CN108564532A - Large scale distance satellite-borne SAR image method for embedding - Google Patents
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Abstract
The present invention provides large scale distance satellite-borne SAR image method for embedding, it is related to satellite SAR (synthetic aperture radar) image mosaics field, necessary pretreatment first is carried out to original image, then to passing through pretreated image zooming-out geographical location information, using geographical location information as priori, cross-correlation correction is carried out to image, the control information inlayed compensates image mosaic error using control information is inlayed；After inlaying error compensation, with Wallis filters to the SAR image of input by search for it is newer in a manner of carry out even color processing, and ultimately generate and inlay rear image；The present invention according to different terrain adaptation cross-correlation method or the two-value based on zero crossing by matching statistic law, to provide alternative for the determination of Matching Offsets；A kind of search more new strategy is provided, ensure that more overlapping regions, multiple directions even color treatment effect, and the grain details in image can be protected well.
Description
Technical field
The present invention relates to satellite SAR (synthetic aperture radar) image mosaics fields, specifically large scale distance satellite-borne SAR figure
As method for embedding.
Background technology
Satellite-borne synthetic aperture radar (SAR) is because of its large area and round-the-clock and imaging capability round the clock, it has also become mapping and
Important tool in geoscience research field.Several SAR images from identical and adjacent imaging track are inlayed for prison
It surveys and the room and time variation of analysis global process is particularly useful.Satellite-borne SAR inlays product and can be widely used for land use, soil
Ground covers the fields such as variation, mapping, coastline, desertification, wetland and glacier monitoring.The key that distance satellite-borne SAR is inlayed
It is to eliminate geometry dislocation and the radiation difference inlayed between image, and do not limited by mass storage.
Currently, having been researched and developed for the digital mosaic technology of the satellite-borne SAR image of specific purposes, such as
Shimada etc. (2010) generates PALSAR based on slant-range image and inlays data set, and Grandi etc. (2004) uses distance image
It generates JERS-1SAR and inlays data set, but limited amount, most of radars inlay experiment or product is all based on airborne radar
What the data of system acquisition were completed.These methods usually require the vision using the same place of vision positioning or the extraction of certain algorithm
Feature is registrated the image data of overlapping, and entire mosaic process was not only laborious but also time-consuming；On the other hand, using being simply fade-in
Unidirectional overlapping region gradual transition can only be realized by gradually going out the even color of formula, it is difficult to eliminate the color that the region overlapping of multiple directions occurs
Poor problem；In addition, some methods are more demanding to the memory size of computer.
Invention content
It is an object of the invention to overcome the deficiencies in the prior art, it is intended to the big of spaceborne distance SAR image be better achieved
Scale is inlayed, of the existing technology to solve the problems, such as.
The present invention is achieved by the following technical solutions：
The present invention provides large scale distance satellite-borne SAR image method for embedding, including several number distance satellite-borne SAR figures
Picture, this approach includes the following steps：
Step 1, image preprocessing
It is obtained containing the pending of geo-localisation information after carrying out parameters revision to each distance satellite-borne SAR image of number
SAR image
Step 2, warp, the latitude coordinate for calculating each pixel in each pending SAR image
Whether step 3, judgement institute SAR image to be handled are overlapped between any two
According to warp, the latitude coordinate of each pixel in the obtained each pending SAR image of step 2, judge to be needed
Whether processing SAR image is overlapped between any two
There are overlapping, the corresponding number of all pending SAR images that there is overlapping between any two and two-by-two is recorded
Between overlapping region range, and generate the number group containing overlapping region range information stored
Step 4, each number group of calculating correspond to the Matching Offsets between the range of overlapping region
For the low region of peak-to-average force ratio, each number group is calculated using cross-correlation method and corresponds between the range of overlapping region
With offset
