CN111986283B - Remote sensing image rapid re-projection method based on lookup table - Google Patents
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Abstract
The invention discloses a remote sensing image rapid 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 after each pixel is re-projected; determining a forward conversion transformation to convert four vertex coordinates of the remote sensing image Raster into a target projection coordinate system DST; determining the original sequence of four vertexes, connecting four coordinate points after re-projection into a quadrilateral, and obtaining the circumscribed rectangle OutRect of the quadrilateral. The invention realizes the accuracy of remote sensing image re-projection, can select the re-projection method according to the need, not only adopts the lookup table to carry out remote sensing image re-projection, reduces the time-consuming calculation process of re-projection, ensures the re-projection efficiency, but also only needs to generate the lookup table once, and can not obviously increase the data quantity.
Description
Technical Field
The invention relates to the technical field of remote sensing image processing, in particular to a remote sensing image rapid re-projection method based on a lookup table.
Background
With the mature and commercialized promotion of satellite remote sensing technology, satellite remote sensing is rapidly developed and applied to more and more fields. The preprocessing of the remote sensing image is a precondition of satellite remote sensing application, and the re-projection of the remote sensing image is one of important links. The remote sensing image is a plurality of kinds of coordinate systems, and the remote sensing image is not necessarily the same as the coordinate system required by the user, so in order to process and analyze the satellite remote sensing image under the required coordinate system, it is generally required to re-project the remote sensing image.
The remote sensing image re-projection calculation process is extremely time-consuming, so as to improve the remote sensing image re-projection efficiency.
Therefore, a fast reprojection method of remote sensing images based on a lookup table is needed.
For the problems in the related art, no effective solution has been proposed at present.
Disclosure of Invention
Aiming at the problems in the related art, the invention provides a remote sensing image rapid re-projection method based on a lookup table, wherein the common lookup table is configured by remote sensing images with the same spatial range and spatial resolution, and the lookup table records coordinate information after re-projection corresponding to all pixels in a remote sensing image space. When the new remote sensing image needs to be subjected to the reprojection operation, the pixel value can be written into the reprojected image under the target projection coordinate system only by reading the recorded coordinate information from the corresponding pixel in the lookup table. So as to overcome the technical problems existing in the prior related art.
The technical scheme of the invention is realized as follows:
a remote sensing image rapid re-projection method based on a lookup table comprises the following steps:
step S1, four empty lookup tables LUX1, LUY1, LUX2 and LUY2 are generated in advance, and coordinate information after each pixel is subjected to re-projection is recorded, wherein the column number and the row number of each lookup table are respectively RasterXSize and RasterYSize;
step S2, determining that the forward transformation Transform transforms four vertex coordinates of the remote sensing image Raster into a target projection coordinate system DST, wherein the four vertex coordinates are expressed as follows:
XRE vertex ,YRE vertex ＝Transform(XE vertex ,YE vertex )，
wherein XE is vertex ,YE vertex For vertex coordinates, XRE vertex ,YRE vertex The vertex coordinates are the coordinates of the vertex coordinates in a target projection coordinate system DST;
step S3, determining the original sequence of four vertexes, connecting four coordinate points after re-projection into a quadrilateral, and obtaining an external rectangle OutRect of the quadrilateral;
step S4, an external rectangle OutRect is expanded, an expanded rectangle ExtendRect is obtained, and an empty projection image Grid is generated and expressed as:
step S5, traversing the pixels in the acquired Grid according to row and column numbers, determining the row and column numbers of the central point of each pixel, converting the row and column numbers into coordinates in a target projection coordinate system DST, and representing the coordinates as follows:
XE * ＝XE+(COL+0.5)*Xres，
YE * ＝YE―(ROW+0.5)*YRes，
wherein XE is * And YE (YEs) * The coordinates of the central point of the ROW-line pixel of the COL column in Grid in the target projection coordinate system DST;
step S6, transforming the acquired coordinates of the pixel center point DST into the SRC, expressed as:
XRE * ,YRE * ＝Transform_Inv(XE * ,YE * )，
wherein XRE is as follows * ,YRE * For coordinates [ XE ] in the target projection coordinate system DST * ,YE * ]Corresponding coordinates in the source projection coordinate system SRC;
step S7, obtaining coordinate point [ XRE ] * ,YRE * ]The image coordinates converted into the original satellite remote sensing image Raster are expressed as:
COL * ＝(XRE * ―XRE)/Xres，
ROW * ＝(YRE―YRE * )/YRes，
wherein COL * And ROW (R-W) * Is coordinate point [ XRE ] * ，YRE * ]Column number and row number in 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 the lookup tables LUX2 and LUY 2;
step S9, obtaining a scene remote sensing Image, generating an empty reprojection Image RepIMage, obtaining row numbers recorded at non-empty pixels from a lookup table, and writing pixel values corresponding to the non-empty pixels in the Image into the row positions recorded at the non-empty pixels in the RepIMage.
