CN111986283A - Remote sensing image fast re-projection method based on lookup table - Google Patents
Remote sensing image fast re-projection method based on lookup table Download PDFInfo
- Publication number
- CN111986283A CN111986283A CN202010789902.3A CN202010789902A CN111986283A CN 111986283 A CN111986283 A CN 111986283A CN 202010789902 A CN202010789902 A CN 202010789902A CN 111986283 A CN111986283 A CN 111986283A
- Authority
- CN
- China
- Prior art keywords
- remote sensing
- row
- sensing image
- projection
- coordinate system
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 36
- 230000009466 transformation Effects 0.000 claims abstract description 15
- 230000001131 transforming effect Effects 0.000 claims description 3
- 230000008569 process Effects 0.000 abstract description 6
- 238000010586 diagram Methods 0.000 description 16
- PCTMTFRHKVHKIS-BMFZQQSSSA-N (1s,3r,4e,6e,8e,10e,12e,14e,16e,18s,19r,20r,21s,25r,27r,30r,31r,33s,35r,37s,38r)-3-[(2r,3s,4s,5s,6r)-4-amino-3,5-dihydroxy-6-methyloxan-2-yl]oxy-19,25,27,30,31,33,35,37-octahydroxy-18,20,21-trimethyl-23-oxo-22,39-dioxabicyclo[33.3.1]nonatriaconta-4,6,8,10 Chemical compound C1C=C2C[C@@H](OS(O)(=O)=O)CC[C@]2(C)[C@@H]2[C@@H]1[C@@H]1CC[C@H]([C@H](C)CCCC(C)C)[C@@]1(C)CC2.O[C@H]1[C@@H](N)[C@H](O)[C@@H](C)O[C@H]1O[C@H]1/C=C/C=C/C=C/C=C/C=C/C=C/C=C/[C@H](C)[C@@H](O)[C@@H](C)[C@H](C)OC(=O)C[C@H](O)C[C@H](O)CC[C@@H](O)[C@H](O)C[C@H](O)C[C@](O)(C[C@H](O)[C@H]2C(O)=O)O[C@H]2C1 PCTMTFRHKVHKIS-BMFZQQSSSA-N 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/003—Reconstruction from projections, e.g. tomography
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Image Analysis (AREA)
Abstract
The invention discloses a remote sensing image fast re-projection method based on a lookup table, which relates to the technical field of remote sensing image processing and comprises the following steps: generating four empty lookup tables LUX1, LUY1, LUX2 and LUY2 in advance, and recording coordinate information of each pixel after the pixel is re-projected; determining a forward transformation Transform to Transform four vertex coordinates of the remote sensing image Raster into a target projection coordinate system DST; determining the original sequence of the four vertexes, connecting the four coordinate points after the re-projection into a quadrangle, and acquiring an external rectangle OutRect of the quadrangle. The invention realizes the precision of the remote sensing image reprojection, can select the reprojection method according to the needs, not only adopts the lookup table mode to carry out the remote sensing image reprojection, reduces the calculation process consuming time for the reprojection, and ensures the reprojection efficiency, but also only needs to generate the lookup table once, and can not obviously increase the data volume.
Description
Technical Field
The invention relates to the technical field of remote sensing image processing, in particular to a remote sensing image fast re-projection method based on a lookup table.
Background
With the advancement of the maturity and commercialization of satellite remote sensing technology, satellite remote sensing is rapidly developed and applied in more and more fields. The remote sensing image preprocessing is the premise of satellite remote sensing application, and the remote sensing image re-projection is an important link. Since the remote sensing image has a wide variety of coordinate systems and the remote sensing image does not necessarily have the same coordinate system as the user needs, it is generally necessary to re-project the remote sensing image in order to process and analyze the satellite remote sensing image in the desired coordinate system.
The computation process of the remote sensing image re-projection is extremely time-consuming, and the efficiency of the remote sensing image re-projection is improved.
Therefore, a method for rapidly re-projecting a remote sensing image based on a lookup table is needed.
An effective solution to the problems in the related art has not been proposed yet.