For the high region of peak-to-average force ratio, corresponded to using the two-value matching statistic law based on zero crossing to calculate each number group
Matching Offsets between the range of overlapping region
Step 5 creates complete zero pixel image and global structure body variable
It is obtained according to warp, latitude coordinate and the step 4 of each pixel in the pending SAR image obtained in step 2 every
A number group corresponds to the Matching Offsets between the range of overlapping region and obtains the revised geographical seat of institute's SAR image to be handled
Mark, each corresponding image to be spliced of pending SAR image after being corrected
Establishment and an equal amount of complete zero pixel image of the mosaic image finally to be generated, while establishing a global structure
Body variable
Step 6, the corresponding overlapping region range of each number group obtained to step 5 using Wallis filters carry out even
Color
Step 7 splices all images to be spliced after homochromatic
Joining method is as follows：
A. it is that even color marker is spliced in all image settings to be spliced, and is reset to 0 in global structure body variable
B. an image to be spliced is inputted, all Chong Die with this image to be spliced and even color markers are found out based on number group
For 0 image to be spliced；
C. assume that the total number of images to be spliced that Chong Die with image to be spliced is currently inputted and even colour code is denoted as 0 is Num, to work as
Preceding input image to be spliced is reference picture, carries out the even colors of Wallis to this Num image to be spliced according to step 6 successively, and
Even color updates corresponding parameter in Wallis filters each time, and even color marker is set to 1 and preserves the image after even color；
After the even colors of d.Num Wallis, complete zero pixel image that will be created in input image write step 5 to be spliced
In, and even color marker will be spliced and be set as 1；
E. to all images to be spliced repeat above-mentioned b, c, Step d obtains final after having handled all images to be spliced
Inlay result.
Further, parameters revision described in step 1 is specially following process：
Phase separation immunoassay is carried out to each distance satellite-borne SAR image of number, to remove coherent speckle noise, is obtained without relevant
The SAR image of spot noise
Radiation calibration is carried out to the SAR image of no coherent speckle noise, to eliminate system radiation error, and will be after calibration
SAR images indicate with backscattering coefficient, the SAR image that acquisition is indicated with backscattering coefficient
Spheroid correction carried out to the SAR image indicated with backscattering coefficient, and by the geo-location in auxiliary information
SAR image is written in information, obtains pending SAR image.
Further, the warp of each pixel, the calculation formula of latitude coordinate are as follows in each pending SAR image in step 3：
E_geo=A (0)+X_pix × A (1)+Y_pix × A (2) (1)
N_geo=A (3)+X_pix × A (4)+Y_pix × A (5) (2)
Wherein：E_geo and N_geo indicates the Longitude and latitude coordinates of pixel in the pending SAR image respectively
X_pix and Y_pix indicates the row coordinate and row coordinate of pixel in the pending SAR image respectively
The geo-localisation information is specifically made of geo-location array, and the geo-location array is specifically by six parameters
A (0), A (1) ... A (5) is constituted, wherein：
A (0) and A (3) indicates to indicate warp, the latitude coordinate in the pending image upper left corner respectively
A (1) and A (5) indicates the laterally and longitudinally resolution ratio of the pending image respectively
A (2) and A (4) indicates coefficient of rotary of the pixel in latitude, longitudinal in the pending image respectively.
Further, the cross-correlation method described in step 4 is specially：
It is any in each number group corresponds to and chooses the corresponding two pending images of the number group within the scope of overlapping region
For a block diagram picture in pending image as template image t (u, v), another pending image is search image I (w, h)
Wherein：T (u, v), dimension are U × V
I (w, h), dimension are W × H
T (u, v) is overlayed and does the search of upper and lower translation formula on I (w, h), enables the region that I (w, h) and t (u, v) are overlapped be：
For subgraph Omn
Wherein：M and n is coordinate of the template image lower left corner on I (w, h)
And：1≤m≤W-U, 1≤n≤H-V
Calculate the two-dimensional cross correlation coefficients R (m, n) of Omn and t (u, v)
I.e.：
The normalizated correlation coefficient ρ (m, n) for calculating Omn and t (u, v), as the two similarity measurement
I.e.：
After completing all search, the maximum value ρ (m of ρ (m, n) are chosenmax,nmax) corresponding subgraphTo match target
It is corresponding two width of the number group to take the offset of matching target opposite formwork image in the horizontal and vertical directions
Matching Offsets between pending image.
