CN104236527A - Quantitative analysis method for epipolar line features of remotely sensed image of linear array satellite based on projection track method - Google Patents

Quantitative analysis method for epipolar line features of remotely sensed image of linear array satellite based on projection track method Download PDF

Info

Publication number
CN104236527A
CN104236527A CN201410468144.XA CN201410468144A CN104236527A CN 104236527 A CN104236527 A CN 104236527A CN 201410468144 A CN201410468144 A CN 201410468144A CN 104236527 A CN104236527 A CN 104236527A
Authority
CN
China
Prior art keywords
image
point
line
picture
row
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201410468144.XA
Other languages
Chinese (zh)
Inventor
巩丹超
龚辉
韩轶龙
汤晓涛
钱方明
周增华
黄艳
胡玲
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
SURVEYING AND MAPPING INST HEADQUARTERS OF GENERAL STAFF CPLA
Original Assignee
SURVEYING AND MAPPING INST HEADQUARTERS OF GENERAL STAFF CPLA
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by SURVEYING AND MAPPING INST HEADQUARTERS OF GENERAL STAFF CPLA filed Critical SURVEYING AND MAPPING INST HEADQUARTERS OF GENERAL STAFF CPLA
Priority to CN201410468144.XA priority Critical patent/CN104236527A/en
Publication of CN104236527A publication Critical patent/CN104236527A/en
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • G01C11/04—Interpretation of pictures

Abstract

The invention relates to an epipolar line model of a remotely sensed image of a linear array push-broom type satellite, belongs to the technical field of photogrammetry and remote sensing, and in particular relates to a quantitative analysis method for epipolar line features of a remotely sensed image of a linear array satellite based on a projection track method. The method comprises a quantitative analysis method for linear features and a quantitative analysis method for conjugate features. The quantitative analysis method provided by the invention mainly aims at the linear features and the conjugate features of an epipolar line according to the characteristics of linear array push-broom type three-dimensional imaging and an epipolar line model constructed based on the projection track method. The method can be used for accurately testing and analyzing the actual application features of the epipolar line model of the linear array push-broom type remotely sensed satellite image, and the summarized features supply important technical support to the subsequent high-precision generation of a three-dimensional epipolar line image of the linear array push-broom type remotely sensed satellite image.

