CN107358583A - A kind of good monitoring system of monitoring performance - Google Patents
A kind of good monitoring system of monitoring performance Download PDFInfo
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- CN107358583A CN107358583A CN201710510377.5A CN201710510377A CN107358583A CN 107358583 A CN107358583 A CN 107358583A CN 201710510377 A CN201710510377 A CN 201710510377A CN 107358583 A CN107358583 A CN 107358583A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 54
- 238000012545 processing Methods 0.000 claims abstract description 35
- 238000004891 communication Methods 0.000 claims abstract description 9
- 230000005540 biological transmission Effects 0.000 claims abstract description 5
- 239000000758 substrate Substances 0.000 claims description 35
- 230000004927 fusion Effects 0.000 claims description 24
- 230000006835 compression Effects 0.000 claims description 14
- 238000007906 compression Methods 0.000 claims description 14
- 230000002708 enhancing effect Effects 0.000 claims description 13
- 238000002203 pretreatment Methods 0.000 claims description 11
- 230000015556 catabolic process Effects 0.000 claims description 3
- 238000000034 method Methods 0.000 claims description 3
- 238000012935 Averaging Methods 0.000 claims description 2
- 238000009499 grossing Methods 0.000 claims description 2
- 230000009286 beneficial effect Effects 0.000 abstract description 4
- 238000005516 engineering process Methods 0.000 description 6
- 239000006002 Pepper Substances 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 238000013139 quantization Methods 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/50—Image enhancement or restoration by the use of more than one image, e.g. averaging, subtraction
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- G06T5/70—
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- G06T5/94—
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T9/00—Image coding
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/30—Transforming light or analogous information into electric information
- H04N5/33—Transforming infrared radiation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10048—Infrared image
Abstract
The invention provides a kind of good monitoring system of monitoring performance, including infrared detector, wireless communication module, infrared image processing device and Surveillance center, the infrared detector is used to be monitored monitor area, obtain the infrared image of HDR, the wireless communication module is used for the infrared image of acquisition by wireless network transmissions to image processing apparatus, the infrared image processing device is used to handle the infrared image of HDR, the infrared image that the Surveillance center is used for after display processing.Beneficial effects of the present invention are：Realize remote monitoring, there is provided a kind of good monitoring system of monitoring performance.
Description
Technical field
The present invention relates to monitoring technology field, and in particular to a kind of good monitoring system of monitoring performance.
Background technology
Infrared image monitoring technology is a kind of strong comprehensively monitoring technology of prevention ability, directly perceived, accurate, timely and interior with its
Hold abundant and be applied to various occasions.With the rapid development of image procossing and transmission technology, picture control technology also obtains
Huge advance.But current monitoring system is still had the problems such as can not realizing remote monitoring, monitoring performance difference.
The content of the invention
A kind of in view of the above-mentioned problems, the present invention is intended to provide good monitoring system of monitoring performance.
The purpose of the present invention is realized using following technical scheme：
A kind of good monitoring system of monitoring performance is provided, including at infrared detector, wireless communication module, infrared image
Device and Surveillance center are managed, the infrared detector is used to be monitored monitor area, obtains the infrared figure of HDR
Picture, the wireless communication module is used for the infrared image of acquisition by wireless network transmissions to image processing apparatus, described red
Outer image processing apparatus is used to handle the infrared image of HDR, after the Surveillance center is used for display processing
Infrared image.
Beneficial effects of the present invention are：Realize remote monitoring, there is provided a kind of good monitoring system of monitoring performance.
Brief description of the drawings
Using accompanying drawing, the invention will be further described, but the embodiment in accompanying drawing does not form any limit to the present invention
System, for one of ordinary skill in the art, on the premise of not paying creative work, can also be obtained according to the following drawings
Other accompanying drawings.
Fig. 1 is the structural representation of the present invention；
Reference：
Infrared detector 1, wireless communication module 2, infrared image processing device 3, Surveillance center 4.
Embodiment
The invention will be further described with the following Examples.
Referring to Fig. 1, a kind of good monitoring system of monitoring performance of the present embodiment, including infrared detector 1, radio communication mold
Block 2, infrared image processing device 3 and Surveillance center 4, the infrared detector 1 are used to be monitored monitor area, obtain high
The infrared image of dynamic range, the wireless communication module 2 are used for the infrared image of acquisition by wireless network transmissions to figure
As processing unit, the infrared image processing device 3 is used to handle the infrared image of HDR, in the monitoring
The infrared image that the heart 4 is used for after display processing.
The present embodiment realizes remote monitoring, there is provided a kind of good monitoring system of monitoring performance.
Preferably, the Surveillance center 4 includes the more display devices for being used for infrared image after display processing.
