CN103258011A - Data sourcing and leak-repairing method for aerial remote sensing data production - Google Patents

Abstract

The invention relates to a data sourcing and leak-repairing method for aerial remote sensing data production. The method includes the steps of firstly, storing aerial remote sensing source data and product data efficiently and parallelly in data production process, establishing correspondence between the source data and the product data according to the aerial remote sensing data production demand, and providing important support for product data sourcing; secondly, performing integral multimode efficient search and extraction which support the aerial remote sensing data and production, acquiring all source data and product data meeting the production demand by single search, and providing important support for repairing data missing in data production. The data sourcing and leak-repairing method for aerial remote sensing data production has the advantages that the data sourcing and leak-repairing problems in aerial remote sensing data production are solved effectively, aerial remote sensing data production can be smoothly performed in the absence of source data, and foundation for the further reuse of the product data is laid.

Description

A kind of produce towards the airborne remote sensing data in data Suo Yuan and craft leakage mending method

Technical field

The invention belongs to magnanimity Aero-Space remotely-sensed data production field, serve digital airborne photography and measure production field; Relate to a kind of produce towards the airborne remote sensing data in data Suo Yuan and craft leakage mending method.

Background technology

Obtaining with productive capacity along with development of technology improves constantly of airborne remote sensing data, the quick production system of airborne remote sensing data is becoming the main flow of industry, divides the work continuous refinement, and its scale is also more and more huger.The airborne remote sensing data that these systems produce have characteristics such as of a great variety, that data volume is big, and the relation of how to coordinate production desired data and data production run, and can reach effectively that the service data production system is the problem that faces at present.Traditional airborne remote sensing data production run is the only input and output of data emphatically often, the inner link of having ignored source data and product data in the production run, therefore restricted the recycling of data on the one hand, two can't guarantee that also the data production run can be proceeded under the source data deletion condition on the one hand.Data Suo Yuan and craft leakage mending method have been set up the corresponding relation between raw data and the product data in the producing towards the airborne remote sensing data of this paper, have effectively satisfied demands such as the data Suo Yuan that faces during real data is produced and mending-leakage.

Summary of the invention

The present invention solves the existing in prior technology technical matters; Provide a kind of tissue of data effectively to serve the process that the airborne remote sensing data are produced, solved data Suo Yuan and mending-leakage problem in the data production run, improved greatly that the airborne remote sensing data are produced and the efficient of recycling a kind of data Suo Yuan and craft leakage mending method in the production of airborne remote sensing data.

Above-mentioned technical matters of the present invention is mainly solved by following technical proposals:

A kind of produce towards the airborne remote sensing data in the method for data Suo Yuan and mending-leakage, it is characterized in that, may further comprise the steps:

Step 1, the data type of source data and product data in the identification airborne remote sensing data production system;

Step 2 according to different types of data, is extracted the parameter information of describing source data and product data respectively;

Step 3 is carried out the parallelization warehouse-in to the parameter information of describing source data parameter information and product data in real time based on the LAN (Local Area Network) operating environment, and foundation can be for the index of inquiry;

Step 4 according to the parameter information of airborne remote sensing data production source data and the parameter information of product data, builds source data and product data inherent corresponding relation between the two automatically;

Step 5, the source data of setting up according to step 4 and the corresponding relation of product data can directly search out corresponding source data by product data, realize data Suo Yuan in the airborne remote sensing data production run; Simultaneously, on the index basis that step 3 is set up, can extract the source data and the product data that satisfy spatial dimension, resolution, many conditional requests of time, realize the mending-leakage under the source data deletion condition in the airborne remote sensing data production run.

Above-mentioned a kind of produce towards the airborne remote sensing data in data Suo Yuan and craft leakage mending method, in the step 1, source data comprised airborne remote sensing raw video, POS data, reference mark information during the airborne remote sensing data were produced, and product data comprise orthography, elements of exterior orientation, digital elevation model; The data type concrete grammar of source data and product data is in the identification airborne remote sensing data production system:

Read source data and product data, and resolution file name suffix, definition suffix name * .Jpg, * .Jgw, * .GIF, * .tfw, * .geotiff, * .dem are raster data; Suffix name * .shp, * .dwg, * .dxf are vector data; Suffix name * .txt, * .cmr, * .grd, * .prj, * .pos are attribute data.