Description

A kind of linear array satellite remote-sensing image core line property quantification analytical approach based on projected footprint method
Technical field
The present invention relates to linear array satellite remote-sensing image data processing, belong to photogrammetry and remote-sensing technique field.Particularly a kind of linear array satellite remote-sensing image core line property quantification analytical approach based on projected footprint method.
Background technology
Utilize spaceborne linear array push-broom sensor to obtain remote sensing image, realize the importance that stereo measurement is remote sensing application.French SPOT satellite, the IKONOS satellite of the U.S., " sky paints No. " of China and " No. three, resource " satellite are all loaded with linear array push-broom sensor.This is the highly effective sensor of current earth observation, has good application prospect.Linear array push-broom type remote sensing image has the feature of " row central projection ", there is it self elements of exterior orientation each scanning provisional capital, have unique radiation and geometrical property, the model and method of what therefore those were traditional be applicable to frame width formula central projection three-dimensional imaging is no longer generally suitable for.
Core line is the key concept analyzing stereogram geometric relationship in stereophotogrammetry.At the beginning of the seventies, american photography is measured scholar U.V.Helava etc. and is proposed the relevant concept of one dimension core line.Extract three-dimensional information from stereopsis, a most important constraint condition is exactly the constraint of core line.Many existing matching algorithms all utilize this constraint condition to limit the search volume of coupling to shorten the reliability of match time and raising matching result.Although the pass of core line ties up in stereo-picture process very useful, but for linear array push-broom type remote sensing image, because its geometric relationship is much more complicated than frame width formula central projection image, therefore it can not have strict core line definition as the frame width formula central projection image of routine.For above-mentioned situation, many photogrammetric workers have done unremitting effort, attempt the core line model setting up line array loudspeakers.At present about the core line model of linear array push-broom type remote sensing image, theory is the most tightly the projected footprint method based on imaging geometry.Existing research shows, the core line model based on projected footprint method has following characteristic: 1. under normal circumstances, and core line is similar hyp curve, but can regard near linear as to process among a small circle; 2. for certain the some q on a core line in piece image and apart from the consecutive point in this certain limit, its corresponding image points is all positioned on the core line of q point; 3. corresponding epipolar line is to being existence.If two points are corresponding image points, two core lines so corresponding to them are one to one, and the point on these two core lines is also one to one.The above-mentioned analysis conclusion about core line characteristic still rests on the stage of qualitative analysis, how carries out quantitative test accurately to the core line model based on projected footprint method so that follow-up practical application, still needs and will carry out deep research.
Summary of the invention
The existing research of the core line model based on projected footprint method shows: for linear array push-broom type remote sensing image, its complete core line is hyperbolic curve, but in subrange, similar with traditional core line image, there is linear characteristic and conjugate property.In order to determine the characteristic of quantitative analysis and total tuberculosis line, the present invention is directed to linear array push-broom type satellite-remote-sensing image, for accurately understanding and grasping the core line model characteristic based on projected footprint method, propose a kind of linear array satellite remote-sensing image core line property quantification analytical approach based on projected footprint method.
Technical solution of the present invention is: a kind of linear array satellite remote-sensing image core line property quantification analytical approach based on projected footprint method, and method comprises the quantitative analysis method of linear characteristic and the quantitative analysis method of conjugate property,
1., the quantitative analysis method of described linear characteristic, its step is as follows:
(1) equally distributed some test points (a) are selected from the left picture of original linear array satellite remote-sensing image stereogram, the foundation selected is that each fixing image blocks selects its central point as test point, the capable n row of some position distribution m on view picture image, total mn test point, m, n are natural number;
(2) according to the picpointed coordinate of each test point on left image (a (x, y)), utilize the RPC parameter of left, a space line by projection centre and picture point is determined according to projected footprint method, then the RPC parameter of right is utilized, project on right by the point on this space line one by one according to periodic sampling, the track of these projections on right photo is exactly corresponding core curve (a 1a 2);
(3) to this core curve (a 1a 2), determine a near linear closest to this curve by the method for data fitting, then add up on this curve a little with the ultimate range of this fitting a straight line;
(4) to mn test point, above-mentioned operation is progressively performed; Determine error maximum with fitting a straight line difference on the curvature of these line correspondences and every bar curve thereof;
2., the quantitative analysis method of described conjugate property, its step is as follows:
(1) the RPC parameter provided according to three-dimensional remote sensing image can obtain actual average height value h in image capturing range ave, maximum height value h max, and minimum height value h min;
