CN110659369B - On-orbit high-precision lightweight global image control point database construction method and system - Google Patents
On-orbit high-precision lightweight global image control point database construction method and system Download PDFInfo
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Abstract
The invention belongs to the technical field of remote sensing image processing, and discloses a method and a system for constructing an on-orbit high-precision lightweight global image control point database, wherein control points of a satellite remote sensing image are obtained by using an image feature extraction algorithm and a uniform sampling algorithm; making a corresponding control point image film and determining point position index information of the control point; arranging attribute information of the control points to form a control point attribute file; constructing a global image control point database system structure; associating the control point image film with the control point attribute file by using a data integration technology to form a control point data block; and formulating a database storage strategy, and storing the control point image into the database. The invention is suitable for remote sensing images provided by different satellites in the world, has the advantages of refined structure, simple realization, small database size, high data precision and strong expandability, and meets the requirement of on-orbit surveying and mapping processing.
Description
Technical Field
The invention belongs to the technical field of remote sensing image processing, and particularly relates to an on-orbit high-precision light-weight global image control point database construction method and system.
Background
Currently, the closest prior art:
satellite remote sensing image data becomes an indispensable important data source for investigation and research of islands and coastal zones in China, and shoreline investigation, sea area use, ecological investigation and evaluation, oil spill and red tide monitoring and the like all need the satellite image to provide data support. However, remote sensing image data has long been stored in a computer in a file form and is subjected to extensive management by an operating system. With the continuous increase of data volume, the defect of the management mode becomes more obvious, and the requirement for establishing a remote sensing image database is brought forward. A remote sensing image database is established, and the remote sensing image data can be efficiently and quickly stored, retrieved and extracted. The database can facilitate management of remote sensing image data, and when images are stored in the database together with other auxiliary data, modification of the image data and the auxiliary data can be realized in the same transaction, thereby reducing the risk of inconsistency between the auxiliary data and the image data. Databases have more availability than file-wise deposits, databases can replicate, distribute, and potentially modify data in a distributed environment, and log transfers provide a way to keep a backup copy of a database in the event of a failure of the primary system. The database has good safety measures and a data recovery mechanism, and is beneficial to the safety of data. In addition, the database is used for managing the image data, so that the images can be distributed and shared conveniently.
The geometric fine correction technique of the original image is a step which is generally necessary for processing work such as image fusion, classification, change detection, image mosaic and the like, and particularly, the geometric fine correction technique of the high-precision original image becomes one of necessary conditions for acquiring accurate information from the image. With the increasing application requirements of remote sensing images in the fields of surveying and mapping, resource environment, urban planning and military, geometric fine correction of original images becomes one of the hot spots and difficult problems of computer vision, mode identification, photogrammetry, remote sensing and other researches. And whether the image geometric correction is good or bad depends on the quality of the acquired control points. The traditional use topography is surveyed and is actually measured with the field two kinds of modes and obtain the required control point of image geometric correction, but gathers the control point and need a large amount of collection and the manual work operation of distinguishing, acquires the cycle length, wastes time and energy. Because the collected control points are not effectively managed, the control points are thrown away after being used, and the data reutilization rate is low.
The image matching based on the control point image database can improve the speed and the reliability of image matching by improving the efficiency and the precision of point selection; in addition, the method has immeasurable effects on effective management of control point images, safety of control point data, effective utilization of control point results, and expansion of application range of control points, and has important significance on improvement of measurement and remote sensing work and other surveying and mapping application work.
With the development of database technology and image processing technology, image databases are gradually mature, and in recent years, many commercial systems for managing image databases have been developed at home and abroad.
Microsoft Terrraverer is the most well-known remote sensing image database system based on the Internet. The terraServer image database system is a geographic information website which is established by Microsoft and faces urban areas by utilizing networked database management software SQLServer of Microsoft and is based on the Internet with the assistance of the United states geological survey bureau, the United states aviation image office and Russian space arrangement. TerrowServer adopts a pyramid image query mechanism, seamlessly splices the processed satellite images, and visitors can freely roam, zoom and query the images through the Internet. The target can be searched by inputting the place name. However, the image data is subjected to single-band lossy compression, and the TerraServer only provides a browsing display function and cannot further analyze and process the stored satellite image data. The database does not introduce metadata technology, and a metadata database of the image data is not established, so that the network publishing, sharing and interoperability of the image data are limited.
