, it is clear that described embodiment is the present invention
A part of the embodiment, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not having
Every other embodiment obtained under the premise of creative work is made, shall fall within the protection scope of the present invention.
Fig. 2 is the flow diagram of image layered processing method provided in an embodiment of the present invention, as shown in Figure 1, this implementation
Example provides a kind of image layered processing method, comprising:
S1, the resource metric that each service node is calculated according to the resource utilization parameters of multiple service nodes；
Specifically, image layered processing unit obtains the resource utilization parameters of multiple service nodes of cloud computing platform, root
The resource metric of each service node is calculated according to the resource utilization parameters of the multiple service node.Wherein, the resource
Metric is used to indicate the size of the remaining available resource of each service node, and the service node can be the cloud computing
Any one in platform can provide the node of service for user, can be a server, be also possible to a virtual machine, specifically
It can be configured and adjust according to the actual situation, be not specifically limited herein；The resource utilization parameters may include memory
Resource parameters, cpu resource parameter, GPU resource parameter, external memory resource parameters and network state parameters can also include other moneys
Source utilizes parameter, specifically can be configured and adjust according to the actual situation, be not specifically limited herein.
S2, destination service node is determined according to the resource metric, and according to the resource degree of the destination service node
Magnitude determines initial resolution multiplying power and initial pictures level quantity；
Specifically, the resource metric is greater than the service node of preset threshold as both candidate nodes by described device, from
One is chosen in the both candidate nodes and is used as the destination service node, and according to the resource metric of the destination service node
Determine initial resolution multiplying power and initial pictures level quantity.Wherein, initial resolution multiplying power be two adjacent images level in,
The quotient of resolution ratio corresponding compared with hi-vision level resolution ratio corresponding with lower image level；The initial resolution multiplying power and institute
The resource metric for stating destination service node is negatively correlated, the resource of the initial pictures level quantity and the destination service node
Metric is positively correlated, that is to say, that the resource metric of the destination service node is higher, then the available resources of the service node
More, then the service node has the ability for initial pictures level quantity to be arranged bigger, while initial pictures level quantity is bigger
The computing resource then needed is more, to need to reduce the resolution ratio multiplying power between two adjacent images level.
S3, joined according to the image of the initial resolution multiplying power, the initial pictures level quantity and image to be processed
Number carries out layered shaping to the image to be processed.
Specifically, described device is according to the initial resolution multiplying power, the initial pictures level quantity and to be processed
The image parameter of image carries out layered shaping to the image to be processed, so that, in mobile terminal and the cloud computing platform
Interaction in, according to the self-characteristic of mobile terminal, the image for using some level can be negotiated with the cloud computing, so as to
The image for being suitble to the mobile terminal can directly be presented in the terminal.Wherein, the image parameter of the image to be processed
It may include pixel width, pixel height and color bits depth, can also include other image parameters, it specifically can be according to practical feelings
Condition is configured and adjusts, and is not specifically limited herein.
Image layered processing method provided in an embodiment of the present invention, passes through the resource utilization parameters according to multiple service nodes
The resource measurement for calculating each service node obtained determines destination service node, and according to by the destination service node
Resource metric determines the image parameter of initial resolution multiplying power, initial pictures level quantity and image to be processed, treats place
It manages image and carries out layered shaping, improve cloud computing platform image-capable.
On the basis of the above embodiments, further, described to be calculated according to the resource utilization parameters of multiple service nodes
The resource metric of each service node, comprising:
According to formula:Calculate the resource metric of each service node；Wherein, RiIt is i-th
The resource metric of a service node, αjFor the corresponding resource measurement weighted value of j-th of resource utilization parameters,For jth
The corresponding resource measurement function of a resource utilization parameters,For j-th of resource utilization parameters value of i-th of service node, n is money
Source utilizes the number of parameter.