(2) some equally distributed m image row or row (l) is chosen from left image, here select row or row according to being according to the direction of core line and image is capable or image arranges corner dimension, as the direction of fruit stone line and column direction angle little, then get image column direction, as the direction of fruit stone line and line direction angle little, then get image line direction, get central pixel and two end points of each row or row image, for each picture point (q) in these three points, picture point (q) and projection centre line and maximum elevation, dispersed elevation, the intersection point of minimum elevation is three object space point (Q 1, Q 2, Q 3), utilize elevation maximal value, mean value and minimum value three height value in picpointed coordinate and corresponding image capturing range to calculate three object space point (Q according to rational function model 1, Q 2, Q 3) terrestrial coordinate value,
(3) three object space point (Q are calculated according to rational function model 1, Q 2, Q 3) corresponding original right as the pixel coordinate value of picture point, get mid point at adjacent 2, obtain corresponding to the core line equation (l') of picture point (q) on right image by these two points;
(4) central point (q of the edge on required core line perpendicular to sweep trace is got 0), and the ground point (P of corresponding elevation maximal value 1), and the ground point (P of elevation minimum value 3), calculate two object space point (P according to rational function model 1and P 3) terrestrial coordinate value;
(5) two object space point (P are calculated according to the rational function model of left 1and P 3) pixel coordinate value of corresponding original left image picture point, core line equation (l) on the left image corresponding with the core line equation (l') on right image is obtained by these two points, analyze the relation of the picture point (q) on straight line (l) and left picture, get final product the conjugate property of definite kernel line under near linear characteristic condition;
(6) to above-mentioned m equally distributed image column or row, perform described operation successively, the conjugate property of m row or row image in image capturing range can be obtained.
The core line model quantitative analysis method utilizing the present invention to propose, in conjunction with the test findings of multiple commercial satellite remote sensing image, can to draw about the core line model based on projected footprint method as drawn a conclusion by analyzing:
● for dissimilar remote sensing image, within the scope of film size, the approximate characteristic of straight line is the processing requirements that can meet sub-pixel, therefore within the scope of film size, the model of this core curve can be regarded as straight line to process;
● for dissimilar remote sensing image, within the scope of film size, under the support of core line near linear characteristic, the conjugate property of core line is also the processing requirements that can meet sub-pixel, therefore, within the scope of film size, the process utilizing this core curve can realize Image Matching is simplified to one dimension by two dimension.
In a word, utilize the method can the practical application characteristic of accurate testing and analysis linear array push-broom type satellite-remote-sensing image core line model, these characteristics of summary be that the follow-up spatial nuclei line image generating linear array push-broom type satellite-remote-sensing image is accurately to providing important technical support.
Accompanying drawing explanation
Fig. 1 is projected footprint method core line model.Wherein Q is ground point, S (X s, Y s, Z s) and S'(X' s, Y s', Z' s) be respectively the projection centre of left picture and right picture, a light by ground point Q, through left picture projection centre S (X s, Y s, Z s), imaging point q on left picture, any point Q'(X on this light, Y, Z) all can uniquely project on right image, projected footprints of these points will form a curve on right picture, this curve we be referred to as the core line of q.The same place that q ' is q, is obviously positioned on this curve.
Fig. 2 is linear characteristic test schematic diagram.S 1, S 2be respectively the projection centre of left picture and right picture, a is left picture picture point, A 1a 2for by left picture picture point a and left picture projection centre S 1space line, a 1a 2for space line A 1a 2core curve on right picture, a' is core curve a 1a 2on any point.
Fig. 3 is conjugate property test schematic diagram.L is a certain row (OK) on left picture, and q is the upper picture point of l, h max, h ave, h minbe respectively the maximum elevation value in image capturing range, dispersed elevation value and minimum height value, Q 1, Q 2, Q 3be respectively picture point q and projection centre S 1the intersection point of line and maximum elevation, dispersed elevation, minimum elevation, q 1, q 2, q 3be respectively Q 1, Q 2, Q 3picture point on right picture, l' is q 1, q 2, q 3image row (OK) at place, P 1, P 2, P 3for the edge on l' is perpendicular to the central point q of sweep trace 0with projection centre S 2the intersection point of line and maximum elevation, dispersed elevation, minimum elevation.
Embodiment
1, based on the core line model ultimate principle of projected footprint method
As shown in Figure 1, article one, light is from ground point Q, through the projection centre S (Xs of left picture, Ys, Zs) the q point on left picture is imaged in, if each the object space point on this light is projected on right picture according to formula (1), so projected footprints of these points will form a curve on right picture, this curve we be referred to as the core line of q.If the same place that q ' is q, obviously it is always positioned on this curve.Here it is based on the core line model of projected footprint method.
r n = NumL ( P n , L n , H n ) DenL ( P n , L n , H n ) c n = NumS ( P n , L n , H n ) DenS ( P n , L n , H n ) - - - ( 1 )
In formula:
NumL ( P n , L n , H n ) = a 0 + a 1 L n + a 2 P n + a 3 H n + a 4 L n P n + a 5 L n H n + a 6 P n H n + a 7 L n 2 + a 8 P n 2 + a 9 H n 2 + a 10 P n L n H n + a 11 L n 3 + a 12 L n P n 2 + a 13 L n H n 2 + a 14 L n 2 P n + a 15 P n 3 + a 16 P n H n 2 + a 17 L n 2 H n + a 18 P n 2 H n + a 19 H n 3
DenL ( P n , L n , H n ) = b 0 + b 1 L n + b 2 P n + b 3 H n + b 4 L n P n + b 5 L n H n + b 6 P n H n + b 7 L n 2 + a 8 P n 2 + b 9 H n 2 + b 10 P n L n H n + b 11 L n 3 + b 12 L n P n 2 + b 13 L n H n 2 + b 14 L n 2 P n + b 15 P n 3 + b 16 P n H n 2 + b 17 L n 2 H n + b 18 P n 2 H n + b 19 H n 3
NumS ( P n , L n , H n ) = c 0 + c 1 L n + c 2 P n + c 3 H n + c 4 L n P n + c 5 L n H n + c 6 P n H n + c 7 L n 2 + c 8 P n 2 + c 9 H n 2 + c 10 P n L n H n + c 11 L n 3 + c 12 L n P n 2 + c 13 L n H n 2 + c 14 L n 2 P n + c 15 P n 3 + c 16 P n H n 2 + c 17 L n 2 H n + c 18 P n 2 H n + c 19 H n 3
DenS ( P n , L n , H n ) = d 0 + d 1 L n + d 2 P n + d 3 H n + d 4 L n P n + d 5 L n H n + d 6 P n H n + d 7 L n 2 + d 8 P n 2 + d 9 H n 2 + d 10 P n L n H n + d 11 L n 3 + d 12 L n P n 2 + d 13 L n H n 2 + d 14 L n 2 P n + d 15 P n 3 + d 16 P n H n 2 + d 17 L n 2 H n + d 18 P n 2 H n + d 19 H n 3
Above-mentioned formula is commonly referred to rational function model (rational function model is called for short RFM), (P in model n, L n, H n) be the ground coordinate of regularization, (r n, c n) be the image coordinate of regularization.(a i, b i.c i, d i) be the coefficient (rational polynomial coefficient, be called for short RPC) of rational polynominal.
2, linear characteristic quantitative analysis method
Ultimate principle
Equally distributed some picture points selected by the left picture right from original stereo picture, define, right picture is determined corresponding core curve according to the core line model based on projected footprint method, and the linear characteristic of this core line within the scope of film size of the right picture of statistical study.Otherwise also can the linear characteristic of statistical study left picture coker line.
3, linear characteristic quantitative analysis method basic step
(1) select equally distributed some somes a from the left picture of linear array satellite remote-sensing image stereogram, the foundation of selection is that each fixing image blocks selects its central point as test point, the capable n row of some position distribution m on view picture image, total mn test point.
(2) as shown in Figure 2, according to the picpointed coordinate a (x, y) of each test point on left image, utilize the RPC parameter of left, determine a space line A by left picture picture point a and left picture projection centre S1 according to projected footprint method 1a 2, then utilize the RPC parameter of right, by this space line A 1a 2on point project on right one by one according to periodic sampling, the track of these projections on right photo is exactly corresponding core curve a 1a 2.
(3) to this core curve a 1a 2, determine a near linear closest to this curve by the method for data fitting, then add up on this curve a little with the ultimate range of this fitting a straight line.
(4) to mn test point, above-mentioned operation is progressively performed.Determine error maximum with fitting a straight line difference on the curvature of these line correspondences and every bar curve thereof.
4, conjugate property quantitative analysis method
Ultimate principle
Equally distributed some picture points are selected from the left picture of original remote sensing image stereogram, define according to linear array remote sensing image expansion nuclear line model, determine corresponding core line on right picture, then right picture will be put accordingly reprojection on left picture, and the relation of the core line on the left picture of statistical study and the picture point on left picture, clearly from left picture to the conjugate relation of right picture core line.Otherwise the core line conjugate relation also can added up from right picture to left picture.
5, conjugate property quantitative analysis method basic step
(1) the RPC parameter provided according to three-dimensional remote sensing image can obtain actual average height value h in image capturing range ave, maximum height value h max, and minimum height value h min;
(2) as shown in Figure 3, some equally distributed m images row (OK) are chosen from left image, here select row or row according to being according to the direction of core line and image is capable or image arranges corner dimension, as the direction of fruit stone line and column direction angle little, then get image column direction, as the direction of fruit stone line and line direction angle little, then get image line direction.Get central pixel and two end points of each row (OK) image, for each the picture point q in these three points, elevation maximal value, mean value and minimum value three height value in picpointed coordinate and corresponding image capturing range are utilized to calculate three object space point Q according to rational function model 1, Q 2, Q 3terrestrial coordinate value;
(3) Q is calculated according to rational function model 1, Q 2, Q 3the original right of three some correspondences, as the pixel coordinate value of picture point, gets mid point at adjacent 2, obtains corresponding to the core line equation l' of some q on right image by these two points;
(4) the mid point q of the edge on required core line perpendicular to sweep trace is got 0, and the ground point P of corresponding elevation maximal value 1, and the ground point P of elevation minimum value 3, calculate two object space point P according to rational function model 1and P 3terrestrial coordinate value;
(5) two object space point P are calculated according to the rational function model of left 1and P 3the pixel coordinate value of corresponding original left image picture point, obtains the core line equation l on the left image corresponding with l' by these two points, analyze the relation of the picture point q on straight line l and left picture, can the conjugate property of definite kernel line under near linear characteristic condition.
(6) to above-mentioned m equally distributed image column (OK), perform described operation successively, the conjugate property of m row image in image capturing range can be obtained.