Above-mentioned a kind of produce towards the airborne remote sensing data in data Suo Yuan and craft leakage mending method, in the step 2, the parameter information of raster data and vector data is: resolution, coordinate range, production time, acquisition time, projection pattern; The parameter information of attribute data is determined by file header information.

Extracting parameter information and the product data parameter information of describing source data comprises the steps:

Step 2.1 generates thumbnail for the image data in the raster data according to 64x64～256x256 pixel size resampling, and wherein, pixel size is 2 ⁿ, n is positive integer, this thumbnail is used for browsing data; The gray-scale value of resampling pixel is

I (P)=(1-Δ x) (1-Δ y) I ₁₁+ (1-Δ x) Δ yI ₁₂+ Δ x (1-Δ y) I ₂₁+ Δ x Δ yI ₂₂Formula one;

Step 2.2 is changed for the coordinate range parameter in the parameter information, with the unified coordinate under user's specified coordinate system of the original coordinate of coordinate range parameter, that is:

At first the coordinate data of input is converted to the geocentric rectangular coordinate system of corresponding ellipsoid, utilizes the conversion of 7 parameters with the geocentric rectangular coordinate system of this coordinate conversion to the target-based coordinate system correspondence then, finally obtain the coordinate data of based target coordinate system; Adopt boolean's sand (Bursa) model of 3 translation parameterss, 3 rotation parameters and 7 conversion parameters of 1 yardstick zooming parameter calculating.

$\left[\begin{array}{c}{X}^{\′}\\ Y^{\′}\\ Z^{\′}\end{array}\right]=\left[\begin{array}{c}\mathrm{dx}\\ \mathrm{dy}\\ \mathrm{dz}\end{array}\right]+\mathrm{\κ}\left[\begin{array}{ccc}0& {\mathrm{\ϵ}}_Z& -{\mathrm{\ϵ}}_Y\\ -{\mathrm{\ϵ}}_Z& 0& {\mathrm{\ϵ}}_X\\ {\mathrm{\ϵ}}_Y& -{\mathrm{\ϵ}}_X& 0\end{array}\right]\left[\begin{array}{c}X\\ Y\\ Z\end{array}\right]$ Formula two;

Dx wherein, dy and dz are translation parameters, ε _X, ε _Y, ε _ZBe rotation parameter, k is scale parameter, X ', and Y ', Z ' they are coordinate under the target-based coordinate system, X, Y, Z are coordinate under the former coordinate system.

Above-mentioned a kind of produce towards the airborne remote sensing data in data Suo Yuan and craft leakage mending method, parameter information carries out the parallelization warehouse-in and sets up index comprising the steps: in the step 3

Step 3.1, the parameter information of source data and the parameter information of product data can manage by the oracle database by being distributed in the concurrent server node that is delivered to of a plurality of nodes in the LAN (Local Area Network).

Step 3.2, the time in the parameter information, coordinate range, resolution all can be key word and is used for retrieve data.

Above-mentioned a kind of produce towards the airborne remote sensing data in data Suo Yuan and craft leakage mending method, the foundation of the corresponding relation of orthography and raw video comprises the steps: in the step 4

Step 4.1, the pixel of the width of cloth orthography of lining by line scan, for arbitrary pixel on it (X, Y), its elevation coordinate of interpolation Z on the dem data of correspondence;

Step 4.2, a ground point on known orthography (X, Y, Z) and during arbitrary image elements of exterior orientation, according to central projection collinearity equation as follows obtain picpointed coordinate (x, y):

$x=-f\frac{a_1(X-\mathrm{Xs})+b_1(Y-\mathrm{Ys})+c_1(Z-\mathrm{Zs})}{a_3(X-\mathrm{Xs})+b_3(Y-\mathrm{Ys})+c_3(Z-\mathrm{Zs})}$

Formula three;

