CN107452185A - A kind of effective mountain area natural calamity early warning system - Google Patents
A kind of effective mountain area natural calamity early warning system Download PDFInfo
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- CN107452185A CN107452185A CN201710861356.8A CN201710861356A CN107452185A CN 107452185 A CN107452185 A CN 107452185A CN 201710861356 A CN201710861356 A CN 201710861356A CN 107452185 A CN107452185 A CN 107452185A
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- 238000012544 monitoring process Methods 0.000 claims abstract description 18
- 238000011156 evaluation Methods 0.000 claims description 34
- 238000012545 processing Methods 0.000 claims description 13
- 238000000034 method Methods 0.000 claims description 7
- 238000007781 pre-processing Methods 0.000 claims description 7
- 230000002708 enhancing effect Effects 0.000 claims description 6
- 238000001914 filtration Methods 0.000 claims description 6
- 230000000295 complement effect Effects 0.000 claims description 4
- 230000000694 effects Effects 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 3
- 238000013519 translation Methods 0.000 claims description 3
- 239000007788 liquid Substances 0.000 claims description 2
- 230000035939 shock Effects 0.000 claims description 2
- 238000010586 diagram Methods 0.000 claims 1
- 235000013399 edible fruits Nutrition 0.000 claims 1
- 230000009286 beneficial effect Effects 0.000 abstract description 3
- 230000010365 information processing Effects 0.000 abstract description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/10—Alarms for ensuring the safety of persons responsive to calamitous events, e.g. tornados or earthquakes
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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
- G06T5/70—Denoising; Smoothing
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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
- G06T5/90—Dynamic range modification of images or parts thereof
- G06T5/92—Dynamic range modification of images or parts thereof based on global image properties
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
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- 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
- G06T2207/20—Special algorithmic details
- G06T2207/20024—Filtering details
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- 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
- G06T2207/20—Special algorithmic details
- G06T2207/20024—Filtering details
- G06T2207/20032—Median filtering
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Abstract
The invention provides a kind of effective mountain area natural calamity early warning system, including information collecting device, communicator, information processor and prior-warning device, described information harvester is used to gather monitoring information, the communicator and described information harvester and information processor wireless connection, for the monitoring information of collection to be transferred into information processor, described information processing unit is used to handle monitoring information, result is obtained, the prior-warning device is used to send early warning according to the result；Described information harvester includes image acquiring device, and described image acquisition device is used for the image for obtaining mountain area.Beneficial effects of the present invention are：Realize the accurate early warning of mountain area natural calamity.
Description
Technical field
The present invention relates to disaster alarm technical field, and in particular to a kind of effective mountain area natural calamity early warning system.
Background technology
In recent years, there is natural calamity during China mountain area, seriously constrain mountain area economy development and socialist construction,
How disaster alarm is carried out as the outstanding problem in China's mitigation work.
With the development of science and technology, novel sensor continues to bring out, and the ability that people obtain image improves rapidly, due to
There is obvious limitation and otherness in the image that different images sensor obtains, the information that single-sensor image provides is gradual
Can not meet the needs of application.Because the imaging mechanism of different sensors is different, time of image, angle, environment are obtained also not
With, it is necessary to which registration is first carried out to image could obtain more complete information.
The content of the invention
A kind of in view of the above-mentioned problems, the present invention is intended to provide effective mountain area natural calamity early warning system.
The purpose of the present invention is realized using following technical scheme：
A kind of effective mountain area natural calamity early warning system is provided, including at information collecting device, communicator, information
Device and prior-warning device are managed, described information harvester is used to gather monitoring information, and the communicator gathers with described information
Device and information processor wireless connection, for the monitoring information of collection to be transferred into information processor, at described information
Reason device is used to handle monitoring information, obtains result, and the prior-warning device is used to be sent out according to the result
Go out early warning；Described information harvester includes image acquiring device, and described image acquisition device is used for the image for obtaining mountain area.