Claims (1)

1., based on a linear array satellite remote-sensing image core line property quantification analytical approach for projected footprint method, it is characterized in that: the method comprises the quantitative analysis method of linear characteristic and the quantitative analysis method of conjugate property,
1., the quantitative analysis method of described linear characteristic, its step is as follows:
(1) equally distributed some test points (a) are selected from the left picture of original linear array satellite remote-sensing image stereogram, the foundation selected is that each fixing image blocks selects its central point as test point, the capable n row of some position distribution m on view picture image, total mn test point, m, n are natural number;
(2) according to the picpointed coordinate of each test point on left image (a (x, y)), utilize the RPC parameter of left, a space line by projection centre and picture point is determined according to projected footprint method, then the RPC parameter of right is utilized, project on right by the point on this space line one by one according to periodic sampling, the track of these projections on right photo is exactly corresponding core curve (a 1a 2);
(3) to this core curve (a 1a 2), determine a near linear closest to this curve by the method for data fitting, then add up on this curve a little with the ultimate range of this fitting a straight line;
(4) to mn test point, above-mentioned operation is progressively performed; Determine error maximum with fitting a straight line difference on the curvature of these line correspondences and every bar curve thereof;
2., the quantitative analysis method of described conjugate property, its step is as follows:
(1) the RPC parameter provided according to three-dimensional remote sensing image can obtain actual average height value h in image capturing range ave, maximum height value h max, and minimum height value h min;
(2) some equally distributed m image row or row (l) is chosen from left image, here select row or row according to being according to the direction of core line and image is capable or image arranges corner dimension, as the direction of fruit stone line and column direction angle little, then get image column direction, as the direction of fruit stone line and line direction angle little, then get image line direction, get central pixel and two end points of each row or row image, for each picture point (q) in these three points, picture point (q) and projection centre line and maximum elevation, dispersed elevation, the intersection point of minimum elevation is three object space point (Q 1, Q 2, Q 3), utilize elevation maximal value, mean value and minimum value three height value in picpointed coordinate and corresponding image capturing range to calculate three object space point (Q according to rational function model 1, Q 2, Q 3) terrestrial coordinate value,
(3) three object space point (Q are calculated according to rational function model 1, Q 2, Q 3) corresponding original right as the pixel coordinate value of picture point, get mid point at adjacent 2, obtain corresponding to the core line equation (l') of picture point (q) on right image by these two points;
(4) central point (q of the edge on required core line perpendicular to sweep trace is got 0), and the ground point (P of corresponding elevation maximal value 1), and the ground point (P of elevation minimum value 3), calculate two object space point (P according to rational function model 1and P 3) terrestrial coordinate value;
(5) two object space point (P are calculated according to the rational function model of left 1and P 3) pixel coordinate value of corresponding original left image picture point, core line equation (l) on the left image corresponding with the core line equation (l') on right image is obtained by these two points, analyze the relation of the picture point (q) on straight line (l) and left picture, get final product the conjugate property of definite kernel line under near linear characteristic condition;
(6) to above-mentioned m equally distributed image column or row, perform described operation successively, the conjugate property of m row or row image in image capturing range can be obtained.
CN201410468144.XA 2014-09-15 2014-09-15 Quantitative analysis method for epipolar line features of remotely sensed image of linear array satellite based on projection track method Pending CN104236527A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201410468144.XA CN104236527A (en) 2014-09-15 2014-09-15 Quantitative analysis method for epipolar line features of remotely sensed image of linear array satellite based on projection track method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201410468144.XA CN104236527A (en) 2014-09-15 2014-09-15 Quantitative analysis method for epipolar line features of remotely sensed image of linear array satellite based on projection track method

Publications (1)

Publication Number Publication Date
CN104236527A true CN104236527A (en) 2014-12-24

Family

ID=52225074

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201410468144.XA Pending CN104236527A (en) 2014-09-15 2014-09-15 Quantitative analysis method for epipolar line features of remotely sensed image of linear array satellite based on projection track method

Country Status (1)

Country Link
CN (1) CN104236527A (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108592884A (en) * 2018-04-24 2018-09-28 武汉大学 A kind of general linear array satellite core line image generating method
CN117664088A (en) * 2024-01-31 2024-03-08 中国人民解放军战略支援部队航天工程大学 Method, system and equipment for determining homonymy point by ultra-wide vertical orbit circular scanning satellite image
CN117664087A (en) * 2024-01-31 2024-03-08 中国人民解放军战略支援部队航天工程大学 Method, system and equipment for generating vertical orbit circular scanning type satellite image epipolar line

