CN105785369B - SAR image snow and ice cover information extracting method based on InSAR technologies - Google Patents
SAR image snow and ice cover information extracting method based on InSAR technologies Download PDFInfo
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- CN105785369B CN105785369B CN201610304072.4A CN201610304072A CN105785369B CN 105785369 B CN105785369 B CN 105785369B CN 201610304072 A CN201610304072 A CN 201610304072A CN 105785369 B CN105785369 B CN 105785369B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
- G01S13/9021—SAR image post-processing techniques
- G01S13/9023—SAR image post-processing techniques combined with interferometric techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
Abstract
The invention discloses a kind of SAR image snow and ice cover information extracting method based on InSAR technologies,By being pre-processed to several haplopia plural number SAR images without ice and snow information,Registration,Baseline estimations,And backscattering coefficient figure is obtained to the haplopia plural number SAR image progress radiation calibration of the information containing ice and snow,Two interference groups are chosen by the length of time reference line and Space Baseline in SAR image baseline information respectively again,First interference group is made up of the haplopia plural number SAR image of a width information containing ice and snow and a width without ice and snow information,Second interference group is made up of haplopia plural number SAR image of two width without ice and snow information,Calculate the coherence factor of two images in each interference group respectively by coherence factor formula again,Obtain coherence factor figure,Eventually through the backscattering coefficient figure given threshold to two width coherence factor figures and the SAR image of information containing ice and snow,Realize the extraction of snow and ice cover information.
Description
Technical field
The invention belongs to technical field of image processing, more specifically, is related to a kind of SAR figures based on InSAR technologies
As snow and ice cover information extracting method.
Background technology
Cryosphere affects the various aspects such as the job facilities of the mankind, communications and transportation, electric power, production, economic military activity,
Its change will circulate to water resource and climate change produces profound influence.In addition, ice disaster is made to the normal life of the mankind
Into influence and disaster be also huge, and power network is one of field that most serious is influenceed by ice damage.Power network is modern society
The guarantee of normal operation, and China is one of more serious several countries of power network icing disaster, in recent decades, large area ice
Snow disaster evil happens occasionally throughout the country.There occurs 50 years one ice damages met, more than ten confessions in Hunan Hubei during the Spring Festival in 2005
Electric line is paralysed.Occur in the large area icing disaster of 2008, coverage covers south China most area ten
Several provinces.The transmission of electricity corridor icing detection of early stage relies primarily on national grid at the sight ice station that each transmission line of electricity is set up, but
This observation procedure consumes substantial amounts of manpower and materials, and is greatly constrained by geographical environment, can not be to the mountain area of High aititude
Comprehensively monitored with remote districts.Because microwave has the characteristic for penetrating sexual intercourse, therefore SAR imagings can not by accumulated snow
Area's cloud layer, haze etc. are influenceed, and developing direction is provided for ice and snow information monitoring.
Based on multipolarization, in SAR image ice and snow information extraction the methods of multidate, just with the amplitude of SAR image
Information.It is and larger for the complex region of atural object landform, local incident angle effects such as transmission of electricity corridors so that SAR image data
In backscattering coefficient reliability reduce, the accurate extraction to snow and ice cover information brings certain difficulty, in addition, SAR image
In contained phase information be not also utilized.And InSAR technologies fill the amplitude information in SAR image and phase information
Divide and utilize, the snow and ice cover information extraction for atural object and the complex region of landform provides new direction.
The accurate extraction to the atural objects such as transmission of electricity corridor and the complex region snow and ice cover information of landform is existing skill at present
Art needs the problem solved.
The content of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of SAR image ice and snow based on InSAR technologies
Coverage information extracting method, using High Resolution SAR Images, the region complex to atural object, landform, need not be by
DEM information can effectively reject shadow region, while solve the interference that the non-snow region of Low coherence is brought to ice and snow information extraction,
Ice and snow information extraction precision is improved, overcomes the shortcomings of snow and ice cover information extraction technology at this stage.