Image Catalog Image library management software is one of Image series software of Erdas company, and is used for managing an Image library and Image information, including Image library index query, management and storage with a vector map. The ImageCatalog is database management software based on a file type, has a relatively simple image management function, and is mainly used for displaying relevant information of an image file and a simple display and browsing function.
A remote sensing image database based on the Internet is established by a Canadian remote sensing center (CCRS), and the Web database mainly stores metadata information of remote sensing data. The user can input keywords to inquire, select areas to browse, zoom in and out, and the like. In order to reduce the network load, the image database system transmits the image data to the client as JPEG-formatted files, so that the database is limited to the application field with low resolution requirement.
Google corporation adopts IKONOS, quickbird and other global image data to establish a system for providing map service and image service based on Internet. The Google Earth mainly provides global satellite image search service, various ground features such as streets, houses, farmlands, railways and the like can be conveniently checked through the Google Earth, and images in a library can be amplified, reduced, roamed and the like according to needs.
The domestic popular company develops a set of remote sensing image database system based on IDL language, the system manages remote sensing images based on a file management mode, can manage a large amount of image data, supports panchromatic, multispectral and hyperspectral images, has rich image processing functions, and simultaneously adopts a metadata technology to realize sharing and interoperation of the image data.
MAPGIS of Wuhan Zhongdi information corporation can manage mass image data, and is mainly characterized in that the problems of storage, management, scaling, roaming and the like of large-data-volume images are solved by using a compression technology and a pyramid technology. However, the existing functions are few, and only corrected images can be managed, so that the database cannot support the processing flow of remote sensing images, and the application range of the remote sensing image management system is limited.
In the aspect of a control point image database, the United States Geological Survey (USGS) published a GLS2005 control point library in 2009, which is a globally established and open data set, has the characteristics of large quantity, uniform format, high precision stability and the like, is suitable for geometric fine correction processing of medium and low resolution remote sensing images by a large number of users, and is also suitable for rapid automatic geometric fine correction of large-scale batch data. 80% of data positioning accuracy in the GLS2005 control point library is less than 30m, and 97% of data positioning accuracy is less than 50m. The control point image block has a size of 64 pixels × 64 pixels. A basic geographic information center of Fujian province in China constructs a control point image database according to coordinate information files (with 0.5m resolution images as reference) acquired manually by control points of domestic satellite images such as third-resource, first-high-resolution and the like accumulated in recent years, wherein the size of a control point image block is 400 pixels multiplied by 400 pixels. When the control point image library is used for automatically extracting the control points, the average error precision is slightly lower than that of manual point selection, but the overall precision is still higher. The national surveying and mapping geographic information bureau satellite surveying and mapping application center Tangxinming team builds a high-precision image control point database of 1. The geometric resolution of the database is 0.5 m-5 m, and can meet the requirements of 1. The total data records of the database reach more than 100 ten thousand, and the data volume exceeds 20TB.
At present, satellite image control point data is mainly stored in a ground established database, and a more complete in-orbit image control point database construction scheme does not exist. In addition, the on-orbit surveying and mapping process needs to change the working modes of on-satellite acquisition and ground processing, and a database suitable for the on-orbit surveying and mapping process needs to be constructed, and control point data with the same precision as the ground database is required to be provided on the premise of occupying less on-satellite load.
In summary, the problems of the prior art are as follows:
(1) In the prior art, satellite image control point data is mainly stored in a ground established database, and a more complete in-orbit image control point database construction scheme does not exist. The lack of on-orbit image control point data in the on-orbit mapping process flow results in limited development of on-orbit mapping process technology.
(2) In the prior art, control point information with higher precision is not provided for a surveying and mapping processing flow according to the requirement of on-orbit surveying and mapping processing and under the condition of smaller storage volume of a database, so that the precision of on-orbit surveying and mapping processing products cannot be ensured.
(3) In the prior art, the satellite image control point database has large difference in design ideas, a uniform system standard is not formed, and developers are difficult to perfect and supplement the functions of the database according to the existing conditions, so that the universality of the database is poor, the expandability is poor, and the data utilization rate is low.
(4) In the prior art, satellite remote sensing images are not classified and stored according to a remote sensing image processing flow, so that remote sensing technology developers cannot acquire enough information to carry out related research work.