Beneficial effects of the present invention are：Realize the accurate early warning of mountain area natural calamity.
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：
Information collecting device 1, communicator 2, information processor 3, prior-warning device 4.
Embodiment
The invention will be further described with the following Examples.
Referring to Fig. 1, a kind of effective mountain area natural calamity early warning system of the present embodiment, including it is information collecting device 1, logical
T unit 2, information processor 3 and prior-warning device 4, described information harvester 1 are used to gather monitoring information, the communication dress
2 and described information harvester 1 and the wireless connection of information processor 3 are put, for the monitoring information of collection to be transferred into information
Processing unit 3, described information processing unit 3 are used to handle monitoring information, obtain result, the prior-warning device 4
For sending early warning according to the result；Described information harvester 1 includes image acquiring device, and described image obtains dress
Put the image for obtaining mountain area.
The present embodiment realizes the accurate early warning of mountain area natural calamity.
Preferably, described information harvester 1 also includes liquid level gauge, rainfall gauge and shock sensor.
This preferred embodiment obtains more comprehensively monitoring information, improves monitoring accuracy.
Preferably, the prior-warning device 4 includes early warning sound equipment and early-warning lamp.
This preferred embodiment uses early warning sound equipment and early-warning lamp simultaneously, improves early warning level.
Preferably, it is described that processing is carried out to monitoring information including carrying out registration to mountain area image, it is described that mountain area image is entered
Row registration is carried out using image registration device, and described image registration apparatus includes the first image pre-processing module, the second image is matched somebody with somebody
Quasi-mode block and the 3rd image output module, described first image pretreatment module are used to pre-process image subject to registration, institute
State image and reference picture subject to registration that the second image registration module is used for Jing Guo pretreatment and carry out registration, the 3rd image is defeated
Go out module to be used to export the image after registration；Described first image pretreatment module includes the first image enhaucament submodule, second
Image denoising submodule and the 3rd picture appraisal submodule, described first image enhancing submodule are used to carry out image subject to registration
Enhancing handle, the second image denoising submodule be used for processing is filtered to enhanced image subject to registration, obtain by
The image subject to registration of pretreatment, the 3rd picture appraisal submodule are used to comment the image subject to registration by pretreatment
Valency.
This preferred embodiment realizes image registration, and base has been established for follow-up be more preferably monitored to mountain area natural calamity
Plinth.
Preferably, it is specific that enhancing processing is carried out to image subject to registration using following steps：
The first step, line translation is entered to gray value, carried out using following formula：
In above-mentioned formula, (i, j) represents pixel,Represent image (i, j) place gray scale value complement value, EH (i,
J) gray value of the image at (i, j) place is represented；
Second step, using following formula image is strengthened：
In above-mentioned formula, (k, l) represents pixel,Represent gray scale value complement of the enhanced image at (i, j) place
Value, β and γ expression weight coefficients, β ∈ [0.5,1.3], γ ∈ [0.5,3.5],Represent ash of the image at (k, l) place
Angle value benefit value；
3rd step, inverse transformation is carried out to gray value：
In above-mentioned formula, EH ' (i, j) represents enhanced image.
The first image enhaucament of this preferred embodiment submodule is strengthened image using brand-new Enhancement Method, low-light (level)
The brightness of coloured image is greatly improved, and the overall contrast of image is greatly improved, and enters line translation to image
And inverse transformation, computational efficiency is greatly improved, image enhaucament is carried out in log-domain, more conforms to human vision property, contribute to
Improve information monitoring accuracy.
Preferably, it is specific that processing is filtered to enhanced image subject to registration using following steps：
The first step, for the gray value EH ' (i, j) after image enhaucament, if the maximum allowable size of filtering window is Wmax, adopt
It is W with windowijWave filter medium filtering, calculation window W are carried out to itijThe intermediate value z of interior pixelmed, maximum zmax, minimum value
zminAnd remove the average z after maximum and minimum valueave；Second step, calculating
If meet C1＞ 1 and C2＜ 1, then export zmedAs filtered image intensity value, the 3rd step is otherwise transferred to；3rd step, increase
Window size, if increase rear hatch size is less than Wmax, then the first step is transferred to, otherwise exports zaveAs filtered gradation of image
Value；4th step, the image subject to registration using the output of second step and the 3rd step as process pretreatment.