$y=-f\frac{a_2(X-\mathrm{Xs})+b_2(Y-\mathrm{Ys})+c_2(Z-\mathrm{Zs})}{a_3(X-\mathrm{Xs})+b_3(Y-\mathrm{Ys})+c_3(Z-\mathrm{Zs})}$

Step 4.3 is judged picpointed coordinate (x, y) whether effective, namely whether in image film size scope, if picpointed coordinate (x, y) effective, the used elements of exterior orientation corresponding image of projection is the relevant raw video of orthography, if picpointed coordinate (x, y) invalid, the used elements of exterior orientation corresponding image of projection and orthography are irrelevant;

Step 4.4 repeating step 4.1 to 4.3 is until all pixels that scanned orthography, and at this moment, a width of cloth orthography is relevant with several raw videos, and relevant raw video sequence is looked into heavily, gets rid of the raw video that repeats.

Above-mentioned a kind of produce towards the airborne remote sensing data in data Suo Yuan and craft leakage mending method, data Suo Yuan function realizes comprising the steps: in the step 5

Step 5.1 is calculated the direction vector at raw video projection centre and orthography center;

$\stackrel{\→}{\mathrm{SO}}=\{\mathrm{Xs}-X_0,\mathrm{Ys}-Y_0,\mathrm{Zs}-Z_0\}$ Formula four;

(Xs, Ys Zs) are raw video projection centre coordinate, (X ₀, Y ₀, Z ₀) be orthography central space coordinate;

Step 5.2 compares the direction vector at raw video projection centre and orthography center

With the angle of vertical direction, choose angle less than the raw video of 45 degree, this image is for generating the corresponding raw video data of orthography.

Above-mentioned a kind of produce towards the airborne remote sensing data in data Suo Yuan and craft leakage mending method, the mending-leakage in the step 6 under the source data deletion condition comprises the steps:

Step 6.1 provides the retrieval based on many conditions, comprises data acquisition time, resolution, data type, coordinate range and form, can obtain or further push away obtaining alternative data from retrieve qualified source data and product data;

When the loss of learning of reference mark: a, alternative with retrieving the old reference mark data in this zone; B, further pushed away by the old DOM that retrieves and dem data, be specially by extract minutiae on DOM, again by the controlled point data of old DEM interpolation;

When the landform no change of data processing area territory, save dem data generation step in the production of airborne remote sensing data, directly by the old DEM replacement of the same area that retrieves or by the old DLG interpolation of data generation dem data of collection.

Therefore, the present invention has following advantage: the tissue of data is effectively served the process that the airborne remote sensing data are produced, data Suo Yuan and mending-leakage problem in the data production run have been solved, greatly improved the efficient of the production of airborne remote sensing data and recycling, significant for the data prouctiveness of comprehensive lifting airborne remote sensing data handling system.

Description of drawings

Fig. 1 is method flow synoptic diagram of the present invention.

Fig. 2 is the resampling principle schematic that relates in the step 2 of the present invention.

Embodiment

Below by embodiment, and by reference to the accompanying drawings, technical scheme of the present invention is described in further detail.

Consult Fig. 1, data Suo Yuan and craft leakage mending method comprised following concrete steps in should producing towards the airborne remote sensing data:

Step 1, the source data in the identification airborne remote sensing data quick-processing system and the type of product data are divided into grid, vector and attribute data according to the difference of its data structure.

As for a project, source data is generally raw video (* .GIF), camera parameter (* .cmr), and POS data (* .pos), the reference mark data (X, Y, Z); Product data are orthography (* .GIF, * twf), empty three pass point data (* .txt), Dem data (* .dem).Identification types result is raw video, orthography, and the Dem data are raster data; Camera parameter, the POS data, the reference mark data, empty three elements of exterior orientation data are attribute data.

Step 2, the parameter information of raster data and vector data is: resolution, coordinate range, production time, acquisition time, projection pattern; The parameter information of attribute data is determined by file header information.