The difficulty of solving the technical problems is as follows:
(1) The satellite image control point database needs to be constructed to meet the requirement of on-orbit surveying and mapping processing, data processed by on-orbit surveying and mapping can be provided in real time, and the precision of the on-orbit surveying and mapping processing product can meet the requirement due to the data precision. Therefore, one of the difficulties in the above-mentioned technical problem is that the construction of the satellite image control point database needs to meet the function requirement and data precision requirement of the in-orbit mapping process.
(2) Technical personnel need that control point data information provided by a satellite image control point database is complete and reliable in data quality, information of control point image slices needs to cover the global range as much as possible, and the requirement causes that the unit volume of the control point data block is large. Therefore, one of the difficulties in the above-mentioned technical problem is to reduce the weight of the control point database so that the overall volume of the satellite image control point data is not too large.
(3) In the use process of the satellite image control point database, technicians often influence the working efficiency because the database design does not meet the use requirements, and the existing database can only provide limited functions. Therefore, one of the difficulties of the above technical problems is that a unified design needs to be performed on the system structure, so that the database is suitable for most application scenarios, and the system has the characteristic of extending its own functions.
(4) When a remote sensing technician researches a remote sensing image processing flow, the image data of the corresponding flow is difficult to accurately acquire. Therefore, one of the difficulties of the above technical problems is that data in a satellite image database needs to be classified and stored according to a remote sensing image processing flow, so that a technician can be supported to research the remote sensing image processing flow.
The significance of solving the technical problems is as follows:
(1) The on-orbit control point data is provided for the on-orbit surveying and mapping processing flow, so that the surveying and mapping processing flow does not depend on ground data support, the working modes of on-satellite acquisition and ground processing are changed, and the problem of lack of data conditions in the development of the on-orbit surveying and mapping processing technology is solved.
(2) Corresponding high-precision control point information is provided according to the on-orbit surveying and mapping processing requirements, the on-orbit surveying and mapping processing flow can be smoothly carried out, and the problem factor that the system stops working due to data problems is eliminated.
(3) The control point database has small storage volume, can provide high-precision control point information for on-orbit surveying and mapping processing under the condition of small load on the occupied satellite, and ensures the precision of on-orbit surveying and mapping processing products.
(4) The system standard of the satellite image control point database is relatively unified, developers can conveniently call data in the database, and functions of the database can be added according to the requirements of the developers, so that the data utilization rate of the database is improved.
(5) The database grades and stores the satellite remote sensing images in a classified manner according to the remote sensing image processing flow, and remote sensing technology developers can call image data of the corresponding flow according to research requirements and research interests to develop related research, so that the further development of the remote sensing image processing technology can be promoted.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an on-orbit high-precision lightweight global image control point database construction method and system. According to the demand of on-orbit surveying and mapping processing, the invention can provide high-precision control point information for the surveying and mapping processing flow under the condition of small storage volume of the database, thereby ensuring the precision of on-orbit surveying and mapping processing products.
The invention is realized in the way, and the construction method of the on-orbit high-precision lightweight global image control point database comprises the following steps:
extracting the characteristics of a satellite remote sensing image in the space photogrammetry to obtain effective control points of an image area; making a corresponding control point image film, and determining point position index information of the control point;
arranging attribute data, point index information and other auxiliary information of the control points, and making a control point attribute file;
selecting a database platform, and constructing a global image control point database system structure; associating the control point image film with the control point attribute file by using a data integration technology; and formulating a database storage strategy, and storing the control point image into the database.
According to the method, a global image control point database meeting the on-orbit surveying and mapping processing requirement can be constructed, on-orbit control point data is provided for the on-orbit surveying and mapping processing flow, and the problem that data conditions are lacked in the on-orbit surveying and mapping processing technology development is solved.
The method specifically comprises the following steps:
step one, acquiring a satellite remote sensing image control point. The method comprises the steps of extracting feature points of the satellite remote sensing image by using an image feature extraction algorithm, and uniformly sampling the feature points in an image range, so that the number of the extracted feature points is enough sparse, and the extracted feature points are uniformly distributed in the satellite remote sensing image. Meanwhile, the feature descriptor of the feature point is saved as one of the attribute information of the control point.
And step two, manufacturing a corresponding control point image film. And determining point location coordinates of the control points on the satellite images, and recording the point location coordinates as control point location index information. The point location of the control point is marked by a cross wire, the width of the cross wire is one pixel, and the horizontal and vertical lengths of the cross wire are 11 pixels. And taking the pixel where the point position of the control point is located as a center, respectively extending 511 pixels in four directions of up, down, left and right to obtain an image with the length and width of 1023 pixels. If the boundary of the original image is exceeded, the original image is filled with a background color.
