CN105141930A - Monitoring method and system for optimizing desktop monitoring image quality - Google Patents
Monitoring method and system for optimizing desktop monitoring image quality Download PDFInfo
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Abstract
The invention discloses a monitoring method and system for optimizing desktop monitoring image quality. The monitoring method and system for optimizing desktop monitoring image quality are used for a desktop monitoring system. The monitoring system is used for optimizing quality of images outputted by a monitoring end. The method comprises the steps that step S100, the number of segmentation is calculated by a monitored end based on the preset segmentation coefficient and CPU utilization rate, and monitoring image data to be segmented are segmented according to the number of segmentation and image segments are obtained; and step S200, binary comparison is performed on the image segments and one previous image respectively by the monitored end, and the image segments of which the comparison results indicate difference are transmitted to the monitoring end. The invention also provides the monitoring system for optimizing desktop monitoring image quality. Performance of a network and the monitored equipment is coordinated so that influence of desktop monitoring on image quality can be reduced to the largest extent, quality of the images outputted by the monitoring end can be enhanced and equipment cost can be reduced.
Description
Technical field
The invention belongs to Desktop Monitoring field, particularly a kind of method for supervising and system optimizing Desktop Monitoring picture quality.
Background technology
In prior art, carrying out monitoring in real time to monitored PC desktop has two bottlenecks, needs high CPU disposal ability on the one hand, needs the great network bandwidth on the other hand.
In PC Desktop Monitoring process, its principle on monitored PC desktop, loads a PC desktop record software, then the data recorded carry out playback by Internet Transmission to monitored PC end, a problem is there is in this process, be exactly when the PC desktop disturbance degree needing to record is higher, the data so transmitted are larger, and its network bandwidth needed is larger, otherwise just there will be the problem that video card pauses.
Have two kinds of solutions at present, scheme 1 is the computing capability by improving hardware PC, strengthens the degree of compression of transfer of data.Scheme 2 is by improving the network bandwidth, improves the transmission quantity of network data.
There is following shortcoming in prior art: improves the CPU disposal ability of hardware PC and improve the network bandwidth, adding equipment cost, and can not fundamentally solve above-mentioned Problems existing.
Summary of the invention
The object of this invention is to provide a kind of method for supervising and the system of optimizing desktop picture quality monitoring, the present invention is by the performance of coordination network and monitored device, maximized the impact of Desktop Monitoring on picture quality to be reduced, to promote the picture quality that monitoring client exports, reduce equipment cost.
For achieving the above object, one aspect of the present invention provides a kind of method for supervising optimizing Desktop Monitoring picture quality, for Desktop Monitoring system, the picture quality that described supervisory control system exports for optimizing monitoring client, it comprises monitored end and monitoring client, described method comprises: step S100, monitored end group in the division coefficient preset and CPU usage, computed segmentation quantity, and according to described dividing number, monitoring image data to be split are split, and obtains image segments; Step S200, image segments is carried out binary system with last image and is compared by monitored end respectively, is that not identical image segments is sent to described monitoring client by comparative result.
Wherein, described step S100 comprises: step S110, and monitored end obtains monitoring image data to be split; Step S120, monitored end group in preset division coefficient q and CPU usage n, computed segmentation quantity m, wherein q >=0,0≤n≤1, m >=0; Described monitoring image Data Segmentation to be split, according to described dividing number m, is m image segments by step S130.
Wherein, according to following formula computed segmentation quantity m:m=q/n; Wherein q is division coefficient, and n is CPU usage, and m is dividing number, wherein q >=0,0≤n≤1, m >=0.
Preferably, in step s 200, described is before not identical image segments is sent to the step of monitoring by comparative result, also comprise: step S300, monitoring client is based on the message response time k between the monitored end detected and monitoring client and default picture quality coefficient z, computed image quality p, and described picture quality p is sent to monitored end, described comparative result, according to picture quality p, is be sent to monitoring client again after the picture quality of not identical image segments transforms by monitored end.
