CN108734685A - A kind of joining method of UAV system EO-1 hyperion linear array remote sensing image - Google Patents

A kind of joining method of UAV system EO-1 hyperion linear array remote sensing image Download PDF

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CN108734685A
CN108734685A CN201810444565.7A CN201810444565A CN108734685A CN 108734685 A CN108734685 A CN 108734685A CN 201810444565 A CN201810444565 A CN 201810444565A CN 108734685 A CN108734685 A CN 108734685A
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image
hyperspectral imaging
hyperion
remote sensing
linear array
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CN108734685B (en
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易俐娜
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China University of Mining and Technology Beijing CUMTB
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/50—Image enhancement or restoration by the use of more than one image, e.g. averaging, subtraction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformation in the plane of the image
    • G06T3/40—Scaling the whole image or part thereof
    • G06T3/4038—Scaling the whole image or part thereof for image mosaicing, i.e. plane images composed of plane sub-images
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10032—Satellite or aerial image; Remote sensing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
    • Y02A40/10—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture

Abstract

The invention discloses a kind of joining methods of UAV system EO-1 hyperion linear array remote sensing image, acquire target in hyperspectral remotely sensed image to be spliced first, and carry out the selection of characteristic point and matching to it；Image registration, the image after being registrated are carried out based on the characteristic point selection image transform model after matching；Overlapping region sprout wings based on the image after the registration and color balancing is handled, then carries out pixel-based inlaying to obtain spliced Hyperspectral imaging；Geographic registration is carried out to the spliced Hyperspectral imaging based on the face array orthography with geographical coordinate, obtains the Hyperspectral imaging with true geographical coordinate.The above method can solve the problems, such as that individual image coverage area of unmanned plane is small, spectrum distortion very little after also can guarantee image before a splice while ensureing visual effect, and final splicing result carries true geographical coordinate.