It is understood that the resource utilization parameters may include memory resource parameters, cpu resource parameter, GPU resource
Parameter, external memory resource parameters and network state parameters；Wherein, the memory resource parameters include total memory, caching and it is current oneself
The memory used；Cpu resource parameter includes CPU parameter and the current CPU that oneself uses；GPU resource parameter includes GPU parameter and works as
The preceding GPU that oneself uses；External memory resource parameters include total external memory and the current external memory size that oneself uses；The network state parameters
Including network bandwidth and with the network delay of central node；Certainly, above-mentioned each resource utilization parameters can also include it
His parameter information, specifically can be configured and adjust according to the actual situation, be not specifically limited herein.Should be bright, respectively
The corresponding resource measurement weighted value of the resource utilization parameters can be according to resource utilization parameters each in practical application for resource
The influence size of metric is configured and adjusts, and is not specifically limited herein.
It is on the basis of the above embodiments, further, described that destination service node is determined according to the resource metric,
Include:
The resource metric is greater than the service node of preset threshold as both candidate nodes, and from the both candidate nodes
It chooses one and is used as the destination service node.
Specifically, described device using the resource metric be greater than preset threshold service node as both candidate nodes, and
One is randomly selected from the both candidate nodes is used as the destination service node, it can also be by resource degree in the both candidate nodes
The maximum service node of magnitude specifically can be configured and adjust according to the actual situation as the destination service node, this
Place is not specifically limited；The preset threshold can be configured and adjust according to the actual situation, be not specifically limited herein.
On the basis of the above embodiments, further, the resource metric according to the destination service node is true
Determine initial resolution multiplying power and initial pictures level quantity, comprising:
According to formula:Calculate the initial resolution multiplying power；Wherein, PtoFor initial resolution times
Rate, R*For the resource metric of the destination service node, p1And q1For the first parameter preset, p1≥1；
According to formula:Calculate the initial pictures level quantity；Wherein, QtyLFor initial pictures
Level quantity, R*For the resource metric of the destination service node, p2And q2For the second parameter preset, 0 < p2< 1.
It is understood that first parameter preset can according to the resource metrics of multiple sample service nodes and its
Corresponding initial resolution multiplying power is obtained by machine learning model training；Second parameter preset can also be according to multiple
The resource metric of sample service node and its corresponding initial pictures level quantity are obtained by machine learning model training；
Certainly, first parameter preset and second parameter preset can also obtain by other means, specifically can be according to reality
Border situation is configured and adjusts, and is not specifically limited herein.
On the basis of the above embodiments, further, described according to the initial resolution multiplying power, the initial pictures
The image parameter of level quantity and image to be processed carries out layered shaping to the image to be processed, comprising:
S31, it is calculated between kth tomographic image and the resolution ratio of the image to be processed according to the initial resolution multiplying power
Resolution ratio multiplying power；k≥1；
S32, according to resolution ratio multiplying power between kth tomographic image and the resolution ratio of the image to be processed and described wait locate
The image parameter of image is managed, the data volume of kth tomographic image is calculated；
If S33, judgement know that the data volume of the kth tomographic image is greater than pre-set image block granularity, then follow the steps
S34, it is no to then follow the steps S35
S34, judge whether k is less than the initial pictures level quantity, if so, k=k+1 is enabled, return step S31；It is no
Then, step S36 is executed；
S35, using k as target image level quantity；Then step S37 is executed；
S36, using the initial pictures level quantity as target image level quantity；Then step S37 is executed；
S37, the corresponding each level of the target image level quantity is calculated according to the image parameter of the image to be processed
The image parameter of image generates each level image according to described image parameter.