Wherein, described step S300 comprises: step S310, detects the message response time k between monitored end and monitoring client; Step S320, monitoring client is based on described message response time k and default picture quality coefficient z, computed image quality p.
Wherein, according to following formula computed image quality p:p=z*k; Wherein, z is picture quality coefficient, and k is the message response time between monitored end and monitoring client, and p is the picture quality calculated.
According to a further aspect in the invention, provide a kind of supervisory control system optimizing Desktop Monitoring picture quality, for optimizing the picture quality that monitoring client exports, described system comprises: by monitored end and the monitoring client of cable network or wireless network connectivity; Monitored end, for based on the division coefficient preset and CPU usage, computed segmentation quantity, and according to described dividing number, monitoring image data to be split are split, and obtains image segments; And described monitored end, comparing for respectively image segments being carried out binary system with last image, is that not identical image segments is sent to described monitoring client by comparative result.
Wherein, described monitored end, after getting monitoring image data to be split, performs following operation: described monitored end group in the division coefficient q preset and CPU usage n, computed segmentation quantity m, wherein q >=0,0≤n≤1, m >=0; And according to described dividing number m, be m image segments by described monitoring image Data Segmentation to be split.
Wherein, described monitored end is according to following formula computed segmentation quantity m:m=q/n; Wherein, q is division coefficient, and n is CPU usage, and m is dividing number, wherein q >=0,0≤n≤1, m >=0.
Preferably, be before not identical image segments is sent to monitoring client at described monitored end by described comparative result, perform following operation: described monitoring client is based on the message response time k between the monitored end detected and monitoring client and default picture quality coefficient z, computed image quality p, and described picture quality p is sent to monitored end, described comparative result, according to picture quality p, is be sent to monitoring client again after the picture quality of not identical image segments transforms by monitored end.
Wherein, described monitoring client, for detecting the message response time k between monitored end and monitoring client, and for based on described message response time k and preset picture quality coefficient z, computed image quality p.
Wherein, described monitoring client is according to following formula computed image quality p:p=z*k; Z is picture quality coefficient, and k is the message response time between monitored end and monitoring client, and p is the picture quality calculated.
As mentioned above, the impact of Desktop Monitoring on picture quality, by the performance of coordination network and monitored device, maximizedly to reduce by the present invention, to promote the picture quality that monitoring client exports, reduces equipment cost.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of the method for supervising of optimization Desktop Monitoring picture quality of the present invention;
Fig. 2 shows the method flow diagram splitting data to be monitored based on CPU usage of the present invention;
Fig. 3 shows the method flow diagram of rate calculations picture quality Network Based of the present invention;
Fig. 4 is the structural representation of the supervisory control system of optimization Desktop Monitoring picture quality of the present invention.
Embodiment
For making the object, technical solutions and advantages of the present invention clearly understand, below in conjunction with embodiment also with reference to accompanying drawing, the present invention is described in more detail.Should be appreciated that, these describe just exemplary, and do not really want to limit the scope of the invention.In addition, in the following description, the description to known features and technology is eliminated, to avoid unnecessarily obscuring concept of the present invention.
Fig. 1 is the schematic flow sheet of the method for supervising of optimization Desktop Monitoring picture quality of the present invention.
As shown in Figure 1, the method for supervising of optimization Desktop Monitoring picture quality of the present invention, for Desktop Monitoring system, the picture quality that described supervisory control system exports for optimizing monitoring client, it comprises monitored end and monitoring client, and described method comprises:
Step S100, monitored end group in the division coefficient preset and CPU usage, computed segmentation quantity, and according to described dividing number, monitoring image data to be split are split, and obtains image segments.
In this step, first monitored end obtains monitoring image data to be split, splits the monitoring image data described to be split got.Concrete, based on the division coefficient q preset and CPU usage n, calculate dividing number m.Then, according to the described dividing number m calculated, be m image segments, wherein m >=0 by described monitoring image Data Segmentation to be split.
Step S200, image segments is carried out binary system with last image and is compared by monitored end respectively, is that not identical image segments is sent to monitoring client by comparative result.