Further, the two-value matching statistic law based on zero crossing described in step 4 is specially：
A, the contour feature M (x, y) of each pixel in each pending image is sought
M (x, y)=[▽2G(x,y)]*I(x,y) (5)
Wherein：I (x, y) is image, and x, y are respectively the horizontal, vertical coordinate of the pending each pixel of image in handling
▽2G (x, y) is Gauss-Laplace
B, two-value matching, as M (x, y) ＞ 0, assignment are carried out to the contour feature of each pixel in each pending image
It is 1, as M (x, y)≤0, is assigned a value of 0, obtains the bianry image of every pending image
C, by choosing one piece of conduct two in any width bianry image in the corresponding two pending images of each number group
It is worth template image Ma, the corresponding another pending image of the number group is Mb；Wherein, the two-value template image Ma, which is in, is somebody's turn to do
Within the scope of the corresponding overlapping region of number group
D, Ma is overlayed into progress upper and lower translation formula search on Mb, the region being capped on Mb is sub- binary map Mc；Statistics
Ma and Mb same positions are in the identical quantity S of numerical value on its corresponding bianry image
E, after completing all search, the corresponding sub- binary maps of maximum value Smax for choosing S are matching object
F, matching object is taken to be corresponded to for the number group with respect to the offset of two-value template image in the horizontal and vertical directions
Two pending images between Matching Offsets
Further, the expression formula of Wallis filters is：
Wherein：Each corresponding two images to be spliced of number group are indicated with I and T respectively,For I by even color adjustment it
The gray scale of image afterwards
μT、σTAnd μI、σIIndicate that T and I is located at the pending SAR image gray-scale intensity mean value and standard of overlapping region respectively
Difference
The dimension of I is W × H, 1≤i≤W, 1≤j≤H.
Further, newer relevant parameter described in step 7 is specially μT、σTAnd μI、σI。
The present invention has the following advantages compared with prior art：
(1) by establishing a global structure body variable, to preserve the geographical coordinate after all image corrections to be spliced, from
And ensure at most only to store two images in same time calculator memory, reduce the demand to mass storage；
(2) since radar raster-displaying is sensitive to the variation in imaging geometry, and the radiation characteristic of SAR image tend to by
The image decorrelation of same area from different time imaging, therefore for the region of relatively flat, cross-correlation may be used
Method measures the registration error between image, and for region with a varied topography, then using the two-value matching statistics based on zero crossing
Method, to provide alternative for the determination of registration error；
(3) due to the phenomenon that there may be a width SAR image and several SAR images be overlapped simultaneously in practical mosaic process,
When carrying out even color using global filtering device and handling, a kind of search more new strategy is devised, not only can guarantee multiple folded region, more
The even color treatment effect in a direction, and the grain details in SAR image can be protected well；
(4) flow is inlayed the present invention provides the spaceborne distance SAR image of complete large scale, be not only suitable for spacebornely
Away from strip-type product, it is also applied for spaceborne distance wide mode product.
Description of the drawings
Fig. 1 is the flow chart of large scale distance satellite-borne SAR image method for embedding of the present invention；
Fig. 2 is template matches schematic diagram in cross correlation method provided by the invention；
Fig. 3 is original graph figure a in used three original SAR images in specific embodiment；
Fig. 4 is original graph figure b in used three original SAR images in specific embodiment；
Fig. 5 is original graph figure c in used three original SAR images in specific embodiment；
Fig. 6 is the figure a1 that original graph figure a is obtained after pretreatment in used three original SAR images in specific embodiment；
Fig. 7 is the figure b1 that original graph figure b is obtained after pretreatment in used three original SAR images in specific embodiment；
Fig. 8 is the figure c1 that original graph figure c is obtained after pretreatment in used three original SAR images in specific embodiment；
Fig. 9 is that obtained design sketch is spliced in a1, b1, c1 processing after the completion.
Specific implementation mode
It elaborates below to the embodiment of the present invention, the present embodiment is carried out lower based on the technical solution of the present invention
Implement, gives detailed embodiment and specific operating process, but protection scope of the present invention is not limited to following implementation
Example.
