CN107610054A - A kind of preprocess method of remote sensing image data - Google Patents
A kind of preprocess method of remote sensing image data Download PDFInfo
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Abstract
The present invention provides a kind of preprocess method of remote sensing image data, including：Parse the essential information of some remote sensing images and preserve into tables of data；Start at least two first processes, the essential information of each remote sensing image in tables of data is obtained by each first process, radiation calibration and atmospheric correction are carried out to all remote sensing images parallel；Remote sensing image is divided into some imagery zones；Start at least two second processes, the object coordinates of each imagery zone are obtained by each second process, ortho-rectification is carried out to all imagery zones parallel.This method provided by the invention, when carrying out radiation calibration with atmospheric correction to multiple remote sensing images, the data of multiple remote sensing images are handled simultaneously respectively by multiple processes, when carrying out ortho-rectification to remote sensing image, multiple imagery zones in remote sensing image are handled simultaneously respectively by multiple processes, so as to improve speed and efficiency to remote sensing image data pretreatment.
Description
Technical field
The present invention relates to technical field of image processing, more particularly, to a kind of preprocess method of remote sensing image data.
Background technology
Remote sensing technology is the theory according to electromagnetic wave, and distant object is radiated and reflected using various sensor apparatus
Electromagnetic wave information is collected, handled, and the integrated technology being finally imaged.
At present, the application of various information brings the requirement of mass data processing, and remote sensing image data is also progressively presented
The features such as multi-source, multiple dimensioned, multidate, Global coverage and high-resolution, the data volume of remotely-sensed data is in explosive increase；Together
When, in the acquisition process of remote sensing image, the influence for the factors such as optical lens distorts, air and uneven illumination are even is frequently subjected to,
The remote sensing image of acquisition can not be used directly, and most of remote sensing image directly provided is essentially all without pretreatment
, it is necessary to carry out radiation calibration is converted into absolute brightness value by original DN values, eliminate the influence of sensor error；Need to carry out
Radiance is converted to earth's surface actual reflectance by atmospheric correction, eliminates the shadow of reflection, scattering and absorption to reflectivity of air
Ring；It is also required to carry out ortho-rectification simultaneously, image point displacement caused by modifying factor hypsography and sensor error, ensures image
Accuracy coordinate, how fast and effeciently to realize that remote sensing image pretreatment is important prerequisite that remote sensing image uses, and remote sensing number
According to the important leverage of analysis and application, while also have become what the urgent need that current remote sensing image commercial application is faced solved
Challenge.
The existing preprocess method to all kinds of remote sensing images, the method that the scape remote sensing image of generally use one is gradually handled,
When need remote sensing image to be processed it is a fairly large number of when, the efficiency of this processing method is low, and enters to remote sensing image
When row ortho-rectification, because data volume is big, the processing to the remote sensing image of a scape needs long time, therefore, existing
Remote sensing image preprocess method existing for the shortcoming such as speed is slow, efficiency is low.
The content of the invention
In order to overcome above mentioned problem or solve the above problems at least in part, the present invention provides a kind of remote sensing image data
Preprocess method.
According to an aspect of the present invention, there is provided a kind of preprocess method of remote sensing image data, including：Parse some distant
Feel the essential information of image and preserve into tables of data；Start at least two first processes, obtained by each first process
The essential information of each remote sensing image in tables of data, radiation calibration and atmospheric correction are carried out to all remote sensing images parallel；Will be distant
Sense image is divided into some imagery zones；Start at least two second processes, each image is obtained by each second process
The object coordinates in region, ortho-rectification is carried out to all imagery zones parallel.
Wherein, tables of data includes processing mark, and the processing identifies the state for marking corresponding remote sensing image, the state
To carry out the processing state of radiation calibration and atmospheric correction to remote sensing image.
Wherein, radiation calibration and atmospheric correction are carried out to all remote sensing images parallel, including：For any first process with
And remote sensing image corresponding to any first process, according to the essential information of remote sensing image, radiation calibration is carried out to remote sensing image；Root
The result of radiation calibration is carried out according to the essential information of remote sensing image and to remote sensing image, atmospheric correction is carried out to remote sensing image.
Wherein, radiation calibration is carried out to remote sensing image, including：According to the essential information of remote sensing image, remote sensing image is obtained
Temporal information and original DN values；According to the temporal information of remote sensing image, extracted from database remote sensing image yield value and
Deviant；The air top layer reflectivity of remote sensing image is obtained according to the yield value of remote sensing image, deviant and original DN values.
