CN101783009A - Method for constructing geometric correction of expandable multi-satellite multi-sensor remote sensing images - Google Patents
Method for constructing geometric correction of expandable multi-satellite multi-sensor remote sensing images Download PDFInfo
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- CN101783009A CN101783009A CN201010131986A CN201010131986A CN101783009A CN 101783009 A CN101783009 A CN 101783009A CN 201010131986 A CN201010131986 A CN 201010131986A CN 201010131986 A CN201010131986 A CN 201010131986A CN 101783009 A CN101783009 A CN 101783009A
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Abstract
The invention relates to a method for constructing the geometric correction of expandable multi-satellite multi-sensor remote sensing images, which comprises the following steps: 1) according to the processing flow of a geometric correction algorithm, dividing the geometric correction of the remote sensing images into the steps of image data input, the calculation of the range of output images, image correction model, the conversion of pixel positions, a resampling algorithm and the output of correction images, and then setting the processing logic of the steps in a general invoking method of an abstract class; and 2) dividing the process of the method for constructing the geometric correction into three layers further, namely a geometric correction processing abstract function interface layer, a specific realization layer and a basic arithmetic layer; and taking satellite names or sensor identification as input parameters by users, and selecting a specific realization algorithm to be used to realize the corresponding algorithm and complete the corresponding processing function during program running. The method has the advantage that the function of the geometric correction of the multi-satellite multi-sensor remote sensing images can be processed and the required function can be expanded under the condition of no need of modifying the existing programs.
Description
Technical field
The present invention relates to remote sensing satellite geometric correction of imagery technical field, relate in particular to a kind of extendible multi-satellite multi-sensor remote sensing images method for constructing geometric correction.
Background technology
The remote sensing satellite image is subjected to the influence of factors such as earth rotation, atmospheric refraction, topographic relief, sensing station and attitude variation and distorts when imaging, therefore must carry out geometry correction and location to the image that gets access to, eliminate distortion error, realize image accurate geographic coding.Wherein, the imaging geometry model is that the foundation of calibration model is the basis of the geometric correction of imagery and location, and it has defined the mathematical relation of image pixel coordinate and ground space coordinate.Usually calibration model is divided into strict imaging model and broad sense imaging model two classes.Strict imaging model is the calibration model of setting up according to different sensors imaging characteristic or how much imaging relations, and it will consider information such as satellite orbit and attitude usually; The broad sense imaging model is not then considered the physical factor of sensor imaging, directly adopts the form of mathematical function to describe geometric relationship between ground point and the corresponding picture point.Usually based on ground control point the space remote sensing image is carried out geometry correction in actual applications, algorithm commonly used has: multiple calibration models such as general polynomial, rational function model, collinearity equation model, radar slant-range-Doppler's model, direct linear transformation's model, self checking direct linear transformation model, extendible direct linear transformation's model, tight projection affined transformation model; As follows as the step 1 of geometry correction:
(1) original image input to be corrected will have the image to be corrected of geometric distortion to read in computing machine;
(2) set up calibration model, calibration model has defined the mapping relations of picpointed coordinate and ground coordinate, i.e. the coordinate transform of input picture and output image relation;
(3) determine the image output area, calculate the scope of correcting image;
(4) pixel geometric position conversion, the conversion of pixel geometric position are by certain selected calibration model pixel to be transformed to the output image coordinate from coordinates of original image coordinates;
(5) the pixel gray-scale value resamples, when if the coordinate figure of the relevant position of arbitrary pixel in original image of output image array is not integer, then must utilize in original image near the gray scale of the some pixels this, and consider these pixels to its contribution of doing and influence, algorithms most in use has convolution method, bilinear interpolation method and arest neighbors method of interpolation three times;
(6) image behind the output calibration after resampling through the geometric position conversion of pixel one by one and gray scale, can output to having than the form of accurate geographic image encoded with regulation after proofreading and correct in the file, finishes geometry correction and handles.