Large scale distance satellite-borne SAR image method for embedding, includes the following steps：
(1) image preprocessing：To ensure to inlay the quality of result, it is necessary first to spaceborne distance wide mode SAR image into
Row pretreatment；The three width SAR images that this step is selected are from captured by sentry's No.1 satellite of European Space Agency's transmitting
SAR image within Chinese territory, as Fig. 3,4,5 show three original SAR images：
The longitude range of image is in 135 ° of 73 °~east longitude of east longitude, and latitude scope is at 53 ° of 3 °~north latitude of north latitude, entire pre- place
Reason process is on processing platform SNAP (Sentinels Application Platform) 3.0 versions that European Space Agency provides
It completes；Usually there is coherent speckle noise in SAR image, phase separation immunoassay, choosing are carried out to each distance satellite-borne SAR image of number
Speckle noise is removed with suitable filter, what we selected here is Lee-Sigma filters, and window size is 7 × 7,
Target window size is that 3 × 3, sigma values are 0.9, compares more other common filter (such as median filters, mean filter
Device etc.) in speckle suppression and in terms of keeping edge, the detailed information such as texture there is more apparent advantage, specifically exist
Operation in SNAP3.0 platforms is the Speckle Filtering options chosen under Radar tabss；In addition, radar passes
Sensor itself can eliminate this error by radiation calibration and obtain backscattering coefficient value there are system radiation error
(i) SAR image indicated, by taking sentry's No.1 product of European Space Agency's transmitting as an example, radiation calibration process can be by following formula for we
It indicates：
Wherein, DNi(Digital Number) and AiFour kinds of radiation calibration inquiry tables that value is provided by sentry's No.1
(LookUp Tables) inquiry obtains,；Next spheroid correction, then the geo-localisation information in auxiliary information is written
In SAR image, by taking SNAP3.0 as an example, spheroid correction can be carried out by choosing the Geometric under Radar tabss, most
Pending SAR image is obtained eventually.The three pending SAR images obtained by pretreatment are as shown in Fig. 6,7,8；
(2) it is as follows that the warp of each pixel, latitude coordinate calculation formula in pending SAR image are calculated：
E_geo=A (0)+X_pix × A (1)+Y_pix × A (2) (1)
N_geo=A (3)+X_pix × A (4)+Y_pix × A (5) (2)
Wherein：E_geo and N_geo indicates the Longitude and latitude coordinates of pixel in the pending SAR image respectively
X_pix and Y_pix indicates the row coordinate and row coordinate of pixel in the pending SAR image respectively
The geo-localisation information is specifically made of geo-location array, and the geo-location array is specifically by six parameters
A (0), A (1) ... A (5) is constituted, wherein：
A (0) and A (3) indicates to indicate warp, the latitude coordinate in the pending image upper left corner respectively
A (1) and A (5) indicates the laterally and longitudinally resolution ratio of the pending image respectively
A (2) and A (4) indicates coefficient of rotary of the pixel in latitude, longitudinal in the pending image respectively；
(3) whether judgement institute SAR image to be handled is overlapped between any two
According to warp, the latitude coordinate of each corner pixels in the obtained each pending SAR image of step 2, institute is judged
Whether SAR image to be handled is overlapped between any two
There are overlapping, the corresponding number of all pending SAR images that there is overlapping between any two and two-by-two is recorded
Between overlapping region range, and generate the number group containing overlapping region range information stored
(4) it calculates each number group and corresponds to the Matching Offsets between the range of overlapping region
By the geographic coordinate information that extraction obtains in step (2), SAR image can be registrated, but this matched
Standard would generally be inadequate due to the precision of geographic coordinate information, leads to that there are Matching Offsets；Therefore, for the low area of peak-to-average force ratio
Domain calculates each number group using cross-correlation method and corresponds to Matching Offsets between the range of overlapping region
For the high region of peak-to-average force ratio, corresponded to using the two-value matching statistic law based on zero crossing to calculate each number group
Matching Offsets between the range of overlapping region.It is specific as follows：
(a) cross-correlation method
As shown in Fig. 2, each number group correspond to chosen within the scope of overlapping region the number group it is corresponding two it is pending
For a block diagram picture in image in any pending image as template image t (u, v), another pending image is search graph
As I (w, h)
Wherein：T (u, v), dimension are U × V
I (w, h), dimension are W × H
T (u, v) is overlayed and does the search of upper and lower translation formula on I (w, h), enables the region that I (w, h) and t (u, v) are overlapped be：
For subgraph Omn
Wherein：M and n is coordinate of the template image lower left corner on I (w, h)
And：1≤m≤W-U, 1≤n≤H-V
Calculate OmnWith the two-dimensional cross correlation coefficients R (m, n) of t (u, v)
I.e.：
Calculate OmnWith the normalizated correlation coefficient ρ (m, n) of t (u, v), as the two similarity measurement
I.e.：
After completing all search, the maximum value ρ (m of ρ (m, n) are chosenmax,nmax) corresponding subgraphTo match target
It is corresponding two width of the number group to take the offset of matching target opposite formwork image in the horizontal and vertical directions
Matching Offsets between pending image, since geographic coordinate information passes through, latitude coordinate is it is known that its practical search range can
Control is in 1≤i≤5,1≤j≤5；
The frequency domain realization of this method can be completed in GPU, to achieve the purpose that acceleration.