Specifically, described device is by the 0th tomographic image of conduct of the image to be processed, and according to the initial resolution times
Rate calculates the resolution ratio multiplying power between kth tomographic image and the resolution ratio of the image to be processed, then according to kth tomographic image and institute
The image parameter of the resolution ratio multiplying power and the image to be processed between the resolution ratio of image to be processed is stated, kth layer figure is calculated
The data volume of picture.If described device judgement knows that the data volume of the kth tomographic image is not more than the pre-set image block granularity,
Then directly joined using k as the corresponding target image level quantity of the image to be processed according to the image of the image to be processed
Number calculates separately the 1st to the corresponding image parameter of k tomographic image (pixel width, pixel height, resolution ratio), is joined according to described image
Number generates the corresponding k tomographic image of the image to be processed；Otherwise, described device continues to judge whether k is less than the initial pictures
Level quantity calculates point between+1 tomographic image of kth and the resolution ratio of the image to be processed if so, enabling k=k+1 again
The data volume of resolution multiplying power ,+1 tomographic image of kth, judge again+1 tomographic image of kth data volume and the pre-set image block grain
Spend size relation；If described device judgement knows k not less than the initial pictures level quantity, by the initial pictures level
Quantity is distinguished as the corresponding target image level quantity of the image to be processed according to the image parameter of the image to be processed
Calculate the 1st to QtyLThe corresponding image parameter of tomographic image (pixel width, pixel height, resolution ratio), it is raw according to described image parameter
At the corresponding Q of the image to be processedtyLTomographic image, QtyLFor the initial pictures level quantity.It should be noted that the dress
The image parameter of the corresponding each level image of the target image level quantity according to the image parameter of the image to be processed is set,
It specifically includes according to formula: Wk=W0×Pto k, calculate the pixel width of each level image；Wherein, WkFor the pixel of kth tomographic image
Width, W0For the pixel width of the image to be processed, PtoFor the initial resolution multiplying power；According to formula: Hk=H0×Pto k
Calculate the pixel width of each level image；Wherein, HkFor the pixel height of kth tomographic image, H0For the pixel of the image to be processed
Highly, PtoFor the initial resolution multiplying power；According to formula: Rk=R0×Pto kCalculate the pixel width of each level image；Its
In, RkFor the pixel width of kth tomographic image, R0For the pixel width of the image to be processed, PtoFor the initial resolution times
Rate.
On the basis of the above embodiments, further, described that kth tomographic image is calculated according to the initial resolution multiplying power
Resolution ratio multiplying power between the resolution ratio of the image to be processed, comprising:
According to formula:Calculate the resolution ratio multiplying power between kth tomographic image and the resolution ratio of the image to be processed；
Wherein, PkFor the resolution ratio multiplying power between kth tomographic image and the resolution ratio of the image to be processed, PtoFor the initial resolution
Multiplying power.
On the basis of the above embodiments, further, the image parameter of the image to be processed include: pixel width,
Pixel height and color bits depth；Correspondingly, the resolution according between kth tomographic image and the resolution ratio of the image to be processed
The image parameter of rate multiplying power and the image to be processed calculates the data volume of kth tomographic image, comprising:
According to formula: Qk=W0×H0×Pk 2×Dc, calculate the data volume of kth tomographic image；Wherein, QkFor kth tomographic image
Data volume, W0For the pixel width of the image to be processed, H0For the pixel height of the image to be processed, PkFor kth tomographic image
Resolution ratio multiplying power between the resolution ratio of the image to be processed, DcFor the color bits depth of the image to be processed.
Image layered processing method provided in an embodiment of the present invention, passes through the resource utilization parameters according to multiple service nodes
The resource measurement for calculating each service node obtained determines destination service node, and according to by the destination service node
Resource metric determines the image parameter of initial resolution multiplying power, initial pictures level quantity and image to be processed, treats place
It manages image and carries out layered shaping, improve cloud computing platform image-capable.
Fig. 3 is the structural schematic diagram of image layered processing unit provided in an embodiment of the present invention, as shown in figure 3, of the invention
Embodiment provides a kind of image layered processing unit, comprising: computing unit 201, processing unit 202 and delaminating units 203,
In:
Computing unit 201 is used to calculate the resource of each service node according to the resource utilization parameters of multiple service nodes
Metric；Processing unit 202 is used to according to the resource metric determine destination service node, and according to the destination service section
The resource metric of point determines initial resolution multiplying power and initial pictures level quantity；Delaminating units 203 are used for according to described first
The image parameter of beginning resolution ratio multiplying power, the initial pictures level quantity and image to be processed, to the image to be processed into
Row layered shaping.