But along with available remote sensing satellite quantity and corresponding remote sensor kind thereof constantly increase, how in a system, to make up the universal model that to consider image rectification of multi-satellite multi-sensor remote sensing images, the complete geometry correction disposal route of taking into account again based on the peculiar model of different sensors is a problem that urgently will solve, be necessary to provide a kind of extendible multi-satellite multi-sensor remote sensing images method for constructing geometric correction, satisfy the user and do not realize many satellites number multisensor remote sensing images geometry correction processing capacity and transaction module scaling problem under the situation of update routine.
Summary of the invention
The purpose of this invention is to provide a kind of extendible multi-satellite multi-sensor remote sensing images method for constructing geometric correction, solve many satellites number multisensor remote sensing images geometry correction problem.
The objective of the invention is to be achieved through the following technical solutions:
A kind of extendible multi-satellite multi-sensor remote sensing images method for constructing geometric correction may further comprise the steps:
1) is divided into according to the treatment scheme of geometry correction algorithm step: view data input, output image range computation, image rectification model, pixel evolution, resampling algorithm and correcting image output, the processing logic of the above step of regulation in the overall call method of abstract class then remote sensing images geometry correction needs;
2) process with method for constructing geometric correction is further divided into three layers: abstraction function interface layer, specific implementation layer and rudimentary algorithm layer are handled in geometry correction, and geometry correction is handled the abstraction function interface layer and is used to finish abstract interface definition and abstraction interface Processing Algorithm combination process; The specific implementation layer is used for realizing the algorithm of abstraction interface Processing Algorithm combination, can carry out general polynomial, rational function model, collinearity equation model, radar slant-range-Doppler's model and direct linear transformation's model algorithm, adopt the succession mode to realize handling different satellite sensor geometry correction function expansion; The rudimentary algorithm layer is used to select the needed rudimentary algorithm of geometry correction, can carry out input and output, resampling algorithm and the image range calculating operation of file, and the specific implementation layer can utilize the rudimentary algorithm layer to realize function complicated algorithm more;
3) user uses satellite designation or sensor identification as input parameter, and the specific implementation algorithm that selection will be used can obtain corresponding algorithm and realize when program run, finish corresponding processing capacity.
Beneficial effect of the present invention is: the geometry correction building process is divided into three levels: abstraction function interface layer, specific implementation layer and rudimentary algorithm layer are handled in geometry correction, method by definition abstraction interface, common logic combination, specific implementation correcting algorithm, under the situation that need not revise existing program, just can finish to the geometry correction processing capacity of multi-satellite multi-sensor remote sensing images with to the function of needs and expand.
Description of drawings
With reference to the accompanying drawings the present invention is described in further detail below.
Fig. 1 is the architectural schematic of extendible multi-satellite multi-sensor remote sensing images method for constructing geometric correction of the present invention;
Fig. 2 is the process flow diagram of extendible multi-satellite multi-sensor remote sensing images method for constructing geometric correction of the present invention;
Fig. 3 is that the process flow diagram that the abstraction function interface layer adopts template method to realize is handled in the geometry correction of extendible multi-satellite multi-sensor remote sensing images method for constructing geometric correction of the present invention.