This preferred embodiment can be monitored to many places monitor area simultaneously.
Preferably, the display device is high-clear display.
The high definition that this preferred embodiment realizes monitoring image shows that monitoring performance is greatly improved.
Preferably, the infrared image processing device 3 includes picture breakdown module, image compression module, Image Enhancement Based
Block and image co-registration module, described image decomposing module are used to the infrared image of HDR being decomposed into substrate image and thin
Image is saved, described image compression module is used to carry out substrate image high dynamic range compression processing, described image enhancing module
For detail pictures to be carried out with small dynamic range extension and details enhancing processing, after described image Fusion Module is used for processing
Substrate image and detail pictures are merged, the infrared image after output fusion.
Infrared image is decomposed into substrate image and detail pictures by the present embodiment infrared image processing device, for substrate figure
Picture, the high dynamic range compression of contrast holding is carried out, for detail pictures, carry out small dynamic extension and details enhancing,
While completing the compression of Larger Dynamic range digital image, the contrast of small dynamic temperature difference details is improved.Solves infrared acquisition
In following problem：On the one hand, it is the detectivity and detection range of raising infrared system, it is desirable to which sensor improves as far as possible
The exponent number and FOV of search of quantization, this just produces the imaging of HDR；On the other hand, the perceived tiny temperature difference occupies ash
Degree level is seldom, and local contrast and signal to noise ratio are just lower in the scene of Larger Dynamic scope.
Preferably, described image decomposing module includes the first image acquisition unit and the second image acquisition unit, and described
One image acquisition unit is used for the substrate image for obtaining the infrared image of HDR, and second image acquisition unit is used for
Obtain the detail pictures of the infrared image of HDR：
The substrate image of the infrared image of HDR is obtained by following steps：Step 1, to the red of HDR
Outer image carries out preliminary treatment：F (x, y)=MH5×5{MH5×5[fin(x, y)] }, in formula, MH5×5[fin(x, y)] represent with
5 × 5 windows are to fin(x, y) carries out median filter process, fin(x, y) represents original input picture, and f (x, y) is represented to high dynamic
The infrared image of scope carries out the image after preliminary treatment；
Step 2, image is decomposed, obtain substrate image：
In formula
In, fo(x, y) represents the substrate image after decomposing, and L (x, y) represents the neighborhood of pixel (x, y),Expression standard deviation is σ1's
Gauss low frequency filter, for carrying out the weighting of space length to pixel in neighborhood,Expression standard deviation is σ2Gaussian function,
For carrying out the weighting of Gray homogeneity to pixel in neighborhood；
Detail pictures are obtained in the following manner：fd(x, y)=f (x, y)-fo(x, y), in formula, fd(x, y) is represented
Detail pictures after decomposition.
What this preferred embodiment picture breakdown modular belt came specifically has the beneficial effect that：First image acquisition unit passes through secondary
Median filter process, the salt-pepper noise in original image can be removed, prevent the noise leakage of physical presence inside detector from arriving
It is enhanced in details composition, the influence of bad point and noise in enhancing image is effectively reduced, using fo(x, y) obtains substrate figure
Picture, while the space length and Gray homogeneity of pixel are considered, extracted advantage of this is that can either control in IR Scene
Minimized radiation difference, and can enough avoid to high-contrast edges carry out excess smoothness.
Preferably, described image compression module is handled substrate image using following formula： In formula, STo(x, y) represents to carry out substrate image
Image after the high dynamic range compression processing that contrast is kept, μ (x, y) represent the gray scale neighborhood averaging value of pixel (x, y), ρ
Represent contrast control parameter, fav(x, y) is that the image that Gaussian smoothing convolution obtains is carried out to substrate image.
This preferred embodiment sets image compression module to handle substrate image, sets contrast control parameter, uses
In the holding degree for controlling local contrast in high dynamic range compression, by Reasonable adjustment contrast control parameter, can obtain
To preferable local contrast enhancing effect, the substrate image of high quality is obtained.
Preferably, described image enhancing module is handled detail pictures using following formula：
In formula, PL represents detail pictures entropy, and it is general that p (i) represents that the pixel of i-th of gray level occurs in detail pictures
Rate,Represent all pixels gray level average in detail pictures, STd(x, y) represents to carry out detail pictures in the figure after enhancing processing
Picture, μ and σ represent the global average and variance of detail pictures, μ respectivelyx,yAnd σx,yRepresent respectively detail pictures any pixels (x,
Y) average and variance in 5 × 5 local neighborhoods.
This preferred embodiment sets image enhancement module to be handled to detail pictures, during the entropy difference of image, adopts
Detail pictures are handled with different modes, it is possible to increase the actual effect of enhancing, the violent fluctuating of image background is adapted to,
Obtain the detail pictures of high quality.