Wherein, atmospheric correction is carried out to remote sensing image, including：According to needed for the essential information of remote sensing image obtains 6S models
Parameter；Parameter is input to 6S models, the atmospheric correction parameter of remote sensing image is obtained based on 6S models；According to remote sensing image
Air top layer reflectivity and atmospheric correction parameter, obtain the pixel correction value of each pixel in remote sensing image；By in remote sensing image
The pixel correction value of each pixel expands preset multiple, and is assigned to the pixel value of each pixel in remote sensing image.
Wherein, remote sensing image is divided into some imagery zones, including：Remote sensing image is carried out using parallel as cut-off rule
Division, for any cut-off rule, the region that is formed between the cut-off rule that any cut-off rule is adjacent with any bar cut-off rule as
Imagery zone, and the default number of degrees are differed between any adjacent cut-off rule.
Wherein, the object coordinates of each imagery zone are obtained by each second process, including：Enter for any second
Imagery zone corresponding to journey and any second process, longitude and latitude coordinate information in imagery zone, obtain image
The longitude and latitude of each pixel in region；By extracting the Law of DEM Data of imagery zone, obtain in imagery zone
The height value of each pixel.
Wherein, ortho-rectification is carried out to imagery zone parallel, including：For any second process and any second process
Corresponding imagery zone, the object coordinates of each pixel in imagery zone are converted to the object coordinates of regularization；By regularization
Object coordinates be input to rational polynominal function model, obtain the image space coordinate of regularization；The image space coordinate of regularization is turned
It is changed to the image space coordinate of each pixel in target image region.
Another aspect of the present invention, there is provided a kind of computer program product, the computer program product are non-including being stored in
Computer program in transitory computer readable storage medium, the computer program include programmed instruction, when the programmed instruction quilt
When computer performs, computer is set to perform above-mentioned method.
Another aspect of the present invention, there is provided a kind of non-transient computer readable storage medium storing program for executing, the non-transient computer are readable
Storage medium stores computer program, and the computer program makes computer perform above-mentioned method.
The preprocess method of a kind of remote sensing image data provided by the invention, by the basic letter for parsing some remote sensing images
Cease and preserve into tables of data；Start at least two first processes, radiation calibration and air are carried out to all remote sensing images parallel
Correction；Remote sensing image is divided into some imagery zones；Start at least two second processes, all imagery zones are carried out parallel
Ortho-rectification；So that when carrying out radiation calibration with atmospheric correction to multiple remote sensing images, by multiple processes respectively to multiple
The data of remote sensing image are handled simultaneously, and when carrying out ortho-rectification to remote sensing image, by multiple processes respectively to distant
Multiple imagery zones are handled simultaneously in sense image, so as to improve speed and efficiency to remote sensing image data pretreatment.
Brief description of the drawings
, below will be to embodiment or prior art in order to illustrate more clearly of technical scheme of the invention or of the prior art
The required accompanying drawing used is briefly described in description, it should be apparent that, drawings in the following description are the one of the present invention
A little embodiments, for those of ordinary skill in the art, on the premise of not paying creative work, can also be according to these
Accompanying drawing obtains other accompanying drawings.
Fig. 1 is the flow chart according to the preprocess method of the remote sensing image data of the embodiment of the present invention；
Fig. 2 is the schematic diagram that input database is parsed according to the essential information of the remote sensing image of the embodiment of the present invention；
Fig. 3 is the schematic diagram of data processing in the radiation calibration according to the embodiment of the present invention；
Fig. 4 is the schematic diagram according to the atmospheric correction 6S model occupation modes of the embodiment of the present invention；
Fig. 5 is the schematic diagram of data processing in the atmospheric correction according to the embodiment of the present invention.
Embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with attached in the embodiment of the present invention
Figure, the technical scheme in the present invention is clearly and completely described, it is clear that described embodiment is a part of the invention
Embodiment, rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art are not making wound
The every other embodiment obtained under the premise of the property made work, belongs to the scope of protection of the invention.