And step three, arranging attribute information of the control points, wherein the attribute information comprises feature descriptors of the control points, latitude, longitude and elevation information of the control points on a geographic coordinate system, ground resolution of images, grade types of the control points and the like. And combining other auxiliary information of the control point, such as a control point acquisition source, control point description information and the like, and forming a control point attribute file together with the control point location index information.
And step four, constructing a global image control point database system structure. The overall architecture of the database system is a C/S architecture of a three-layer system, wherein the bottom layer is a database and database access layer, and the main function is to encapsulate a method and a function for accessing an operation database; the middle layer is a service logic layer and mainly realizes service logic, encapsulation service logic and the like, and interaction between the middle layer and the bottom layer is realized; the top layer is a user interaction layer, namely a database use interface, and a user can realize interaction with the bottom layer through the interface.
And step five, integrating control point data. The image control point database needs to integrate the attribute information of the control point and the corresponding image information to form a data block with associated images and attributes. The data block takes the geographic coordinate range and the control point feature descriptor in the control point attribute information as indexes, and a user can search the corresponding control point image film and the specific attribute information thereof by using the control point attribute information as a search condition through a database use interface.
And step six, storing the control point images. The storage design of the invention comprises a data access mode, a data storage position and a data storage structure. In the aspect of data access mode, the invention adopts a data access method of an index method, and establishes a data index by the attribute information of a control point; in the aspect of data storage position, the data backup of the control point image is stored on the hardware disk because the data quantity of the control point image library data backup is large. In the aspect of a data storage structure, in order to improve the system performance, the data table and the data index are stored in different hardware disks, so that the data query and access efficiency is improved.
Further, in the first step, the image feature extraction algorithm is SIFT, SURF and ORB, and the extracted feature points are uniformly distributed in the satellite remote sensing image by using a uniform sampling algorithm. According to the method, the automatic extraction of the data of the satellite remote sensing image control point can be realized, and the automatic realization of the whole system is facilitated.
Further, in the second step, the cross hair mark takes the point position of the control point as the center, the width is one pixel, the horizontal and vertical lengths are 11 pixels, and the pixel value of the remaining part of the cross hair except the center of the cross hair is 0. According to the method, the control point pieces with uniform formats can be obtained, the application range of the control point data in the database is favorably expanded, and the data utilization rate is improved.
Furthermore, in step two, the control point image slice takes the pixel where the control point is located as the center, the length and the width are both 1023 pixels, and the part exceeding the original image boundary is filled with the background color. According to the method, the control point pieces with uniform formats can be obtained, the application range of the control point data in the database is favorably expanded, and the data utilization rate is improved.
Further, in the third step, the attribute information of the control point includes index information of the point location of the control point, a feature descriptor of the control point, latitude, longitude and elevation information on a geographic coordinate system, ground resolution of an image, a level type of the control point, and other auxiliary information of the control point includes acquisition source of the control point and description information of the control point. According to the method, the control point pieces with uniform formats can be obtained, the application range of the control point data in the database can be expanded, and the data utilization rate can be improved.
Further, in the fifth step, the control point data block is constructed by using the geographic coordinate range and the control point feature descriptor in the control point attribute information as indexes and combining the control point image and the corresponding control point attribute information. According to the method, the control point pieces with uniform formats can be obtained, the application range of the control point data in the database can be expanded, and the data utilization rate can be improved.
Further, the control point image storage method in the sixth step adopts a data access method of an index method, the data backup of the control point image is stored on the hardware disk, and the data table and the data index are respectively stored on different hardware disks. According to the method, the control point database can be effectively reduced, and a lightweight database can be obtained.
Another object of the present invention is to provide an on-orbit high-precision lightweight global image control point database construction system for implementing the on-orbit high-precision lightweight global image control point database construction method.
The invention also aims to provide a satellite remote sensing image processing device in space photogrammetry for implementing the method for constructing the on-orbit high-precision lightweight global image control point database.
According to the on-orbit high-precision lightweight global image control point database constructed by the method, the reasonable management of the satellite image control point data is realized, the database can meet the requirement of on-orbit surveying and mapping processing, the requirement of common remote sensing image processing can be further met, and the utilization rate of the satellite image control point data can be further improved.