In this step, respectively the binary data of correspondence position in the binary data of the m a be partitioned into image segments and last image is compared, if comparative result is not identical, be then that not identical image segments sends to monitoring client by comparative result, such as, when the 1st image segments is not identical with the binary data comparative result of last image correspondence position, 1st image segments is sent to monitoring client, by that analogy, when m-1 image segments is identical with the binary data comparative result of last image correspondence position, abandon this m-1 image segments, until all image segments comparisons are completed, monitoring client only needs to monitor the image segments changed (image segments that after namely carrying out binary data contrast, result is different).
Here illustratively, less when monitoring image Data Segmentation to be split, need the quantity of the image segments compared more, so the occupancy of cpu resource is also more; When monitoring image data to be split are not split, the image segments quantity compared only has one, and the occupancy of the cpu resource so taken is also fewer.For example, when monitoring image data to be split are not split, so these monitoring image data to be split (both whole image) are carried out binary data with a upper image to compare, as long as there are data not identical, then directly send whole image to monitoring client; When monitoring image data image to be split is divided into 1000 image segments, these 1000 image segments are compared one by one, when wherein there being 500 image segments not identical, these 500 image segments are transferred to monitoring client, like this relative to ameristic situation, the image more complete than compares 999 times more.
In step s 200, described is that not identical image segments is sent to monitoring client by comparative result, wherein a kind of preferred method is: step S300, monitoring client is based on the message response time k between the monitored end detected and monitoring client and default picture quality coefficient z, computed image quality p, and described picture quality p is sent to monitored end, described comparative result, according to picture quality p, is be sent to monitoring client again after the picture quality of not identical image segments transforms by monitored end.
In this step, before described image segments is transferred to described monitoring client, first the message response time k between monitored end and monitoring client is detected, the message response time, k indicated the size of bandwidth, monitoring client is based on described message response time k and default picture quality coefficient z, carry out computed image quality p, binary system comparative result, after acquisition picture quality p, is be sent to monitoring client again after the picture quality of not identical image segments transforms by monitored end.
Fig. 2 shows the method flow diagram splitting data to be monitored based on CPU usage of the present invention.
As shown in Figure 2, abovementioned steps S100 comprises the steps: further
Step S110, monitored end obtains monitoring image data to be split.
In this step, first at monitored end, Desktop Monitoring software is installed, Desktop Monitoring software collection monitoring image data to be split.
Step S120, monitored end group in preset division coefficient q and CPU usage n, computed segmentation quantity m, wherein q >=0,0≤n≤1, m >=0.
In this step, monitored end group is in the division coefficient q preset and CPU usage n, computed segmentation quantity m.
Concrete, calculate described dividing number m according to following formula:
m＝q/n；
Wherein, q is division coefficient, and n is CPU usage, and m is dividing number, q >=0,0≤n≤1, m >=0.
For example, when CPU usage is 20%, user arranges division coefficient q and gets 100, and so calculating dividing number m is 500, is namely 500 image segments by monitoring image Data Segmentation to be split.Preferably, for the ease of segmentation, process can be rounded to the m calculated.
Here, because the division coefficient q after arranging is a definite value, when CPU usage is higher, dividing number m is less, such as 0,1 etc.; When CPU usage is lower, dividing number m is larger, and such as 500,800 etc.
Monitoring image Data Segmentation to be split, according to described dividing number m, is m image segments by step S130.
In this step, according to the described dividing number m calculated, monitoring image data to be split are split, be divided into m image segments.Such as, when the numerical value of m is 10, is 10 image segments by described monitoring image Data Segmentation to be split, respectively binary system is carried out to 10 image segments and compare.When the numerical value of m is 0, described monitoring image data to be split are not split, directly described monitoring image data to be split are carried out binary system as an image segments and compare.
Fig. 3 shows the method flow diagram of rate calculations picture quality Network Based of the present invention.
As shown in Figure 3, abovementioned steps S300 comprises the steps: further
Step S310, detects the message response time k between monitored end and monitoring client.
In this step, when comparative result be image segments not identical with last image time, described image segments is transferred to monitoring client, before described data slot is transferred to monitoring client, need the message response time k detected between monitored end and monitoring client, the message response time, k indicated the size of bandwidth.