In one embodiment of the invention, with reference to figure 1, there is provided a kind of preprocess method of remote sensing image data, including：
S11, parse the essential information of some remote sensing images and preserve into tables of data；S12, start at least two first processes, pass through
Each first process obtains the essential information of each remote sensing image in tables of data, parallel all remote sensing images radiate and determined
Mark and atmospheric correction；S13, remote sensing image is divided into some imagery zones；S14, start at least two second processes, by every
One the second process obtains the object coordinates of each imagery zone, carries out ortho-rectification to all imagery zones parallel.
Specifically, the limitation due to remote sensing system on space, wave spectrum, time and radiometric resolution, it is difficult to accurately
Complicated earth's surface information is recorded, thus error is inevitably present in the acquisition process of remote sensing image.These errors reduce
The quality of remote sensing image data, have impact on the precision of graphical analysis, therefore, before the image analysing computer and use of reality, have
Necessity pre-processes to remote sensing image data.Also referred to as image rectification and reconstruction, it is led for the pretreatment of remote sensing image data
Syllabus is that the geometry corrected in raw video deforms with radiation.
ID number, central point longitude and latitude, the sensor volume of the remote sensing image are contained in the subsidiary xml document of remote sensing image
Number, the information such as solar azimuth, by parsing this document, essential information of the above about remote sensing image can be obtained, can be used for
Radiation calibration and atmospheric correction are carried out to remote sensing image, these essential informations are preserved into tables of data, in case inquiry and batch
Change is handled.For example, as shown in Fig. 2 establish a LV1A table in database, using ID number as major key, in addition to central point longitude and latitude
The fields such as degree, sensor number, sun altitude, solar azimuth, RESULT, by parsing xml document, automatically by image
Metadata information be stored in a manner of one records in LV1A tables, the corresponding record of metadata information of image.
Start the process of multiple radiation calibrations and atmospheric correction simultaneously, each process obtains not identical by other in tables of data
The essential information for the remote sensing image that process obtains, radiation calibration and air school are carried out to remote sensing image according to essential information
Just, so, several remote sensing images can be handled respectively simultaneously in the presence of several processes simultaneously, its treatment effeciency is in theory
On be one process processing several times.
Generally, the size of remote sensing image is bigger, comprising data volume it is very big, if to whole remote sensing shadow
The data of picture carry out ortho-rectification, it is possible that the situation that internal memory overflows, it is common practice to be divided into remote sensing image more
Individual imagery zone, one by one successively to each imagery zone carry out ortho-rectification, with complete school is just penetrated to whole remote sensing image
Just.In the present embodiment, remote sensing image is divided into more and smaller imagery zones, ensured in some processes simultaneously to corresponding
Be not in that internal memory overflows when the imagery zone of quantity carries out ortho-rectification.
Start the process of multiple ortho-rectifications simultaneously, each process obtains the object coordinates of an imagery zone, according to shadow
As region object coordinates to remote sensing image carry out ortho-rectification, likewise, can simultaneously exist several processes simultaneously it is right respectively
Several imagery zones carry out ortho-rectification.
The present embodiment parses the essential information of some remote sensing images and preserved into tables of data；Start at least two first to enter
Journey, radiation calibration and atmospheric correction are carried out to all remote sensing images parallel；Remote sensing image is divided into some imagery zones；Start
At least two second processes, ortho-rectification is carried out to all imagery zones parallel；So as to be radiated to multiple remote sensing images
When calibration is with atmospheric correction, the data of multiple remote sensing images are handled simultaneously respectively by multiple processes, and to remote sensing
When image carries out ortho-rectification, multiple imagery zones in remote sensing image are handled simultaneously respectively by multiple processes, so as to
Improve the speed and efficiency to remote sensing image data pretreatment.
Based on above example, tables of data, which includes handling, to be identified, and processing mark is used for the shape for marking corresponding remote sensing image
State, state are that the processing state of radiation calibration and atmospheric correction is carried out to remote sensing image.
For example, the RESULT fields in the LV1A tables of above-described embodiment, are the processing mark in tables of data, with value for 0
Represent and wait radiation calibration and atmospheric correction, be worth and represent to handle error for -1, be worth and represent radiation and atmospheric correction completion for 1.When
When the value that process reads RESULT fields is 0, then the data message of respective record is read, and according to data message to corresponding
Remote sensing image carries out radiation calibration and atmospheric correction；When the value that process reads RESULT fields is 1, then without processing；
When the value that process reads RESULT fields is -1, then processing is re-started to the data of corresponding remote sensing image or carried out
Other special processing.