Extracting parameter information and the product data parameter information of describing source data comprises the steps:

Step 2.1 generates thumbnail for the image data in the raster data according to 64x64～256x256 pixel size resampling, and wherein, pixel size is 2 ⁿ, n is positive integer, this thumbnail is used for browsing data; The gray-scale value of resampling pixel is

I (P)=(1-Δ x) (1-Δ y) I ₁₁+ (1-Δ x) Δ yI ₁₂+ Δ x (1-Δ y) I ₂₁+ Δ x Δ yI ₂₂Formula one;

Step 2.2 is changed for the coordinate range parameter in the parameter information, with the unified coordinate under user's specified coordinate system of the original coordinate of coordinate range parameter, that is:

At first the coordinate data of input is converted to the geocentric rectangular coordinate system of corresponding ellipsoid, utilizes the conversion of 7 parameters with the geocentric rectangular coordinate system of this coordinate conversion to the target-based coordinate system correspondence then, finally obtain the coordinate data of based target coordinate system; Adopt boolean's sand (Bursa) model of 3 translation parameterss, 3 rotation parameters and 7 conversion parameters of 1 yardstick zooming parameter calculating.

$\left[\begin{array}{c}{X}^{\′}\\ Y^{\′}\\ Z^{\′}\end{array}\right]=\left[\begin{array}{c}\mathrm{dx}\\ \mathrm{dy}\\ \mathrm{dz}\end{array}\right]+\mathrm{\κ}\left[\begin{array}{ccc}0& {\mathrm{\ϵ}}_Z& -{\mathrm{\ϵ}}_Y\\ -{\mathrm{\ϵ}}_Z& 0& {\mathrm{\ϵ}}_X\\ {\mathrm{\ϵ}}_Y& -{\mathrm{\ϵ}}_X& 0\end{array}\right]\left[\begin{array}{c}X\\ Y\\ Z\end{array}\right]$ Formula two;

Dx wherein, dy and dz are translation parameters, ε _X, ε _Y, ε _ZBe rotation parameter, k is scale parameter, X ', and Y ', Z ' they are coordinate under the target-based coordinate system, X, Y, Z are coordinate under the former coordinate system.

For raw video (* .GIF), parameter information is: image is wide, image height, pixel size, acquisition time;

For camera parameter (* .cmr), parameter information is: principal point X coordinate, principal point Y coordinate, focal length, pixel size, distortion factor k1, distortion factor k2, distortion factor p1, distortion factor p2, acquisition time;

For POS (* .pos) data, parameter information is: eastern coordinate, northern coordinate, elevation, phi, omega, kappa, gps time;

(Z), parameter information is for X, Y: X coordinate, Y coordinate, Z coordinate, acquisition time for the reference mark data;

For Dem data (* .dem), parameter information is: lower left corner X coordinate, lower left corner Y coordinate, lower left corner Z coordinate, DEM graticule mesh X interval, DEM graticule mesh Y interval, DEM graticule mesh Z interval, DEM line number ROWS, DEM line number COLS, acquisition time;

For empty three elements of exterior orientation data (* .txt), parameter information is: projection centre Xs, projection centre Ys, projection centre Zs, projection centre phi, projection centre omega, projection centre kappa, acquisition time;

For orthography data (* .GIF, * twf), (* twf) parameter information is: lower left corner X coordinate, lower left corner Y coordinate, image resolution, line number ROWS, line number COLS, acquisition time.

Generate the 256x256 breviary for image data, coordinate system is transformed under the WGS-84 coordinate system.

Step 3 is set up the index of source data and product data and corresponding relation between the two according to parameter information.

Step 3.1, the pixel of the width of cloth orthography of lining by line scan, for arbitrary pixel on it (X, Y), its elevation coordinate of interpolation Z on the dem data of correspondence;

Step 3.2, a ground point on known orthography (X, Y, Z) and during arbitrary image elements of exterior orientation, according to central projection collinearity equation as follows obtain picpointed coordinate (x, y):

$x=-f\frac{a_1(X-\mathrm{Xs})+b_1(Y-\mathrm{Ys})+c_1(Z-\mathrm{Zs})}{a_3(X-\mathrm{Xs})+b_3(Y-\mathrm{Ys})+c_3(Z-\mathrm{Zs})}$