(b) two-value based on zero crossing matches statistic law
A, the contour feature M (x, y) of each pixel in each pending image is sought
M (x, y)=[▽2G(x,y)]*I(x,y) (5)
Wherein：I (x, y) is image, and x, y are respectively the horizontal, vertical coordinate of the pending each pixel of image in handling
▽2G (x, y) is Gauss-Laplace
B, two-value matching, as M (x, y) ＞ 0, assignment are carried out to the contour feature of each pixel in each pending image
It is 1, as M (x, y)≤0, is assigned a value of 0, obtains the bianry image of every pending image
C, by choosing one piece of conduct two in any width bianry image in the corresponding two pending images of each number group
It is worth template image Ma, the corresponding another pending image of the number group is Mb；
Wherein, the two-value template image MaWithin the scope of the corresponding overlapping region of number group
D, by MaOverlay MbUpper progress flat search up and down, MbUpper capped region is sub- binary map Mc
D, statistics Ma and Mb same positions are in the identical quantity S of numerical value on its corresponding bianry image
E, after completing all search, the maximum value S of S is chosenmaxCorresponding sub- binary map is matching object
F, matching object is taken to be corresponded to for the number group with respect to the offset of two-value template image in the horizontal and vertical directions
Two pending images between Matching Offsets.
(5) complete zero pixel image and global structure body variable are created
It is obtained according to warp, latitude coordinate and the step 4 of each pixel in the pending SAR image obtained in step 2 every
A number group corresponds to the Matching Offsets between the range of overlapping region and obtains the revised geographical seat of institute's SAR image to be handled
Mark, each corresponding image to be spliced of pending SAR image after being corrected
Establishment and an equal amount of complete zero pixel image of the mosaic image finally to be generated, while establishing a global structure
Body variable.
(6) Wallis filters is used to carry out global even color and splicing to overlapping SAR image
Since there may be the strength differences of multiple directions between spaceborne distance SAR image, spliced image weight can be caused
Folded area's transition is unnatural, therefore needs to carry out global even color processing.Here we use Wallis filters to being overlapped SAR image
Carry out even color；
The expression formula of Wallis filters is：The expression formula of Wallis filters is：
Wherein：Each corresponding two images to be spliced of number group are indicated with I and T respectively,For I by even color adjustment it
The gray scale of image afterwards
μT、σTAnd μI、σIIndicate that T and I is located at the pending SAR image gray-scale intensity mean value and standard of overlapping region respectively
Difference
The dimension of I is W × H, 1≤i≤W, 1≤j≤H
Homochromatic joining method is as follows：
A. it is that even color marker is spliced in all image settings to be spliced, and is reset to 0 in global structure body variable
B. an image to be spliced is inputted, all Chong Die with this image to be spliced and even color markers are found out based on number group
For 0 image to be spliced；
C. assume that the total number of images to be spliced that Chong Die with image to be spliced is currently inputted and even colour code is denoted as 0 is Num, to work as
Preceding input image to be spliced is reference picture, successively according toThis Num image to be spliced is carried out
The even colors of Wallis, and even color updates μ each timeT、σTAnd μI、σI, even color marker is set to 1 and preserves the image after even color；
After the even colors of d.Num Wallis, complete zero pixel image that will be created in input image write step 5 to be spliced
In, and even color marker will be spliced and be set as 1；
E. to all images to be spliced repeat above-mentioned b, c, Step d obtains final after having handled all images to be spliced
Inlay that the results are shown in Figure 9：
It is inlayed shown in result figure 9 by what the above invention process obtained, splicing of the present invention to several SAR images is inlayed
As a result the seam crossing in obtains radiation smoothly, and whole aberration is smaller.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
All any modification, equivalent and improvement etc., should all be included in the protection scope of the present invention made by within refreshing and principle.