Based on above example, parallel all remote sensing images are carried out with radiation calibration and atmospheric correction, including：For any
Remote sensing image corresponding to first process and any first process, according to the essential information of remote sensing image, remote sensing image is carried out
Radiation calibration；The result of radiation calibration is carried out according to the essential information of remote sensing image and to remote sensing image, remote sensing image is carried out
Atmospheric correction.
In the present embodiment, radiation calibration is all from tables of data with the required partial parameters during atmospheric correction, and radiation is fixed
Mark is successively completed with atmospheric correction in a process, can improve the efficiency of data processing.
Based on above example, radiation calibration is carried out to remote sensing image, including：According to the essential information of remote sensing image, obtain
Take the temporal information of remote sensing image and original DN values；According to the temporal information of remote sensing image, remote sensing image is extracted from database
Yield value and deviant；The air top layer of remote sensing image is obtained according to the yield value of remote sensing image, deviant and original DN values
Reflectivity.Atmospheric correction is carried out to remote sensing image, including：Ginseng according to needed for the essential information of remote sensing image obtains 6S models
Number；Parameter is input to 6S models, the atmospheric correction parameter of remote sensing image is obtained based on 6S models；According to the air of remote sensing image
Top layer reflectivity and atmospheric correction parameter, obtain the pixel correction value of each pixel in remote sensing image；Will be each in remote sensing image
The pixel correction value of pixel expands preset multiple, and is assigned to the pixel value of each pixel in remote sensing image.
Specifically, the temporal information of remote sensing image is first read from tables of data, using the temporal information of remote sensing image from number
According to the parameter information extracted in storehouse required for radiation calibration：Yield value gain and deviant offset, read in essential information
Original DN values deposit database in, and pass through equation below and calculate air top layer reflectivity Le：
Le=gain*DN+offset,
Wherein, gain is yield value, and offset is deviant, the brightness value that it is remote sensing image picture element that DN, which is,.
As shown in figure 3, GDAL (Geospatial Data Abstraction Library) is recycled by database
Original DN values are converted into LeValue, original DN and LeValue is stored in database, and transfer process can mass processing.
Then using the information of the existing information of remote sensing image and part acquiescence as input parameter, by being obtained after 6S models
To the parameter information of atmospheric correction.As shown in figure 4, entitled in and out two texts are automatically generated using program (such as C#)
File, wherein out file contents are sky, and (value is the geometrical condition IGEOM for containing in files required for 6S models calculate
0, and input solar zenith angle, sun altitude, satellite zenith angle, elevation of satellite, month and the date letter of remote sensing image
Breath), (1 represents the torrid zone to climate type IDATM；2 represent middle latitude summer；3 represent middle latitude winter；4 with representing proximal pole summers；5
With representing proximal pole winter), aerosol type IAER (acquiescence 1, represent continent type), visibility V (acquiescence 40), target height above sea level
The information such as XPS (by reading RPC file acquisitions).The 6S models of fortran compilings are called, using in files as input file,
Out files automatically generate atmospheric correction parameter x as output file in out filesa、xb、xc, recycle equation below meter
Calculate pixel correction value arc：
Wherein, xa、xb、xcFor atmospheric correction parameter, LeFor air top layer reflectivity.
Likewise, as shown in figure 5, using GDAL by the L in databaseeValue is converted into arc values, LeValue and arc values store
In database, transfer process can mass processing.It is each that arc expansion preset multiples (such as 10,000 times) are finally assigned to image
Pixel value completes image radiation calibration and atmospheric correction.
Based on above example, remote sensing image is divided into some imagery zones, including：Using parallel as cut-off rule to distant
Sense image is divided, and for any cut-off rule, will be formed between any cut-off rule cut-off rule adjacent with any bar cut-off rule
Region as imagery zone, and the default number of degrees are differed between any adjacent cut-off rule.
For example, in ortho-rectification process, in order to improve treatment effeciency, the object coordinates of pixel are stored in remote sensing image
In internal memory, by test, for 16 meters of remote sensing images of high score No.1, when all differing 0.01875 ° between adjacent segmentation line, just
It is not in internal memory spillover to penetrate in trimming process；The smaller default number of degrees are divided into by 0.01875 °, then by the preset degree
It is several to Remote Sensing Image Segmentation into some imagery zones, to meet the processes of multiple processing ortho-rectifications while when running, will not go out
Existing internal memory overflows.