Disclosure of Invention
Aiming at the problems in the related art, the invention provides a remote sensing image fast re-projection method based on a lookup table, a common lookup table is configured by remote sensing images with the same spatial range and spatial resolution, and the lookup table records the coordinate information after re-projection corresponding to all pixels in the remote sensing image space. When a new remote sensing image needs to be subjected to re-projection operation, the recorded coordinate information is read from the corresponding pixel in the lookup table, and the pixel value can be written into the re-projected image in the target projection coordinate system. To overcome the above technical problems of the related art.
The technical scheme of the invention is realized as follows:
a remote sensing image fast re-projection method based on a lookup table comprises the following steps:
step S1, generating four empty lookup tables LUX1, LUY1, LUX2 and LUY2 in advance, and recording coordinate information of each pixel after the pixel is re-projected, wherein the column number and the row number of each lookup table are RasterXSize and RasterYSize respectively;
step S2, determining a forward transformation Transform to Transform the four vertex coordinates of the remote sensing image Raster into a target projection coordinate system DST, wherein the four vertex coordinates are expressed as:
XREvertex,YREvertex＝Transform(XEvertex,YEvertex)，
wherein XEvertex,YEvertexAs vertex coordinates, XREvertex,YREvertexCoordinates of the vertex coordinates in a target projection coordinate system DST are obtained;
step S3, determining the original sequence of the four vertexes, connecting the four coordinate points after the re-projection into a quadrangle, and acquiring an external rectangle OutRect of the quadrangle;
step S4, expanding the external rectangle OutRect, obtaining the expanded rectangle ExtendedRect, and generating a space-weight projection image Grid, which is expressed as:
step S5, traversing the pixels in the obtained Grid according to the row and column numbers, determining the row and column numbers of the center point of each pixel, and converting the row and column numbers into coordinates in a target projection coordinate system DST, wherein the coordinates are expressed as:
XE*＝XE+(COL+0.5)*Xres，
YE*＝YE―(ROW+0.5)*YRes，
wherein XE*And YE*The coordinates of the central point of the pixel of the ROW line of the COL column in Grid in a target projection coordinate system DST;
step S6, transforming the acquired pixel center DST coordinates into SRC, which is expressed as:
XRE*,YRE*＝Transform_Inv(XE*,YE*)，
wherein, XRE*,YRE*For the coordinate [ XE ] in the target projection coordinate system DST*,YE*]Corresponding coordinates in a source projection coordinate system SRC;
step S7, acquiring coordinate point [ XRE ]*,YRE*]And converting the image coordinate into an original satellite remote sensing image Raster, and expressing as follows:
COL*＝(XRE*―XRE)/Xres，
ROW*＝(YRE―YRE*)/YRes，
wherein, COL*And ROW*As a coordinate point [ XRE*，YRE*]The column number and the row number in the remote sensing image Raster;
step S8, extracting all empty pixels in the OutRect range in Grid, and writing the row and column numbers of the pixels into lookup tables LUX2 and LUY 2;
step S9, obtaining a scene remote sensing Image, generating an empty-weighted projection Image RepImage, obtaining the row and column numbers recorded at the positions of the non-empty pixels from the lookup table, and writing the pixel values corresponding to the positions of the non-empty pixels in the Image into the positions of the rows and columns recorded at the positions of the RepImage corresponding to the non-empty pixels.
Furthermore, the width and height of the scene remote sensing image Raster of the lookup table are rasterXSize and rasterYSize respectively, the resolution is XRes and YRES, and the coordinates at the upper left corner are [ XRE, YRE ];
further, the determining forward transformation Transform transforms the coordinates of four vertexes of the remote sensing image Raster into a target projection coordinate system DST, and comprises the following steps:
calibrating a projection coordinate system of the remote sensing image Raster as a source projection coordinate system SRC;
calibrating a target projection coordinate system to be DST;
calibrating the transformation forward transformation of the SRC coordinate system coordinate into the DST coordinate system coordinate;
the transformation that scales its DST coordinate system coordinates to SRC coordinate system coordinates is called the inverse Transform Inv.
Further, the generating of the empty and heavy projection image Grid further includes the following steps:
determining that the width and height of ExtendRect can be divided by XRes and YRes respectively;
taking XRes and YRes as resolutions and an ExtendRect range as a spatial range;
and calibrating the projection coordinate of the upper left corner of the Grid as [ XE, YE ].
