CN109064501A - A kind of working method of sewage treatment monitoring system - Google Patents
A kind of working method of sewage treatment monitoring system Download PDFInfo
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Abstract
The present invention relates to a kind of working method of sewage treatment monitoring system, the sewage treatment monitoring system includes: Cloud Server, monitor terminal, sewage disposal device；Wherein the sewage disposal device includes: processor, the data acquisition device and video monitoring apparatus being connected with the processor；The working method includes: the data acquisition device acquisition sewage data, and is sent to Cloud Server by a communication module；The video data of the video monitoring apparatus acquisition sewage disposal device, and Cloud Server is sent to by the communication module；And the Cloud Server stores sewage data and video data, and sewage data and video data are sent to monitor terminal；The working method of sewage treatment monitoring system of the present invention can be completed remotely to monitor the working condition of sewage data and sewage disposal device, instead of artificial on-site supervision, improve monitoring efficiency and quality monitoring.
Description
Technical field
The present invention relates to technical field of sewage more particularly to a kind of working methods of sewage treatment monitoring system.
Background technique
Development is protruded into national environmental protection informationization capacity building, the processing and monitoring for sewage have great meaning
Justice.The processing equipment of sewage is substantially at present and manually carries out observing and recording data, this method labor intensive compared with
Greatly, and remote real time monitoring can not be carried out, it the problems such as there are monitoring cycle length, large labor intensity, slow acquisition speed, cannot
It is well reflected the continuous dynamic change and equipment state of sewage treatment, such as when event occurs in wherein certain equipment damage of sewage treatment
When barrier, it is unfavorable for staff and timely finds failure and repair, entire sewage disposal process is easy to cause to be unable to complete
Subsequent processing work.
Summary of the invention
The object of the present invention is to provide a kind of working methods of sewage treatment monitoring system.
It is described in order to solve the above-mentioned technical problems, the present invention provides a kind of working method of sewage treatment monitoring system
Sewage treatment monitoring system includes: Cloud Server, monitor terminal, sewage disposal device；Wherein the sewage disposal device includes:
Processor, the data acquisition device and video monitoring apparatus being connected with the processor；The working method includes: that the data are adopted
Acquisition means acquire sewage data, and are sent to Cloud Server by a communication module；At the video monitoring apparatus acquisition sewage
The video data of equipment is managed, and Cloud Server is sent to by the communication module；And the Cloud Server stores sewage number
According to and video data, and sewage data and video data are sent to monitor terminal.
Preferably, the video monitoring apparatus uses the general camera of more light；The general camera of more light, which is suitable for identification in real time, is supervised
Target position is controlled, and the method for identification target to be monitored position includes the following steps: in real time
Step 1: the spectrum picture of target area is obtained by multi-optical spectrum imaging system, involved by the multi-optical spectrum imaging system
And optical filter wave-length coverage covers visible wavelength to infrared wavelength；Step 2: extracting any imaging of the multi-optical spectrum imaging system
The spectral information is directed into the spectral information data of the multi-optical spectrum imaging system by the spectral information of the spectrum picture in channel
Library carries out Data Matching, completes preliminary information screening；Step 3: if it fails to match for the spectral information, the multispectral imaging
Main control chip control in system carries out the acquisition of next frame target area spectrum picture；Step 4: if the spectral information data
Corresponding spectral information is matched in library, the main control chip is automatically positioned out position of the spectral information in spectrum picture
Coordinate, and according to the position coordinates, the main control chip controls the full side that the multi-optical spectrum imaging system carries out target area
Position camera-shooting scanning, obtains the spectrum picture under visible wavelength and infrared wavelength scale respectively, and to the visible wavelength and
Spectrum picture under infrared wavelength scale carries out image co-registration processing；Step 5: the image after the fusion treatment being carried out non-equal
Even correction.
Preferably, the main control chip includes FPGA, and the spectral information carries out data in the internal RAM of FPGA
Match.
