CN109697693A - A method of it realizes based on big data spatial operation - Google Patents
A method of it realizes based on big data spatial operation Download PDFInfo
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- CN109697693A CN109697693A CN201811468540.7A CN201811468540A CN109697693A CN 109697693 A CN109697693 A CN 109697693A CN 201811468540 A CN201811468540 A CN 201811468540A CN 109697693 A CN109697693 A CN 109697693A
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- 238000012545 processing Methods 0.000 claims abstract description 32
- 238000012163 sequencing technique Methods 0.000 claims abstract description 10
- 238000000354 decomposition reaction Methods 0.000 claims abstract description 4
- 238000006243 chemical reaction Methods 0.000 claims description 10
- 238000011835 investigation Methods 0.000 claims description 7
- 230000002708 enhancing effect Effects 0.000 claims description 4
- 230000006837 decompression Effects 0.000 claims description 3
- 238000005259 measurement Methods 0.000 description 6
- 230000006835 compression Effects 0.000 description 2
- 238000007906 compression Methods 0.000 description 2
- 238000012217 deletion Methods 0.000 description 2
- 230000037430 deletion Effects 0.000 description 2
- 238000012876 topography Methods 0.000 description 2
- 238000012937 correction Methods 0.000 description 1
- 239000002537 cosmetic Substances 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformation in the plane of the image
- G06T3/40—Scaling the whole image or part thereof
- G06T3/4038—Scaling the whole image or part thereof for image mosaicing, i.e. plane images composed of plane sub-images
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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
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
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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
- G06T2207/20021—Dividing image into blocks, subimages or windows
Abstract
The present invention provides a kind of methods realized based on big data spatial operation, include the following steps: to obtain unpressed remote sensing image, unpressed remote sensing image is subjected to processing decomposition according to the time point of shooting, remote sensing image after processing is compressed by Standard division range and is exported to operation scheduler module, one group of calculation process module is at least set, operation scheduler module sequence reads compressed remote sensing image, and calculation process module is separately input into according to the rule of setting, the calculation process module carries out grey level histogram processing to input remote sensing image, sequencing according to processing is stored in local hard drive；One group of comparison module is at least set, the grey level histogram in local hard drive is obtained in sequence, grey level histogram is compared one by one, obtain each remote sensing image that grey level histogram has multiple identical boundary points, and spliced according to identical boundary and corresponding coding, obtain the continuous remote sensing image atlas of longitude and latitude.
Description
Technical field
The invention belongs to a kind of electronic map processing technology fields, and in particular to a kind of realize is based on big data spatial operation
Method.
Background technique
Remote sensing image is earth surface " photograph ", truly presents shape, size, color of earth surface object etc.
Information.This is easier to be accepted by the public than traditional map, and photomap has become important one of map type.Remote sensing shadow
There is information abundant as upper, these earth resources informations can play in fields such as agricultural, forestry, water conservancy, ocean, ecological environments
Important function.
The display of existing remote sensing image such as carries out radiant correction to remote sensing images and geometry entangles by special processing
Just, image cosmetic, projective transformation, inlay, feature extraction, classification and it is various special topic processing etc. sequence of operations, then show
Over the display.Traditional remote sensing image needs to carry out artificial division region, needs to be arranged on the boundary in region bright in acquisition
Aobvious boundary, then subregion carries out data acquisition, is spliced according to boundary, it is relatively flat that this mode is only suitable for topography
Area, however, sharp can not be carried out with the aforedescribed process for the area of topography complexity.
Summary of the invention
In view of this, there is provided a kind of methods realized based on big data spatial operation for the main object of the present invention.