For achieving the above object, a kind of SAR image snow and ice cover information extraction side based on InSAR technologies of the present invention
Method, it is characterised in that comprise the following steps：
(1) pending original SAR image, is obtained
Obtain the haplopia plural number SAR image P of monitored area information containing snow and ice coversnow, and two width or two it is contained above
Monitored area but the haplopia plural number SAR image P without snow and ice cover informationk, k=1,2 ... represent comprising monitored area but are free of
The number of the haplopia plural number SAR image of snow and ice cover information；
(2), image preprocessing
To haplopia plural number SAR image PsnowMultiple look processing and radiation calibration are carried out, obtains backscattering coefficient intensity map
pwr；
Using ENVI softwares to several haplopia plural number SAR images PkIt is filtered, registering and baseline estimations, removes image spot
Spot noise, while obtain several haplopia plural number SAR images PkBetween baseline information；
(3), the selection of interference group
The baseline information obtained according to step (2), from several haplopia plural number SAR images PkIn, choose and haplopia plural number SAR
Image PsnowBetween time reference line and the most short width haplopia plural number SAR image of Space Baseline, then with haplopia plural number SAR image
PsnowCollectively as an interference group Z1；
The baseline information obtained according to step (2), from several haplopia plural number SAR images PkIt is middle respectively access time baseline with
Z1 is identical, and two relatively short width haplopia plural number SAR images of Space Baseline are as an interference group Z2；
(4) coherence factor figure, is generated
That reads in interference group Z1 each pixel point storage in two width haplopia plural number SAR images includes atural object amplitude and phase
The complex data S (m, n) of information, (m, n) are pixel point coordinates；
Calculate the coherence factor ρ (m, n) that two width haplopia plural number SAR images correspond to pixel point：
Wherein, S1(m, n) represents the complex data of the first width haplopia plural number SAR image pixel point storage, S2(m, n) is represented
The complex data of second width haplopia plural number SAR image pixel point storage, S1 *(m, n) and S2 *(m, n) represents S respectively1(m, n), S2
The conjugation of (m, n), ＜ ＞ represent desired value, andRepresent imageThe expectation of window
Value；
The coherence factor ρ (m, n) of pixel point is corresponded to further according to two width haplopia plural number SAR images, generates coherence factor figure
CC1；
Similarly, according to step (4) methods described, coherence factor figure CC is generated using interference group Z22；
(5) snow and ice cover frame, is generated
Set coherence factor figure CC1In threshold value be M1；Coherence factor figure CC1With coherence factor figure CC2Between phase responsibility
Number change given threshold is M2；The threshold interval for setting backscattering coefficient intensity map pwr is [p, q]；
Ice and snow region is judged according to the threshold value of setting, if pixel point (m, n) while meeting CC1(m, n) ＜ M1, CC2
(m,n)-CC1(m, n) ＞ M2, p ＜ pwr (m, n) ＜ q, then the pixel point (m, n) is determined as ice and snow, and to the pixel point assignment
1；If above three condition can not be met simultaneously, the pixel point (m, n) is determined as non-ice and snow, and to the pixel point assignment 0,
Finally give binaryzation snow and ice cover frame.
What the goal of the invention of the present invention was realized in：
SAR image snow and ice cover information extracting method of the invention based on InSAR technologies, by believing without ice and snow several
The haplopia plural number SAR image of breath is pre-processed, registration, baseline estimations, and the haplopia plural number SAR image of the information containing ice and snow is entered
Row radiation calibration obtains backscattering coefficient figure, then passes through the length of time reference line and Space Baseline in SAR image baseline information
Two interference groups are chosen respectively, and first interference group is by the haplopia plural number of a width information containing ice and snow and a width without ice and snow information
SAR image is formed, and second interference group is made up of haplopia plural number SAR image of two width without ice and snow information, then passes through phase responsibility
Number formula calculates the coherence factor of two images in each interference group respectively, coherence factor figure is obtained, eventually through to two width phases
The backscattering coefficient figure given threshold of responsibility number figure and the SAR image of information containing ice and snow, realizes the extraction of snow and ice cover information.
Meanwhile the SAR image snow and ice cover information extracting method of the invention based on InSAR technologies also has following beneficial effect
Fruit：
(1) the defects of, being judged by accident instant invention overcomes ice and snow region caused by complicated landform, atural object, for complex topographic area
The snow and ice cover information extraction in domain still keeps higher precision；
(2), the present invention does not need the assistance data such as DEM, you can realizes to shade in SAR image, folded the unreliable area such as covers
Domain is rejected, and reduces the requirement of assistance data so that the scope of application is more extensive.
(3), present invention tool has large area, real-time monitoring capability and low cost under conditions of degree of precision is kept
Feature；
Brief description of the drawings
Fig. 1 is the SAR image snow and ice cover information extracting method flow chart of the invention based on InSAR technologies；
Fig. 2 is the backscattering coefficient intensity map pwr of the SAR image of information containing ice and snow
Fig. 3 is baseline information between several haplopia plural number SAR images obtained by baseline estimations；
Fig. 4 is coherence factor figure；
Fig. 5 is part snow and ice cover information extraction result figure；
Fig. 6 is optical imagery snow and ice cover information extraction figure corresponding with the SAR image same time.