Formula three;

$y=-f\frac{a_2(X-\mathrm{Xs})+b_2(Y-\mathrm{Ys})+c_2(Z-\mathrm{Zs})}{a_3(X-\mathrm{Xs})+b_3(Y-\mathrm{Ys})+c_3(Z-\mathrm{Zs})}$

Step 3.3 is judged picpointed coordinate (x, y) whether effective, namely whether in image film size scope, if picpointed coordinate (x, y) effective, the used elements of exterior orientation corresponding image of projection is the relevant raw video of orthography, if picpointed coordinate (x, y) invalid, the used elements of exterior orientation corresponding image of projection and orthography are irrelevant;

Step 3.4 repeating step 3.1 to 3.3 is until all pixels that scanned orthography, and at this moment, a width of cloth orthography is relevant with several raw videos, and relevant raw video sequence is looked into heavily, gets rid of the raw video that repeats.

Step 4 provides data Suo Yuan function, directly finds raw data by the orthography product data, is the further recycling service of data, and data Suo Yuan function realizes comprising the steps:

Step 4.1 is calculated the direction vector at raw video projection centre and orthography center;

$\stackrel{\→}{\mathrm{SO}}=\{\mathrm{Xs}-X_0,\mathrm{Ys}-Y_0,\mathrm{Zs}-Z_0\}$ Formula four;

(Xs, Ys Zs) are raw video projection centre coordinate, (X ₀, Y ₀, Z ₀) be orthography central space coordinate;

Step 4.2 compares the direction vector at raw video projection centre and orthography center

With the angle of vertical direction, choose angle less than the raw video of 45 degree, this image is for generating the corresponding raw video data of orthography.

Can find the raw video collection of orthography correspondence from the corresponding relation of orthography and raw video.Calculate raw video and concentrate the direction vector at every width of cloth raw video projection centre and orthography center.Relatively raw video projection centre and the direction vector at orthography center and the angle of vertical direction are chosen angle less than the raw video of 45 degree, and this image is for generating the corresponding raw video data of orthography.

Step 5 provides data integrated retrieval and data mending-leakage function, is implemented in and fast, accurately retrieves and navigate to the multi-source heterogeneous Aero-Space remotely-sensed data of satisfying the demand under the distributed network environment, serves data mending-leakage function.

Integrated retrieval comprises that WGS-84 unifies coordinate, the time, to inquire about under the image resolution, form etc., and the data that satisfy condition are the alternative data of mending-leakage in the data production run the most.According to the missing data type, in automatic alternative data, judge and select needed mending-leakage data.Can select the reference mark of old the same area, old orthography and dem data etc. for the reference mark data; Concrete implementation method is as follows:

Mending-leakage under the source data deletion condition comprises the steps:

Step 6.1 provides the retrieval based on many conditions, comprises data acquisition time, resolution, data type, coordinate range and form, can obtain or further push away obtaining alternative data from retrieve qualified source data and product data;

When the loss of learning of reference mark: a, alternative with retrieving the old reference mark data in this zone; B, further pushed away by the old DOM that retrieves and dem data, be specially by extract minutiae on DOM, again by the controlled point data of old DEM interpolation;

When the landform no change of data processing area territory, save dem data generation step in the production of airborne remote sensing data, directly by the old DEM replacement of the same area that retrieves or by the old DLG interpolation of data generation dem data of collection.

This method effectively realized digital airborne photography measure produce in being associated of data and production run, changed the situation that the production of airborne remote sensing data separates with the data tissue.

Further say, the present invention can by effectively organize data and set up source data and the related solution data production run of product data in the data Suo Yuan and the mending-leakage problem that face, the airborne remote sensing data are produced and the efficient of recycling thereby improved.

Specific embodiment described herein only is that the present invention's spirit is illustrated.Those skilled in the art can make various modifications or replenish or adopt similar mode to substitute described specific embodiment, but can't depart from spirit of the present invention or surmount the defined scope of appended claims.