Its specific technical solution is as follows:
A method of it realizes based on big data spatial operation, includes the following steps: to obtain unpressed remote sensing image, it will not
The remote sensing image of compression carries out processing decomposition according to the time point of shooting, and the remote sensing image after processed is pressed Standard division range
It compresses and exports to operation scheduler module, one group of calculation process module is at least set, after operation scheduler module sequence reads compression
Remote sensing image, and be separately input into calculation process module according to the rule of setting, the calculation process module is distant to inputting
Feel striograph and carry out grey level histogram processing, the sequencing according to processing is stored in local hard drive；
One group of comparison module is at least set, each calculation process module is corresponded to, obtains the gray scale in local hard drive in sequence
Histogram compares grey level histogram one by one, obtains each remote sensing shadow that grey level histogram has multiple identical boundary points
As figure, and spliced according to identical boundary and corresponding coding, obtains the continuous remote sensing image atlas of longitude and latitude.
Further, the step of calculation process module carries out grey level histogram processing to input remote sensing image is such as
Under: the remote sensing image of input is unziped it, piecemeal is carried out according to the rule of setting to the remote sensing image after decompression,
Different sub-blocks is stored in caching, multiple operation threads are opened, obtains the data of each sub-block respectively, counts sub-block data
The number of pixels of interior each grey level is translated to obtain the grey level histogram of a sub-block according to the rule of setting is counter,
Each sub-block is merged to obtain the grey level histogram of each remote sensing image, obtained grey level histogram is increased
Strength reason, encodes enhanced grey level histogram, and the sequencing according to processing is stored in local hard drive.
Further, described the step of being compared one by one to grey level histogram, is as follows:
Sequence obtains the grey level histogram in local hard drive, using the first width grey level histogram as template, one by one will in sequence
Remaining grey level histogram is compared with template, obtains whether having multiple identical boundary points；Then according to same edge
Boundary carries out corresponding coding and is stored in ontology hard disk；Then sequence obtains the second width grey level histogram as template and so on.
Further, further include more than at least two width grey level histogram multiple spot covering it is identical when, retain it is therein
One, by remaining deletion.
It further, further include after carrying out coordinate conversion and format conversion to the continuous remote sensing image atlas of acquisition longitude and latitude
Imported into database, in the database according to newest remote sensing image atlas, according to the continuity of longitude and latitude by remote sensing shadow
As exporting by Standard division range, field operation measurement investigation base map is produced.
The invention has the benefit that by acquisition remote sensing image atlas, by big data method to remote sensing image into
Row operation, obtaining, there is the remote sensing image on the identical boundary of multiple points to be spliced, and then carry out coordinate conversion and format conversion
Importeding into database afterwards, in the database according to newest remote sensing image atlas, according to the continuity of longitude and latitude by remote sensing
Image is exported by Standard division range, produces field operation measurement investigation base map.This method is compared with the traditional technology, and is not had to setting and is surveyed
Boundary is measured, the splicing of measurement investigation base map can be completed.
Figure of description
Below in conjunction with attached drawing, the present invention will be described in detail.
Fig. 1 is flow chart of the method for the present invention；
Fig. 2 is the method flow diagram of grey level histogram processing in the present invention.
Specific embodiment
Below in conjunction with attached drawing and specific embodiment, the present invention will be described in detail, herein illustrative examples of the invention
And explanation is used to explain the present invention, but not as a limitation of the invention.
Referring to Fig.1, a method of realize based on big data spatial operation, include the following steps: to obtain unpressed distant
Feel striograph, unpressed remote sensing image is subjected to processing decomposition according to the time point of shooting, the remote sensing shadow after processing
As figure is compressed by Standard division range and is exported to operation scheduler module, one group of calculation process module, operation scheduler module are at least set
Sequence reads compressed remote sensing image, and is separately input into calculation process module according to the rule of setting, at the operation
It manages module and grey level histogram processing is carried out to input remote sensing image, the sequencing according to processing is stored in local hard drive；Extremely
One group of comparison module is set less, corresponds to each calculation process module, obtains the grey level histogram in local hard drive in sequence,
Grey level histogram is compared one by one, obtains each remote sensing image that grey level histogram has multiple identical boundary points, and
Spliced according to identical boundary and corresponding coding, obtains the continuous remote sensing image atlas of longitude and latitude.