Embodiment
The embodiment of the present invention is described below in conjunction with the accompanying drawings, so as to those skilled in the art preferably
Understand the present invention.Requiring particular attention is that in the following description, when known function and the detailed description of design perhaps
When can desalinate the main contents of the present invention, these descriptions will be ignored herein.
Embodiment
In order to facilitate description, first the relevant speciality term occurred in embodiment is illustrated：
SAR(Synthetic Aperture Radar)：Synthetic aperture radar；
INSAR(Interferometric Synthetic Aperture Radar)：Interference synthetic aperture radar；
Fig. 1 is the SAR image snow and ice cover information extracting method flow chart of the invention based on InSAR technologies.
In the present embodiment, as shown in figure 1, a kind of SAR image snow and ice cover information based on InSAR technologies of the present invention carries
Method is taken, is comprised the following steps：
S1, obtain pending original SAR image
In the present embodiment, a certain monitored area scope is：102.3368 ° of E-102.3886 ° of E of longitude, latitude
27.7325°N-27.6964°N.Obtain spaceborne Terra-SAR, X-band, HH polarization, range resolution 0.6m, orientation
Resolution ratio is 1m high-resolution haplopia plural number SAR image, wherein the haplopia plural number SAR containing monitored area information containing snow and ice cover
Image PsnowOne width, the width of haplopia plural number SAR image three comprising monitored area but without snow and ice cover information, i.e. Pk, k=1,2,
3。
S2, image preprocessing
To haplopia plural number SAR image PsnowMultiple look processing and radiation calibration are carried out, obtains backscattering coefficient intensity map
Pwr, as shown in Figure 2；
Using ENVI softwares, with haplopia plural number SAR image PsnowFor master image, to several haplopia plural number SAR images PkCarry out
Filtering, registration and baseline estimations, remove image speckle noise, while obtain several haplopia plural number SAR images PkBetween baseline believe
Breath, baseline information include time reference line and Space Baseline again, and specific baseline information is as shown in figure 3, include any two width in figure
Time reference line and Space Baseline information between haplopia plural number SAR image.
S3, interference group selection
The baseline information obtained according to step S2, from several haplopia plural number SAR images PkIn, choose and haplopia plural number SAR
Image PsnowBetween time reference line and the most short width haplopia plural number SAR image of Space Baseline, then with haplopia plural number SAR image
PsnowCollectively as an interference group Z1；
In the present embodiment, the Space Baseline length in the interference group Z1 obtained is 198.079m, and time reference line length is
11 days；
The baseline information obtained according to step S2, from several haplopia plural number SAR images PkIt is middle respectively access time baseline with
Z1 is identical, and two relatively short width haplopia plural number SAR images of Space Baseline are as an interference group Z2；
In the present embodiment, the Space Baseline length in the interference group Z2 obtained is 166.861m, and time reference line is 11 days.
S4, generation coherence factor figure
Coherence factor is one of important parameter of interferometry, mainly by between the time between two images in interference group
Influenceed every factors such as, Space Baselines, and the influence of time interval is mainly due to phase caused by the change of underlying surface scattering signatures
Dryness difference, its scope between 0-1,0 represent it is irrelevant, 1 represent it is completely relevant；
That reads in interference group Z1 each pixel point storage in two width haplopia plural number SAR images includes atural object amplitude and phase
The complex data S (m, n) of information, (m, n) are pixel point coordinates；
In the present embodiment, m rows in two width haplopia plural number SAR images, the complex data S that the n-th row pixel point includes1
(m, n), S2(m, n) can be represented respectively：
S1(m, n)=S1r(m, n)+jS1i(m, n)
S2(m, n)=S2r(m, n)+jS2i(m, n)
Wherein S1r(m, n) and S2r(m, n) represents the real part of complex data, S respectively1i(m, n) and S2i(m, n) is represented respectively
The imaginary part of complex data；
Two width haplopia plural number SAR images are divided into 30 × 30 wicket, then calculate two width haplopia plural number SAR images pair
Answer the coherence factor ρ (m, n) of pixel point：
Wherein, S1(m, n) represents the complex data of the first width haplopia plural number SAR image pixel point storage, S2(m, n) is represented
The complex data of second width haplopia plural number SAR image pixel point storage, S1 *(m, n) and S2 *(m, n) represents S respectively1(m, n), S2
The conjugation of (m, n), ＜ ＞ represent desired value, andRepresent the phase of the window of image 30 × 30
Prestige value；
The coherence factor ρ (m, n) of pixel point is corresponded to further according to two width haplopia plural number SAR images, generates coherence factor figure
CC1, as shown in Fig. 4 (a)；
Similarly, according to step S4 methods describeds, coherence factor figure CC is generated using interference group Z22, as shown in Fig. 4 (b)；
S5, generation snow and ice cover frame
Set coherence factor figure CC1In threshold value be M1=2.5；Coherence factor figure CC1With coherence factor figure CC2Between
Coherence factor change given threshold is M2=1.8；The threshold interval for setting backscattering coefficient intensity map pwr is [- 20, -13]；
Coherence factor figure CC1In threshold value M1Setting：Due to the influence of accumulated snow, for containing accumulated snow picture in interference group Z1
The characteristics of coherence factor of member can drastically decline and show Low coherence.Therefore threshold value M is passed through1It is big that atural object in image is divided into two
Class：CC will be met1(m, n) ＜ M1Region division be the first kind, include accumulated snow and the non-snow region of some Low coherences；For discontented
This condition of foot is entirely non-snow region then by the second class, in the second class.