Image layered processing unit provided in an embodiment of the present invention, passes through the resource utilization parameters according to multiple service nodes
The resource measurement for calculating each service node obtained determines destination service node, and according to by the destination service node
Resource metric determines the image parameter of initial resolution multiplying power, initial pictures level quantity and image to be processed, treats place
It manages image and carries out layered shaping, improve cloud computing platform image-capable.
Optionally, computing unit 201 is specifically used for according to formula:Calculate each service node
Resource metric；Wherein, RiFor the resource metric of i-th of service node, αjFor the corresponding money of j-th of resource utilization parameters
Source metric weights value,For the corresponding resource measurement function of j-th of resource utilization parameters,For i-th service node
J-th of resource utilization parameters value, n are the number of resource utilization parameters.
Optionally, processing unit 202 be specifically used for using the resource metric be greater than preset threshold service node as
Both candidate nodes, and choose one from the both candidate nodes and be used as the destination service node.
Optionally, processing unit 202 is specifically used for according to formula:Calculate the initial resolution
Multiplying power；Wherein, PtoFor initial resolution multiplying power, R*For the resource metric of the destination service node, p1And q1It is default for first
Parameter, p1≥1；According to formula:Calculate the initial pictures level quantity；Wherein, QtyLIt is initial
Image layer number of stages, R*For the resource metric of the destination service node, p2And q2For the second parameter preset, 0 < p2< 1.
Optionally, delaminating units 203 are specifically used for executing following steps:
S31, it is calculated between kth tomographic image and the resolution ratio of the image to be processed according to the initial resolution multiplying power
Resolution ratio multiplying power；k≥1；
S32, according to resolution ratio multiplying power between kth tomographic image and the resolution ratio of the image to be processed and described wait locate
The image parameter of image is managed, the data volume of kth tomographic image is calculated；
If S33, judgement know that the data volume of the kth tomographic image is greater than pre-set image block granularity, then follow the steps
S34, it is no to then follow the steps S35；
S34, judge whether k is less than the initial pictures level quantity, if so, k=k+1 is enabled, return step S31；It is no
Then, step S36 is executed；
S35, using k as target image level quantity；Then step S37 is executed；
S36, using the initial pictures level quantity as target image level quantity；Then step S37 is executed；
S37, the corresponding each level image of the target image level quantity according to the image parameter of the image to be processed
Image parameter, each level image is generated according to described image parameter.
Optionally, delaminating units 203 are specifically used for according to formula: Pk=Pto k, calculate kth tomographic image with it is described to be processed
Resolution ratio multiplying power between the resolution ratio of image；Wherein, PkBetween kth tomographic image and the resolution ratio of the image to be processed
Resolution ratio multiplying power, PtoFor the initial resolution multiplying power.
Optionally, delaminating units 203 are specifically used for according to formula: Qk=W0×H0×Pk 2×Dc, calculate kth tomographic image
Data volume；Wherein, QkFor the data volume of kth tomographic image, W0For the pixel width of the image to be processed, H0It is described to be processed
The pixel height of image, PkFor the resolution ratio multiplying power between kth tomographic image and the resolution ratio of the image to be processed, DcIt is described
The color bits depth of image to be processed.
Image layered processing unit provided in an embodiment of the present invention, passes through the resource utilization parameters according to multiple service nodes
The resource measurement for calculating each service node obtained determines destination service node, and according to by the destination service node
Resource metric determines the image parameter of initial resolution multiplying power, initial pictures level quantity and image to be processed, treats place
It manages image and carries out layered shaping, improve cloud computing platform image-capable.
The embodiment of device provided by the invention specifically can be used for executing the process flow of above-mentioned each method embodiment,
Details are not described herein for function, is referred to the detailed description of above method embodiment.
Fig. 4 is electronic equipment entity apparatus structural schematic diagram provided in an embodiment of the present invention, as shown in figure 4, the electronics is set
Standby may include: processor (processor) 301, memory (memory) 302 and bus 303, wherein processor 301 is deposited
Reservoir 302 completes mutual communication by bus 303.Processor 301 can call the computer program in memory 302,
To execute method provided by above-mentioned each method embodiment, for example, according to the resource utilization parameters meter of multiple service nodes
Calculate the resource metric of each service node；Destination service node is determined according to the resource metric, and according to the mesh
The resource metric of mark service node determines initial resolution multiplying power and initial pictures level quantity；According to the initial resolution
The image parameter of multiplying power, the initial pictures level quantity and image to be processed carries out at layering the image to be processed
Reason.