Referring to Fig. 2, the calculation process module is as follows to the step of remote sensing image carries out grey level histogram processing is inputted:
In Fig. 2, it is provided with N number of thread, according to shown in Fig. 2, the remote sensing image of input is unziped it, to distant after decompression
Feel striograph and carry out piecemeal according to the rule of setting, different sub-blocks is stored in caching, multiple operation threads are opened, respectively
The data of the one one sub-block are obtained, the number of pixels of the first grey level in sub-block data is counted, to obtain the first sub-block
Grey level histogram, enhancing processing is carried out to the first obtained grey level histogram, enhanced grey level histogram is encoded,
Sequencing according to processing is stored in local hard drive；The data of the second sub-block are obtained respectively, count second in sub-block data
The number of pixels of grey level increases the second obtained grey level histogram to obtain the grey level histogram of the second sub-block
Strength reason, encodes enhanced grey level histogram, and the sequencing according to processing is stored in local hard drive, obtains respectively
The data of N sub-block count the number of pixels of the N grey level in sub-block data, to obtain the intensity histogram of N sub-block
Figure, carries out enhancing processing to obtained N grey level histogram, encodes to enhanced grey level histogram, according to processing
Sequencing is stored in local hard drive.
The data of each sub-block are obtained respectively, the number of pixels of each grey level in sub-block data are counted, to obtain
The grey level histogram for taking a sub-block is translated according to the rule of setting is counter, each sub-block is merged to obtain each distant
The grey level histogram for feeling striograph, carries out enhancing processing to obtained grey level histogram, carries out to enhanced grey level histogram
Coding, the sequencing according to processing are stored in local hard drive.
Described the step of being compared one by one to grey level histogram, is as follows:
Sequence obtains the grey level histogram in local hard drive, using the first width grey level histogram as template, one by one will in sequence
Remaining grey level histogram is compared with template, obtains whether having multiple identical boundary points；Then according to same edge
Boundary carries out corresponding coding and is stored in ontology hard disk；Then sequence obtains the second width grey level histogram as template, and in sequence one
One remaining grey level histogram is compared with template, obtains whether having multiple identical boundary points；Then according to phase
Corresponding coding, which is carried out, with boundary is stored in ontology hard disk；··· ；Then sequence obtains N width grey level histogram as template,
Remaining grey level histogram is compared one by one with template in sequence, obtains whether there are multiple identical boundary points；Then
Ontology hard disk is stored according to corresponding coding is carried out with identical boundary.
Multiple threads progress among the above, can also opened while being handled, by taking N number of thread as an example, sequence obtains this
Grey level histogram in ground hard disk in sequence one by one will be remaining using the first width grey level histogram as the template of first thread
Grey level histogram be compared with template, obtain whether have multiple identical boundary points；Then according to identical boundary into
The corresponding coding of row is stored in ontology hard disk；Using the second width grey level histogram as the template of the second thread, one by one will in sequence
Remaining grey level histogram is compared with template, obtains whether having multiple identical boundary points；Then according to same edge
Boundary carries out corresponding coding and is stored in ontology hard disk；；··· ；Then sequence obtains N width grey level histogram as n-th line
Remaining grey level histogram is compared with template one by one in sequence for the template of journey, obtains whether having multiple same edges
Boundary's point；Then corresponding coding deposit ontology hard disk is carried out according to identical boundary.
Among the above, compared each other again between each thread.
Among the above, when the grey level histogram multiple spot covering more than at least two width is identical, retain one of those, it will
Remaining deletion.
After to the continuous remote sensing image atlas progress coordinate conversion of longitude and latitude and format conversion is obtained
It imported into database, in the database according to newest remote sensing image atlas, according to the continuity of longitude and latitude by remote sensing image
It is exported by Standard division range, produces field operation measurement investigation base map.