In this example, coherence factor figure CC1Threshold value be M1=2.5；
Coherence factor figure CC1With coherence factor figure CC2Between coherence factor change given threshold M2Setting：Due to one
Low coherence region caused by a little complicated atural objects and landform (such as：Lake, shade, vegetation etc.) can be to snow cover information extraction band
Necessarily disturb, but it has been investigated that these regions can be chronically at Low coherence, when there is accumulated snow to occur, these Low coherence areas
The coherence factor in domain still can reduce, therefore by for threshold value M2Setting, by shadow region and some are low without accumulated snow
Coherent area movement is rejected；
In this example, coherence factor figure CC1With coherence factor figure CC2Between coherence factor change given threshold be M2=
1.8；
The setting that backscattering coefficient intensity map pwr threshold interval is：By using accumulated snow and the pole in non-accumulated snow region
Change feature and the difference of scattering mechanism, using backscattering coefficient, further non-accumulated snow region is rejected；
In this example, backscattering coefficient intensity map pwr threshold interval is [- 20, -13]；
Ice and snow region is judged according to the threshold value of setting, if pixel (m, n) while meeting CC1(m, n) ＜ 2.5, CC2
(m,n)-CC1(m, n) ＞ 1.8, -20 ＜ pwr (m, n) ＜ -13, then the pixel (m, n) is determined as ice and snow, and the pixel is assigned
Value 1；If above three condition can not be met simultaneously, the pixel (m, n) is determined as non-ice and snow, and to the pixel assignment 0, most
Binaryzation snow and ice cover frame is obtained eventually, in the present embodiment, as shown in figure 5, part snow and ice cover information extraction result
Figure.
In the present embodiment, because image is larger, intercept part binaryzation snow and ice cover frame, using with containing ice and snow
Coverage information SAR image 16 × 16 meters of resolution ratio GF-1 optical imagerys of the same period verify that it schemes with SAR to extraction result
Optical imagery snow and ice cover information extraction result is as shown in Figure 6 as corresponding to the same time.Because resolution ratio is different, using mixing picture
First method so that optics of each pixel with representing same spatial location in High Resolution SAR Images in each 16 × 27 window
A pixel in image is contrasted one by one, so as to obtain ice and snow extraction to its correctness of extraction result verification, final checking
Precision is 82.44%.
Although the illustrative embodiment of the present invention is described above, in order to the technology of the art
Personnel understand the present invention, it should be apparent that the invention is not restricted to the scope of embodiment, to the common skill of the art
For art personnel, if various change in the spirit and scope of the present invention that appended claim limits and determines, these
Change is it will be apparent that all utilize the innovation and creation of present inventive concept in the row of protection.