The method that the second image denoising of this preferred embodiment submodule is combined using medium filtering and mean filter, which is treated, matches somebody with somebody
Quasi- image is filtered processing, can not only remove noise, and farthest remains the details of image, specifically, to the greatest extent
The window of small size may be used to retain details, in maximized window of the filter window beyond setting, be filtered using average
Ripple, filtering performance is effectively increased, further increase information monitoring accuracy.
Preferably, the 3rd picture appraisal submodule includes an evaluation unit, second evaluation unit and evaluated three times
Unit, an evaluation unit is used for the first evaluation points for determining the image subject to registration by pretreatment, described secondary to comment
Valency unit is used for the second evaluation points for determining the image subject to registration by pretreatment, and the evaluation unit three times is used for according to the
One evaluation points and the second evaluation points carry out overall merit to the image subject to registration by pretreatment；
Specific the first evaluation points that the image subject to registration by pretreatment is determined using following formula：
In above-mentioned formula, M × N represents image size subject to registration, YW1Represent first of the image subject to registration by pretreatment
Evaluation points, EH " (i, j) represent the gray value of the image subject to registration by pretreatment；
Specific the second evaluation points that the image subject to registration by pretreatment is determined using following formula：
In above-mentioned formula, μ represents the gray value average of the image subject to registration by pretreatment, YW2Represent by pretreatment
Image subject to registration the second evaluation points；
It is specific that overall merit is carried out to the image subject to registration by pretreatment using following formula：According to the first evaluation points and
Two evaluation points calculate overall merit factor YW：
The overall merit factor is bigger, and image preprocessing effect is better.
Pretreated image is quantitatively described the picture appraisal submodule of this preferred embodiment the 3rd, realizes image
The accurate evaluation of pretreating effect, and the evaluation module considers many-sided factor of evaluation, evaluation it is with a high credibility, after being easy to
It is continuous that image pre-processing method is improved, ensure effective progress of image registration, so as to ensure that the standard of natural calamity early warning
True property.
Early warning is carried out to mountain area natural calamity using effective mountain area natural calamity early warning system of the invention, chooses 5 mountains
Area carries out simulated experiment, respectively mountain area 1, mountain area 2, mountain area 3, mountain area 4, mountain area 5, and early warning accuracy rate and early warning efficiency are carried out
Statistics, it is compared with the existing technology, caused to have the beneficial effect that shown in table：
| Early warning accuracy rate improves | Early warning efficiency improves | |
| Mountain area 1 | 29% | 21% |
| Mountain area 2 | 27% | 23% |
| Mountain area 3 | 26% | 25% |
| Mountain area 4 | 25% | 27% |
| Mountain area 5 | 24% | 29% |
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. a kind of effective mountain area natural calamity early warning system, it is characterised in that including information collecting device, communicator, letter
Processing unit and prior-warning device are ceased, described information harvester is used to gather monitoring information, the communicator and described information
Harvester and information processor wireless connection, for the monitoring information of collection to be transferred into information processor, the letter
Breath processing unit is used to handle monitoring information, obtains result, and the prior-warning device is used to be tied according to the processing
Fruit sends early warning；Described information harvester includes image acquiring device, and described image acquisition device is used for the figure for obtaining mountain area
Picture.
2. effective mountain area natural calamity early warning system according to claim 1, it is characterised in that described information collection dress
Putting also includes liquid level gauge, rainfall gauge and shock sensor.
3. effective mountain area natural calamity early warning system according to claim 2, it is characterised in that the prior-warning device bag
Include early warning sound equipment and early-warning lamp.