Further, the extracting all null pixels in the range of OutRect in Grid includes the following steps:
determine its COL*And ROW*As a coordinate point [ XRE*，YRE*]Whether the column number and the row number in the remote sensing image Raster fall within the range of the remote sensing image Raster or not;
the method comprises the following steps of (1) obtaining integer row and column numbers R and C by downwards taking integers for the row and column numbers in a range of a master;
the obtained COL is written into column C, ROW R in LUX1, and ROW is written into column C, ROW R in LUXY 1.
The invention has the beneficial effects that:
the invention relates to a remote sensing image fast re-projection method based on a lookup table, which configures a common lookup table through remote sensing images in the same space range and space resolution, wherein the lookup table records coordinate information after re-projection corresponding to all pixels in a remote sensing image space, when a new remote sensing image needs to be re-projected, the pixel value can be written into a re-projected image under a target projection coordinate system only by reading the recorded coordinate information from the corresponding pixel position in the lookup table, so that the accuracy of the re-projection of the remote sensing image is realized, a re-projection method can be selected according to needs, the re-projection of the remote sensing image is performed by adopting the lookup table, the calculation process consumed by the re-projection is reduced, the re-projection efficiency is ensured, and in addition, only one lookup table needs to be generated, so that the data volume is not obviously increased.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic flowchart of a method for rapidly reprojecting a remote sensing image based on a lookup table according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a Sentinel-2 satellite remote sensing image and a re-projected image of a remote sensing image fast re-projection method based on a lookup table according to an embodiment of the present invention, where fig. 2(a) is an initial diagram of a satellite remote sensing image, fig. 2(b) is a schematic diagram of a circumscribed rectangle, and fig. 2(c) is a schematic diagram of a vertex coordinate;
fig. 3 is a schematic diagram of updating a lookup table of a remote sensing image fast re-projection method based on the lookup table according to an embodiment of the present invention, where fig. 3(a) is a traversal initial diagram, fig. 3(b) is a row-column number diagram, and fig. 3(c) is a corresponding position diagram;
fig. 4 is a schematic diagram of a pixel without a label value of a screening look-up table in a remote sensing image fast re-projection method based on the look-up table according to an embodiment of the present invention, where fig. 4(a) is a schematic diagram of traversal of LUX1 and LUY1, fig. 4(b) is a schematic diagram of a pixel at the same position, and fig. 4(c) is a schematic diagram of writing a pixel value;
fig. 5 is a schematic diagram of the remote sensing image reprojection based on the lookup table according to the method for rapidly reprojecting the remote sensing image based on the lookup table of the embodiment of the present invention, in which fig. 5(a) is a schematic diagram of traversing non-empty pixels of the lookup table, fig. 5(b) is a schematic diagram of pixels at the same position of the satellite remote sensing image, and fig. 5(c) is a schematic diagram of a newly generated reprojected image.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments that can be derived by one of ordinary skill in the art from the embodiments given herein are intended to be within the scope of the present invention.
According to the embodiment of the invention, a remote sensing image fast re-projection method based on a lookup table is provided.