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103630120A (en) * 2013-07-16 2014-03-12 中国人民解放军信息工程大学 Mars surface linear array image epipolar ray resampling method based on strict geometric model

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103630120A (en) * 2013-07-16 2014-03-12 中国人民解放军信息工程大学 Mars surface linear array image epipolar ray resampling method based on strict geometric model

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
TAEJUNG KIM: "A Study on the Epipolarity of Linear Pushbroom Images", 《PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING》 *
巩丹超 等: "卫星立体像对核线影像生成方法研究", 《测绘科学与工程》 *
张过 等: "基于RPC模型的线阵卫星影像核线排列及其几何关系重建", 《国土资源遥感》 *
聂倩 等: "基于有理函数模型的线阵推扫式卫星近似核线影像的生成", 《城市勘测》 *
胡芬 等: "基于投影基准面的线阵推扫式卫星立体像对近似核线影像生成方法", 《测绘学报》 *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108592884A (en) * 2018-04-24 2018-09-28 武汉大学 A kind of general linear array satellite core line image generating method
CN117664088A (en) * 2024-01-31 2024-03-08 中国人民解放军战略支援部队航天工程大学 Method, system and equipment for determining homonymy point by ultra-wide vertical orbit circular scanning satellite image
CN117664087A (en) * 2024-01-31 2024-03-08 中国人民解放军战略支援部队航天工程大学 Method, system and equipment for generating vertical orbit circular scanning type satellite image epipolar line
CN117664088B (en) * 2024-01-31 2024-04-02 中国人民解放军战略支援部队航天工程大学 Method, system and equipment for determining homonymy point by ultra-wide vertical orbit circular scanning satellite image
CN117664087B (en) * 2024-01-31 2024-04-02 中国人民解放军战略支援部队航天工程大学 Method, system and equipment for generating vertical orbit circular scanning type satellite image epipolar line

Similar Documents

Publication Publication Date Title
CN102003938B (en) Thermal state on-site detection method for large high-temperature forging
CN104299228B (en) A kind of remote sensing image dense Stereo Matching method based on Accurate Points position prediction model
CN103630120B (en) Martian surface linear array image core line method for resampling based on tight geometric model
CN106526593B (en) Sub-pixel-level corner reflector automatic positioning method based on the tight imaging model of SAR
Sun et al. RBA: Reduced Bundle Adjustment for oblique aerial photogrammetry
CN103559708B (en) Industrial fixed-focus camera parameter calibration device based on side's target model
CN101814192A (en) Method for rebuilding real 3D face
CN104268876A (en) Camera calibration method based on partitioning
CN110378001A (en) A kind of Pillarless caving remote sensing satellite geometric positioning accuracy analysis method
CN104778716A (en) Truck carriage volume measurement method based on single image
Di et al. Co-registration of Chang’E-1 stereo images and laser altimeter data with crossover adjustment and image sensor model refinement
Lenz et al. Automatic in-flight boresight calibration considering topography for hyperspectral pushbroom sensors
Viana et al. Algorithms for extraction of structural attitudes from 3D outcrop models
CN104236527A (en) Quantitative analysis method for epipolar line features of remotely sensed image of linear array satellite based on projection track method
Altuntas et al. Image based methods for surveying heritage of masonry arch bridge with the example of Dokuzunhan in Konya, Turkey
CN104197898A (en) Epipolar ray image generating method of linear array satellite remote sensing image based on projection track method
Qiao et al. Assessment of geo-positioning capability of high resolution satellite imagery for densely populated high buildings in metropolitan areas
CN102798851B (en) Geometric-imaging-based MODIS (Moderate Resolution Imaging Spectroradiometer) LAI product verification method
Jurjević et al. 3D data acquisition based on OpenCV for close-range photogrammetry applications
CN105631849A (en) Polygon object change detection method and device
Willneff et al. Single-image high-resolution satellite data for 3D information extraction
Kirk et al. Further adventures in Mars DTM quality: Smoothing errors, sharpening details
Kirk et al. Evaluating stereo dtm quality at jezero crater, mars with hrsc, ctx, and hirise images
Liu et al. Evaluation of rational function model for geometric modeling of Chang'E-1 CCD images
Zhao et al. Epipolar line generation from IKONOS imagery based on rational function model

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20141224

WD01 Invention patent application deemed withdrawn after publication