Based on above example, the object coordinates of each imagery zone are obtained by each second process, including：For
Imagery zone corresponding to any second process and any second process, longitude and latitude coordinate letter in imagery zone
Breath, obtain the longitude and latitude of each pixel in imagery zone；By extracting the Law of DEM Data of imagery zone, obtain
The height value of each pixel in imagery zone.
Based on above example, ortho-rectification is carried out to imagery zone parallel, including：For any second process and appoint
Imagery zone corresponding to one second process, the object space that the object coordinates of each pixel in imagery zone are converted to regularization are sat
Mark；The object coordinates of regularization are input to rational polynominal function model, obtain the image space coordinate of regularization；By regularization
Image space Coordinate Conversion is the image space coordinate of each pixel in target image region.
Specifically, although the ortho-rectification comparison of multiplicative model is accurate, its parameter for needing is various and parameter acquiring
More difficult, that the present embodiment is taken is rational polynominal function (Rational Polynomial Camera, referred to as RPC)
Model carries out ortho-rectification, and the model calculation formula is as follows：
Wherein：
Ns(P, L, H)=c1+c2L+c3P+c4H+c5LP+c6LH+c7PH+c8L2+c9P2
+c10H2+c11PLH+c12L3+c13LP2+c14LH2+c15L2P+c16P3+c17PH2
+c18L2H+c19P2H+c20H3
Ds(P, L, H)=d1+d2L+d3P+d4H+d5LP+d6LH+d7PH+d8L2+d9P2
+d10H2+d11PLH+d12L3+d13LP2+d14LH2+d15L2P+d16P3+d17PH2
+d18L2H+d19P2H+d20H3
Nl(P, L, H)=a1+a2L+a3P+a4H+a5LP+a6LH+a7PH+a8L2+a9P2
+a10H2+a11PLH+a12L3+a13LP2+a14LH2+a15L2P+a16P3+a17PH2
+a18L2H+a19P2H+a20H3
Dl(P, L, H)=b1+b2L+b3P+b4H+b5LP+b6LH+b7PH+b8L2+b9P2
+b10H2+b11PLH+b12L3+b13LP2+b14LH2+b15L2P+b16P3+b17PH2
+b18L2H+b19P2H+b20H3
In above-mentioned calculating formula, ai, bi, ci, diFor RPC model coefficients (i=1,2 ..., 20), (P, L, H) is regularization
Object coordinates, (X, Y) are the image space coordinate of regularization, and its Regularization function is as follows：
Wherein,Dlon_scale、Dhei_off、Dhei_scaleFor the canonical of object coordinates
Change parameter；Soff、sscale、loff、lscaleFor the regularization parameter of image space coordinate.
In the object coordinates (D of imagery zone extraction pixellat, Dlon, Dhei) preserve afterwards into memory array, then basis
Above-mentioned formula calculates the object coordinates (P, L, H) of regularization, the image space coordinate (X, Y) of regularization successively, finally image space using just
Then change image space coordinate (s, l) of the inverse function of function by the image space Coordinate Conversion of regularization for pixel.In RPC model coefficients and just
Under the premise of then changing known to parameter, according to object coordinates (Dlat, Dlon, Dhei) calculate image space coordinate (s, l) process be RPC
Inverse transformation, a scape remote sensing image data is finally regenerated according to inverse transformation result and completes the ortho-rectification of image.
Another embodiment as the present invention, there is provided a kind of computer program product, the computer program product include
The computer program being stored on non-transient computer readable storage medium storing program for executing, the computer program include programmed instruction, work as program
Instruction is when being computer-executed, and computer is able to carry out the method that above-mentioned each method embodiment is provided, such as including：If parsing
The essential information of dry remote sensing image is simultaneously preserved into tables of data；Start at least two first processes, pass through each the first process
The essential information of each remote sensing image in tables of data is obtained, radiation calibration and atmospheric correction are carried out to all remote sensing images parallel；
Remote sensing image is divided into some imagery zones；Start at least two second processes, obtained by each second process each
The object coordinates of imagery zone, ortho-rectification is carried out to all imagery zones parallel.