As shown in fig. 1, the method for rapidly reprojecting a remote sensing image based on a lookup table according to an embodiment of the present invention includes the following steps:
step S1, generating four empty lookup tables LUX1, LUY1, LUX2 and LUY2 in advance, and recording coordinate information of each pixel after the pixel is re-projected, wherein the column number and the row number of each lookup table are RasterXSize and RasterYSize respectively;
step S2, determining a forward transformation Transform to Transform the four vertex coordinates of the remote sensing image Raster into a target projection coordinate system DST, wherein the four vertex coordinates are expressed as:
XREvertex,YREvertex＝Transform(XEvertex,YEvertex)，
wherein XEvertex,YEvertexAs vertex coordinates, XREvertex,YREvertexCoordinates of the vertex coordinates in a target projection coordinate system DST are obtained;
step S3, determining the original sequence of the four vertexes, connecting the four coordinate points after the re-projection into a quadrangle, and acquiring an external rectangle OutRect of the quadrangle;
step S4, expanding the external rectangle OutRect, obtaining the expanded rectangle ExtendedRect, and generating a space-weight projection image Grid, which is expressed as:
step S5, traversing the pixels in the obtained Grid according to the row and column numbers, determining the row and column numbers of the center point of each pixel, and converting the row and column numbers into coordinates in a target projection coordinate system DST, wherein the coordinates are expressed as:
XE*＝XE+(COL+0.5)*Xres，
YE*＝YE―(ROW+0.5)*YRes，
wherein XE*And YE*The coordinates of the central point of the pixel of the ROW line of the COL column in Grid in a target projection coordinate system DST;
step S6, transforming the acquired pixel center DST coordinates into SRC, which is expressed as:
XRE*,YRE*＝Transform_Inv(XE*,YE*)，
wherein, XRE*,YRE*For the coordinate [ XE ] in the target projection coordinate system DST*,YE*]Corresponding coordinates in a source projection coordinate system SRC;
step S7, acquiring coordinate point [ XRE ]*,YRE*]And converting the image coordinate into an original satellite remote sensing image Raster, and expressing as follows:
COL*＝(XRE*―XRE)/Xres，
ROW*＝(YRE―YRE*)/YRes，
wherein, COL*And ROW*As a coordinate point [ XRE*，YRE*]The column number and the row number in the remote sensing image Raster;
step S8, extracting all empty pixels in the OutRect range in Grid, and writing the row and column numbers of the pixels into lookup tables LUX2 and LUY 2;
step S9, obtaining a scene remote sensing Image, generating an empty-weighted projection Image RepImage, obtaining the row and column numbers recorded at the positions of the non-empty pixels from the lookup table, and writing the pixel values corresponding to the positions of the non-empty pixels in the Image into the positions of the rows and columns recorded at the positions of the RepImage corresponding to the non-empty pixels.
Furthermore, the width and height of the scene remote sensing image Raster of the lookup table are rasterXSize and rasterYSize respectively, the resolution is XRes and YRES, and the coordinates at the upper left corner are [ XRE, YRE ];
further, the determining forward transformation Transform transforms the coordinates of four vertexes of the remote sensing image Raster into a target projection coordinate system DST, and comprises the following steps:
calibrating a projection coordinate system of the remote sensing image Raster as a source projection coordinate system SRC;
calibrating a target projection coordinate system to be DST;
calibrating the transformation forward transformation of the SRC coordinate system coordinate into the DST coordinate system coordinate;
the transformation that scales its DST coordinate system coordinates to SRC coordinate system coordinates is called the inverse Transform Inv.
Further, the generating of the empty and heavy projection image Grid further includes the following steps:
determining that the width and height of ExtendRect can be divided by XRes and YRes respectively;
taking XRes and YRes as resolutions and an ExtendRect range as a spatial range;
and calibrating the projection coordinate of the upper left corner of the Grid as [ XE, YE ].
Further, the extracting all null pixels in the range of OutRect in Grid includes the following steps:
determine its COL*And ROW*As a coordinate point [ XRE*，YRE*]Whether the column number and the row number in the remote sensing image Raster fall within the range of the remote sensing image Raster or not;
the method comprises the following steps of (1) obtaining integer row and column numbers R and C by downwards taking integers for the row and column numbers in a range of a master;
the obtained COL is written into column C, ROW R in LUX1, and ROW is written into column C, ROW R in LUXY 1.
By means of the scheme, a common lookup table is configured through remote sensing images in the same space range and space resolution, the lookup table records the coordinate information after the re-projection corresponding to all pixels in the remote sensing image space, when the re-projection operation needs to be carried out on a new remote sensing image, the pixel value can be written into the re-projected image under a target projection coordinate system only by reading the recorded coordinate information from the corresponding pixel in the lookup table, the accuracy of the re-projection of the remote sensing image is achieved, the re-projection method can be selected according to needs, the remote sensing image re-projection is carried out in the lookup table mode, the calculation process consumed by the re-projection is reduced, the re-projection efficiency is guaranteed, in addition, only one lookup table needs to be generated, and the data volume cannot be obviously increased.
As shown in fig. 2 to 5, the specific example of the reprojection of the remote sensing image with a resolution of 10 m from the Sentinel-2 satellite between adjacent projection bands is as follows:
as shown in FIG. 2(a), the vertices A, B, C and D are Sentinel-2 satellite remote images, and the projection coordinate system is WGS 84/UTM zone 50N.