Claims (2)
1. a kind of SAR image snow and ice cover information extracting method based on InSAR technologies, it is characterised in that comprise the following steps：
(1) pending original SAR image, is obtained
Obtain the haplopia plural number SAR image P of monitored area information containing snow and ice coversnow, and two width or two monitoring sections contained above
Domain but the haplopia plural number SAR image P without snow and ice cover informationk, k=1,2 ... represent comprising monitored area but are covered without ice and snow
The number of the haplopia plural number SAR image of lid information；
(2), image preprocessing
To haplopia plural number SAR image PsnowMultiple look processing and radiation calibration are carried out, obtains backscattering coefficient intensity map pwr；
Using ENVI softwares to several haplopia plural number SAR images PkIt is filtered, registration and baseline estimations, removal Image Speckle are made an uproar
Sound, while obtain several haplopia plural number SAR images PkBetween baseline information；
(3), the selection of interference group
The baseline information obtained according to step (2), from several haplopia plural number SAR images PkIn, choose and haplopia plural number SAR image
PsnowBetween time reference line and the most short width haplopia plural number SAR image of Space Baseline, then with haplopia plural number SAR image PsnowAltogether
It is same to be used as an interference group Z1；
The baseline information obtained according to step (2), from several haplopia plural number SAR images PkMiddle access time baseline and Z1 phases respectively
Together, two relatively short width haplopia plural number SAR images of Space Baseline are as an interference group Z2；
(4) coherence factor figure, is generated
That reads in interference group Z1 each pixel point storage in two width haplopia plural number SAR images includes atural object amplitude and phase information
Complex data S (m, n), (m, n) is pixel point coordinates；
Calculate the coherence factor ρ (m, n) that two width haplopia plural number SAR images correspond to pixel point：
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Wherein, S1(m, n) represents the complex data of the first width haplopia plural number SAR image pixel point storage, S2(m, n) represents second
The complex data of width haplopia plural number SAR image pixel point storage, S1 *(m, n) and S2 *(m, n) represents S respectively1(m, n), S2(m,n)
Conjugation, ＜ ＞ represent desired value, andRepresent imageThe desired value of window；
The coherence factor ρ (m, n) of pixel point, generation coherence factor figure CC are corresponded to further according to two width haplopia plural number SAR images1；
Similarly, according to step (4) methods described, coherence factor figure CC is generated using interference group Z22；
(5) snow and ice cover frame, is generated
Set coherence factor figure CC1In threshold value be M1；Coherence factor figure CC1With coherence factor figure CC2Between coherence factor become
Change given threshold is M2；The threshold interval for setting backscattering coefficient intensity map pwr is [p, q]；
Ice and snow region is judged according to the threshold value of setting, if pixel (m, n) while meeting CC1(m, n) ＜ M1, CC2(m,n)-
CC1(m, n) ＞ M2, p ＜ pwr (m, n) ＜ q, then the pixel (m, n) is determined as ice and snow, and to the pixel assignment 1；If can not be same
When meet above three condition, then the pixel (m, n) is determined as non-ice and snow, and to the pixel assignment 0, finally give binaryzation
Snow and ice cover frame.
2. the SAR image snow and ice cover information extracting method according to claim 1 based on InSAR technologies, its feature exist
In in the step (4), m rows in haplopia plural number SAR image, the complex data S (m, n) that the n-th row pixel includes can be represented
For：
S (m, n)=Sr(m, n)+jSi(m, n)
Wherein Sr(m, n) represents complex data S (m, n) real part, Si(m, n) represents complex data S (m, n) imaginary part.
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| CN109001730A (en) * | 2018-05-08 | 2018-12-14 | 中国电力科学研究院有限公司 | A kind of passway for transmitting electricity snows cover extent extracting method and system |
| CN110456352B (en) * | 2019-08-30 | 2022-03-04 | 南京大学 | Glacier identification method based on coherence coefficient threshold |
| CN110633851B (en) * | 2019-09-11 | 2022-04-19 | 电子科技大学 | Power transmission corridor icing early warning method based on multi-source data |
| CN113609898B (en) * | 2021-06-23 | 2023-09-29 | 国网山东省电力公司泗水县供电公司 | SAR image-based power transmission line icing monitoring method and system |
| CN113420717A (en) * | 2021-07-16 | 2021-09-21 | 西藏民族大学 | Three-dimensional monitoring method, device and equipment for ice and snow changes and readable storage medium |
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| US6677885B1 (en) * | 2003-01-02 | 2004-01-13 | Raytheon Company | Method for mitigating atmospheric propagation error in multiple pass interferometric synthetic aperture radar |
| GB0316858D0 (en) * | 2003-07-18 | 2003-08-20 | Univ Nottingham | A process for radar measurements of the position and movement of indivual targets and of areas of land and ice |
| CN103761524B (en) * | 2014-01-17 | 2016-11-16 | 电子科技大学 | A kind of linear goal identification based on image and extracting method |
| CN104715255B (en) * | 2015-04-01 | 2017-11-21 | 电子科技大学 | A kind of landslide extracting method based on SAR image |
| CN104700110B (en) * | 2015-04-03 | 2018-08-07 | 电子科技大学 | A kind of vegetative coverage information extracting method based on full polarimetric SAR |
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2016
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111895903A (en) * | 2020-07-21 | 2020-11-06 | 太原理工大学 | Remote sensing estimation method for snow depth in northern area of Xinjiang |
| CN111895903B (en) * | 2020-07-21 | 2021-06-01 | 太原理工大学 | Remote sensing estimation method for snow depth of detection area |
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