Preferably, the step 4 specifically includes: step 4.1: the main control chip is automatically positioned out the spectral information and exists
After position coordinates in spectrum picture, determines the center of the spectral information of successful match, calculate the imaging
The angle of the imaging target and horizontal direction of system, and determine the camera module in the imaging target and the imaging system
Between deflection angle, the main control chip, which controls the multi-optical spectrum imaging system, to carry out resolution ratio along the deflection angle and sweeps
It retouches, completes the comprehensive camera-shooting scanning of target area；Step 4.2: in the multi-optical spectrum imaging system along the deflection angle
When carrying out resolution scan, the main control chip passes through to the spectral information identification region and infrared wavelength in visible wavelength
Interior spectral information identification region carries out motion detection, determines its motion profile, and complete the fitting of two motion profiles, chooses
Change of scale matrix generates visible images and infrared image to be fused using the matrix；Step 4.3: the master control core
Piece further control the image co-registration processing unit in FPGA to the visible images and infrared image carry out brightness regulation,
The operation such as denoising, centre registration, fusion and image enhancement, wherein described image fusion treatment unit includes DSP, FLASH with
And dimension correction memory；The FPGA combination dimension correction memory completes the detail extraction and profile of infrared image jointly
It extracts, and completes to be registrated geometric scale transformation and image detail and profile fusion between spectrum picture and infrared image；Institute
DSP connection image encoder is stated, and combines the RAM in connection FLASH and FPGA, for believing treated digital video
Number combine that row, field sync signal synthesizes analog video signal and driven in order to show；Step 4.4: when the master control
When chip controls carry out the visible images and infrared image fusion, described image fusion treatment unit is to the visible light
Image and infrared image are each separated into nonoverlapping piece, calculate separately information content therein, by the visible images and
Infrared image is divided into the image of different scale using gaussian pyramid, and the FPGA extracts minutia, and root in different scale
It is weighted assessment according to the information measure feature, is finally synthesized using laplacian pyramid, forms new blending image；
Step 4.5: brightness detection being carried out to fused image, and is compared with a normal brightness, when described image brightness is lower than
When the normal brightness, brightness of image is handled to reach the brightness value for being suitable for test；Step 4.6: to fused figure
As carrying out image denoising, described image denoising is denoised only for the spectral information identification region, to reduce the master control
The operation of chip consumes；Step 4.7: image enhancement processing is carried out to fused image using adaptive image enhancement technology；
Preferably, in the step 5, non-uniform correction method is carried out to the image after the fusion treatment, it is specific
Include:
Step 5.1: before the multi-optical spectrum imaging system is for target area imaging, acquiring the multispectral imaging respectively
Response data of the photosensitive member of each imaging band of system under each temperature value, and each temperature is calculated separately using following formula
The gain coefficient G of sectionijWith biasing coefficient Qij
Wherein Xij(H) and XijIt (L) is response of the pixel (i, j) under high temperature and low temperature homogeneous radiation background, V respectivelyHWith
VLIt is the average output of all pixels in the infrared camera respectively；
Step 5.2: the main control chip of the imaging system is by the gain coefficient G of above-mentioned each temperature sectionijWith biasing coefficient Qij
Real-time storage is to FPGA internal RAM, in case subsequent use；
Step 5.3: special using the texture and edge of blending image for fused image after the completion of the step 4
It levies and depth recognition is carried out to the spectral information identification region in blending image；Step 5.4: the different spectrum according to blending image are believed
Target optical spectrum region is carried out image segmentation, forms each characteristic area by breath distribution；Step 5.5: the parallel processing based on FPGA
Ability carries out nonuniformity correction to each characteristic area of the blending image respectively simultaneously；For each characteristic area, institute
The mean temperature that main control chip calculates each point in the characteristic area first is stated, then according to the mean temperature, from described
Corresponding correction parameter is read in RAM in FPGA, and completes nonuniformity correction according to the following formula
WhereinThe image that infrared detector exports under the conditions of expression Uniform Irradiation degree；
Step 5.6: the blending image after correction compensates boundary gray value using mean filter method.