The embodiment of the present invention discloses a kind of computer program product, and the computer program product is non-transient including being stored in
Computer program on computer readable storage medium, the computer program include program instruction, when described program instructs quilt
When computer executes, computer is able to carry out method provided by above-mentioned each method embodiment, for example, according to multiple services
The resource utilization parameters of node calculate the resource metric of each service node；Determine that target takes according to the resource metric
Business node, and initial resolution multiplying power and initial pictures number of levels are determined according to the resource metric of the destination service node
Amount；According to the image parameter of the initial resolution multiplying power, the initial pictures level quantity and image to be processed, to described
Image to be processed carries out layered shaping.
The embodiment of the present invention provides a kind of non-transient computer readable storage medium, the non-transient computer readable storage
Medium storing computer program, the computer program make the computer execute side provided by above-mentioned each method embodiment
Method, for example, the resource metric of each service node is calculated according to the resource utilization parameters of multiple service nodes；According to
The resource metric determines destination service node, and determines initial differentiate according to the resource metric of the destination service node
Rate multiplying power and initial pictures level quantity；According to the initial resolution multiplying power, the initial pictures level quantity and wait locate
The image parameter for managing image carries out layered shaping to the image to be processed.
In addition, the logical order in above-mentioned memory 302 can be realized by way of SFU software functional unit and conduct
Independent product when selling or using, can store in a computer readable storage medium.Based on this understanding, originally
Substantially the part of the part that contributes to existing technology or the technical solution can be in other words for the technical solution of invention
The form of software product embodies, which is stored in a storage medium, including some instructions to
So that a computer equipment (can be personal computer, server or the network equipment etc.) executes each implementation of the present invention
The all or part of the steps of example the method.And storage medium above-mentioned include: USB flash disk, mobile hard disk, read-only memory (ROM,
Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic or disk etc. it is various
It can store the medium of program code.
The apparatus embodiments described above are merely exemplary, wherein described, unit can as illustrated by the separation member
It is physically separated with being or may not be, component shown as a unit may or may not be physics list
Member, it can it is in one place, or may be distributed over multiple network units.It can be selected according to the actual needs
In some or all of the modules achieve the purpose of the solution of this embodiment.Those of ordinary skill in the art are not paying creativeness
Labour in the case where, it can understand and implement.
Through the above description of the embodiments, those skilled in the art can be understood that each embodiment can
It realizes by means of software and necessary general hardware platform, naturally it is also possible to pass through hardware.Based on this understanding, on
Stating technical solution, substantially the part that contributes to existing technology can be embodied in the form of software products in other words, should
Computer software product may be stored in a computer readable storage medium, such as ROM/RAM, magnetic disk, CD, including several fingers
It enables and using so that a computer equipment (can be personal computer, server or the network equipment etc.) executes each implementation
Method described in certain parts of example or embodiment.
Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although
Present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: it still may be used
To modify the technical solutions described in the foregoing embodiments or equivalent replacement of some of the technical features；
And these are modified or replaceed, technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution spirit and
Range.
Claims (10)
1. a kind of image layered processing method characterized by comprising
The resource metric of each service node is calculated according to the resource utilization parameters of multiple service nodes；
Destination service node is determined according to the resource metric, and is determined according to the resource metric of the destination service node
Initial resolution multiplying power and initial pictures level quantity；
According to the image parameter of the initial resolution multiplying power, the initial pictures level quantity and image to be processed, to institute
It states image to be processed and carries out layered shaping.
2. the method according to claim 1, wherein the resource utilization parameters meter according to multiple service nodes
Calculate the resource metric of each service node, comprising:
According to formula:Calculate the resource metric of each service node；Wherein, RiIt is serviced for i-th
The resource metric of node, αjFor the corresponding resource measurement weighted value of j-th of resource utilization parameters,For j-th of resource
Using the corresponding resource measurement function of parameter,For j-th of resource utilization parameters value of i-th of service node, n is the utilization of resources
The number of parameter.