Claims (7)
1. large scale distance satellite-borne SAR image method for embedding, including several number distance satellite-borne SAR images, it is characterised in that：
This approach includes the following steps：
Step 1, image preprocessing
The pending SAR figures containing geo-localisation information are obtained after carrying out parameters revision to each distance satellite-borne SAR image of number
Picture
Step 2, warp, the latitude coordinate for calculating each pixel in each pending SAR image
Whether step 3, judgement institute SAR image to be handled are overlapped between any two
According to warp, the latitude coordinate of each pixel in the obtained each pending SAR image of step 2, judge that institute is to be handled
Whether SAR image is overlapped between any two
There are overlapping, the corresponding number of all pending SAR images that there is overlapping between any two and between any two is recorded
Overlapping region range, and generate the number group containing overlapping region range information and stored
Step 4, each number group of calculating correspond to the Matching Offsets between the range of overlapping region
For the low region of peak-to-average force ratio, it is inclined that the matching that each number group corresponds between the range of overlapping region is calculated using cross-correlation method
Shifting amount
For the high region of peak-to-average force ratio, overlapping is corresponded to calculate each number group using the two-value matching statistic law based on zero crossing
Matching Offsets between regional extent
Step 5 creates complete zero pixel image and global structure body variable
The each volume obtained according to warp, latitude coordinate and the step 4 of each pixel in the pending SAR image obtained in step 2
Number group corresponds to the Matching Offsets between the range of overlapping region and obtains institute's revised geographical coordinate of SAR image to be handled, obtains
The corresponding image to be spliced of each pending SAR image after to amendment
Establishment and an equal amount of complete zero pixel image of the mosaic image finally to be generated, while establishing a global structure body and becoming
Amount
Step 6, the corresponding overlapping region range of each number group obtained to step 5 using Wallis filters carry out even color
Step 7 splices all images to be spliced after homochromatic
Joining method is as follows：
A. it is that even color marker is spliced in all image settings to be spliced, and is reset to 0 in global structure body variable
B. an image to be spliced is inputted, all Chong Die with this image to be spliced and even colour codes are found out based on number group and are denoted as 0
Image to be spliced；
C. assume that the total number of images to be spliced that Chong Die with image to be spliced is currently inputted and even colour code is denoted as 0 is Num, with current defeated
It is reference picture to enter image to be spliced, carries out the even colors of Wallis to this Num image to be spliced according to step 6 successively, and each
Secondary even color updates corresponding parameter in Wallis filters, and even color marker is set to 1 and preserves the image after even color；
After the even colors of d.Num Wallis, by complete zero pixel image created in input image write step 5 to be spliced, and
Even color marker will be spliced and be set as 1；
E. above-mentioned b, c, Step d are repeated to all images to be spliced, after having handled all images to be spliced, obtains final inlay
As a result.
2. large scale distance satellite-borne SAR image method for embedding according to claim 1, which is characterized in that described in step 1
Parameters revision is specially following process：
Phase separation immunoassay is carried out to each distance satellite-borne SAR image of number, to remove coherent speckle noise, acquisition is made an uproar without coherent spot
The SAR image of sound
Radiation calibration is carried out to the SAR image of no coherent speckle noise, to eliminate system radiation error, and the SAR after calibration is schemed
As being indicated with backscattering coefficient, the SAR image that acquisition is indicated with backscattering coefficient
Spheroid correction carried out to the SAR image indicated with backscattering coefficient, and by the geo-localisation information in auxiliary information
SAR image is written, obtains pending SAR image.