Preferably, described image Fusion Module includes preparatory unit and integrated unit, and the preparatory unit is used for processing
Substrate image and detail pictures afterwards carries out fusion pre-treatment, and the integrated unit is used for the substrate image after fusion pre-treatment
Merged with detail pictures；
Fusion pre-treatment is carried out to the substrate image after processing and detail pictures is specially：To STo(x, y) and STd(x,y)
Carry out fusion pre-treatment：
In formula, CFo(x, y) represents STo(x, y) carries out the result after fusion pre-treatment, CFd(x, y) represents STdBefore (x, y) fusion
Result after processing；
Substrate image after fusion pre-treatment and detail pictures are merged specially：To CFo(x, y) and CFd(x,y)
Merged：EU (x, y)=(1-2β)CFo(x,y)+2βCFd(x, y), in formula, β expression fusion coefficients, 0<eβ<1, in place
In the output of wide W bit, the dynamic range series that substrate image is occupied is (1-2β)·2W, dynamic range that detail pictures are occupied
Series is 2β·2W, the image after EU (x, y) expression fusions.
This preferred embodiment image co-registration module is to STo(x, y) and STd(x, y) is handled, and takes full advantage of whole ash
Level scope is spent, two-part result is subjected to dynamic range distribution and fusion, it is achieved thereby that infrared image high dynamic range
Confined pressure contracts and details enhancing, is advantageous to improve monitoring level.
It is monitored using the good monitoring system of monitoring performance of the present invention, chooses 5 monitoring scenes, and compiled respectively and be
Scene 1, scene 2, scene 3, scene 4 and scene 5, monitoring cost and monitoring security are analyzed, compared with monitoring system
Compare, it is caused to have the beneficial effect that shown in table：
| Monitoring cost reduces | Security is monitored to improve | |
| Scene 1 | 23% | 21% |
| Scene 2 | 25% | 20% |
| Scene 3 | 24% | 19% |
| Scene 4 | 27% | 22% |
| Scene 5 | 24% | 23% |
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected
The limitation of scope is protected, although being explained with reference to preferred embodiment to the present invention, one of ordinary skill in the art should
Work as understanding, technical scheme can be modified or equivalent substitution, without departing from the reality of technical solution of the present invention
Matter and scope.
Claims (7)
1. the good monitoring system of a kind of monitoring performance, it is characterised in that including infrared detector, wireless communication module, infrared figure
As processing unit and Surveillance center, the infrared detector is used to be monitored monitor area, obtains the red of HDR
Outer image, the wireless communication module are used for the infrared image of acquisition by wireless network transmissions to image processing apparatus, institute
State infrared image processing device to be used to handle the infrared image of HDR, the Surveillance center is used for display processing
Infrared image afterwards.
2. the good monitoring system of monitoring performance according to claim 1, it is characterised in that the Surveillance center includes more
Display device for infrared image after display processing.
3. the good monitoring system of monitoring performance according to claim 2, it is characterised in that the display device shows for high definition
Show device.
4. the good monitoring system of monitoring performance according to claim 3, it is characterised in that the infrared image processing device
Including picture breakdown module, image compression module, image enhancement module and image co-registration module, described image decomposing module is used for
The infrared image of HDR is decomposed into substrate image and detail pictures, described image compression module is used for substrate image
High dynamic range compression processing is carried out, described image enhancing module is used to carry out small dynamic range extension and details to detail pictures
Enhancing is handled, and described image Fusion Module is used to merge the substrate image after processing and detail pictures, after output fusion
Infrared image.
5. the good monitoring system of monitoring performance according to claim 4, it is characterised in that described image decomposing module includes
First image acquisition unit and the second image acquisition unit, described first image acquiring unit are used to obtain the red of HDR
The substrate image of outer image, second image acquisition unit are used for the detail pictures for obtaining the infrared image of HDR：
The substrate image of the infrared image of HDR is obtained by following steps：Step 1, the infrared figure to HDR
As carrying out preliminary treatment：F (x, y)=MH5×5{MH5×5[fin(x, y)] }, in formula, MH5×5[fin(x, y)] represent with 5 × 5
Window is to fin(x, y) carries out median filter process, fin(x, y) represents original input picture, and f (x, y) is represented to HDR
Infrared image carry out preliminary treatment after image；
Step 2, image is decomposed, obtain substrate image：
In formula,
fo(x, y) represents the substrate image after decomposing, and L (x, y) represents the neighborhood of pixel (x, y),Expression standard deviation is σ1Height
This low pass filter, for carrying out the weighting of space length to pixel in neighborhood,Expression standard deviation is σ2Gaussian function, use
Pixel carries out the weighting of Gray homogeneity in neighborhood；
Detail pictures are obtained in the following manner：fd(x, y)=f (x, y)-fo(x, y), in formula, fd(x, y) represents to decompose
Detail pictures afterwards.