Description

A kind of joining method of UAV system EO-1 hyperion linear array remote sensing image
Technical field
The present invention relates to technical field of remote sensing image processing more particularly to a kind of UAV system EO-1 hyperion linear array remote sensing shadows The joining method of picture.
Background technology
Hyperspectral technique obtains related data using a large amount of very narrow electromagnetic wave bands from interested object, contains rich Rich space, radiation and the triple information of spectrum, most important feature and mark are exactly that spectrum is combined into one with image, this is The Disciplinary Frontiers of current world remote sensing technology.Since target in hyperspectral remotely sensed image has very high spectral resolution, it is capable of providing more The earth surface information of horn of plenty, therefore covered by the very big concern of domestic and foreign scholars and extensive use, application field The various aspects of geoscience become geologic mapping, vegetation investigation, ocean remote sensing, agricultural remote sensing, atmospheric research, environment prison The effective technology means in the fields such as survey, play increasingly important role.Imaging spectrometer hardware technology is constantly sent out in recent years Exhibition, volume is smaller and smaller, weight increasingly mitigates, cost is gradually lowered so that obtains Hyperspectral imaging using imaging spectrometer It is more convenient, quick, as mobility strong, at low cost, aerial survey of unmanned aerial vehicle remote sensing system with high accuracy develop, by imaging spectrometer It is integrated with unmanned plane and has become emerging research field to obtain high-spectral data.With satellite remote-sensing image, traditional air remote sensing Image is compared, and low latitude Unmanned Aerial Vehicle Data acquisition modes are flexible, and image precision is high, image definition, and terrain surface specifications are abundant, and unmanned plane is distant The characteristics of feeling image is that big face is completed in the shooting back and forth being continuously shot with different air strips by low altitude aircraft in same air strips The acquisition of product terrestrial object information, establishes same air strips panorama sketch, but single air strips are contained to establish wide viewing angle panorama sketch people The terrestrial object information of lid is still limited, needs to splice a plurality of air strips, could effectively cover survey region.
The essence that more air strips full-view images in unmanned aerial vehicle remote sensing field are established is that multiple of adjacent a plurality of air strips are had overlapping The single Image compounding in region covers region widely seamless high resolution image, and a series of image by unmanned planes is complete At the drafting task with the new view of accurate true terrestrial object information, in order to the application in later stage, foundation is to splice.Figure Refer to being overlapped two width or several sequence images according to its common portion as splicing, obtain a secondary large size has wider regard The seamless image at angle.Spliced image not only facilitates the global effect of our visual institute sector of observation, and also retains original Detailed information in beginning image.Image mosaic includes mainly two key technologies of image registration and image co-registration, the purpose of registration Be according to geometry motion model, will be in image registration to the same coordinate system；Fusion is then that the image after being registrated synthesizes one Big stitching image, the common image fusion technology of the prior art are generally based on the fusion method of pixel, wherein there are commonly Directly be averaged fusion method, weighted average fusion method and multi-resolution pyramid fusion method etc., but the image mosaic skill of the prior art Art has some limitations.
Invention content
The object of the present invention is to provide a kind of joining method of UAV system EO-1 hyperion linear array remote sensing image, this method energy It enough solves the problems, such as that individual image coverage area of unmanned plane is small, also can guarantee image before a splice while ensureing visual effect Spectrum distortion very little afterwards, and final splicing result carries true geographical coordinate.
The purpose of the present invention is what is be achieved through the following technical solutions：
A kind of joining method of UAV system EO-1 hyperion linear array remote sensing image, the method includes：
Step 1, acquisition target in hyperspectral remotely sensed image to be spliced, and the selection of characteristic point and matching are carried out to it；
Step 2 carries out image registration, the shadow after being registrated based on the characteristic point selection image transform model after matching Picture；
Step 3 carries out emergence and color balancing processing to overlapping region based on the image after the registration, then is based on Pixel inlays to obtain spliced Hyperspectral imaging；
Step 4 carries out ground based on the face array orthography with geographical coordinate to the spliced Hyperspectral imaging Reason registration, obtains the Hyperspectral imaging with true geographical coordinate.
The process of the step 1 is specially：
Hyperspectral imaging to be spliced is acquired first, and air strips are cut and rotated；