4. effective mountain area natural calamity early warning system according to claim 3, it is characterised in that described to monitoring information
Carrying out processing includes carrying out mountain area image registration, described that image progress registration in mountain area is carried out using image registration device, institute
Stating image registration device includes the first image pre-processing module, the second image registration module and the 3rd image output module, described
First image pre-processing module is used to pre-process image subject to registration, and the second image registration module is used for by pre- place
The image and reference picture subject to registration of reason carry out registration, and the 3rd image output module is used to export the image after registration；Institute
Stating the first image pre-processing module includes the first image enhaucament submodule, the second image denoising submodule and the 3rd picture appraisal
Module, described first image enhancing submodule are used to carry out image subject to registration enhancing processing, the second image denoising submodule
Block is used to be filtered processing to enhanced image subject to registration, obtains the image subject to registration by pretreatment, the 3rd figure
As evaluation submodule is used to evaluate the image subject to registration by pretreatment.
5. effective mountain area natural calamity early warning system according to claim 4, it is characterised in that specifically using following step
Suddenly enhancing processing is carried out to image subject to registration：
The first step, line translation is entered to gray value, carried out using following formula：
In above-mentioned formula, (i, j) represents pixel,Represent image in the gray scale value complement value at (i, j) place, EH (i, j) table
Gray value of the diagram picture at (i, j) place；
Second step, using following formula image is strengthened：
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In above-mentioned formula, (k, l) represents pixel,Represent gray scale value complement value of the enhanced image at (i, j) place, β
With γ represent weight coefficient, β ∈ [0.5,1.3], γ ∈ [0.5,3.5],Represent gray value of the image at (k, l) place
Benefit value；
3rd step, inverse transformation is carried out to gray value：
In above-mentioned formula, EH ' (i, j) represents enhanced image.
6. effective mountain area natural calamity early warning system according to claim 5, it is characterised in that specifically using following step
Suddenly processing is filtered to enhanced image subject to registration：
The first step, for the gray value EH ' (i, j) after image enhaucament, if the maximum allowable size of filtering window is Wmax, use
Window is WijWave filter medium filtering, calculation window W are carried out to itijThe intermediate value z of interior pixelmed, maximum zmax, minimum value
zminAnd remove the average z after maximum and minimum valueave；Second step, calculating
If meet C1＞ 1 and C2＜ 1, then export zmedAs filtered image intensity value, the 3rd step is otherwise transferred to；3rd step, increase
Window size, if increase rear hatch size is less than Wmax, then the first step is transferred to, otherwise exports zaveAs filtered gradation of image
Value；4th step, the image subject to registration using the output of second step and the 3rd step as process pretreatment.
7. effective mountain area natural calamity early warning system according to claim 6, it is characterised in that the 3rd image is commented
Valency submodule includes an evaluation unit, second evaluation unit and evaluation unit, an evaluation unit are used to determine three times
First evaluation points of the image subject to registration by pretreatment, the second evaluation unit are used to determine to wait to match somebody with somebody by pretreatment
Second evaluation points of quasi- image, the evaluation unit three times are used for according to the first evaluation points and the second evaluation points to passing through
The image subject to registration of pretreatment carries out overall merit；
Specific the first evaluation points that the image subject to registration by pretreatment is determined using following formula：
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In above-mentioned formula, M × N represents image size subject to registration, YW1Represent the first evaluation of the image subject to registration by pretreatment
The factor, EH " (i, j) represent the gray value of the image subject to registration by pretreatment；
Specific the second evaluation points that the image subject to registration by pretreatment is determined using following formula：
In above-mentioned formula, μ represents the gray value average of the image subject to registration by pretreatment, YW2Represent to wait to match somebody with somebody by pretreatment
Second evaluation points of quasi- image；
It is specific that overall merit is carried out to the image subject to registration by pretreatment using following formula：Commented according to the first evaluation points and second
The valency factor calculates overall merit factor YW：
The overall merit factor is bigger, and image preprocessing effect is better.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
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