Claims (7)

1. One kind produce towards the airborne remote sensing data in the method for data Suo Yuan and mending-leakage, it is characterized in that, may further comprise the steps:

   Step 1, the data type of source data and product data in the identification airborne remote sensing data production system;

   Step 2 according to different types of data, is extracted the parameter information of describing source data and product data respectively;

   Step 3 is carried out the parallelization warehouse-in to the parameter information of describing source data parameter information and product data in real time based on the LAN (Local Area Network) operating environment, and foundation can be for the index of inquiry;

   Step 4 according to the parameter information of airborne remote sensing data production source data and the parameter information of product data, builds source data and product data inherent corresponding relation between the two automatically;

   Step 5, the source data of setting up according to step 4 and the corresponding relation of product data can directly search out corresponding source data by product data, realize data Suo Yuan in the airborne remote sensing data production run; Simultaneously, on the index basis that step 3 is set up, can extract the source data and the product data that satisfy spatial dimension, resolution, many conditional requests of time, realize the mending-leakage under the source data deletion condition in the airborne remote sensing data production run.
2. According to claim 1 a kind of produce towards the airborne remote sensing data in data Suo Yuan and craft leakage mending method, it is characterized in that, in the step 1, source data comprised airborne remote sensing raw video, POS data, reference mark information during the airborne remote sensing data were produced, product data comprise orthography, elements of exterior orientation, digital elevation model; The data type concrete grammar of source data and product data is in the identification airborne remote sensing data production system:

   Read source data and product data, and resolution file name suffix, definition suffix name * .Jpg, * .Jgw, * .GIF, * .tfw, * .geotiff, * .dem are raster data; Suffix name * .shp, * .dwg, * .dxf are vector data; Suffix name * .txt, * .cmr, * .grd, * .prj, * .pos are attribute data.
3. According to claim 2 a kind of produce towards the airborne remote sensing data in data Suo Yuan and craft leakage mending method, it is characterized in that, in the step 2, the parameter information of raster data and vector data is: resolution, coordinate range, production time, acquisition time, projection pattern; The parameter information of attribute data is determined by file header information;

   Extracting parameter information and the product data parameter information of describing source data comprises the steps:

   Step 2.1 generates thumbnail for the image data in the raster data according to 64x64～256x256 pixel size resampling, and wherein, pixel size is 2 ⁿ, n is positive integer, this thumbnail is used for browsing data; The gray-scale value of resampling pixel is

   I (P)=(1-Δ x) (1-Δ y) I ₁₁+ (1-Δ x) Δ yI ₁₂+ Δ x (1-Δ y) I ₂₁+ Δ x Δ yI ₂₂Formula one;

   Step 2.2 is changed for the coordinate range parameter in the parameter information, with the unified coordinate under user's specified coordinate system of the original coordinate of coordinate range parameter, that is:

   At first the coordinate data of input is converted to the geocentric rectangular coordinate system of corresponding ellipsoid, utilizes the conversion of 7 parameters with the geocentric rectangular coordinate system of this coordinate conversion to the target-based coordinate system correspondence then, finally obtain the coordinate data of based target coordinate system; Adopt 3 translation parameterss, 3 rotation parameters and 1 husky model of boolean that the yardstick zooming parameter calculates 7 conversion parameters:

   $\left[\begin{array}{c}{X}^{\′}\\ Y^{\′}\\ Z^{\′}\end{array}\right]=\left[\begin{array}{c}\mathrm{dx}\\ \mathrm{dy}\\ \mathrm{dz}\end{array}\right]+\mathrm{\κ}\left[\begin{array}{ccc}0& {\mathrm{\ϵ}}_Z& -{\mathrm{\ϵ}}_Y\\ -{\mathrm{\ϵ}}_Z& 0& {\mathrm{\ϵ}}_X\\ {\mathrm{\ϵ}}_Y& -{\mathrm{\ϵ}}_X& 0\end{array}\right]\left[\begin{array}{c}X\\ Y\\ Z\end{array}\right]$ Formula two;