Feature same place is selected based on processed air strips.
The process of the step 2 is specially：
Based on the characteristic point after matching, on the basis of an air strips, to another air strips using Curved Surface Spline Function method into Row image converts, and obtains the correct image of relative position, the image after being as registrated.
The formula of the Curved Surface Spline Function method is expressed as：
Wherein, a0,a1,a2,Fi(i=1,2 ..., n) be undetermined coefficient；ri 2=(x-xi)2+(y-yi)2；ε is to adjust song The empirical parameter of face curvature size；
Use Curved Surface Spline Function method carry out image transformation detailed process for：
The feature point coordinates for obtaining the first image first is (x1, y1), (x2, y2) ... (xn, yn), and (n >=3) are right successively It is (w1, v1), (w2, v2) ... (wn, vn) to answer the feature point coordinates of the second image, and corrects institute on the basis of second image State the first image；
Then with (xi, yi, wi) and (xi, yi, vi) (i=1,2 ... n) based on two groups of data, build matrix equation, Calculate separately the fitting surface coefficient W of geographical abscissa and geographical ordinatew(x, y) and Wv(x, y)；
The first image to be corrected is coordinately transformed again, bilinear interpolation method is used in combination to carry out the resampling of pixel.
In the step 3, the process of color balancing processing is：
The gray level histogram of original image is calculated first；
Then each gray-scale cumulative distribution function of original image is obtained, and thus constructs gradation conversion function；
Original image all pixels gray value is mapped to output image further according to the gradation conversion function.
In the step 3, the process for processing of sprouting wings is：
Setting I (i, j) is the new gray value of image after sprouting wings；I1、I2For the gray value of image with splicing image, then have：
I (i, j)=eI1(i,j)+(1-e)I2(i,j)(i,j)∈I1∩I2,0≤e≤1
Wherein, e is weighting coefficient, if maximum value and minimum value are respectively in the X-axis direction for the overlapping region of two width images： xmax、xmin, then weighting coefficient e be expressed as：
The process of the step 4 is specially：
It is to be adopted to spliced linear array Hyperspectral imaging with reference to image with the face array orthography with geographical coordinate Geographic registration is carried out with affine Transform Model, obtains the Hyperspectral imaging with true geographical coordinate.
The formula of the affine Transform Model is expressed as：
Wherein, m0、m1、m3、m4Indicate image change scale and rotation angle；m2、m5Indicate horizontal and vertical direction displacement；
Use affine Transform Model carry out geographic registration detailed process for：
Obtain first Hyperspectral imaging to be registered feature point coordinates be (x1, y1), (x2, y2) ... (xn, yn), (n >= 3) it is (w1, v1), (w2, v2) ... (wn, vn), to be corresponding in turn to as the feature point coordinates of the orthography with reference to image；
Then by Hyperspectral imaging coordinate points to be registered to substituting into the affine Transform Model, using least square method Solve modulus type unknown parameter；
Hyperspectral imaging to be registered is transformed to and the same seat of the orthography further according to the transformation model acquired Under mark system, and resampling is carried out to pixel value using bilinear interpolation method.
As seen from the above technical solution provided by the invention, the above method can solve unmanned plane individual image covering The small problem of range, spectrum distortion very little after also can guarantee image before a splice while ensureing visual effect, and it is final Splicing result carry true geographical coordinate.
Description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, required use in being described below to embodiment Attached drawing be briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for this For the those of ordinary skill in field, without creative efforts, other are can also be obtained according to these attached drawings Attached drawing.
Fig. 1 is that the joining method flow of UAV system EO-1 hyperion linear array remote sensing image provided in an embodiment of the present invention is illustrated Figure.
Specific implementation mode
With reference to the attached drawing in the embodiment of the present invention, technical solution in the embodiment of the present invention carries out clear, complete Ground describes, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Based on this The embodiment of invention, every other implementation obtained by those of ordinary skill in the art without making creative efforts Example, belongs to protection scope of the present invention.
The embodiment of the present invention is described in further detail below in conjunction with attached drawing, is implemented as shown in Figure 1 for the present invention The joining method flow diagram for the UAV system EO-1 hyperion linear array remote sensing image that example provides, the method includes：
Step 1, acquisition target in hyperspectral remotely sensed image to be spliced, and the selection of characteristic point and matching are carried out to it；
In this step, Hyperspectral imaging to be spliced is acquired first, and air strips are cut and rotated；
Feature same place is selected based on processed air strips.
Step 2 carries out image registration, the shadow after being registrated based on the characteristic point selection image transform model after matching Picture；