The beneficial effects of the present invention are: the working method of sewage treatment monitoring system of the present invention can be completed to sewage data
It is remotely monitored with the working condition of sewage disposal device, instead of artificial on-site supervision, improves monitoring efficiency and quality monitoring.
Detailed description of the invention
Fig. 1 is the functional block diagram of sewage treatment monitoring system in the present invention；
Fig. 2 is the flow chart for identifying the method for target to be monitored position in the present invention in real time；
Fig. 3 is the image co-registration process flow diagram for the method for identifying target to be monitored position in the present invention in real time；
Fig. 4 is the Nonuniformity Correction flow chart for the method for identifying target to be monitored position in the present invention in real time.
Specific embodiment
It is described below for disclosing the present invention so that those skilled in the art can be realized the present invention.It is excellent in being described below
Embodiment is selected to be only used as illustrating, it may occur to persons skilled in the art that other obvious modifications.It defines in the following description
Basic principle of the invention can be applied to other embodiments, deformation scheme, improvement project, equivalent program and do not carry on the back
Other technologies scheme from the spirit and scope of the present invention.
Embodiment
As shown in Figure 1, a kind of working method of sewage treatment monitoring system is present embodiments provided, the sewage treatment prison
Control system includes: Cloud Server, monitor terminal, sewage disposal device；Wherein the sewage disposal device includes: processor, with
The processor connected data acquisition device and video monitoring apparatus；The working method includes: that the data acquisition device is adopted
Dirt collection water number evidence, and Cloud Server is sent to by a communication module；The video monitoring apparatus acquisition sewage disposal device
Video data, and Cloud Server is sent to by the communication module；And the Cloud Server stores sewage data and video
Data, and sewage data and video data are sent to monitor terminal.
Specifically, the data acquisition device includes: that temperature sensor, concentration sensor, flow sensor and flow pass
Sensor, to acquire the temperature data, concentration data, flow speed data, data on flows of sewage；The video monitoring apparatus is for monitoring
The working condition of sewage disposal device.
The working method of sewage treatment monitoring system of the present invention can complete the work to sewage data and sewage disposal device
Make state remotely to be monitored, instead of artificial on-site supervision, improves monitoring efficiency and quality monitoring.
Further, in order to improve the monitoring accuracy of video monitoring apparatus, to further increase monitoring efficiency of the invention
And quality monitoring, the video monitoring apparatus use the general camera of more light；The general camera of more light is suitable for identifying monitored mesh in real time
Cursor position, and the method for identification target to be monitored position includes the following steps: in real time
Step 1: the spectrum picture of target area is obtained by multi-optical spectrum imaging system, involved by the multi-optical spectrum imaging system
And optical filter wave-length coverage covers visible wavelength to infrared wavelength；
Step 2: the spectral information of the spectrum picture of any imaging band of the multi-optical spectrum imaging system is extracted, by the light
The spectral information database that spectrum information is directed into the multi-optical spectrum imaging system carries out Data Matching, completes preliminary information screening；
Step 3: if it fails to match for the spectral information, the main control chip in the multi-optical spectrum imaging system, which controls, to be carried out
The acquisition of next frame target area spectrum picture；
Step 4: if being matched to corresponding spectral information in the spectral information database, the main control chip automatic positioning
Position coordinates of the spectral information in spectrum picture out, and according to the position coordinates, described in the main control chip control
Multi-optical spectrum imaging system carries out the comprehensive camera-shooting scanning of target area, obtains under visible wavelength and infrared wavelength scale respectively
Spectrum picture, and under the visible wavelength and infrared wavelength scale spectrum picture carry out image co-registration processing；
Step 5: the image after the fusion treatment is subjected to nonuniformity correction.
Preferably, the main control chip includes FPGA, and the spectral information carries out data in the internal RAM of FPGA
Match.