3. large scale distance satellite-borne SAR image method for embedding according to claim 2, which is characterized in that each in step 3
The warp of each pixel, the calculation formula of latitude coordinate are as follows in pending SAR image：
E_geo=A (0)+X_pix × A (1)+Y_pix × A (2) (1)
N_geo=A (3)+X_pix × A (4)+Y_pix × A (5) (2)
Wherein：E_geo and N_geo indicates the Longitude and latitude coordinates of pixel in the pending SAR image respectively
X_pix and Y_pix indicates the row coordinate and row coordinate of pixel in the pending SAR image respectively
The geo-localisation information is specifically made of geo-location array, and the geo-location array is specifically by six parameter A
(0), (1) A ... A (5) is constituted, wherein：
A (0) and A (3) indicates to indicate warp, the latitude coordinate in the pending image upper left corner respectively
A (1) and A (5) indicates the laterally and longitudinally resolution ratio of the pending image respectively
A (2) and A (4) indicates coefficient of rotary of the pixel in latitude, longitudinal in the pending image respectively.
4. large scale distance satellite-borne SAR image method for embedding according to claim 3, which is characterized in that described in step 4
Cross-correlation method is specially：
Any width waits in each number group corresponds to and chooses the corresponding two pending images of the number group within the scope of overlapping region
The block diagram picture in image is handled as template image t (u, v), another pending image is search image I (w, h)
Wherein：T (u, v), dimension are U × V
I (w, h), dimension are W × H
T (u, v) is overlayed and does the search of upper and lower translation formula on I (w, h), enables the region that I (w, h) and t (u, v) are overlapped be：For son
Scheme Omn
Wherein：M and n is coordinate of the template image lower left corner on I (w, h)
And：1≤m≤W-U, 1≤n≤H-V
Calculate the two-dimensional cross correlation coefficients R (m, n) of Omn and t (u, v)
I.e.：
The normalizated correlation coefficient ρ (m, n) for calculating Omn and t (u, v), as the two similarity measurement
I.e.：
After completing all search, the maximum value ρ (m of ρ (m, n) are chosenmax,nmax) corresponding subgraphTo match target
It is that corresponding two width of the number group waits locating to take the offset of matching target opposite formwork image in the horizontal and vertical directions
Manage the Matching Offsets between image.
5. large scale distance satellite-borne SAR image method for embedding according to claim 4, which is characterized in that described in step 4
Two-value based on zero crossing matches statistic law：
A, the contour feature M (x, y) of each pixel in each pending image is sought
M (x, y)=[▽2G(x,y)]*I(x,y) (5)
Wherein：I (x, y) is image, and x, y are respectively the horizontal, vertical coordinate of the pending each pixel of image in handling
▽2G (x, y) is Gauss-Laplace
B, two-value matching is carried out to the contour feature of each pixel in each pending image and is assigned a value of 1 as M (x, y) ＞ 0,
As M (x, y)≤0, it is assigned a value of 0, obtains the bianry image of every pending image
C, it is used as two-value mould by choosing one piece in any width bianry image in the corresponding two pending images of each number group
Plate image Ma, the corresponding another pending image of the number group are Mb；Wherein, the two-value template image Ma is in the number
Within the scope of the corresponding overlapping region of group
D, Ma is overlayed into progress upper and lower translation formula search on Mb, the region being capped on Mb is sub- binary map Mc；Count Ma and
Mb same positions are in the identical quantity S of numerical value on its corresponding bianry image
E, after completing all search, the corresponding sub- binary maps of maximum value Smax for choosing S are matching object
F, it is the number group corresponding two to take and match object with respect to the offset of two-value template image in the horizontal and vertical directions
Matching Offsets between pending image.