Four empty lookup tables LUX1, LUY1, LUX2 and LUY2 are generated. GDAL is used to read the image information of vertices A, B, C and D, including the width, height, and top left vertex projection coordinates.
As shown in fig. 2(b), the default method of GDAL is selected as the coordinate system forward transform and inverse transform method. The remote sensing image vertex A, B, C and the D coordinates are transformed into corresponding coordinates A1, B1, C1 and D1 in an adjacent projection coordinate system WGS 84/UTM zone 49N, and an external rectangle EFGH of quadrangles A1, B1, C1 and D1 is calculated.
As shown in FIG. 2(c), the EFGH expansion rectangle, E1F1G1H1 in FIG. 2(c), is calculated with the following vertex coordinates:
E1X＝H1X,F1X＝G1X
E1Y＝F1Y,G1Y＝H1Y
E1X＝Floor(EX÷XRes)×XRes
F1X＝Ceil(FX÷XRes)×XRes
E1Y＝Ceil(EY÷YRes)×YRes
G1Y＝Floor(GY÷YRes)×YRes
in the above formula, EX, FX, GX, HX, E1X, F1X, G1X, H1X, EY, FY, GY, HY, E1Y, F1Y, G1Y and H1Y are E, F, G, H and E1, F1, G1 and H1 point coordinates. Floor is the number of rounding down functions and Ceil is the rounding up function. Here XRes and YRES both take 10 meter resolution.
E1F1G1H1 was aliquoted according to the resolution of 10 meters. A reprojected image mGrid is generated as a grid in fig. 2(c), with each grid representing a pixel.
In addition, as shown in fig. 3, each pixel in the mGrid (fig. 3(a)) is traversed, and the center point row number of each pixel is converted into a projection coordinate in the WGS 84/UTM zone 49N coordinate system. These coordinates are converted into coordinates in WGS 84/UTM zone 50N coordinate system by GDAL, and converted into row and column numbers mRow and mCon in Sentinel-2 remote sensing image ABCD (FIG. 3 (b)).
If the row and column numbers are in the remote sensing images A, B, C and D, the row and column numbers corresponding to the mGrid pixel row and column numbers in the lookup table are obtained by taking down integers from mRow and mChol, and the mGrid pixel row and column numbers are respectively written into the corresponding positions of the pixels in the lookup tables LUX1 and LUY1 (FIG. 2 (c)).
As shown in fig. 4, the non-empty pixels of LUX1 and LUY1 (fig. 4(a)), that is, black dots in fig. 4(a), are traversed, the row and column numbers of the pixel record are obtained, and the pixel value of the pixel at the same position in the Sentinel-2 remote sensing image, that is, the black dot in fig. 4(b), is written into the mGrid (fig. 4 (c)).
Pixels whose mGrid falls within the range of A1B1C1D1 are traversed, null pixels (at the location of the hollow circle in fig. 4(C)) are extracted, and the pixel row and column numbers are written into LUX2, LUY 2.
Referring to fig. 5, given another Sentinel-2 satellite remote-sensed image A2B2C2D2, which has the same spatial range and resolution as ABCD, a new re-projected image E2F2G2H2 is generated, the non-empty pixels in the lookup table, i.e., the black dots in fig. 5(a), are traversed, the row and column numbers recorded at the position are extracted, and the pixel values of the same-position pixels in the satellite remote-sensed images A2, B2, C2 and D2, i.e., the black dots in fig. 5(B), are written into the newly generated re-projected image, i.e., the black dots in fig. 5 (C).