In this step, another air strips can specifically be adopted based on the characteristic point after matching, on the basis of an air strips Image transformation is carried out with Curved Surface Spline Function method, obtains the correct image of relative position, the image after being as registrated.
In the specific implementation, the formula of the Curved Surface Spline Function method is expressed as：
Wherein, a0,a1,a2,Fi(i=1,2 ..., n) be undetermined coefficient；ri 2=(x-xi)2+(y-yi)2；ε is to adjust song The empirical parameter of face curvature size, it suitably chooses depending on actual conditions, usually, needs curved surface reduction distortion, curved surface smooth, answers Make ε=1~10-2, for distorting, larger curved surface even takes ε=10-5~10-6。
Above-mentioned undetermined coefficient a0,a1,a2,Fi(i=1,2..., n) can be acquired by following equations group：
Wherein, CjIt is a parameter about coefficient of elasticity, according to CjDifferent values, surface fitting can be divided into three Kind application mode：A. flexible fitting (such as generation DEM, establish geographical coordinate and map reference contacts)；B. elasticity fitting (such as light Sliding surface)；C. rigidity is fitted (correction of such as digital map), and C is taken in the present embodimentj=0.
Further, use Curved Surface Spline Function method carry out image transformation detailed process for：
The feature point coordinates for obtaining the first image first is (x1, y1), (x2, y2) ... (xn, yn), and (n >=3) are right successively It is (w1, v1), (w2, v2) ... (wn, vn) to answer the feature point coordinates of the second image, and corrects institute on the basis of second image State the first image；
Then with (xi, yi, wi) and (xi, yi, vi) (i=1,2 ... n) based on two groups of data, build matrix equation, Calculate separately the fitting surface coefficient W of geographical abscissa and geographical ordinatew(x, y) and Wv(x, y)；
The first image to be corrected is coordinately transformed again, bilinear interpolation method is used in combination to carry out the resampling of pixel.
Step 3 carries out emergence and color balancing processing to overlapping region based on the image after the registration, then is based on Pixel inlays to obtain spliced Hyperspectral imaging；
In this step, the process of progress color balancing processing is：
The gray level histogram of original image is calculated first；
Then each gray-scale cumulative distribution function of original image is obtained, and thus constructs gradation conversion function；
Original image all pixels gray value is mapped to output image further according to the gradation conversion function.
In addition, the process for carrying out emergence processing is：
Setting I (i, j) is the new gray value of image after sprouting wings；I1、I2For the gray value of image with splicing image, then have：
I (i, j)=eI1(i,j)+(1-e)I2(i,j)(i,j)∈I1∩I2,0≤e≤1
Wherein, e is weighting coefficient, if maximum value and minimum value are respectively in the X-axis direction for the overlapping region of two width images： xmax、xmin, then weighting coefficient e be expressed as：
Step 4 carries out ground based on the face array orthography with geographical coordinate to the spliced Hyperspectral imaging Reason registration, obtains the Hyperspectral imaging with true geographical coordinate.
In this step, the face array orthography that can specifically carry geographical coordinate is with reference to image, to spliced Linear array Hyperspectral imaging carries out geographic registration using affine Transform Model, obtains the EO-1 hyperion shadow with true geographical coordinate Picture.
In the specific implementation, the formula of above-mentioned affine Transform Model is expressed as：
Wherein, m0、m1、m3、m4Indicate image change scale and rotation angle；m2、m5Indicate horizontal and vertical direction displacement；
Further, use affine Transform Model carry out geographic registration detailed process for：
Obtain first Hyperspectral imaging to be registered feature point coordinates be (x1, y1), (x2, y2) ... (xn, yn), (n >= 3) it is (w1, v1), (w2, v2) ... (wn, vn), to be corresponding in turn to as the feature point coordinates of the orthography with reference to image；
Then by Hyperspectral imaging coordinate points to be registered to substituting into the affine Transform Model, using least square method Solve modulus type unknown parameter；
Hyperspectral imaging to be registered is transformed to and the same seat of the orthography further according to the transformation model acquired Under mark system, and resampling is carried out to pixel value using bilinear interpolation method.
It is worth noting that, the content not being described in detail in the embodiment of the present invention belongs to professional and technical personnel in the field's public affairs The prior art known.
In conclusion the UAV system EO-1 hyperion linear array remote sensing image joining method that the embodiment of the present invention is provided can It effectively removes and occurs apparent splicing line because of difference in exposure, obtain higher region registration accuracy, and make final splicing knot Fruit carries true geographical coordinate, the application of convenient high-spectral data thereafter.
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto, Any one skilled in the art is in the technical scope of present disclosure, the change or replacement that can be readily occurred in, It should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be with the protection model of claims Subject to enclosing.