Preferably, as shown in Fig. 2, the step 4 specifically includes:
Step 4.1: after the main control chip is automatically positioned out position coordinates of the spectral information in spectrum picture, really
The center of making the spectral information of successful match calculates the imaging target and horizontal direction of the imaging system
Angle, and determine the deflection angle between the camera module in the imaging target and the imaging system, the master control core
Piece controls the multi-optical spectrum imaging system and carries out resolution scan along the deflection angle, completes the comprehensive of target area and takes the photograph
As scanning；
Step 4.2: when the multi-optical spectrum imaging system carries out resolution scan along the deflection angle, the master control
Chip is carried out by the spectral information identification region to the spectral information identification region in visible wavelength and in infrared wavelength
Motion detection determines its motion profile, and completes the fitting of two motion profiles, chooses change of scale matrix, uses the matrix
Generate visible images and infrared image to be fused；
Step 4.3: the main control chip further controls the image co-registration processing unit in FPGA to the visible light figure
Picture and infrared image carry out the operation such as brightness regulation, denoising, centre registration, fusion and image enhancement, wherein described image
Fusion treatment unit includes DSP, FLASH and dimension correction memory；The FPGA combination dimension correction memory is jointly complete
At the detail extraction and contours extract of infrared image, and complete to be registrated geometric scale change between spectrum picture and infrared image
Change and image detail and profile fusion；The DSP connection image encoder, and combine in connection FLASH and FPGA
RAM, for combining row, field sync signal to synthesize analog video signal treated digital video signal and driving
In order to show；
Step 4.4: when main control chip control carries out the visible images and infrared image merges, the figure
As fusion treatment unit is each separated into nonoverlapping piece to the visible images and infrared image, letter therein is calculated separately
The visible images and infrared image, are divided into the image of different scale by breath amount using gaussian pyramid, and the FPGA exists
Different scale extracts minutia, and is weighted assessment according to the information measure feature, finally uses laplacian pyramid
It is synthesized, forms new blending image；
Step 4.5: brightness detection being carried out to fused image, and is compared with a normal brightness, described image is worked as
When brightness is lower than the normal brightness, brightness of image is handled to reach the brightness value for being suitable for test；
Step 4.6: image denoising being carried out to fused image, described image denoising is identified only for the spectral information
Region is denoised, to reduce the operation consumption of the main control chip；
Step 4.7: image enhancement processing is carried out to fused image using adaptive image enhancement technology；
Preferably, as shown in figure 3, in the step 5, nonuniformity correction side is carried out to the image after the fusion treatment
Method specifically includes:
Step 5.1: before the multi-optical spectrum imaging system is for target area imaging, acquiring the multispectral imaging respectively
Response data of the photosensitive member of each imaging band of system under each temperature value, and each temperature is calculated separately using following formula
The gain coefficient G of sectionijWith biasing coefficient Qij
Wherein Xij(H) and XijIt (L) is response of the pixel (i, j) under high temperature and low temperature homogeneous radiation background, V respectivelyHWith
VLIt is the average output of all pixels in the infrared camera respectively；
Step 5.2: the main control chip of the imaging system is by the gain coefficient G of above-mentioned each temperature sectionijWith biasing coefficient Qij
Real-time storage is to FPGA internal RAM, in case subsequent use；
Step 5.3: special using the texture and edge of blending image for fused image after the completion of the step 4
It levies and depth recognition is carried out to the spectral information identification region in blending image；
Step 5.4: the different spectral informations according to blending image are distributed, and target optical spectrum region is carried out image segmentation, shape
At each characteristic area；
Step 5.5: the parallel processing capability based on FPGA, respectively to each characteristic area of the blending image simultaneously into
Row nonuniformity correction；For each characteristic area, the main control chip calculates being averaged for each point in the characteristic area first
Temperature reads corresponding correction parameter then according to the mean temperature from the RAM in the FPGA, and according to following public affairs
Formula completes nonuniformity correction
WhereinThe image that infrared detector exports under the conditions of expression Uniform Irradiation degree；
Step 5.6: the blending image after correction compensates boundary gray value using mean filter method.