Here, can message keep-alive mode be passed through, obtain message response time k, but be not limited to message keep-alive mode.Concrete, monitored end can be set and send a message to monitoring client at interval of predetermined period of time, such as 10 seconds, be responded the time of described message by test and monitoring end, carry out detection messages response time k.
Step S320, monitoring client is based on described message response time k and default picture quality coefficient z computed image quality p.
In this step, after monitoring client receives the next one or more image segments of monitored end transmission, the described message response time k detected based on abovementioned steps and the picture quality coefficient z preset, computed image quality p.
Concrete, according to following formula computed image quality p, p=z*k;
Wherein, z is picture quality coefficient, and k is the message response time between monitored end and monitoring client, and p is the picture quality calculated.
Here, by message response time k, the quality of present image transmission is set, picture quality p=z*k.Concrete, the picture quality of transmission is the original image quality of image segments and the product of picture quality p.Such as, when z is arranged to 66.67, now when k is 0.01 second, if the original image quality comparing the different image segments of binary data result is the high-definition image of 1080P, so only need the view data transmitting 720P corresponding to this image segments.
As mentioned above, describe the method for supervising of optimization monitoring image quality of the present invention in detail, the present invention is by optimized transmission data, large Data Segmentation is become small data, adopt small data transmission mode, solve the problem that transfer of data pressure is large, bandwidth occupancy is high, when for high quality screen image, by the data that transmission is less, also the less network bandwidth can be taken.
Fig. 4 is the structural representation of the supervisory control system of optimization Desktop Monitoring picture quality of the present invention.
As shown in Figure 4, the supervisory control system of described optimization Desktop Monitoring picture quality, for optimizing the picture quality that monitoring client exports, described system comprises: by monitored end 10 and the monitoring client 20 of cable network or wireless network connectivity.
Monitored end 10 based on the division coefficient preset and CPU usage, computed segmentation quantity, and according to described dividing number, view data to be split is split, and obtains image segments.
Specifically, first at monitored end 10, Desktop Monitoring software is installed, Desktop Monitoring software collection monitoring image data to be split.Monitored end 10 is split the monitoring image data described to be split got.Concrete, monitored end 10, based on the division coefficient q preset and CPU usage n, calculates dividing number m.Then, according to the described dividing number m calculated, be m image segments, wherein m >=0 by described monitoring image Data Segmentation to be split.
Described monitored end 10 is according to following formula computed segmentation quantity m:m=q/n;
Wherein, q is division coefficient, and n is CPU usage, and m is dividing number, q >=0,0≤n≤1, m >=0.
For example, when CPU usage is 20%, user arranges division coefficient q and gets 100, and so calculating dividing number m is 500, is namely 500 image segments by monitoring image Data Segmentation to be split.Preferably, for the ease of segmentation, process can be rounded to the m calculated.
Here, because the division coefficient q after arranging is a definite value, when CPU usage is higher, dividing number m is less, such as 0,1 etc.; When CPU usage is lower, dividing number m is larger, and such as 500,800 etc.
Finally, according to the described dividing number m calculated, monitoring image data to be split are split, be divided into m image segments.Such as, when the numerical value of m is 10, be 10 image segments by described monitoring image Data Segmentation to be split, respectively binary system carried out to these 10 image segments and compare.When the numerical value of m is 0, then described monitoring image data to be split are not split, directly described monitoring image data to be split are carried out binary system as an image segments and compare.
Monitored end 10 compares for respectively image segments being carried out binary system with last image, is that not identical image segments is sent to described monitoring client 20 by comparative result.
Specifically, the binary data of correspondence position in the binary data of the m a be partitioned into image segments and last image compares by monitored end 10 respectively, if comparative result is not identical, be then that not identical image segments sends to described monitoring client 20 by described comparative result, such as, when the 1st image segments is not identical with the binary data comparative result of last image correspondence position, 1st image segments is sent to monitoring client 20, by that analogy, when m-1 image segments is identical with the binary data comparative result of last image correspondence position, abandon this m-1 image segments, until all image segments comparisons are completed, monitoring client 20 needs to monitor the image segments changed (image segments that after namely carrying out binary data contrast, result is different).