Further, the wide and high of a remote sensing image Raster of the lookup table are RasterXSize and RasterYSize respectively, the resolution is XRes and YRes, and the upper left corner coordinate is [ XRE, YRE ];
further, the determining the forward transformation Transform transforms four vertex coordinates of the remote sensing image Master into the target projection coordinate system DST, including 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 as DST;
calibrating the transformation from SRC coordinate system coordinate to DST coordinate system coordinate to positive transformation;
the transformation that scales its DST coordinate system coordinates to SRC coordinate system coordinates is called the inverse transform_inv.
Further, the generating the empty projection image Grid further includes the following steps:
determining the width and the height of ExtendRect to be divided by XRes and YRes respectively;
taking XRes and YRes as resolution ratios and taking an extendsect range as a space range;
the projection coordinate of the upper left corner of Grid is marked as [ XE, YE ].
Further, the extracting all the empty pixels in the OutRect range in Grid includes the following steps:
judging COL thereof * And ROW (R-W) * Is coordinate point [ XRE ] * ，YRE * ]Whether the column number and the row number in the remote sensing image Raster fall into the range of the remote sensing image Raster or not;
the method comprises the steps that the method falls into a range of a Raster, and integer numbers are taken downwards from row numbers to obtain integer row numbers R and integer column numbers C;
and writing the acquired COL into the C column and the R ROW in the LUX1, and writing the ROW into the C column and the R ROW in the LUXY 1.
The invention has the beneficial effects that:
according to the remote sensing image rapid re-projection method based on the lookup table, the common lookup table is configured through the remote sensing images with the same spatial range and spatial resolution, the lookup table records coordinate information after re-projection corresponding to all pixels in the remote sensing image space, when new remote sensing images are required to be subjected to re-projection operation, the recorded coordinate information is read from the corresponding pixels in the lookup table, the pixel value can be written into the re-projected images under the target projection coordinate system, the re-projection precision of the remote sensing images is realized, the re-projection method can be selected according to the requirement, the remote sensing image re-projection is performed in a lookup table mode, the time-consuming calculation process of re-projection is reduced, the re-projection efficiency is ensured, and in addition, the lookup table is only required to be generated once, and the data quantity is not obviously increased.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are 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 other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a remote sensing image fast re-projection method based on a lookup table according to an embodiment of the invention;
fig. 2 is a schematic diagram of a Sentinel-2 satellite remote sensing image and a reprojection image of a remote sensing image rapid reprojection method based on a lookup table according to an embodiment of the present invention, where fig. 2 (a) is an initial view of the satellite remote sensing image, fig. 2 (b) is a schematic diagram of an external rectangle, and fig. 2 (c) is a schematic diagram of vertex coordinates;
fig. 3 is a schematic diagram of updating a lookup table according to a method for fast reprojection of remote sensing images based on a lookup table according to an embodiment of the present invention, where fig. 3 (a) is a traversal initial diagram, fig. 3 (b) is a schematic diagram of row and column numbers, and fig. 3 (c) is a schematic diagram of corresponding positions;
fig. 4 is a schematic diagram of a screening lookup table without a marker value pixel according to a lookup table-based remote sensing image fast re-projection method according to an embodiment of the present invention, where fig. 4 (a) is a schematic diagram traversing 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 a remote sensing image reprojection based on a lookup table according to a fast remote sensing image reprojection method based on a lookup table according to an embodiment of the present invention, where fig. 5 (a) is a schematic diagram of non-empty pixels traversing the lookup table, fig. 5 (b) is a schematic diagram of pixels at the same position of a satellite remote sensing image, and fig. 5 (c) is a schematic diagram of a newly generated reprojection image.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which are derived by a person skilled in the art based on the embodiments of the invention, fall within the scope of protection of the invention.
According to the embodiment of the invention, a remote sensing image rapid re-projection method based on a lookup table is provided.
As shown in fig. 1, a remote sensing image fast reprojection method based on a lookup table according to an embodiment of the present invention includes the following steps:
step S1, four empty lookup tables LUX1, LUY1, LUX2 and LUY2 are generated in advance, and coordinate information after each pixel is subjected to re-projection is recorded, wherein the column number and the row number of each lookup table are respectively RasterXSize and RasterYSize;
step S2, determining that the forward transformation Transform transforms four vertex coordinates of the remote sensing image Raster into a target projection coordinate system DST, wherein the four vertex coordinates are expressed as follows:
XRE vertex ,YRE vertex ＝Transform(XE vertex ,YE vertex )，
wherein XE is vertex ,YE vertex For vertex coordinates, XRE vertex ,YRE vertex The vertex coordinates are the coordinates of the vertex coordinates in a target projection coordinate system DST;
step S3, determining the original sequence of four vertexes, connecting four coordinate points after re-projection into a quadrilateral, and obtaining an external rectangle OutRect of the quadrilateral;
step S4, an external rectangle OutRect is expanded, an expanded rectangle ExtendRect is obtained, and an empty projection image Grid is generated and expressed as:
step S5, traversing the pixels in the acquired Grid according to row and column numbers, determining the row and column numbers of the central point of each pixel, converting the row and column numbers into coordinates in a target projection coordinate system DST, and representing the coordinates as follows:
XE * ＝XE+(COL+0.5)*Xres，
YE * ＝YE―(ROW+0.5)*YRes，
wherein XE is * And YE (YEs) * The coordinates of the central point of the ROW-line pixel of the COL column in Grid in the target projection coordinate system DST;
step S6, transforming the acquired coordinates of the pixel center point DST into the SRC, expressed as:
XRE * ,YRE * ＝Transform_Inv(XE * ,YE * )，
wherein XRE is as follows * ,YRE * For coordinates [ XE ] in the target projection coordinate system DST * ,YE * ]Corresponding coordinates in the source projection coordinate system SRC;
step S7, obtaining coordinate point [ XRE ] * ,YRE * ]The image coordinates converted into the original satellite remote sensing image Raster are expressed as:
COL * ＝(XRE * ―XRE)/Xres，
ROW * ＝(YRE―YRE * )/YRes，
wherein COL * And ROW (R-W) * Is coordinate point [ XRE ] * ，YRE * ]Column number and row number in 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 the lookup tables LUX2 and LUY 2;
step S9, obtaining a scene remote sensing Image, generating an empty reprojection Image RepIMage, obtaining row numbers recorded at non-empty pixels from a lookup table, and writing pixel values corresponding to the non-empty pixels in the Image into the row positions recorded at the non-empty pixels in the RepIMage.
Further, the wide and high of a remote sensing image Raster of the lookup table are RasterXSize and RasterYSize respectively, the resolution is XRes and YRes, and the upper left corner coordinate is [ XRE, YRE ];
further, the determining the forward transformation Transform transforms four vertex coordinates of the remote sensing image Master into the target projection coordinate system DST, including 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 as DST;
calibrating the transformation from SRC coordinate system coordinate to DST coordinate system coordinate to positive transformation;
the transformation that scales its DST coordinate system coordinates to SRC coordinate system coordinates is called the inverse transform_inv.
Further, the generating the empty projection image Grid further includes the following steps:
determining the width and the height of ExtendRect to be divided by XRes and YRes respectively;
taking XRes and YRes as resolution ratios and taking an extendsect range as a space range;
the projection coordinate of the upper left corner of Grid is marked as [ XE, YE ].
Further, the extracting all the empty pixels in the OutRect range in Grid includes the following steps:
judging COL thereof * And ROW (R-W) * Is coordinate point [ XRE ] * ，YRE * ]Whether the column number and the row number in the remote sensing image Raster fall into the range of the remote sensing image Raster or not;
the method comprises the steps that the method falls into a range of a Raster, and integer numbers are taken downwards from row numbers to obtain integer row numbers R and integer column numbers C;
and writing the acquired COL into the C column and the R ROW in the LUX1, and writing the ROW into the C column and the R ROW in the LUXY 1.
By means of the scheme, the common lookup table is configured through the remote sensing images with the same spatial range and spatial resolution, the lookup table records coordinate information after the re-projection corresponding to all pixels in the remote sensing image space, when new remote sensing images are required to be subjected to re-projection operation, the recorded coordinate information is only required to be read from the corresponding pixels in the lookup table, the pixel values can be written into the re-projected images under the target projection coordinate system, the re-projection precision of the remote sensing images is realized, a re-projection method can be selected according to the requirement, the remote sensing image re-projection is performed in a lookup table mode, the time-consuming calculation process of the re-projection is reduced, the re-projection efficiency is guaranteed, and in addition, the lookup table is only required to be generated once, and the data quantity is not increased obviously.
In addition, as shown in fig. 2-5, specifically, taking a re-projection of a Sentinel-2 satellite remote sensing image with a resolution of 10 meters between adjacent projection belts as an example, the following is shown:
as shown in FIG. 2 (a), the vertices A, B, C and D are Sentinel-2 satellite remote sensing images, and the projection coordinate system is WGS 84/UTM zone 50N.
Four empty lookup tables LUX1, LUY1, LUX2, and LUY2 are generated. The GDAL is used to read the image information of vertices A, B, C and D, including the width, height, top left corner vertex projection coordinates.
As shown in fig. 2 (b), the default method of GDAL is selected as the coordinate system forward and inverse transformation method. And transforming the remote sensing image vertex A, B, C and the D coordinate into corresponding coordinates A1, B1, C1 and D1 in an adjacent projection coordinate system WGS 84/UTM zone 49N, and calculating the circumscribed rectangle EFGH of the quadrangles A1, B1, C1 and D1.
As shown in fig. 2 (c), an EFGH expansion rectangle, that is, E1F1G1H1 in fig. 2 (c), is calculated, and the vertex coordinates thereof are as follows:
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, H1Y is E, F, G, H and the coordinates of E1, F1, G1, H1 points. Floor is the number of downward rounding functions and Ceil is the upward rounding function. Where XRes and yrs are both at 10 meter resolution.
E1F1G1H1 was aliquoted according to a resolution of 10 meters. The mGrid image is generated as a grid in fig. 2 (c), and each small square represents one pixel.
In addition, as shown in FIG. 3, each pixel in mGRID (FIG. 3 (a)) is traversed to convert each pixel center point rank number to projected coordinates in the WGS 84/UTM zone 49N coordinate system. These coordinates are converted to coordinates in the WGS 84/UTM zone 50N coordinate system using GDAL, and converted to rank numbers mRow, mCol in the Sentinel-2 remote sensing image ABCD (FIG. 3 (b)).
If the row and column numbers are within the remote sensing images A, B, C and D, the mRow and mCol are down-numbered to obtain row and column numbers corresponding to the mGrid pixel row and column numbers in the lookup table, and the mGrid pixel row and column numbers are written into the corresponding positions of the pixels in the lookup tables LUX1 and LUY1 (fig. 2 (c)).
As shown in fig. 4, the black dots in fig. 4 (a) are traversed for non-empty pixels of LUX1 and LUY1 (fig. 4 (a)), the row and column numbers of the pixel records are acquired, and the pixel values of the black dots in fig. 4 (b) at the same position in the Sentinel-2 remote sensing image are written into mGrid (fig. 4 (c)).
Pixels whose mGrid falls within the range of A1B1C1D1 are traversed, empty pixels (at open circle positions in fig. 4 (C)) are extracted, and these pixel row and column numbers are written into LUX2, LUY2.
Referring to fig. 5, given another satellite remote sensing image A2B2C2D2 of a second scene sentel-2, the remote sensing image has the same spatial range and resolution as ABCD, a new reprojection image E2F2G2H2 is generated, non-empty pixels of the lookup table, that is, black dots in fig. 5 (a), are traversed, row and column numbers recorded at the positions are extracted, and pixel values of pixels in the same positions in the satellite remote sensing images A2, B2, C2 and D2, that is, black dots in fig. 5 (B), are written into the newly generated reprojection image, that is, at the black dots in fig. 5 (C).
In summary, by means of the above technical solution of the present invention, a common lookup table is configured by remote sensing images with the same spatial range and spatial resolution, the lookup table records 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, only the recorded coordinate information needs to be read from the corresponding pixel in the lookup table, and the pixel value can be written into the re-projected image under the target projection coordinate system, thereby realizing the accuracy of re-projection of the remote sensing image.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (5)
1. The remote sensing image rapid re-projection method based on the lookup table is characterized by comprising the following steps of:
generating four empty lookup tables LUX1, LUY1, LUX2 and LUY2 in advance, and recording coordinate information after each pixel is subjected to re-projection, wherein the column number and the row number of each lookup table are respectively RasterXSize and RasterYSize;
determining a forward conversion Transform to convert four vertex coordinates of the remote sensing image Raster into a target projection coordinate system DST, wherein the four vertex coordinates are expressed as follows:
XRE vertex ,YRE vertex ＝Transform(XE vertex ,YE vertex )，
wherein XE is vertex ,YE vertex For vertex coordinates, XRE vertex ,YRE vertex The vertex coordinates are the coordinates of the vertex coordinates in a target projection coordinate system DST;
determining the original sequence of four vertexes, connecting four coordinate points after re-projection into a quadrilateral, and obtaining an external rectangle OutRect of the quadrilateral;
expanding an external rectangle OutRect, obtaining an expanded rectangle ExtendRect, and generating an empty projection image Grid, wherein the empty projection image Grid is expressed as:
traversing the pixels in the acquired Grid according to row and column numbers, determining the row and column numbers of the central point of each pixel, converting the row and column numbers into coordinates in a target projection coordinate system DST, and representing the coordinates as follows:
XE * ＝XE+(COL+0.5)*Xres，
YE * ＝YE―(ROW+0.5)*YRes，
wherein XE is * And YE (YEs) * The coordinates of the central point of the ROW-line pixel of the COL column in Grid in the target projection coordinate system DST;
transforming the acquired coordinates of the pixel center point DST into SRC, wherein the coordinates are expressed as follows:
XRE * ,YRE * ＝Transform_Inv(XE * ,YE * )，
wherein XRE is as follows * ,YRE * For coordinates [ XE ] in the target projection coordinate system DST * ,YE * ]Corresponding coordinates in the source projection coordinate system SRC;
coordinate point to be acquired [ XRE * ,YRE * ]The image coordinates converted into the original satellite remote sensing image Raster are expressed as:
COL * ＝(XRE * ―XRE)/Xres，
ROW * ＝(YRE―YRE * )/YRes，
wherein COL * And ROW (R-W) * Is coordinate point [ XRE ] * ，YRE * ]Column number and row number in 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 the lookup tables LUX2 and LUY 2;
and acquiring a scene remote sensing Image, generating an empty reprojected Image RepIMage, acquiring a 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 row position recorded at the non-empty pixel position in the RepIMage.
2. The method for rapidly reprojecting remote sensing images based on the lookup table according to claim 1, wherein the lookup table has a scene remote sensing image Raster with wide height of RasterXSize and RasterYSize, resolution of XRes and YRes, and upper left corner coordinates of [ XRE, YRE ].
3. The method for fast reprojection of remote sensing images based on lookup tables according to claim 1, wherein the determining the forward Transform transforms four vertex coordinates of the remote sensing image Master into the target projection coordinate system DST, 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 as DST;
calibrating the transformation from SRC coordinate system coordinate to DST coordinate system coordinate to positive transformation;
the transformation that scales its DST coordinate system coordinates to SRC coordinate system coordinates is called the inverse transform_inv.
4. The method for fast reprojection of remote sensing images based on lookup tables according to claim 2, wherein said generating an empty reprojection image Grid further comprises the steps of:
determining the width and the height of ExtendRect to be divided by XRes and YRes respectively;
taking XRes and YRes as resolution ratios and taking an extendsect range as a space range;
the projection coordinate of the upper left corner of Grid is marked as [ XE, YE ].
5. The method for fast reprojection of remote sensing images based on lookup tables according to claim 1, wherein said extracting all empty pixels in the scope of OutRect in Grid comprises the steps of:
judging COL thereof * And ROW (R-W) * Is coordinate point [ XRE ] * ，YRE * ]Whether the column number and the row number in the remote sensing image Raster fall into the range of the remote sensing image Raster or not;
the method comprises the steps that the method falls into a range of a Raster, and integer numbers are taken downwards from row numbers to obtain integer row numbers R and integer column numbers C;
and writing the acquired COL into the C column and the R ROW in the LUX1, and writing the ROW into the C column and the R ROW in the LUXY 1.
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