The above-mentioned target identification method based on multi-optical spectrum imaging system is simple to operation, using FPGA as imaging system
Main control chip, so that imaging system operation efficiency with higher, algorithm is accurate, can faster carry out to target to be identified real
When identify have the advantages that simple and easy, accuracy is higher, be suitable for popularization and application.
The present embodiment is identified in the method for target to be monitored position in real time and is tentatively sieved by the spectral information to extraction
It selects, main control chip control multi-optical spectrum imaging system carries out omnibearing imaging scanning after successful match, passes through the visible light to acquisition
Image and infrared image carry out image co-registration processing and nonuniformity correction, complete final target identification, avoid single
Visible images and single infrared image are unsuitable for lacking for target identification in clarity, texture and in terms of highlighting degree
It falls into, so that multi-optical spectrum imaging system can quickly and accurately carry out the realtime graphic identification of target to be identified；The present embodiment is known in real time
Imaging system may be implemented adaptively in the method for other target to be monitored position, by image co-registration processing unit to visible light figure
Picture and infrared image carry out the processing such as brightness regulation, denoising, fusion, image enhancement, then carry out nonuniformity correction to blending image,
So that blending image resolution ratio is further enhanced, to improve the accuracy of identification of target to be identified；The present embodiment it is more
Spectrum camera uses core processing unit of the FPGA as imaging system main control chip, makes full use of its parallel processing capability to figure
Each of picture cut zone carries out nonuniformity correction, image processing speed is greatly improved, so that the knowledge of imaging system
It does not feed back much sooner.
It should be understood by those skilled in the art that foregoing description and the embodiment of the present invention shown in the drawings are only used as illustrating
And it is not intended to limit the present invention.The purpose of the present invention has been fully and effectively achieved.Function and structural principle of the invention exists
It shows and illustrates in embodiment, under without departing from the principle, implementation method of the invention can have any form or modification.
Claims (5)
1. a kind of working method of sewage treatment monitoring system, which is characterized in that the sewage treatment monitoring system includes: cloud clothes
Business device, monitor terminal, sewage disposal device；Wherein
The sewage disposal device includes: processor, the data acquisition device and video monitoring apparatus being connected with the processor；
The working method includes:
The data acquisition device acquires sewage data, and is sent to Cloud Server by a communication module；
The video data of the video monitoring apparatus acquisition sewage disposal device, and cloud service is sent to by the communication module
Device；And
The Cloud Server storage sewage data and video data, and sewage data and video data are sent to monitor terminal.
2. the working method of sewage treatment monitoring system according to claim 1, which is characterized in that
The video monitoring apparatus uses the general camera of more light；
The general camera of more light is suitable for identification target to be monitored position in real time, and the method packet of identification target to be monitored position in real time
Include following steps:
Step 1: the spectrum picture of target area, the involved filter of the multi-optical spectrum imaging system are obtained by multi-optical spectrum imaging system
Mating plate wave-length coverage covers visible wavelength to infrared wavelength；
Step 2: extracting the spectral information of the spectrum picture of any imaging band of the multi-optical spectrum imaging system, the spectrum is believed
The spectral information database that breath is directed into the multi-optical spectrum imaging system carries out Data Matching, completes preliminary information screening；
Step 3: if it fails to match for the spectral information, the main control chip control in the multi-optical spectrum imaging system carries out next
The acquisition of frame target area spectrum picture；
Step 4: if being matched to corresponding spectral information in the spectral information database, the main control chip is automatically positioned out institute
Position coordinates of the spectral information in spectrum picture are stated, and according to the position coordinates, the main control chip controls the mostly light
Spectrum imaging system carries out the comprehensive camera-shooting scanning of target area, obtains the light under visible wavelength and infrared wavelength scale respectively
Spectrogram picture, and image co-registration processing is carried out to the spectrum picture under the visible wavelength and infrared wavelength scale；
Step 5: the image after the fusion treatment is subjected to nonuniformity correction.