Here, less when monitoring image Data Segmentation to be split, need the quantity of the image segments compared more, so the occupancy of cpu resource is also more; When monitoring image data to be split are not split, the image segments quantity compared only has one, and the occupancy of the cpu resource so taken is also fewer.For example, when monitoring image data to be split are not split, so these monitoring image data to be split (both whole image) are carried out binary data with a upper image to compare, as long as there are data not identical, then directly send whole image to monitoring client 20; When monitoring image data image to be split is divided into 1000 image segments, these 1000 image segments are compared one by one, when wherein there being 500 image segments not identical, these 500 image segments are transferred to monitoring client 20, like this relative to ameristic situation, the image more complete than compares 999 times more.
In a preferred embodiment, be before not identical image segments is sent to monitoring client 20 at described monitored end 10 by described comparative result, perform following operation: described monitoring client 20 is based on the message response time k between the monitored end 10 detected and monitoring client 20 and default picture quality coefficient z, computed image quality p, and described picture quality p is sent to monitored end 10, described comparative result, according to picture quality p, is be sent to monitoring client 20 again after the picture quality of not identical image segments transforms by monitored end 10.
Specifically, when the comparative result of monitored end 10 be image segments not identical with last image time, the image segments that described comparative result is not identical is sent to monitoring client 20, be before not identical image segments sends to monitoring client 20 by described comparative result, described monitoring client 20 detects the message response time k between monitored end 10 and monitoring client 20, the message response time, k indicated the size of bandwidth, monitoring client 20 is based on described message response time k and default picture quality coefficient z, carry out computed image quality p, monitored end 10 is after acquisition picture quality p, be be sent to monitoring client 20 again after the picture quality of not identical image segments transforms by binary system comparative result.
Optionally, can message keep-alive mode be passed through, obtain message response time k, but be not limited to message keep-alive mode.Concrete, monitored end 10 can be set and send a message to monitoring client 20 at interval of predetermined period of time, such as 10 seconds, be responded the time of described message by test and monitoring end 20, carry out detection messages response time k.
Finally, after monitoring client 20 receives the next one or more image segments of monitored end 10 transmission, the described message response time k detected based on monitoring client 20 and the picture quality coefficient z preset, computed image quality p.
Monitoring client 20 is according to following formula computed image quality p, p=z*k;
Wherein, z is picture quality coefficient, and k is the message response time k between monitored end and monitoring client, and p is the picture quality calculated.
Here, by message response time k, the quality of present image transmission is set, picture quality p=z*k.Concrete, the picture quality of transmission is the original image quality of image segments and the product of picture quality p.Such as, when z is arranged to 66.67, now when k is 0.01 second, if the original image quality comparing the different image segments of binary data result is the high-definition image of 1080P, so only need the view data transmitting 720P corresponding to this image segments.
As mentioned above, describe the supervisory control system of optimization Desktop Monitoring picture quality of the present invention in detail, the present invention is by optimized transmission data, large transfer of data is divided into small data, adopt the mode of small data transmission, solve bandwidth problem, when screen image especially for high quality, transmit minimum data, to take the less network bandwidth.
As mentioned above, the invention provides a kind of method for supervising and the system of optimizing Desktop Monitoring picture quality, the present invention is by the performance of coordination network and monitored device, maximizedly Desktop Monitoring is affected quality promote, greatly improve the quality monitoring of network monitoring image, more efficient to the utilance of equipment and network.
Should be understood that, above-mentioned embodiment of the present invention only for exemplary illustration or explain principle of the present invention, and is not construed as limiting the invention.Therefore, any amendment made when without departing from the spirit and scope of the present invention, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.In addition, claims of the present invention be intended to contain fall into claims scope and border or this scope and border equivalents in whole change and modification.