Compared with the current situation of establishing a database on the ground in the prior art, the method changes the current situation of establishing the existing database on the ground, ensures that the surveying and mapping processing flow does not depend on ground data support, and further changes the working modes of data acquisition and ground data processing on the current surveying and mapping processing satellite.
According to the method, the control point of the satellite remote sensing image is obtained, the current situation that the control point is manually selected in the prior art is compared, and automatic extraction of control point information and automatic generation of control point image films are achieved.
In the second step of the invention, the corresponding control point image film is manufactured, and compared with the current situation that the control point image film in the prior art has larger design difference and is not beneficial to expanded use, the unified design of the control point image film is realized.
In the invention, the fourth step to the sixth step, a global image control point database system structure is constructed, control point data is integrated and stored, the establishment of a lightweight database is realized by comparing the current situation that the sizes of image databases established in the prior art are larger, the redundancy of the database is reduced as much as possible while the completeness and accuracy of control point data information are ensured, and the size of the database is reduced.
In summary, the advantages and positive effects of the invention are as follows:
the method of the invention extracts the characteristics of the satellite remote sensing image in the space photography measurement to obtain the effective control points of the image area; making a corresponding control point image film, and determining point position index information of the control point; arranging attribute data, point index information and other auxiliary information of the control points, and making a control point attribute file; selecting a proper database platform and constructing a global image control point database system structure; associating the control point image film with the control point attribute file by using a data integration technology; and formulating a database storage strategy, and storing the control point image into the database.
According to the demand of on-orbit surveying and mapping processing, the invention can provide high-precision control point information for the surveying and mapping processing flow under the condition of small storage volume of the database, thereby ensuring the precision of on-orbit surveying and mapping processing products.
The invention is suitable for remote sensing images provided by different global satellites, has the advantages of refined structure, simple realization, small database size, high data precision and strong expandability, and meets the requirement of on-orbit mapping processing.
Drawings
Fig. 1 is a flowchart of an on-orbit high-precision lightweight global image control point database construction method according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a method for constructing an on-orbit high-precision lightweight global image control point database according to an embodiment of the present invention.
Fig. 3 is a flow chart of SIFT image feature extraction provided by the embodiment of the invention.
Fig. 4 is a schematic diagram of an image feature descriptor of the SIFT algorithm provided in the embodiment of the present invention.
Fig. 5 is a schematic diagram of a control point image slice according to an embodiment of the invention.
Fig. 6 is a structural diagram of an on-orbit high-precision light-weight global image control point database system according to an embodiment of the present invention.
FIG. 7 is a block diagram of control point data provided by an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In the prior art, control point information with higher precision is not provided for a surveying and mapping processing flow according to the requirement of on-orbit surveying and mapping processing and under the condition of smaller storage volume of a database, so that the precision of on-orbit surveying and mapping processing products cannot be ensured.
In order to solve the above technical problems, the present invention will be described in detail with reference to specific embodiments.
As shown in fig. 1, the method for constructing an on-orbit high-precision lightweight global image control point database according to an embodiment of the present invention includes the following steps:
and S101, acquiring control points of the satellite remote sensing images. The method comprises the steps of extracting feature points of the satellite remote sensing image by using an image feature extraction algorithm, and uniformly sampling the feature points in an image range, so that the number of the extracted feature points is enough sparse, and the extracted feature points are uniformly distributed in the satellite remote sensing image. Meanwhile, the feature descriptor of the feature point is saved as one of the attribute information of the control point.
S102, making a corresponding control point image film. And determining point location coordinates of the control points on the satellite images, and recording the point location coordinates as control point location index information. The point location of the control point is marked by a cross wire, the width of the cross wire is one pixel, and the horizontal and vertical lengths of the cross wire are 11 pixels. And taking the pixel where the point position of the control point is located as a center, respectively extending 511 pixels in four directions of up, down, left and right to obtain an image with the length and width of 1023 pixels. If the boundary of the original image is exceeded, the original image is filled with a background color.
S103, arranging attribute information of the control points, including characteristic descriptors of the control points, latitude, longitude and elevation information of the control points on a geographic coordinate system, ground resolution of images, level types of the control points and the like. And combining other auxiliary information of the control point, such as a control point acquisition source, control point description information and the like, and forming a control point attribute file together with the control point location index information.