Embodiment
Shown in Fig. 1-2, extendible multi-satellite multi-sensor remote sensing images method for constructing geometric correction of the present invention may further comprise the steps:
1) is divided into according to the treatment scheme of geometry correction algorithm step: view data input, output image range computation, image rectification model, pixel evolution, resampling algorithm and correcting image output, the processing logic of the above step of regulation in the overall call method of abstract class then remote sensing images geometry correction needs;
2) process with method for constructing geometric correction is further divided into three layers: abstraction function interface layer 101, specific implementation layer 102 and rudimentary algorithm layer 103 are handled in geometry correction; Abstraction function interface layer 101 is handled in described geometry correction, be used to finish abstract interface definition and abstraction interface Processing Algorithm combination process, wherein correcting algorithm is the Core Feature of geometric correction method, one class calibration model can be defined as a kind of correcting algorithm and related data thereof, in correcting algorithm, consider that the geometric correction model that relates in the system reaches kind more than ten or more, in order to guarantee algorithm and interface interchange independence, define a calibration model abstraction interface class and allow the user call, made up the Processing Algorithm flow process that to finish in this interface; Described specific implementation layer 102, be used for realizing the algorithm of abstraction interface Processing Algorithm combination, can carry out general polynomial, rational function model, collinearity equation model, radar slant-range-Doppler's model and direct linear transformation's model scheduling algorithm, definition basic step interface allows the developer realize, thereby interface and realization are separated, guaranteed the expandability of correcting algorithm and model; Described rudimentary algorithm layer 103 is used to select the needed rudimentary algorithm of geometry correction, can carry out the operations such as input and output, resampling algorithm and image range calculating of file, and the specific implementation layer can utilize the rudimentary algorithm layer to realize function complicated algorithm more;
3) user uses satellite designation or sensor identification as input parameter, and the specific implementation algorithm that selection will be used can obtain corresponding algorithm and realize when program run, finish corresponding processing capacity.
As shown in Figure 3, geometry correction is handled the abstraction function interface layer and can be adopted template method (Work) to realize, also can adopt simultaneously function pointer, reflection, factory method or workflow combination method to realize, wherein geometry correction processing abstraction function interface layer adopts template method to realize may further comprise the steps:
1) treatment scheme of abstract geometry correcting algorithm, summarize geometric correction method and need these three steps of operation function function 1 (doFunction1), power function 2 (doFunction2) and power function 3 (doFunction3), stipulate the processing logic of these three steps in the template method of abstract class, example code is as follows:
void?AbstractClass::Work()
{
doFunction1()；
doFunction2()；
……
doFunction3()；
}
The Work method is template method, determines the actuating logic of geometry correction module in template method: power function 1, power function 2 and power function 3 these three steps;
2) adopt mode such as succession to realize handling different satellite sensor geometry correction function expansion, as " concrete geometry correction class one " or " concrete geometry correction class two ", as follows at the example code of " concrete geometry correction class one " and " concrete geometry correction class two ":
void?ConcreteClass1::doFunction1()
{
……
}
void?ConcreteClass1::doFunction2()
{
……
}
void?ConcreteClass1::doFunction3()
{
……
}
void?ConcreteClass2::doFunction1()
{
……
}
void?ConcreteClass2::doFunction2()
{
……
}
void?ConcreteClass2::doFunction3()
{
……
}
3) input satellite or sensor identification are as suction parameter, return corresponding concrete realization example according to parameter, as " concrete geometry correction class one ", the user only need call masterplate (Work) interface of " geometry correction abstract class ", can realize use to multiple geometric correction method, therefore the increase of processing capacity can not have influence on user's calling interface, and the user need not change calling program, can finish the use to new extension process algorithm and model.Example code is as follows:
int?main()
{
AbstractClass*GeometryCalibration＝
ClassFactory::Creat(SatelliteSensor)；
if(GeometryCalibration！＝NULL)
{
GeometryCalibration-＞Work()；
}
else
{
pintf(″SatelliteSensor?GeometryCalibration?not?implemented?yet！”)；
exit(-1)；
}
}
Wherein, ClassFactory::Creat can followingly realize.
AbstractClass*ClassFactory::Creat(SatelliteSensor)
{
If (SatelliteSensor is the sign of concrete geometry correction class 1)
{
return?new?ConcreteClass1()；
}
Else if (SatelliteSensor is the sign of concrete geometry correction class 2)
{
return?new?ConcreteClass2()；
}
}
Above step can adopt factory method in the software design pattern, also can adopt methods such as function pointer, Reflection reflex mechanism to realize.
By the above embodiments as seen, this extendible multi-satellite multi-sensor remote sensing images method for constructing geometric correction of the present invention has solved geometry correction processing and scaling problem that the user does not realize many satellites number multisensor remote sensing images under the situation of update routine.