3. the method according to claim 1, wherein described determine destination service section according to the resource metric
Point, comprising:
The service node that the resource metric is greater than preset threshold is chosen as both candidate nodes, and from the both candidate nodes
One is used as the destination service node.
4. the method according to claim 1, wherein the resource metric according to the destination service node
Determine initial resolution multiplying power and initial pictures level quantity, comprising:
According to formula:Calculate the initial resolution multiplying power；Wherein, PtoFor initial resolution multiplying power, R*
For the resource metric of the destination service node, p1And q1For the first parameter preset, p1≥1；
According to formula:Calculate the initial pictures level quantity；Wherein, QtyLFor initial pictures level
Quantity, R*For the resource metric of the destination service node, p2And q2For the second parameter preset, 0 < p2< 1.
5. the method according to claim 1, wherein it is described according to the initial resolution multiplying power, it is described initial
The image parameter of image layer number of stages and image to be processed carries out layered shaping to the image to be processed, comprising:
S31, the resolution between kth tomographic image and the resolution ratio of the image to be processed is calculated according to the initial resolution multiplying power
Rate multiplying power；k≥1；
S32, according between kth tomographic image and the resolution ratio of the image to be processed resolution ratio multiplying power and the figure to be processed
The image parameter of picture calculates the data volume of kth tomographic image；
If S33, judgement know that the data volume of the kth tomographic image is greater than pre-set image block granularity, S34 is thened follow the steps, it is no
Then follow the steps S35；
S34, judge whether k is less than the initial pictures level quantity, if so, k=k+1 is enabled, return step S31；Otherwise, it holds
Row step S36；
S35, using k as target image level quantity；Then step S37 is executed；
S36, using the initial pictures level quantity as target image level quantity；Then step S37 is executed；
S37, the corresponding each level image of the target image level quantity is calculated according to the image parameter of the image to be processed
Image parameter, each level image is generated according to described image parameter.
6. according to the method described in claim 5, it is characterized in that, described calculate kth layer according to the initial resolution multiplying power
Resolution ratio multiplying power between image and the resolution ratio of the image to be processed, comprising:
According to formula: Pk=Pto k, calculate the resolution ratio multiplying power between kth tomographic image and the resolution ratio of the image to be processed；Its
In, PkFor the resolution ratio multiplying power between kth tomographic image and the resolution ratio of the image to be processed, PtoFor the initial resolution times
Rate.
7. according to the method described in claim 5, it is characterized in that, the image parameter of the image to be processed includes: that pixel is wide
Degree, pixel height and color bits depth；Correspondingly, described according between kth tomographic image and the resolution ratio of the image to be processed
The image parameter of resolution ratio multiplying power and the image to be processed calculates the data volume of kth tomographic image, comprising:
According to formula: Qk=W0×H0×Pk 2×Dc, calculate the data volume of kth tomographic image；Wherein, QkFor the data of kth tomographic image
Amount, W0For the pixel width of the image to be processed, H0For the pixel height of the image to be processed, PkFor kth tomographic image and institute
State the resolution ratio multiplying power between the resolution ratio of image to be processed, DcFor the color bits depth of the image to be processed.
8. a kind of image layered processing unit characterized by comprising
Computing unit, for calculating the resource measurement of each service node according to the resource utilization parameters of multiple service nodes
Value；
Processing unit, for determining destination service node according to the resource metric, and according to the destination service node
Resource metric determines initial resolution multiplying power and initial pictures level quantity；
Delaminating units, for according to the initial resolution multiplying power, the initial pictures level quantity and image to be processed
Image parameter carries out layered shaping to the image to be processed.
9. a kind of electronic equipment, which is characterized in that including processor, memory and bus, in which:
The processor, the memory complete mutual communication by bus；
The processor can call the computer program in memory, to execute as described in claim 1-7 any one
The step of method.
10. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is by processor
It realizes when execution such as the step of claim 1-7 any one the method.
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