Another embodiment as the present invention, there is provided a kind of non-transient computer readable storage medium storing program for executing, the non-transient meter
Calculation machine readable storage medium storing program for executing stores computer program, and the computer program is put forward the above-mentioned each method embodiment of computer execution
The method of confession, such as including：Parse the essential information of some remote sensing images and preserve into tables of data；Start at least two first
Process, the essential information of each remote sensing image in tables of data is obtained by each first process, parallel to all remote sensing images
Carry out radiation calibration and atmospheric correction；Remote sensing image is divided into some imagery zones；Start at least two second processes, pass through
Each second process obtains the object coordinates of each imagery zone, carries out ortho-rectification to all imagery zones parallel.
One of ordinary skill in the art will appreciate that：Realizing all or part of step of above method embodiment can pass through
The related hardware of computer program instructions is completed, and foregoing computer program can be stored in a computer-readable storage and be situated between
In matter, the computer program upon execution, execution the step of including above method embodiment；And foregoing storage medium includes：
ROM, RAM, magnetic disc or CD etc. are various can be with the medium of store program codes.
Through the above description of the embodiments, those skilled in the art can be understood that each embodiment can
Realized by the mode of software plus required general hardware platform, naturally it is also possible to pass through hardware.Based on such understanding, on
The part that technical scheme substantially in other words contributes to prior art is stated to embody in the form of software product, should
Computer software product can store in a computer-readable storage medium, such as ROM/RAM, magnetic disc, CD, including some fingers
Make to cause a computer equipment (can be personal computer, server, or network equipment etc.) to perform each implementation
Method described in some parts of example or embodiment.
What is finally illustrated is：The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although ginseng
The present invention is described in detail according to previous embodiment, it will be understood by those within the art that：It still can be with
Technical scheme described in foregoing embodiments is modified, or equivalent substitution is carried out to which part technical characteristic；And
These modifications are replaced, and the essence of appropriate technical solution is departed from the spirit and model of various embodiments of the present invention technical scheme
Enclose.
Claims (10)
- A kind of 1. preprocess method of remote sensing image data, it is characterised in that including：Parse the essential information of some remote sensing images and preserve into tables of data；Start at least two first processes, the basic of each remote sensing image in the tables of data is obtained by each first process Information, radiation calibration and atmospheric correction are carried out to all remote sensing images parallel；Remote sensing image is divided into some imagery zones；Start at least two second processes, the object coordinates of each imagery zone are obtained by each second process, it is parallel right All imagery zones carry out ortho-rectification.
- 2. according to the method for claim 1, it is characterised in that the tables of data includes processing and identified, the processing mark For marking the state of corresponding remote sensing image, the state is that the processing of radiation calibration and atmospheric correction is carried out to remote sensing image State.
- 3. according to the method for claim 1, it is characterised in that it is described parallel to all remote sensing images carry out radiation calibration with Atmospheric correction, including：For remote sensing image corresponding to any first process and any first process, according to the basic of the remote sensing image Information, radiation calibration is carried out to the remote sensing image；The result of radiation calibration is carried out according to the essential information of the remote sensing image and to the remote sensing image, to the remote sensing shadow As carrying out atmospheric correction.
- 4. according to the method for claim 3, it is characterised in that it is described to remote sensing image progress radiation calibration, including：According to the essential information of the remote sensing image, the temporal information of the remote sensing image and original DN values are obtained；According to the temporal information of the remote sensing image, the yield value and deviant of the remote sensing image are extracted from database；The air top layer that the remote sensing image is obtained according to the yield value of the remote sensing image, deviant and original DN values reflects Rate.
- 5. according to the method for claim 4, it is characterised in that it is described to remote sensing image progress atmospheric correction, including：Parameter according to needed for the essential information of the remote sensing image obtains 6S models；The parameter is input to the 6S models, the atmospheric correction parameter of the remote sensing image is obtained based on the 6S models；According to the air top layer reflectivity and atmospheric correction parameter of the remote sensing image, each pixel in the remote sensing image is obtained Pixel correction value；The pixel correction value of each pixel in the remote sensing image is expanded into preset multiple, and is assigned in the remote sensing image every The pixel value of one pixel.
- 6. according to the method for claim 1, it is characterised in that described that remote sensing image is divided into some imagery zones, bag Include：Remote sensing image is divided using parallel as cut-off rule, for any cut-off rule, by any cut-off rule with it is described The region formed between the adjacent cut-off rule of any bar cut-off rule differs as imagery zone between any adjacent cut-off rule The default number of degrees.