Claims (1)
1. an extendible multi-satellite multi-sensor remote sensing images method for constructing geometric correction is characterized in that, may further comprise the steps:
1) is divided into according to the treatment scheme of geometry correction algorithm step: view data input, output image range computation, image rectification model, pixel evolution, resampling algorithm and correcting image output, the processing logic of the above step of regulation in the overall call method of abstract class then remote sensing images geometry correction needs;
2) process with method for constructing geometric correction is further divided into three layers: the abstraction function interface layer is handled in geometry correction, specific implementation layer and rudimentary algorithm layer, wherein geometry correction processing abstraction function interface layer is used to finish abstract interface definition and abstraction interface Processing Algorithm combination process, the specific implementation layer is used for realizing the algorithm of abstraction interface Processing Algorithm combination, can carry out general polynomial, rational function model, the collinearity equation model, radar slant-range-Doppler's model and direct linear transformation's model algorithm, adopt the succession mode to realize handling different satellite sensor geometry correction function expansion, the rudimentary algorithm layer is used to select the needed rudimentary algorithm of geometry correction, can carry out the input and output of file, resampling algorithm and image range calculating operation, specific implementation layer can utilize the rudimentary algorithm layer to realize function complicated algorithm more;
3) user uses satellite designation or sensor identification as input parameter, and the specific implementation algorithm that selection will be used can obtain corresponding algorithm and realize when program run, finish corresponding processing capacity.
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Cited By (6)
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|---|---|---|---|---|
| CN102509275A (en) * | 2011-11-25 | 2012-06-20 | 北京航空航天大学 | Resample method for remote sensing image composited based on image element imaging areas |
| CN103745450A (en) * | 2013-12-31 | 2014-04-23 | 华中科技大学 | Method for carrying out aero-optic effect calibration on airport airplane target image |
| CN104537614A (en) * | 2014-12-03 | 2015-04-22 | 中国资源卫星应用中心 | Orthographic correction method of CCD image of HJ-1 satellite |
| CN104992150A (en) * | 2015-06-29 | 2015-10-21 | 浪潮集团有限公司 | Automatic extracting method for urban roads based on high-resolution remote sensing image |
| CN112445497A (en) * | 2020-11-25 | 2021-03-05 | 中国电子科技集团公司第五十四研究所 | Remote sensing image processing system based on plug-in extensible architecture |
| CN113674166A (en) * | 2021-07-30 | 2021-11-19 | 中国环境科学研究院 | Accounting method for methane emission generated by waste incineration treatment |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102509275A (en) * | 2011-11-25 | 2012-06-20 | 北京航空航天大学 | Resample method for remote sensing image composited based on image element imaging areas |
| CN103745450A (en) * | 2013-12-31 | 2014-04-23 | 华中科技大学 | Method for carrying out aero-optic effect calibration on airport airplane target image |
| CN103745450B (en) * | 2013-12-31 | 2015-08-26 | 华中科技大学 | Airport Aircraft Targets image aero-optical effect bearing calibration |
| CN104537614A (en) * | 2014-12-03 | 2015-04-22 | 中国资源卫星应用中心 | Orthographic correction method of CCD image of HJ-1 satellite |
| CN104992150A (en) * | 2015-06-29 | 2015-10-21 | 浪潮集团有限公司 | Automatic extracting method for urban roads based on high-resolution remote sensing image |
| CN112445497A (en) * | 2020-11-25 | 2021-03-05 | 中国电子科技集团公司第五十四研究所 | Remote sensing image processing system based on plug-in extensible architecture |
| CN112445497B (en) * | 2020-11-25 | 2022-12-27 | 中国电子科技集团公司第五十四研究所 | Remote sensing image processing system based on plug-in extensible architecture |
| CN113674166A (en) * | 2021-07-30 | 2021-11-19 | 中国环境科学研究院 | Accounting method for methane emission generated by waste incineration treatment |
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Application publication date: 20100721 |