In summary, with the above technical solution of the present invention, a common lookup table is configured by remote sensing images of the same spatial range and spatial resolution, the lookup table records coordinate information after reprojection corresponding to all pixels in the remote sensing image space, when a reprojection operation needs to be performed on a new remote sensing image, the pixel value can be written into a reprojected image under a target projection coordinate system by reading the recorded coordinate information from the corresponding pixel in the lookup table, so as to achieve the precision of the reprojection of the remote sensing image, a reprojection method can be selected as needed, not only is the remote sensing image reprojection performed by using the lookup table, but also the calculation process consumed by the reprojection is reduced, the reprojection efficiency is ensured, and in addition, only one lookup table needs to be generated, so that the data size is not significantly increased.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (5)
1. A remote sensing image fast re-projection method based on a lookup table is characterized by comprising the following steps:
generating four empty lookup tables LUX1, LUY1, LUX2 and LUY2 in advance, and recording coordinate information of each pixel after the pixel is re-projected, wherein the column number and the row number of each lookup table are RasterXSize and RasterYSize respectively;
determining a forward transformation to Transform four vertex coordinates of the remote sensing image Raster into a target projection coordinate system DST, wherein the four vertex coordinates are expressed as:
XREvertex,YREvertex＝Transform(XEvertex,YEvertex)，
wherein XEvertex,YEvertexAs vertex coordinates, XREvertex,YREvertexCoordinates of the vertex coordinates in a target projection coordinate system DST are obtained;
determining the original sequence of the four vertexes, connecting the four coordinate points after the re-projection into a quadrangle, and acquiring an external rectangle OutRect of the quadrangle;
expanding an external rectangle OutRect, acquiring an expanded rectangle ExtendRect, and generating a blank and heavy projection image Grid, wherein the blank and heavy projection image Grid is expressed as:
traversing the pixels in the obtained Grid according to the row and column numbers, determining the row and column numbers of the center point of each pixel, and converting the row and column numbers into coordinates in a target projection coordinate system DST, wherein the coordinates are expressed as:
XE*＝XE+(COL+0.5)*Xres，
YE*＝YE―(ROW+0.5)*YRes，
wherein XE*And YE*The coordinates of the central point of the pixel of the ROW line of the COL column in Grid in a target projection coordinate system DST;
transforming the acquired pixel center point DST coordinates into SRC, which is expressed as:
XRE*,YRE*＝Transform_Inv(XE*,YE*)，
wherein, XRE*,YRE*For the coordinate [ XE ] in the target projection coordinate system DST*,YE*]Corresponding coordinates in a source projection coordinate system SRC;
coordinate point [ XRE ] to be acquired*,YRE*]And converting the image coordinate into an original satellite remote sensing image Raster, and expressing as follows:
COL*＝(XRE*―XRE)/Xres，
ROW*＝(YRE―YRE*)/YRes，
wherein, COL*And ROW*As a coordinate point [ XRE*，YRE*]The column number and the row number in the remote sensing image Raster;
extracting all empty pixels in the OutRect range in Grid, and writing the row and column numbers of the pixels into lookup tables LUX2 and LUY 2;
the method comprises the steps of obtaining a scene remote sensing Image, generating an empty weight projection Image RepImage, obtaining a line and row number recorded at a non-empty pixel position from a lookup table, and writing a pixel value corresponding to the non-empty pixel position in the Image into the line and row position recorded at the non-empty pixel position in the RepImage.
2. The method for rapidly reprojecting remote sensing images based on lookup tables as claimed in claim 1, wherein the lookup table has a remote sensing image Raster with a width and a height of RasterXSize and RasterYSize, respectively, a resolution of XRes and YRes, and an upper left-hand coordinate of [ XRE, YRE ].
3. The lookup table-based remote sensing image fast re-projection method as claimed in claim 1, wherein said determining forward Transform transforms the four vertex coordinates of the remote sensing image Raster into the target projection coordinate system DST, comprising the steps of:
calibrating a projection coordinate system of the remote sensing image Raster as a source projection coordinate system SRC;
calibrating a target projection coordinate system to be DST;
calibrating the transformation forward transformation of the SRC coordinate system coordinate into the DST coordinate system coordinate;
the transformation that scales its DST coordinate system coordinates to SRC coordinate system coordinates is called the inverse Transform Inv.
4. The lookup table-based remote sensing image fast re-projection method according to claim 2, wherein the generating of the empty-weighted projected image Grid further comprises the steps of:
determining that the width and height of ExtendRect can be divided by XRes and YRes respectively;
taking XRes and YRes as resolutions and an ExtendRect range as a spatial range;
and calibrating the projection coordinate of the upper left corner of the Grid as [ XE, YE ].