And S104, constructing a global image control point database system structure. The overall architecture of the database system is a C/S architecture of a three-layer system, wherein the bottom layer is a database and database access layer, and the main function is to encapsulate a method and a function for accessing an operation database; the middle layer is a service logic layer and mainly realizes service logic, encapsulation service logic and the like, and interaction between the middle layer and the bottom layer is realized; the top layer is a user interaction layer, namely a database use interface, and a user can realize interaction with the bottom layer through the interface.
And S105, integrating control point data. The image control point database needs to integrate the attribute information of the control point and the corresponding image information to form a data block with the associated image and attribute. The data block takes the geographic coordinate range and the control point feature descriptor in the control point attribute information as indexes, and a user can search the corresponding control point image film and the specific attribute information thereof by using the control point attribute information as a search condition through a database use interface.
And S106, storing the control point images. The storage design comprises a data access mode, a data storage position and a data storage structure. In the aspect of a data access mode, a data access method of an index method is adopted, and a data index is established by the attribute information of a control point; in the aspect of data storage position, the data backup of the control point image is stored on the hardware disk because the data quantity of the control point image library data backup is large. In the aspect of a data storage structure, in order to improve the system performance, the data table and the data index are stored on different hardware disks, so that the data query and access efficiency is improved.
The image feature extraction algorithm in step S101 is a feature extraction algorithm with a constructed feature description subsection, such as SIFT, SURF, ORB, and the like, and the extracted feature points are uniformly distributed in the satellite remote sensing image by using a uniform sampling algorithm.
The cross hair identifier described in step S102 is centered on the point position of the control point, has a width of one pixel, has horizontal and vertical lengths of 11 pixels, and has pixel values of 0 in other parts of the cross hair except the center of the cross hair.
The control point image slice in step S102 is centered on the pixel where the control point is located, and has a length and a width of 1023 pixels, and the portion exceeding the boundary of the original image is filled with a background color.
The attribute information of the control point in step S103 includes index information of the point location of the control point, a feature descriptor of the control point, latitude, longitude, and elevation information of the control point on a geographic coordinate system, ground resolution of an image, class type of the control point, and the like, and other auxiliary information of the control point includes a collection source of the control point, description information of the control point, and the like.
The global image control point database system structure in step S104 is a three-layer C/S architecture, the bottom layer is a database and database access layer, the middle layer is a service logic layer, and the top layer is a user interaction layer.
The control point data block described in step S105 is constructed by using the geographical coordinate range and the control point feature descriptor in the control point attribute information as an index, and combining the control point image and the control point attribute information corresponding thereto.
The control point image storage method in step S106 adopts a data access method of an index method, and stores the data backup of the control point image on the hardware disk, and stores the data table and the data index on different hardware disks, respectively.
The invention will be further described with reference to the following examples.
Example (b):
as shown in fig. 2, the method for constructing an in-orbit high-precision lightweight global image control point database according to the embodiment of the present invention first obtains a satellite remote sensing image to be processed and attribute information of a control point corresponding to the satellite remote sensing image to be processed, and includes the following specific steps:
step 1, carrying out primary feature point extraction on the satellite remote sensing image by using an SIFT image feature extraction algorithm, wherein the process is shown in fig. 3, and then applying a uniform sampling algorithm to ensure that the number of feature points in the image range is sparse and uniformly distributed. Image feature descriptors calculated using the SIFT algorithm are represented by 8-dimensional direction vectors in 16 seed blocks of 4 × 4, as shown in fig. 4, and thus each feature descriptor is a 128-dimensional feature vector.
And 2, determining point position coordinates (x, y) of the control points in the image, wherein the point positions of the control points are marked by cross hairs, the width of each cross hair is one pixel, the horizontal and vertical lengths of the cross hairs are 11 pixels, and 5 pixels in the upper, lower, left and right directions of the control points are filled with gray values of 0. With the pixel where the control point location (x, y) is located as the center, 511 pixels are respectively extended upwards, downwards, leftwards and rightwards, and an image with length and width of 1023 pixels is obtained, as shown in fig. 5, and stored as an image slice in a specified format.
And 3, arranging attribute information of the control points, wherein the attribute information comprises characteristic descriptors of the control points, latitude, longitude and elevation information of the control points on a geographic coordinate system, ground resolution of images, grade types of the control points and the like. The control point attribute file is formed by combining other auxiliary information of the control point, such as a control point acquisition source, control point description information and the like, with the control point index information, and the specific format of the control point attribute file is shown in table 1 below.