Claims (8)

1. a kind of joining method of UAV system EO-1 hyperion linear array remote sensing image, which is characterized in that the method includes：
Step 1, acquisition target in hyperspectral remotely sensed image to be spliced, and the selection of characteristic point and matching are carried out to it；
Step 2 carries out image registration, the image after being registrated based on the characteristic point selection image transform model after matching；
Step 3 carries out emergence and color balancing processing to overlapping region based on the image after the registration, then carries out being based on pixel Inlay obtain spliced Hyperspectral imaging；
Step 4 matches the spliced Hyperspectral imaging progress geography based on the face array orthography with geographical coordinate Standard obtains the Hyperspectral imaging with true geographical coordinate.
2. the joining method of UAV system EO-1 hyperion linear array remote sensing image according to claim 1, which is characterized in that described The process of step 1 is specially：
Hyperspectral imaging to be spliced is acquired first, and air strips are cut and rotated；
Feature same place is selected based on processed air strips.
3. the joining method of UAV system EO-1 hyperion linear array remote sensing image according to claim 1, which is characterized in that described The process of step 2 is specially：
Based on the characteristic point after matching, on the basis of an air strips, figure is carried out using Curved Surface Spline Function method to another air strips As transformation, the correct image of relative position, the image after being as registrated are obtained.
4. the joining method of UAV system EO-1 hyperion linear array remote sensing image according to claim 3, which is characterized in that described The formula of Curved Surface Spline Function method is expressed as：
Wherein, a0,a1,a2,Fi(i=1,2 ..., n) be undetermined coefficient；ε is to adjust curved surface curved The empirical parameter of rate size；
Use Curved Surface Spline Function method carry out image transformation detailed process for：
The feature point coordinates for obtaining the first image first is (x1, y1), (x2, y2) ... (xn, yn), and (n >=3) are corresponding in turn to the The feature point coordinates of two images is (w1, v1), (w2, v2) ... (wn, vn), and corrects on the basis of second image described the One image；
Then with (xi, yi, wi) and (xi, yi, vi), (i=1,2 ... n) based on two groups of data, build matrix equation, respectively Calculate the fitting surface coefficient W of geographical abscissa and geographical ordinatew(x, y) and Wv(x, y)；
The first image to be corrected is coordinately transformed again, bilinear interpolation method is used in combination to carry out the resampling of pixel.
5. the joining method of UAV system EO-1 hyperion linear array remote sensing image according to claim 1, which is characterized in that in institute It states in step 3, the process of color balancing processing is：
The gray level histogram of original image is calculated first；
Then each gray-scale cumulative distribution function of original image is obtained, and thus constructs gradation conversion function；
Original image all pixels gray value is mapped to output image further according to the gradation conversion function.
6. the joining method of UAV system EO-1 hyperion linear array remote sensing image according to claim 1, which is characterized in that in institute It states in step 3, the process for processing of sprouting wings is：
Setting I (i, j) is the new gray value of image after sprouting wings；I1、I2For the gray value of image with splicing image, then have：
I (i, j)=eI1(i,j)+(1-e)I2(i,j) (i,j)∈I1∩I2,0≤e≤1
Wherein, e is weighting coefficient, if maximum value and minimum value are respectively in the X-axis direction for the overlapping region of two width images：xmax、 xmin, then weighting coefficient e be expressed as：
7. the joining method of UAV system EO-1 hyperion linear array remote sensing image according to claim 1, which is characterized in that described The process of step 4 is specially：
It is with reference to image, to spliced linear array Hyperspectral imaging using imitative with the face array orthography with geographical coordinate It penetrates transformation model and carries out geographic registration, obtain the Hyperspectral imaging with true geographical coordinate.
8. the joining method of UAV system EO-1 hyperion linear array remote sensing image according to claim 7, which is characterized in that described The formula of affine Transform Model is expressed as：
Wherein, m0、m1、m3、m4Indicate image change scale and rotation angle；m2、m5Indicate horizontal and vertical direction displacement；
Use affine Transform Model carry out geographic registration detailed process for：
Obtain first Hyperspectral imaging to be registered feature point coordinates be (x1, y1), (x2, y2) ... (xn, yn), (n >=3), It is (w1, v1), (w2, v2) ... (wn, vn) to be corresponding in turn to as the feature point coordinates of the orthography with reference to image；
Then Hyperspectral imaging coordinate points to be registered are asked using least square solution substituting into the affine Transform Model Unknown-model parameter；
Hyperspectral imaging to be registered is transformed to and the same coordinate system of the orthography further according to the transformation model acquired Under, and resampling is carried out to pixel value using bilinear interpolation method.
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CN114022385B (en) * 2021-11-07 2024-03-26 桂林电子科技大学 Image restoration method based on local surface fitting

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