3. the working method of sewage treatment monitoring system according to claim 2, which is characterized in that the main control chip packet
FPGA is included, the spectral information carries out Data Matching in the internal RAM of FPGA.
4. the working method of sewage treatment monitoring system according to claim 3, which is characterized in that the step 4 is specific
Include:
Step 4.1: after the main control chip is automatically positioned out position coordinates of the spectral information in spectrum picture, determining
The center of the spectral information of successful match calculates the folder of the imaging target and horizontal direction of the imaging system
Angle, and determine the deflection angle between the camera module in the imaging target and the imaging system, the main control chip
It controls the multi-optical spectrum imaging system and carries out resolution scan along the deflection angle, complete the comprehensive camera shooting of target area
Scanning；
Step 4.2: when the multi-optical spectrum imaging system carries out resolution scan along the deflection angle, the main control chip
By being moved to the spectral information identification region in visible wavelength and the spectral information identification region in infrared wavelength
Detection determines its motion profile, and completes the fitting of two motion profiles, chooses change of scale matrix, is generated using the matrix
Visible images and infrared image to be fused；
Step 4.3: the main control chip further control the image co-registration processing unit in FPGA to the visible images with
And infrared image carries out the operation such as brightness regulation, denoising, centre registration, fusion and image enhancement, wherein described image fusion
Processing unit includes DSP, FLASH and dimension correction memory；The FPGA combination dimension correction memory is completed red jointly
The detail extraction and contours extract of outer image, and complete to be registrated geometric scale transformation between spectrum picture and infrared image,
And image detail and profile merge；The DSP connection image encoder, and the RAM in connection FLASH and FPGA is combined,
For by treated digital video signal combine row, field sync signal synthesize analog video signal and drive so as to
In display；
Step 4.4: when main control chip control carries out the visible images and infrared image merges, described image is melted
It closes processing unit and nonoverlapping piece is each separated into the visible images and infrared image, calculate separately information therein
The visible images and infrared image, are divided into the image of different scale, the FPGA is not by amount using gaussian pyramid
Extract minutia with scale, and assessment be weighted according to the information measure feature, finally use laplacian pyramid into
Row synthesis, forms new blending image；
Step 4.5: brightness detection being carried out to fused image, and is compared with a normal brightness, when described image brightness
When lower than the normal brightness, brightness of image is handled to reach the brightness value for being suitable for test；
Step 4.6: image denoising being carried out to fused image, described image is denoised only for the spectral information identification region
It is denoised, to reduce the operation consumption of the main control chip；
Step 4.7: image enhancement processing is carried out to fused image using adaptive image enhancement technology；
5. the working method of sewage treatment monitoring system according to claim 4, which is characterized in that in the step 5,
Non-uniform correction method is carried out to the image after the fusion treatment, is specifically included:
Step 5.1: before the multi-optical spectrum imaging system is for target area imaging, acquiring the multi-optical spectrum imaging system respectively
Each imaging band response data of the photosensitive member under each temperature value, and calculate separately each temperature section using following formula
Gain coefficient GijWith biasing coefficient Qij
Wherein Xij(H) and XijIt (L) is response of the pixel (i, j) under high temperature and low temperature homogeneous radiation background, V respectivelyHAnd VLPoint
It is not the average output of all pixels in the infrared camera；