6. the good monitoring system of monitoring performance according to claim 5, it is characterised in that described image compression module uses
Following formula is handled substrate image：In formula, STo
(x, y) represents to carry out substrate image the image after the high dynamic range compression processing of contrast holding, and μ (x, y) represents pixel
The gray scale neighborhood averaging value of (x, y), ρ represent contrast control parameter, fav(x, y) is to carry out Gaussian smoothing convolution to substrate image
Obtained image；
Described image enhancing module is handled detail pictures using following formula：
In formula, PL represents detail pictures entropy, and it is general that p (i) represents that the pixel of i-th of gray level occurs in detail pictures
Rate,Represent all pixels gray level average in detail pictures, STd(x, y) represents to carry out detail pictures in the figure after enhancing processing
Picture, μ and σ represent the global average and variance of detail pictures, μ respectivelyx,yAnd σx,yRepresent respectively detail pictures any pixels (x,
Y) average and variance in 5 × 5 local neighborhoods.
7. the good monitoring system of monitoring performance according to claim 6, it is characterised in that described image Fusion Module includes
Preparatory unit and integrated unit, the preparatory unit are used to the substrate image after processing and detail pictures are carried out merging preceding place
Reason, the integrated unit are used to merge the substrate image after fusion pre-treatment and detail pictures；
Fusion pre-treatment is carried out to the substrate image after processing and detail pictures is specially：To STo(x, y) and STd(x, y) is carried out
Merge pre-treatment：
In formula, CFo(x, y) represents STo(x, y) carries out the result after fusion pre-treatment, CFd(x, y) represents STdLocate before (x, y) fusion
Result after reason；
Substrate image after fusion pre-treatment and detail pictures are merged specially：To CFo(x, y) and CFd(x, y) is carried out
Fusion：EU (x, y)=(1-2β)CFo(x,y)+2βCFd(x, y), in formula, β expression fusion coefficients, 0<eβ<1, in bit wide W ratios
In special output, the dynamic range series that substrate image is occupied is (1-2β)·2W, the dynamic range series that detail pictures are occupied is
2β·2W, the image after EU (x, y) expression fusions.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107995492A (en) * | 2017-11-27 | 2018-05-04 | 上海交通大学 | A kind of code check control bit distribution method suitable for high dynamic range |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103024281A (en) * | 2013-01-11 | 2013-04-03 | 重庆大学 | Infrared and visible video integration system |
| CN104021532A (en) * | 2014-06-19 | 2014-09-03 | 电子科技大学 | Image detail enhancement method of infrared image |
| CN104995910A (en) * | 2012-12-21 | 2015-10-21 | 菲力尔系统公司 | Infrared imaging enhancement with fusion |
| US20150312489A1 (en) * | 2009-03-02 | 2015-10-29 | Flir Systems, Inc. | Anomalous pixel detection |
| CN105096285A (en) * | 2014-05-23 | 2015-11-25 | 南京理工大学 | Image fusion and target tracking system based on multi-core DSP |
| US20170004609A1 (en) * | 2010-04-23 | 2017-01-05 | Flir Systems Ab | Infrared resolution and contrast enhancement with fusion |
-
2017
- 2017-06-28 CN CN201710510377.5A patent/CN107358583A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150312489A1 (en) * | 2009-03-02 | 2015-10-29 | Flir Systems, Inc. | Anomalous pixel detection |
| US20170004609A1 (en) * | 2010-04-23 | 2017-01-05 | Flir Systems Ab | Infrared resolution and contrast enhancement with fusion |
| CN104995910A (en) * | 2012-12-21 | 2015-10-21 | 菲力尔系统公司 | Infrared imaging enhancement with fusion |
| CN103024281A (en) * | 2013-01-11 | 2013-04-03 | 重庆大学 | Infrared and visible video integration system |
| CN105096285A (en) * | 2014-05-23 | 2015-11-25 | 南京理工大学 | Image fusion and target tracking system based on multi-core DSP |
| CN104021532A (en) * | 2014-06-19 | 2014-09-03 | 电子科技大学 | Image detail enhancement method of infrared image |
Non-Patent Citations (1)
| Title |
|---|
| 孙刚: "《大视场红外搜索系统目标检测关键技术研究》", 《中国博士学位论文全文数据库 信息科技辑》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107995492A (en) * | 2017-11-27 | 2018-05-04 | 上海交通大学 | A kind of code check control bit distribution method suitable for high dynamic range |
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