   Dx wherein, dy and dz are translation parameters, ε _X, ε _Y, ε _ZBe rotation parameter, k is scale parameter, X ', and Y ', Z ' they are coordinate under the target-based coordinate system, X, Y, Z are coordinate under the former coordinate system.
4. According to claim 1 a kind of produce towards the airborne remote sensing data in data Suo Yuan and craft leakage mending method, it is characterized in that parameter information carries out the parallelization warehouse-in and set up index comprising the steps: in the step 3

   Step 3.1, the parameter information of source data and the parameter information of product data can manage by the oracle database by being distributed in the concurrent server node that is delivered to of a plurality of nodes in the LAN (Local Area Network);

   Step 3.2, the time in the parameter information, coordinate range, resolution all can be key word and is used for retrieve data.
5. According to claim 1 a kind of produce towards the airborne remote sensing data in data Suo Yuan and craft leakage mending method, it is characterized in that the foundation of the corresponding relation of orthography and raw video comprises the steps: in the step 4

   Step 4.1, the pixel of the width of cloth orthography of lining by line scan, for arbitrary pixel on it (X, Y), its elevation coordinate of interpolation Z on the dem data of correspondence;

   Step 4.2, a ground point on known orthography (X, Y, Z) and during arbitrary image elements of exterior orientation, according to central projection collinearity equation as follows obtain picpointed coordinate (x, y):

   $x=-f\frac{a_1(X-\mathrm{Xs})+b_1(Y-\mathrm{Ys})+c_1(Z-\mathrm{Zs})}{a_3(X-\mathrm{Xs})+b_3(Y-\mathrm{Ys})+c_3(Z-\mathrm{Zs})}$

   Formula three;

   $y=-f\frac{a_2(X-\mathrm{Xs})+b_2(Y-\mathrm{Ys})+c_2(Z-\mathrm{Zs})}{a_3(X-\mathrm{Xs})+b_3(Y-\mathrm{Ys})+c_3(Z-\mathrm{Zs})}$

   Step 4.3 is judged picpointed coordinate (x, y) whether effective, namely whether in image film size scope, if picpointed coordinate (x, y) effective, the used elements of exterior orientation corresponding image of projection is the relevant raw video of orthography, if picpointed coordinate (x, y) invalid, the used elements of exterior orientation corresponding image of projection and orthography are irrelevant;

   Step 4.4 repeating step 4.1 to 4.3 is until all pixels that scanned orthography, and at this moment, a width of cloth orthography is relevant with several raw videos, and relevant raw video sequence is looked into heavily, gets rid of the raw video that repeats.
6. According to claim 1 a kind of produce towards the airborne remote sensing data in data Suo Yuan and craft leakage mending method, it is characterized in that data Suo Yuan function realizes comprising the steps: in the step 5

   Step 5.1 is calculated the direction vector at raw video projection centre and orthography center;

   $\stackrel{\→}{\mathrm{SO}}=\{\mathrm{Xs}-X_0,\mathrm{Ys}-Y_0,\mathrm{Zs}-Z_0\}$ Formula four;

   (Xs, Ys Zs) are raw video projection centre coordinate, (X ₀, Y ₀, Z ₀) be orthography central space coordinate;

   Step 5.2 compares the direction vector at raw video projection centre and orthography center

   

   With the angle of vertical direction, choose angle less than the raw video of 45 degree, this image is for generating the corresponding raw video data of orthography.
7. According to claim 1 a kind of produce towards the airborne remote sensing data in data Suo Yuan and craft leakage mending method, it is characterized in that the mending-leakage in the step 6 under the source data deletion condition comprises the steps:

   Step 6.1 provides the retrieval based on many conditions, comprises data acquisition time, resolution, data type, coordinate range and form, can obtain or further push away obtaining alternative data from retrieve qualified source data and product data;

   When the loss of learning of reference mark: a, alternative with retrieving the old reference mark data in this zone; B, further pushed away by the old DOM that retrieves and dem data, be specially by extract minutiae on DOM, again by the controlled point data of old DEM interpolation;

   When the landform no change of data processing area territory, save dem data generation step in the production of airborne remote sensing data, directly by the old DEM replacement of the same area that retrieves or by the old DLG interpolation of data generation dem data of collection.

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