Table 1 control point attribute file format
And 4, constructing an image control point database system structure. As shown in fig. 6, the overall architecture of the database system is a three-layer C/S architecture, the bottom layer is a database and a database access layer, and the database and database access layer mainly comprises a control point image database and a database access operation component, the control point image database is a data storage location, and the database access operation component includes methods and functions for accessing and operating the database; the middle layer is a business logic layer, which mainly comprises a system management operation component and a MapX-based control component, and the layer is mainly used for connecting the bottom layer and the top layer, receiving an application operation instruction from the top layer, converting the application operation instruction into language logic which can be analyzed by the bottom layer, and enabling the database in the bottom layer to access and the operation component to call data in the database; the top layer is a user interaction layer, which mainly comprises a control point quality control module, a control point database entry updating module, a database management module and a control point application module, wherein the control point quality control module corresponds to each operation of the bottom database, and a user sends a corresponding operation instruction to the bottom layer by calling the corresponding module.
And 5, integrating control point data. As shown in fig. 7, the control point image slice and the corresponding control point attribute information are associated, and the geographic coordinates and the control point feature descriptors in the control point attribute information are extracted as the control point index, and finally a control point data block is constructed as the most basic data storage unit in the database.
And 6, storing the control point image. The method for accessing the data of the control point database adopts an index method, and as stated in step 5, the geographic coordinates and the control point feature descriptors in the control point attribute information are extracted to form a control point index. The backup data storage position of the control point image is selected as a hardware disk, so that the load pressure of the database is reduced. In order to optimize the overall performance of the system, the data table and the data index are stored separately.
According to the steps, the on-orbit high-precision lightweight global image control point database meeting the requirements can be finally obtained.
The invention realizes the automatic management of control point data on an in-orbit surveying and mapping processing platform in a light weight storage mode, provides a method and a system for constructing an in-orbit high-precision light-weight global image control point database aiming at the requirements of in-orbit processing and common processing of remote sensing images, realizes the structured automatic generation of satellite remote sensing image control point information under the support of a satellite remote sensing image control point acquisition technology, a control point image film manufacturing technology and a control point data integration technology, realizes the migration of the satellite remote sensing image control point data from a ground manual management mode to an in-orbit automatic management mode, and improves the utilization efficiency of the current satellite remote sensing image control point data.
From the development of remote sensing image processing systems, currently, the existing satellite remote sensing image processing and application is a basic process of detecting data acquired by a satellite, sending data to the ground by means of a communication satellite, receiving and processing the data by a ground processing center, and then distributing images to users, and the whole process has long data processing and feedback links, so that the users need to acquire information for at least several hours. The development of the on-orbit remote sensing image processing technology is beneficial to simplifying the traditional process. Under the support of the on-orbit remote sensing image processing technology, the detection satellite can complete data acquisition and data processing on the satellite, so that the processing complexity in the traditional process is reduced; in a data transmission link, a satellite only needs to transmit a remote sensing image final product, so that the transmission load in the traditional process is reduced. The on-orbit remote sensing image processing technology needs an on-orbit remote sensing image database technology to provide data support. Links such as geometric positioning, orthorectification and the like in remote sensing image processing all need accurate ground control point information addition processing, and the ground control point information is usually not sorted and needs to be collected in advance by a ground processing center, so that the real-time performance of remote sensing image processing is poor, and the utilization rate of the ground control point information is low. Collecting and sorting ground control point information, and establishing an on-orbit remote sensing image database, so that the remote sensing image processing can acquire the ground control point information in real time, a remote sensing image product is output in real time, and the remote sensing image processing efficiency is improved; on the other hand, the ground control point information is effectively managed without repeated collection and arrangement work, and the utilization rate of the ground control point information is improved.
From the perspective of remote sensing technology research, although the existing satellite image databases are of many types, it is still very difficult for researchers to acquire the required satellite image data, mainly because the image data formats stored in the existing databases are not unified, only a small amount of necessary information can be provided, and the data information is not comprehensive. Therefore, it is necessary to design a satellite image database with a uniform and complete data format to highly integrate the existing satellite image data, so as to provide a high-efficiency and convenient data acquisition path for researchers. In addition, most of the existing satellite image databases store corrected products, which cannot be used for research in the fields of remote sensing imaging technology and the like, and satellite images are classified and classified for the remote sensing image processing flow, so that remote sensing technology researchers can acquire the satellite images as required, relevant research work is carried out, and the high-speed development of the remote sensing technology is promoted.