- 7. according to the method for claim 6, it is characterised in that described that each image area is obtained by each second process The object coordinates in domain, including：For imagery zone corresponding to any second process and any second process, according to the warp in the imagery zone Degree and latitude coordinate information, obtain the longitude and latitude of each pixel in the imagery zone；By extracting the Law of DEM Data of the imagery zone, the elevation of each pixel in the imagery zone is obtained Value.
- 8. according to the method for claim 7, it is characterised in that it is described that ortho-rectification is carried out to the imagery zone parallel, Including：The object coordinates of each pixel in the imagery zone are converted to the object coordinates of regularization；The object coordinates of the regularization are input to rational polynominal function model, obtain the image space coordinate of regularization；By the image space coordinate that the image space Coordinate Conversion of the regularization is each pixel in the target image region.
- 9. a kind of computer program product, it is characterised in that the computer program product includes being stored in non-transient computer Computer program on readable storage medium storing program for executing, the computer program include programmed instruction, when described program is instructed by computer During execution, the computer is set to perform the method as described in claim 1 to 8 is any.
- 10. a kind of non-transient computer readable storage medium storing program for executing, it is characterised in that the non-transient computer readable storage medium storing program for executing is deposited Computer program is stored up, the computer program makes the computer perform the method as described in claim 1 to 8 is any.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109376206A (en) * | 2018-09-13 | 2019-02-22 | 复旦大学 | The path optimal selection intelligent method of remote sensing image parallel processing based on data segmentation |
| CN109377476A (en) * | 2018-09-20 | 2019-02-22 | 中国农业大学 | The dynamic threshold acquisition methods and device of remote sensing image cloud detection characteristic parameter |
| CN110047049A (en) * | 2019-04-19 | 2019-07-23 | 西安航天恒星科技实业(集团)有限公司 | The compatible real-time quick radiation correction method of more stars |
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| CN112288641B (en) * | 2020-09-16 | 2024-05-17 | 江苏省气候中心 | Batch preprocessing method for high-resolution satellite image data |
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Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109376206A (en) * | 2018-09-13 | 2019-02-22 | 复旦大学 | The path optimal selection intelligent method of remote sensing image parallel processing based on data segmentation |
| CN109376206B (en) * | 2018-09-13 | 2021-06-22 | 复旦大学 | Intelligent path optimal selection method for remote sensing image parallel processing based on data segmentation |
| CN109377476A (en) * | 2018-09-20 | 2019-02-22 | 中国农业大学 | The dynamic threshold acquisition methods and device of remote sensing image cloud detection characteristic parameter |
| CN109377476B (en) * | 2018-09-20 | 2020-10-23 | 中国农业大学 | Method and device for acquiring dynamic threshold of cloud detection characteristic parameter of remote sensing image |
| CN110047049A (en) * | 2019-04-19 | 2019-07-23 | 西安航天恒星科技实业(集团)有限公司 | The compatible real-time quick radiation correction method of more stars |
| CN111597496A (en) * | 2020-05-18 | 2020-08-28 | 中国科学院空天信息创新研究院 | Rational polynomial coefficient-based single satellite-borne remote sensing image target height calculation method |
| CN112288641A (en) * | 2020-09-16 | 2021-01-29 | 江苏省气候中心 | High-resolution satellite image data batch preprocessing method |
| CN112288641B (en) * | 2020-09-16 | 2024-05-17 | 江苏省气候中心 | Batch preprocessing method for high-resolution satellite image data |
| CN112579677A (en) * | 2020-11-27 | 2021-03-30 | 福建省星云大数据应用服务有限公司 | Automatic processing method for satellite remote sensing image |
| CN112817918A (en) * | 2021-01-14 | 2021-05-18 | 厦门精图信息技术有限公司 | High-resolution three-number data conversion method, terminal equipment and storage medium |
| CN117152361A (en) * | 2023-10-26 | 2023-12-01 | 天津市滨海新区气象局(天津市滨海新区气象预警中心) | Remote sensing image visibility estimation method based on attention mechanism |
| CN117152361B (en) * | 2023-10-26 | 2024-01-30 | 天津市滨海新区气象局(天津市滨海新区气象预警中心) | Remote sensing image visibility estimation method based on attention mechanism |
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