Step 5.2: the main control chip of the imaging system is by the gain coefficient G of above-mentioned each temperature sectionijWith biasing coefficient QijIn real time
It stores to FPGA internal RAM, in case subsequent use；
Step 5.3: after the completion of the step 4, for fused image, utilizing the texture and edge feature pair of blending image
Spectral information identification region in blending image carries out depth recognition；
Step 5.4: the different spectral informations according to blending image are distributed, and target optical spectrum region is carried out image segmentation, are formed each
A characteristic area；
Step 5.5: the parallel processing capability based on FPGA respectively carries out each characteristic area of the blending image non-simultaneously
Uniformity correction；For each characteristic area, the main control chip calculates the mean temperature of each point in the characteristic area first,
Then according to the mean temperature, corresponding correction parameter is read from the RAM in the FPGA, and is completed according to the following formula
Nonuniformity correction
WhereinThe image that infrared detector exports under the conditions of expression Uniform Irradiation degree；
Step 5.6: the blending image after correction compensates boundary gray value using mean filter method.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110021031A (en) * | 2019-03-29 | 2019-07-16 | 中广核贝谷科技有限公司 | A kind of radioscopic image Enhancement Method based on image pyramid |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103034211A (en) * | 2012-12-19 | 2013-04-10 | 江南大学 | Wastewater treatment process monitoring system based on wireless network |
| CN103390281A (en) * | 2013-07-29 | 2013-11-13 | 西安科技大学 | Double-spectrum night vision instrument vehicle-mounted system and double-spectrum fusion design method |
| CN203396769U (en) * | 2013-08-08 | 2014-01-15 | 北京宇图天下软件有限公司 | 3S (remote sensing, global position system and geographical information system)-based automatic monitoring and alarming emergency treatment system for water pollution in drainage basin |
| CN105865723A (en) * | 2016-05-25 | 2016-08-17 | 山东中安科创光电科技有限公司 | Non-uniformity correction method for gas leakage detection and gas leakage detection device |
| CN106277566A (en) * | 2016-08-08 | 2017-01-04 | 深圳十方清新生态环保科技有限公司 | A kind of environment water in-situ purification system |
| CN106441804A (en) * | 2015-08-04 | 2017-02-22 | 宁波舜宇光电信息有限公司 | Resolving power testing method |
| CN106950197A (en) * | 2017-03-03 | 2017-07-14 | 环境保护部卫星环境应用中心 | The Remotely sensed acquisition methods, devices and systems of sewage draining exit polluted-water |
| WO2018068165A1 (en) * | 2016-10-14 | 2018-04-19 | 徐春艳 | Sewage discharge control system |
-
2018
- 2018-09-14 CN CN201811079648.7A patent/CN109064501A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103034211A (en) * | 2012-12-19 | 2013-04-10 | 江南大学 | Wastewater treatment process monitoring system based on wireless network |
| CN103390281A (en) * | 2013-07-29 | 2013-11-13 | 西安科技大学 | Double-spectrum night vision instrument vehicle-mounted system and double-spectrum fusion design method |
| CN203396769U (en) * | 2013-08-08 | 2014-01-15 | 北京宇图天下软件有限公司 | 3S (remote sensing, global position system and geographical information system)-based automatic monitoring and alarming emergency treatment system for water pollution in drainage basin |
| CN106441804A (en) * | 2015-08-04 | 2017-02-22 | 宁波舜宇光电信息有限公司 | Resolving power testing method |
| CN105865723A (en) * | 2016-05-25 | 2016-08-17 | 山东中安科创光电科技有限公司 | Non-uniformity correction method for gas leakage detection and gas leakage detection device |
| CN106277566A (en) * | 2016-08-08 | 2017-01-04 | 深圳十方清新生态环保科技有限公司 | A kind of environment water in-situ purification system |
| WO2018068165A1 (en) * | 2016-10-14 | 2018-04-19 | 徐春艳 | Sewage discharge control system |
| CN106950197A (en) * | 2017-03-03 | 2017-07-14 | 环境保护部卫星环境应用中心 | The Remotely sensed acquisition methods, devices and systems of sewage draining exit polluted-water |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110021031A (en) * | 2019-03-29 | 2019-07-16 | 中广核贝谷科技有限公司 | A kind of radioscopic image Enhancement Method based on image pyramid |
| CN110021031B (en) * | 2019-03-29 | 2023-03-10 | 中广核贝谷科技有限公司 | X-ray image enhancement method based on image pyramid |
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