6. large scale distance satellite-borne SAR image method for embedding according to claim 5, which is characterized in that Wallis is filtered
The expression formula of device is：
Wherein：Each corresponding two images to be spliced of number group are indicated with I and T respectively,It is that I passes through after even color adjustment
The gray scale of image
μT、σTAnd μI、σIIndicate that T and I is located at the pending SAR image gray-scale intensity mean value and standard deviation of overlapping region respectively
The dimension of I is W × H, 1≤i≤W, 1≤j≤H.
7. large scale distance satellite-borne SAR image method for embedding according to claim 6, which is characterized in that described in step 7
Newer relevant parameter is specially μT、σTAnd μI、σI。
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111028152A (en) * | 2019-12-02 | 2020-04-17 | 哈尔滨工程大学 | Super-resolution reconstruction method of sonar image based on terrain matching |
| CN111738929A (en) * | 2020-05-08 | 2020-10-02 | 中国科学院空天信息创新研究院 | Image processing method and device, electronic equipment and storage medium |
| WO2022213784A1 (en) * | 2021-04-09 | 2022-10-13 | 杭州睿胜软件有限公司 | Image processing method and apparatus, and electronic device and storage medium |
| CN116503274A (en) * | 2023-04-07 | 2023-07-28 | 中山大学 | Image color homogenizing method and device based on image overlapping area |
| CN117541469A (en) * | 2024-01-10 | 2024-02-09 | 中山大学 | SAR image stitching method and device based on graph theory |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103761709A (en) * | 2014-01-07 | 2014-04-30 | 西安电子科技大学 | Parallel real-time SAR image spot and noise reducing method based on multiple DSPs |
| US20140226916A1 (en) * | 2009-10-09 | 2014-08-14 | At&T Intellectual Property I, L.P. | No-reference spatial aliasing measure for digital image resizing |
| CN106127683A (en) * | 2016-06-08 | 2016-11-16 | 中国电子科技集团公司第三十八研究所 | A kind of real-time joining method of unmanned aerial vehicle SAR image |
-
2018
- 2018-03-30 CN CN201810299312.5A patent/CN108564532B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140226916A1 (en) * | 2009-10-09 | 2014-08-14 | At&T Intellectual Property I, L.P. | No-reference spatial aliasing measure for digital image resizing |
| CN103761709A (en) * | 2014-01-07 | 2014-04-30 | 西安电子科技大学 | Parallel real-time SAR image spot and noise reducing method based on multiple DSPs |
| CN106127683A (en) * | 2016-06-08 | 2016-11-16 | 中国电子科技集团公司第三十八研究所 | A kind of real-time joining method of unmanned aerial vehicle SAR image |
Non-Patent Citations (1)
| Title |
|---|
| 郎文辉等: "采用自适应块拼接的北极海冰SAR图像合成", 《仪器仪表学报》 * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111028152A (en) * | 2019-12-02 | 2020-04-17 | 哈尔滨工程大学 | Super-resolution reconstruction method of sonar image based on terrain matching |
| CN111028152B (en) * | 2019-12-02 | 2023-05-05 | 哈尔滨工程大学 | Super-resolution reconstruction method of sonar image based on terrain matching |
| CN111738929A (en) * | 2020-05-08 | 2020-10-02 | 中国科学院空天信息创新研究院 | Image processing method and device, electronic equipment and storage medium |
| CN111738929B (en) * | 2020-05-08 | 2022-08-30 | 中国科学院空天信息创新研究院 | Image processing method and device, electronic equipment and storage medium |
| WO2022213784A1 (en) * | 2021-04-09 | 2022-10-13 | 杭州睿胜软件有限公司 | Image processing method and apparatus, and electronic device and storage medium |
| CN116503274A (en) * | 2023-04-07 | 2023-07-28 | 中山大学 | Image color homogenizing method and device based on image overlapping area |
| CN116503274B (en) * | 2023-04-07 | 2023-12-22 | 中山大学 | Image color homogenizing method and device based on image overlapping area |
| CN117541469A (en) * | 2024-01-10 | 2024-02-09 | 中山大学 | SAR image stitching method and device based on graph theory |
| CN117541469B (en) * | 2024-01-10 | 2024-05-10 | 中山大学 | SAR image stitching method and device based on graph theory |
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