5. The method for rapidly reprojection of remote sensing images based on lookup tables according to claim 1, wherein said extracting all empty pixels within the range of out rect in Grid comprises the following steps:
determine its COL*And ROW*As a coordinate point [ XRE*，YRE*]Whether the column number and the row number in the remote sensing image Raster fall within the range of the remote sensing image Raster or not;
the method comprises the following steps of (1) obtaining integer row and column numbers R and C by downwards taking integers for the row and column numbers in a range of a master;
the obtained COL is written into column C, ROW R in LUX1, and ROW is written into column C, ROW R in LUXY 1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010789902.3A CN111986283B (en) | 2020-08-07 | 2020-08-07 | Remote sensing image rapid re-projection method based on lookup table |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010789902.3A CN111986283B (en) | 2020-08-07 | 2020-08-07 | Remote sensing image rapid re-projection method based on lookup table |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111986283A true CN111986283A (en) | 2020-11-24 |
| CN111986283B CN111986283B (en) | 2023-10-27 |
Family
ID=73445686
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010789902.3A Active CN111986283B (en) | 2020-08-07 | 2020-08-07 | Remote sensing image rapid re-projection method based on lookup table |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111986283B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070188516A1 (en) * | 2006-02-10 | 2007-08-16 | Ioup Elias Z K | Method for Efficiently Transforming a raster image from one map projection to another map projection |
| CN103218789A (en) * | 2013-04-24 | 2013-07-24 | 中国科学院遥感与数字地球研究所 | Automation ortho-rectification method based on geometric deformation step resolving |
| CN111460060A (en) * | 2020-03-04 | 2020-07-28 | 华中科技大学 | User region-of-interest remote sensing image space indexing method |
-
2020
- 2020-08-07 CN CN202010789902.3A patent/CN111986283B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070188516A1 (en) * | 2006-02-10 | 2007-08-16 | Ioup Elias Z K | Method for Efficiently Transforming a raster image from one map projection to another map projection |
| CN103218789A (en) * | 2013-04-24 | 2013-07-24 | 中国科学院遥感与数字地球研究所 | Automation ortho-rectification method based on geometric deformation step resolving |
| CN111460060A (en) * | 2020-03-04 | 2020-07-28 | 华中科技大学 | User region-of-interest remote sensing image space indexing method |
Non-Patent Citations (1)
| Title |
|---|
| 李自力;高光军;沙万里;: "基于World文件的遥感影像坐标转换研究", 现代测绘, no. 04 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111986283B (en) | 2023-10-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US5155805A (en) | Method and apparatus for moving control points in displaying digital typeface on raster output devices | |
| EP2036046B1 (en) | Anisometric texture synthesis | |
| US5159668A (en) | Method and apparatus for manipulating outlines in improving digital typeface on raster output devices | |
| US7609263B2 (en) | Drawing processing apparatus and method for compressing drawing data | |
| CN101071508A (en) | Image processing apparatus, image processing method, and image processing program | |
| JP2005100177A (en) | Image processor and its method | |
| US20110141112A1 (en) | Image processing techniques | |
| JPH10105723A (en) | Memory constitution for texture mapping | |
| CN111630560B (en) | Method and system for correcting a distorted input image | |
| CN102326183A (en) | Image processing system, image processing method, and image processing program | |
| US8537173B2 (en) | Graphics rendering apparatus, graphics rendering method, Recording medium having recorded therein graphics rendering program, and integrated circuit for rendering a high-quality image using a scaling coefficient | |
| US8587609B1 (en) | Accuracy-adaptive and scalable vector graphics rendering | |
| CN108416729B (en) | Device and method for realizing anti-aliasing of line segment in GPU | |
| CN111986283A (en) | Remote sensing image fast re-projection method based on lookup table | |
| JP3547250B2 (en) | Drawing method | |
| JP2002519793A (en) | Method and system for rendering graphic elements | |
| US11869123B2 (en) | Anti-aliasing two-dimensional vector graphics using a compressed vertex buffer | |
| CN101739696A (en) | System and method for rasterizing convex polygon | |
| CN114625990A (en) | Method, device, equipment and medium for rendering webpage end grid data | |
| JP3747859B2 (en) | Image processing apparatus and method | |
| JP4042462B2 (en) | Image processing apparatus and method | |
| JP2011053263A (en) | Image processing device, image processing method, image output system, program and recording medium | |
| JP2003263650A (en) | Image processor and image processing method | |
| JPS63208898A (en) | Character processor | |
| JP2675363B2 (en) | Character processor |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |