CN116452438A - Positive solution correction method and system for aviation three-linear-array camera image - Google Patents
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Abstract
The invention provides a forward solution correction method and a forward solution correction system for an aviation three-linear-array camera image. The method extracts weights of 4 pixels of each target position on the target image; decomposing the gray value of the original pixel into pixels according to the weights, and accumulating the allocated gray and weights into corresponding variables of the target pixel respectively; normalizing according to the gray value and the weight obtained by the target pixel to form a target image; and detecting a target image, and if the weight is smaller than a preset threshold value, compensating by adopting the average value of adjacent pixels. The method can effectively solve the precision problem caused by the discontinuity of adjacent lines of targets in the aerial linear array image reaction method, remarkably improves the correction precision and quality of the linear array images, and is particularly suitable for the image correction of the aerial linear array camera.
Description
Technical Field
The invention relates to the technical field of remote sensing image correction, in particular to a forward solution correction method for an aviation three-linear array camera image, wherein target pixel splitting is a key technology of the forward solution correction method.
Background
Three CCD detectors are arranged on a focal plane of the three-line array camera, three CCD linear arrays are imaged simultaneously, a front line-of-sight array (F) is imaged obliquely forwards, a lower line-of-sight array (N) is imaged vertically to the ground, and a rear line-of-sight array (B) is imaged obliquely backwards during flight, and the working principle is shown in figure 1. Along with the forward push scanning of the load platform, the camera continuously scans and images the ground at a certain frequency, and three ground linear images can be obtained at the same time at each exposure time.
The original images of the three-line array camera are recorded respectively according to CCD lines, each CCD line records an image file, and each line of the image file is data of a certain line on the ground, which is acquired by the CCD line at a certain moment in a central imaging mode, according to the principle of continuous push-broom imaging. Each line of the image is imaged once in a central imaging mode, so that CCD pixels are imaged continuously, namely the CCD line direction is consistent with the actual ground position, but the image lines are imaged independently, and the lines are not adjacent to each other on the ground. Particularly when the aircraft is affected by atmospheric air flow, vibration of an aircraft engine and the like, the attitude of the aircraft is not stable and unchanged, and thus, the acquired image has a certain deformation, as shown in fig. 2.
Since the original image of the three-line camera is greatly deformed and cannot be directly observed and measured, image correction is necessary to correct the image to an image consistent with the actual position, as shown in fig. 3. In the three-linear array processing system, an image having a distortion originally is referred to as an L0 level image, and an image corrected for the distortion is referred to as an L1 level image.
The traditional image correction adopts an inverse solution method image correction, and the basic principle is that the position of a target image in an original image is solved according to an imaging equation according to the whole pixel position (namely row number) of the target image, then the original image is subjected to sub-pixel interpolation to obtain the gray level of the original image, and the gray level is placed on the position of the target image.
In the process of correcting an image by an inverse solution method, when the original image is subjected to sub-pixel interpolation, the image participating in interpolation must be required to be continuously imaged, that is, each adjacent pixel is continuous on the original target. However, for the aerial linear array image, because the flight platform is not as stable as a satellite linear array camera due to the influence of natural environment and flight carrier in the imaging process, the adjacent scanning lines of the aerial linear array image are not necessarily continuous targets, so that the conventional inverse solution image correction has theoretical defects on the aerial linear array image, and the correction processing precision is seriously lost.
Therefore, the invention provides an orthographic image correction method of an aviation three-line camera, which is characterized in that an original image is directly projected to a target image according to an imaging equation, sub-pixel splitting is carried out on the gray scale of the original pixel according to weight on the target image, the target image is recombined, and orthographic correction of the linear array image is finally realized.
Disclosure of Invention
The method mainly solves the problem that the precision loss of the image corrected by adopting the conventional inverse solution method is large in the image acquired by the aviation three-linear array camera.
The technical scheme of the invention provides a forward solution correction method for an aviation three-linear array camera image, which is characterized in that an original image is directly projected to a target image according to an imaging equation, gray scales of the original pixels are split according to weight on the target image, the whole pixels are split into sub-pixels, then the target image is recombined, and finally the forward solution correction of the linear array image is realized.
Moreover, the implementation process comprises the following steps,
firstly, dividing a large linear array image to be corrected into logic image blocks, and then distributing floating-point type and short integer type two-dimensional memory spaces according to the logic image blocks;
step 2, using the internal and external azimuth elements of the linear array image, directly projecting each pixel of the current logic image block into a target space through an imaging collineation equation, and calculating corresponding target image coordinates from the image point coordinates of the original image pixels;
step 3, dividing the whole pixel into sub-pixels based on the coordinates projected on the target image obtained in the step 2, and then recombining the target image, wherein the steps comprise extracting weights of 4 pixels of each target position on the target image; decomposing the gray value of the original pixel into 4 pixels according to the weights, and accumulating the allocated gray and weights into corresponding variables of the target pixel respectively; after all the pixels are projected, carrying out normalization processing according to the gray value and the weight obtained by the target pixel to form a target image; detecting a target image, and if the weight is found to be smaller than a preset threshold value, giving the pixel an average value of adjacent pixels to make up;
and 4, repeating the operations of the step 2 and the step 3 until all the logic image blocks are corrected, and obtaining a final corrected image.
After the two-dimensional memory space of the floating point type and the short integer type is allocated in the step 1, the floating point type memory space is used for storing the accumulated weight of each pixel in the subsequent processing, and the short integer type memory space is used for storing the gray information of the logic image block.
In step 2, when the target space in which the image is directly projected by using the internal and external azimuth elements, a direct projection forward solution method is adopted, so that errors and time consumption caused by iterative computation of a linear array image reverse solution are avoided.
In step 3, the weights of 4 adjacent pixels on the target image at each target position are extracted by the following formula,
c＝(int)x
r＝(int)y
dx＝x-c
dy＝y-r
q00＝(1-dx)×(1-dy)
q01＝(1-dx)×dy
q10＝dx×(1-dy)
q11＝dx×dy
in the formula, (int) represents a floating point rounding operation; c, r is the row number of the target pixels; x and y are the accurate coordinates of the target pixel; dx, dy is the difference between the exact coordinates and the number of rows and columns, representing the sub-pixel portion; q00, q01, q10, q11 are target pixel 4 neighborhood weights.
Moreover, the preset threshold value is taken to be 0.15.
On the other hand, the invention also provides a forward-correcting system for the aviation three-linear-array camera image, which is used for realizing the forward-correcting method for the aviation three-linear-array camera image.
Furthermore, the device comprises the following modules,
the first module is used for dividing the large linear array image to be corrected into logic image blocks, and then distributing floating-point type and short integer type two-dimensional memory spaces according to the logic image blocks;
the second module is used for directly projecting each pixel of the current logic image block into a target space through an imaging collineation equation by using the internal and external azimuth elements of the linear array image, and calculating corresponding target image coordinates by the image point coordinates of the original image pixels;
a third module for splitting the whole pixel into sub-pixels based on the coordinates projected onto the target image obtained by the second module, and recombining the target image, including extracting weights of 4 pixels on the target image for each target position; decomposing the gray value of the original pixel into 4 pixels according to the weights, and accumulating the allocated gray and weights into corresponding variables of the target pixel respectively; after all the pixels are projected, carrying out normalization processing according to the gray value and the weight obtained by the target pixel to form a target image; detecting a target image, and if the weight is found to be smaller than a preset threshold value, giving the pixel an average value of adjacent pixels to make up;
and the fourth module is used for repeating the operations of the second module and the third module until all the logic image blocks are corrected, and obtaining a final corrected image.
Or, the system comprises a processor and a memory, wherein the memory is used for storing program instructions, and the processor is used for calling the stored instructions in the memory to execute the forward solution correction method of the aviation three-line array camera image.
Or comprises a readable storage medium, wherein the readable storage medium is stored with a computer program, and the computer program realizes the forward solution correction method of the aviation three-line camera image when being executed.
The method can effectively solve the problem of precision loss caused by discontinuous adjacent row targets in the aerial linear array image reaction method, remarkably improves the precision and quality of three-linear array image correction, and is particularly suitable for the image correction processing of aerial three-linear array cameras.
Drawings
Fig. 1 is a schematic diagram of the working principle of an aviation three-linear array camera in the prior art, wherein the left image is a three-linear array imaging principle, and the right image is a three-view intersection geometric positioning principle.
Fig. 2 is a schematic diagram of the discontinuity phenomenon of an image line acquired by an aviation tri-linear array in the prior art, wherein the left image is a ground projection discontinuity effect of the image line, and the right image is a distortion of the discontinuity phenomenon in the image.
Fig. 3 is a schematic diagram of an effect of correcting an aerial three-linear array image in the prior art, wherein the left image is an original uncorrected image, and the right image is a corrected image.
FIG. 4 is a process flow diagram of an embodiment of the present invention.
Fig. 5 is a schematic diagram of a target pixel splitting principle according to an embodiment of the present invention.
Detailed Description
The technical scheme of the invention is specifically described below with reference to the accompanying drawings and examples.
The invention provides a positive solution correction method for an aviation three-linear array camera image, which is to directly project an original image into a target space according to an imaging collineation equation, and splitting the gray scale of the original pixels on the target image according to the weight, recombining the target image, and finally realizing the correction of the linear array image by using a positive solution method.
Referring to fig. 4, an embodiment of the present invention provides a forward-solution correction method for aerial linear array camera images, where the whole process flow is shown in fig. 4, and in the process, the target pixel splitting algorithm is a key technology of the forward-solution correction method, and the core process includes the following steps:
step 1, dividing a large linear array image to be corrected into logic image blocks (such as 4096×4096, 5120×5120) according to proper rows and columns, and then distributing two-dimensional memory spaces (namely row×column spaces) of floating point type (occupying 4 bytes and marked as float type) and short integer type (occupying 2 bytes and marked as short) according to the size of the logic image blocks, wherein the two-dimensional memory spaces are respectively represented by letters S and T; the floating-point memory space is used for storing the accumulated weight of each pixel in the subsequent processing, and the short integer memory space is used for storing the gray information of the logic image block.
In the step 1 of the invention, through logically partitioning the image and adopting the float type and the short type as intermediate data, the accuracy is ensured, the memory space is also saved, the practicability and the robustness of the processing method are effectively improved, and the image with any size can be processed.
Step 2, using the inside and outside orientation elements of the linear array image, directly projecting each pixel of the logic image block into the target space through an imaging collineation equation, and obtaining the image point coordinates (p 'of the original image pixels' x ,p' y ) And calculating corresponding target image coordinates (x, y).
In the step 2, the image is directly projected to the target space by using the internal and external azimuth elements, and a direct projection orthometric solution is adopted, so that errors and time consumption caused by iterative calculation of a linear array image inverse solution are avoided.
The target image space is defined as an object space with a constant elevation. The coordinate system is usually selected as a local tangential plane coordinate system, the origin of the coordinate system is defined as the geometric center point of the flight area, the eastern direction is taken as the X axis, the north direction is taken as the Y axis, and the Z axis is determined according to the right-hand coordinate system principle.
The imaging collinearity equation for the projection of the original pixel to the target pixel is:
wherein:
P x ,P y is the X coordinate and Y coordinate projected on the target space position;
P z is the Z coordinate value of the space elevation plane of the target image;
(X s ,Y s ,Z s ) Is the projection center coordinate of the exposure time;
f is the camera focal length;
p' x ,p' y is the position of the original image point;
a 1 ,a 2 ,a 3 ,b 1 ,b 2 ,b 3 ,c 1 ,c 2 ,c 3 is a rotation matrix of imaging momentsRow and column elements of (a);
and calculating the coordinates of the starting point of the corrected image in the target space coordinate system according to the above formula. The edge pixels of a certain number of linear arrays at two ends of the linear array image are projected to the ground, and the minimum value (P) of the projection coordinates in the x and y directions is calculated x0 ,P y0 ) As a starting point for correcting the image. And calculates the ground sampling interval gsd as the sampling interval of the corrected image according to the focal length f, the pixel size m and the relative altitude:
gsd＝m×(P z -Z s )/f
calculating the target position P according to the calculation x ,P y Coordinates on the target image:
x＝(P x -P x0 )/gsd
y＝(P y -P y0 )/gsd
and 3, splitting the whole pixel into sub-pixels based on the coordinates projected onto the target image obtained in the step 2, and then recombining the target image.
The coordinates x, y projected onto the target image are not all integers, so the whole pixel needs to be split into sub-pixels. The process and formula provided by the embodiment of the invention are as follows:
(1) The weights of 4 adjacent pixels of each target position on the target image are extracted, and the weight calculation formula is as follows:
c＝(int)x
r＝(int)y
dx＝x-c
dy＝y-r
q00＝(1-dx)×(1-dy)
q01＝(1-dx)×dy
q10＝dx×(1-dy)
q11＝dx×dy
in the formula, (int) represents a floating point rounding operation; c, r is the row number (integer) of the target pixels; x and y are the exact coordinates (floating point number) of the target pixel; dx, dy is the difference between the exact coordinates and the number of rows and columns, i.e., the sub-pixel portion; q00, q01, q10 and q11 are neighborhood weights of the target pixel 4, and the meaning of each parameter is shown in fig. 5;
(2) Accumulating q00, q01, q10, q11 into the corresponding position of the target pixel:
S[r,c]+＝q00
S[r,c+1]+＝q01
S[r+1,c]+＝q10
S[r+1,c+1]+＝q11
wherein S [ i, j ] represents the j-th element of the i-th row in S;
and the gray value I of the original pixel p is calculated according to the corresponding weight p The decomposition adds up to 4 pixels:
T[r,c]+＝q00×I p
T[r,c+1]+＝q01×I p
T[r+1,c]+＝q10×I p
T[r+1,c+1]+＝q11×I p
wherein T [ i, j ]]Represents the j element of the I line in T, I p Representing the gray value of the original pixel;
(3) And after all the pixels are projected, carrying out normalization processing according to the gray value and the weight obtained by the target pixel to form a target image. Namely, for each target pixel, the following operation is performed:
T[r,c]＝T[r,c]/S[r,c]
(4) And detecting each pixel of the target image, and if the weight is found to be smaller than the threshold value, adopting the average value of the adjacent pixels to endow the pixel with filling. More specifically, starting from the pixel needing filling at present, searching each adjacent pixel by outward expansion, and taking the gray average value of four or eight neighborhoods.
In the embodiment, the threshold value is recommended to be 0.15 according to experience, and the implementation can be adjusted according to actual conditions.
In step 3 of the present invention, a detailed splitting process and a corresponding calculation formula are provided, where the calculation formula and the theoretical derivation of the inverse operation from bilinear interpolation are also experiences containing a large amount of experimental summary, and are the core and originality of the present method.
And 4, repeating the operations of the step 2 and the step 3 until all the logic image block data are corrected, and obtaining a final corrected image.
In particular, the method according to the technical solution of the present invention may be implemented by those skilled in the art using computer software technology to implement an automatic operation flow, and a system apparatus for implementing the method, such as a computer readable storage medium storing a corresponding computer program according to the technical solution of the present invention, and a computer device including the operation of the corresponding computer program, should also fall within the protection scope of the present invention.
In some possible embodiments, an orthographic correction system for an image of an aviation three-line camera is provided, which comprises a first module, a second module and a third module, wherein the first module is used for dividing a large linear array image to be corrected into logic image blocks, and then distributing floating-point type and short integer type two-dimensional memory spaces according to the logic image blocks;
the second module is used for directly projecting each pixel of the current logic image block into a target space through an imaging collineation equation by using the internal and external azimuth elements of the linear array image, and calculating corresponding target image coordinates by the image point coordinates of the original image pixels;
a third module for splitting the whole pixel into sub-pixels based on the coordinates projected onto the target image obtained by the second module, and recombining the target image, including extracting weights of 4 pixels on the target image for each target position; decomposing the gray value of the original pixel into 4 pixels according to the weights, and accumulating the allocated gray and weights into corresponding variables of the target pixel respectively; after all the pixels are projected, carrying out normalization processing according to the gray value and the weight obtained by the target pixel to form a target image; detecting a target image, and if the weight is found to be smaller than a preset threshold value, giving the pixel an average value of adjacent pixels to make up;
and the fourth module is used for repeating the operations of the second module and the third module until all the logic image blocks are corrected, and obtaining a final corrected image.
In some possible embodiments, an orthographic correction system for an aerial three-line camera image is provided, including a processor and a memory, the memory for storing program instructions, the processor for invoking the stored instructions in the memory to perform an orthographic correction method for an aerial three-line camera image as described above.
In some possible embodiments, an orthographic correction system for an aerial three-line camera image is provided, which includes a readable storage medium having a computer program stored thereon, the computer program, when executed, implementing an orthographic correction method for an aerial three-line camera image as described above.
The specific embodiments described herein are offered by way of example only to illustrate the spirit of the invention. Those skilled in the art may make various modifications or additions to the described embodiments or substitutions thereof without departing from the spirit of the invention or exceeding the scope of the invention as defined in the accompanying claims.
Claims (10)
1. A positive solution correction method for aviation three-linear array camera images is characterized by comprising the following steps of: the original image is directly projected to the target image according to an imaging equation, the gray scale of the original pixel is split according to weight on the target image, the whole pixel is split into sub-pixels, the target image is recombined, and the correction of the linear array image by the orthometric method is finally realized.
2. The orthorectification method of an aerial three-linear-array camera image of claim 1, wherein the method comprises the steps of: the implementation process comprises the following steps of,
firstly, dividing a large linear array image to be corrected into logic image blocks, and then distributing floating-point type and short integer type two-dimensional memory spaces according to the logic image blocks;
step 2, using the internal and external azimuth elements of the linear array image, directly projecting each pixel of the current logic image block into a target space through an imaging collineation equation, and calculating corresponding target image coordinates from the image point coordinates of the original image pixels;
step 3, dividing the whole pixel into sub-pixels based on the coordinates projected on the target image obtained in the step 2, and then recombining the target image, wherein the steps comprise extracting weights of 4 pixels of each target position on the target image; decomposing the gray value of the original pixel into 4 pixels according to the weights, and accumulating the allocated gray and weights into corresponding variables of the target pixel respectively; after all the pixels are projected, carrying out normalization processing according to the gray value and the weight obtained by the target pixel to form a target image; detecting a target image, and if the weight is found to be smaller than a preset threshold value, giving the pixel an average value of adjacent pixels to make up;
and 4, repeating the operations of the step 2 and the step 3 until all the logic image blocks are corrected, and obtaining a final corrected image.
3. The method for correcting the forward solution of the image of the aviation tri-linear array camera as claimed in claim 2, wherein the method comprises the following steps: after the two-dimensional memory space of the floating point type and the short integer type is allocated in the step 1, the floating point type memory space is used for storing the accumulated weight of each pixel in the subsequent processing, and the short integer type memory space is used for storing the gray information of the logic image block.
4. The method for correcting the forward solution of the image of the aviation tri-linear array camera as claimed in claim 2, wherein the method comprises the following steps: in the step 2, when the target space of the direct projection of the image is used by using the internal and external azimuth elements, a direct projection orthometric solution method is adopted, so that errors and time consumption caused by iterative calculation of a linear array image inverse solution are avoided.
5. The method for correcting the forward solution of the image of the aviation tri-linear array camera as claimed in claim 2, wherein the method comprises the following steps: in step 3, the weights of 4 adjacent pixels on the target image at each target position are extracted by the following formula,
c＝(int)x
r＝(int)y
dx＝x-c
dy＝y-r
q00＝(1-dx)×(1-dy)
q01＝(1-dx)×dy
q10＝dx×(1-dy)
q11＝dx×dy
in the formula, (int) represents a floating point rounding operation; c, r is the row number of the target pixels; x and y are the accurate coordinates of the target pixel; dx, dy is the difference between the exact coordinates and the number of rows and columns, representing the sub-pixel portion; q00, q01, q10, q11 are target pixel 4 neighborhood weights.
6. The method for correcting the forward solution of the aerial three-linear-array camera image according to claim 1 or 2 or 3 or 4 or 5, wherein the method comprises the following steps: the preset threshold value is taken to be 0.15.
7. An orthotopic correction system for aviation three-linear array camera images is characterized in that: a method for implementing orthometric correction of an aerial three-line camera image as claimed in any one of claims 1 to 6.
8. The orthographic correction system for aerial three-line camera images of claim 7, wherein: the system comprises a first module, a second module and a third module, wherein the first module is used for dividing a large linear array image to be corrected into logic image blocks, and then distributing floating-point type and short integer type two-dimensional memory spaces according to the logic image blocks;
the second module is used for directly projecting each pixel of the current logic image block into a target space through an imaging collineation equation by using the internal and external azimuth elements of the linear array image, and calculating corresponding target image coordinates by the image point coordinates of the original image pixels;
a third module for splitting the whole pixel into sub-pixels based on the coordinates projected onto the target image obtained by the second module, and recombining the target image, including extracting weights of 4 pixels on the target image for each target position; decomposing the gray value of the original pixel into 4 pixels according to the weights, and accumulating the allocated gray and weights into corresponding variables of the target pixel respectively; after all the pixels are projected, carrying out normalization processing according to the gray value and the weight obtained by the target pixel to form a target image; detecting a target image, and if the weight is found to be smaller than a preset threshold value, giving the pixel an average value of adjacent pixels to make up;
and the fourth module is used for repeating the operations of the second module and the third module until all the logic image blocks are corrected, and obtaining a final corrected image.
9. The orthographic correction system for aerial three-line camera images of claim 7, wherein: the method comprises a processor and a memory, wherein the memory is used for storing program instructions, and the processor is used for calling the stored instructions in the memory to execute the forward solution correction method of the aviation three-line camera image according to any one of claims 1-6.
10. The orthographic correction system for aerial three-line camera images of claim 7, wherein: comprising a readable storage medium having stored thereon a computer program which, when executed, implements a method of orthographic correction of an aerial three-line camera image as claimed in any one of claims 1 to 6.
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