Claims (12)
1. optimize a method for supervising for Desktop Monitoring picture quality, for Desktop Monitoring system, the picture quality that described supervisory control system exports for optimizing monitoring client, it comprises monitored end and monitoring client, and described method comprises:
Step S100, monitored end group in the division coefficient preset and CPU usage, computed segmentation quantity, and according to described dividing number, monitoring image data to be split are split, and obtains image segments;
Step S200, image segments is carried out binary system with last image and is compared by monitored end respectively, is that not identical image segments is sent to monitoring client by comparative result.
2. method according to claim 1, is characterized in that, described step S100 comprises:
Step S110, monitored end obtains monitoring image data to be split;
Step S120, monitored end group in preset division coefficient q and CPU usage n, computed segmentation quantity m, wherein q >=0,0≤n≤1, m >=0;
Described monitoring image Data Segmentation to be split, according to described dividing number m, is m image segments by step S130.
3. the method according to any one of claim 1-2, is characterized in that, calculates described dividing number m according to following formula:
m＝q/n；
Wherein, q is division coefficient, and n is CPU usage, and m is dividing number, q >=0,0≤n≤1, m >=0.
4. method according to claim 1, is characterized in that, in step s 200, described be, before not identical image segments is sent to the step of monitoring client, also comprise by comparative result:
Step S300, monitoring client is based on the message response time k between the monitored end detected and monitoring client and default picture quality coefficient z, computed image quality p, and described picture quality p is sent to monitored end, described comparative result, according to picture quality p, is be sent to monitoring client again after the picture quality of not identical image segments transforms by monitored end.
5. method according to claim 4, is characterized in that, described step S300 comprises:
Step S310, detects the message response time k between monitored end and monitoring client;
Step S320, monitoring client is based on described message response time k and default picture quality coefficient z, computed image quality p.
6. the method according to claim 4 or 5, is characterized in that, according to following formula computed image quality p:
p＝z*k；
Wherein, z is picture quality coefficient, and k is the message response time between monitored end and monitoring client, and p is the picture quality calculated.
7. optimize a supervisory control system for Desktop Monitoring picture quality, for optimizing the picture quality that monitoring client exports, described system comprises:
By monitored end (10) and the monitoring client (20) of cable network or wireless network connectivity;
Described monitored end (10), for based on the division coefficient preset and CPU usage, computed segmentation quantity, and according to described dividing number, monitoring image data to be split are split, and obtains image segments; And
Described monitored end (10), compares for respectively image segments being carried out binary system with last image, is that not identical image segments is sent to monitoring client (20) by comparative result.
8. system according to claim 7, it is characterized in that, described monitored end (10) is after getting monitoring image data to be split, perform following operation: described monitored end (10) based on the division coefficient q preset and CPU usage n, computed segmentation quantity m, wherein q >=0,0≤n≤1, m >=0, and according to described dividing number m, be m image segments by monitoring image Data Segmentation to be split.
9. the system according to any one of claim 7-8, is characterized in that, described monitored end (10) is according to following formula computed segmentation quantity m:
m＝q/n；
Wherein, q is division coefficient, and n is CPU usage, and m is dividing number, q >=0,0≤n≤1, m >=0.
10. system according to claim 7, it is characterized in that, be before not identical image segments is sent to monitoring client (20) described monitored end (10) by described comparative result, perform following operation: described monitoring client (20) is based on the message response time k between the monitored end (10) detected and monitoring client (20) and default picture quality coefficient z, computed image quality p, and described picture quality p is sent to monitored end (10), monitored end (10) is according to picture quality p, be be sent to monitoring client (20) again after the picture quality of not identical image segments transforms by described comparative result.
11. systems according to claim 7 or 10, it is characterized in that, described monitoring client (20), for detecting the message response time k between monitored end (10) and monitoring client (20), and based on described message response time k and default picture quality coefficient z, computed image quality p.
12. systems according to claim 10, is characterized in that, described monitoring client (20) is according to following formula computed image quality p:
p＝z*k；
Wherein, z is picture quality coefficient, and k is the message response time between monitored end and monitoring client, and p is the picture quality calculated.
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Application publication date: 20151209 |