In conclusion, the method has obvious technical effect, can provide better technical contribution to the development of remote sensing image processing systems and the research of remote sensing technologies, and has wide application prospect in the field of remote sensing and considerable economic benefit.
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 and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (9)
1. An on-orbit high-precision lightweight global image control point database construction method is characterized by comprising the following steps of:
acquiring a satellite remote sensing image control point; extracting feature points of the satellite remote sensing image by using an image feature extraction algorithm, and uniformly sampling the feature points in an image range to ensure that the extracted feature points are sparse in number and are uniformly distributed in the satellite remote sensing image; meanwhile, saving the feature descriptors of the feature points as the attribute information of the control points;
step two, manufacturing a corresponding control point image film, determining the point location coordinates of the control points on the satellite image, and recording the point location coordinates as control point location index information; the point position of the control point is marked by a cross wire, the width of the cross wire is one pixel, and the horizontal and vertical lengths are 11 pixels; taking the pixel where the point location of the control point is located as the center, respectively extending 511 pixels in four directions of up, down, left and right to obtain an image with length and width of 1023 pixels; if the boundary of the original image is exceeded, filling with a background color;
thirdly, arranging attribute information of the control points, including feature descriptors of the control points, latitude, longitude and elevation information on a geographic coordinate system, ground resolution of images and control point grade types; combining a control point acquisition source of a control point, control point description information and control point index information to form a control point attribute file;
step four, a global image control point database system structure is constructed, the overall architecture of the database system is a three-layer C/S architecture, and the bottom layer is a method and a function for packaging and accessing the operation database by a database and database access layer; the middle layer is a service logic layer and is used for service logic and encapsulation of the service logic, and interaction between the middle layer and the bottom layer is realized; the top layer is a user interaction layer and is used for realizing the interaction with the bottom layer through an interface;
integrating control point data, wherein an image control point database integrates control point attribute information and corresponding image information to form data blocks related to images and attributes; the data block takes the geographic coordinate range and the control point feature descriptor in the control point attribute information as indexes, and a user searches the corresponding control point image film and the specific attribute information by taking the control point attribute information as a search condition through a database use interface;
step six, storing images of the control points, wherein the data access mode adopts data access of an index method, and a data index is established by using the attribute information of the control points; in the data storage position, storing the data backup of the control point image on a hardware disk; in the data storage structure, the data table and the data index are stored on different hardware disks for data query and access.
2. The method for constructing the on-orbit high-precision light-weight global image control point database as claimed in claim 1, wherein in the first step, the image feature extraction algorithm is SIFT, SURF and ORB, and the extracted feature points are uniformly distributed in the satellite remote sensing image by using a uniform sampling algorithm.
3. The method for constructing an on-orbit high-precision lightweight global image control point database as claimed in claim 1, wherein in step two, the cross hair mark is centered on the control point, has a width of one pixel, has horizontal and vertical lengths of 11 pixels, and has a pixel value of 0 in the remaining portion of the cross hair except the center of the cross hair.
4. The method according to claim 1, wherein in step two, the control point image slice is filled with a background color in a portion exceeding the boundary of the original image, with the length and width of 1023 pixels centered on the pixel where the control point is located.
5. The method according to claim 1, wherein in step three, the attribute information of the control points includes index information of point locations of the control points, feature descriptors of the control points, latitude, longitude and elevation information on a geographic coordinate system, ground resolution of the image, class type of the control points, and other auxiliary information of the control points includes acquisition source of the control points and description information of the control points.
6. The method for constructing the on-orbit high-precision lightweight global image control point database according to claim 1, wherein in the fifth step, the control point data block is constructed by using the geographic coordinate range and the control point feature descriptor in the control point attribute information as indexes and combining the control point image and the corresponding control point attribute information.
7. The method for constructing an on-orbit high-precision lightweight global image control point database according to claim 1, wherein the control point image storage method in the sixth step adopts a data access method of an index method, and the data of the control point image is stored in a hardware disk in a backup manner, and the data table and the data index are respectively stored in different hardware disks.
8. An on-orbit high-precision lightweight global image control point database construction system for implementing the on-orbit high-precision lightweight global image control point database construction method according to claim 1.
9. A satellite remote sensing image processing device in space photography measurement for implementing the on-orbit high-precision light-weight global image control point database construction method of claim 1.
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