The present invention carries out operation to remote sensing image by acquisition remote sensing image atlas, by big data method, obtains tool
There is the remote sensing image on the identical boundary of multiple points to be spliced, then carries out coordinate conversion with after format conversion and imported into data
In library, in the database according to newest remote sensing image atlas, remote sensing image is pressed into Standard division range according to the continuity of longitude and latitude
Field operation measurement investigation base map is produced in output.This method is compared with the traditional technology, and does not have to setting Measured Boundary, can be complete
At the splicing of measurement investigation base map.
Technical solution disclosed in the embodiment of the present invention is described in detail above, specific implementation used herein
Example is expounded the principle and embodiment of the embodiment of the present invention, and the explanation of above embodiments is only applicable to help to understand
The principle of the embodiment of the present invention；At the same time, for those skilled in the art is being embodied according to an embodiment of the present invention
There will be changes in mode and application range, in conclusion the content of the present specification should not be construed as to limit of the invention
System.
Claims (4)
1. a kind of method realized based on big data spatial operation, which comprises the steps of: obtain unpressed distant
Feel striograph, unpressed remote sensing image is subjected to processing decomposition according to the time point of shooting, the remote sensing shadow after processing
As figure is compressed by Standard division range and is exported to operation scheduler module, one group of calculation process module, operation scheduler module are at least set
Sequence reads compressed remote sensing image, and is separately input into calculation process module according to the rule of setting, at the operation
It manages module and grey level histogram processing is carried out to input remote sensing image, the sequencing according to processing is stored in local hard drive；
One group of comparison module is at least set, each calculation process module is corresponded to, obtains the gray scale in local hard drive in sequence
Histogram compares grey level histogram one by one, obtains each remote sensing shadow that grey level histogram has multiple identical boundary points
As figure, and spliced according to identical boundary and corresponding coding, obtains the continuous remote sensing image atlas of longitude and latitude.
2. method of the realization based on big data spatial operation according to claim 1, which is characterized in that the calculation process
The step of module carries out grey level histogram processing to input remote sensing image is as follows: decompressing to the remote sensing image of input
Contracting carries out piecemeal according to the rule of setting to the remote sensing image after decompression, different sub-blocks is stored in caching, is opened
Multiple operation threads obtain the data of each sub-block respectively, count the number of pixels of each grey level in sub-block data, from
And the grey level histogram of a sub-block is obtained, it is translated according to the rule of setting is counter, each sub-block is merged to obtain every
The grey level histogram of one remote sensing image carries out enhancing processing to obtained grey level histogram, to enhanced grey level histogram
It is encoded, the sequencing according to processing is stored in local hard drive.
3. method of the realization based on big data spatial operation according to claim 1, which is characterized in that described straight to gray scale
The step of side's figure is compared one by one is as follows:
Sequence obtains the grey level histogram in local hard drive, using the first width grey level histogram as template, one by one will in sequence
Remaining grey level histogram is compared with template, obtains whether having multiple identical boundary points；Then according to same edge
Boundary carries out corresponding coding and is stored in ontology hard disk；Then sequence obtains the second width grey level histogram as template and so on.
4. method of the realization based on big data spatial operation according to claim 1, which is characterized in that further include to acquisition
The continuous remote sensing image atlas of longitude and latitude carries out importeding into database after coordinate conversion and format conversion, in the database according to
According to newest remote sensing image atlas, remote sensing image is exported by Standard division range according to the continuity of longitude and latitude, produces field operation survey
Amount investigation base map.
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| CN111565220A (en) * | 2020-04-24 | 2020-08-21 | 中国科学院空天信息创新研究院 | Remote sensing image data quick access method and system |
| CN113807171A (en) * | 2021-08-10 | 2021-12-17 | 三峡大学 | Text classification method based on semi-supervised transfer learning |
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| CN113807171A (en) * | 2021-08-10 | 2021-12-17 | 三峡大学 | Text classification method based on semi-supervised transfer learning |
| CN113807171B (en) * | 2021-08-10 | 2023-09-29 | 三峡大学 | Text classification method based on semi-supervised transfer learning |
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