CN107274441A - The wave band calibration method and system of a kind of high spectrum image - Google Patents
The wave band calibration method and system of a kind of high spectrum image Download PDFInfo
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- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
- G06T7/33—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
- G06T7/337—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods involving reference images or patches
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Abstract
The invention provides a kind of waveband registration method of high spectrum image, including：Some wave band is chosen as benchmark wave band, new image is generated and is used as benchmark image；Characteristic point is extracted on band image subject to registration, template window is extracted centered on characteristic point；Selection extracts search window, thick match point is obtained using template matching method with characteristic point identical coordinate as center on benchmark image；The thick transformation relation of band image subject to registration and benchmark image is set up, match point of the characteristic point on benchmark image is calculated, search window is extracted centered on the match point, smart match point is obtained using template matching method；The smart transformation relation of band image subject to registration and benchmark image is set up, the correction of band image subject to registration is completed.Using technical scheme, the wave band registration of unmanned plane high spectrum image can be automatically performed, makes all wave bands of unmanned plane high spectrum image that there is Space Consistency, processing speed is fast, and registration accuracy is high.
Description
Technical field
The invention belongs to Hyperspectral imagery processing technical field, it is related to a kind of unmanned plane high spectrum image waveband registration method
And system.
Background technology
Unmanned plane has the advantages that mobility is high, cost is low, in recent years small range large scaled cartography, emergency disaster relief,
It is widely used in terms of resource environment investigation, precision agriculture, one as satellite remote sensing and traditional air remote sensing important
Arbitrary way.Unmanned plane high-spectrum remote-sensing is compared with satellite high-spectrum remote-sensing its advantageous advantage, due to unmanned plane
Flying height is low, the existing abundant spectral information of high spectrum image of acquisition, also there is very high spatial resolution, spatial discrimination
Rate can reach a centimetre rank, and can apply to environmental monitoring, precision agriculture, (crop growing state judgement, agricultural output assessment, pest and disease damage are pre-
It is alert) in terms of.
The characteristics of due to unmanned plane itself and the imaging mode for the hyperspectral imager being mounted on unmanned plane, unmanned plane
The processing of high spectrum image is a no small challenge.The traditional hyperspectral imager being mounted on satellite has optical splitter, wave band
Between all be alignment, it is not necessary to carry out the registration between wave band.Unmanned plane particularly rotor type unmanned plane is limited due to load,
Generally several kilograms, it is impossible to carry traditional hyperspectral imager.The hyperspectral imager mostly frame carried on current unmanned plane
Width formula imager, using the imaging mode of continuous exposure, obtains multiwave high spectrum image.Unmanned plane exists during due to exposure
Motion, therefore between same scape image different-waveband alignd, it is necessary to carry out the registration between wave band.
The content of the invention
In view of this, the invention provides a kind of waveband registration method of high spectrum image, including：
Step S100, chooses some wave band as benchmark wave band, then respectively expands the image of the wave band up and down
Several pixels, generate new image and are used as benchmark image；
Step S200, characteristic point is extracted on band image subject to registration, and each characteristic point is extracted centered on characteristic point
Template window；
Step S300, to each characteristic point, selection and the characteristic point identical coordinate are on benchmark image
The heart, extracts search window, thick match point is obtained using template matching method；
Step S400, the thick transformation relation of band image subject to registration and benchmark image is set up based on the thick match point, right
Each characteristic point, calculates match point of the characteristic point on benchmark image, with described according to the thick transformation relation
With search window is extracted centered on point, smart match point is obtained using template matching method；
Step S500, the smart transformation relation of band image subject to registration and benchmark image is set up based on the smart match point, so
The correction of band image subject to registration is completed using the smart transformation relation afterwards；
Step S600, repeat step S200~S500, complete the registration of next wave band.
Further, before characteristic point is extracted, the enhancing that band image subject to registration protrude contrast is operated.
Further, the thick match point described in step S400 is to use stochastical sampling coherence method and least square method
Reject the later thick match point of Mismatching point, the smart match point described in step S500 be using stochastical sampling coherence method and
Least square method rejects the later smart match point of Mismatching point.
Further, after per registering a wave band, offset of the wave band relative to benchmark wave band is calculated, in step
In S300 to next wave band using characteristic point coordinate add offset after coordinate centered on extract search window.
Further, in step s 200, useOr SIFT or Harris or SURF is used as extraction characteristic point
Operator.
The present invention also provides a kind of wave band registration system of high spectrum image, including：
Benchmark image generation module, for choosing some wave band as benchmark wave band, then by the image of the wave band
Several pixels are respectively expanded in lower left and right, generate new image and are used as benchmark image；
Template window extraction module, for extracting characteristic point on band image subject to registration, is extracted centered on characteristic point
The template window of each characteristic point；
Thick matching module, for each characteristic point, being selected and the characteristic point identical coordinate on benchmark image
As center, search window is extracted, thick match point is obtained using template matching method；
Smart matching module, the thick conversion for being set up band image subject to registration and benchmark image based on the thick match point is closed
System, to each characteristic point, calculates match point of the characteristic point on benchmark image, with institute according to the thick transformation relation
State and extract search window centered on match point, smart match point is obtained using template matching method
Geometric correction module, the essence conversion for setting up band image subject to registration and benchmark image based on the smart match point
Relation, then completes the correction of band image subject to registration using the smart transformation relation；
Further, above-mentioned wave band registration system also includes image enhancement module, for before characteristic point is extracted, treating
Registering band image protrude the enhancing operation of contrast.
Further, above-mentioned wave band registration system also includes Mismatching point rejecting module, for consistent using stochastical sampling
Property method and least square method reject Mismatching point.
Further, above-mentioned wave band registration system also includes offset computing module, for after a registering wave band,
Calculate offset of the wave band relative to benchmark wave band.
Using above-mentioned technical proposal, the wave band registration of unmanned plane high spectrum image can be automatically performed, makes unmanned plane bloom
All wave bands of spectrogram picture have Space Consistency, and processing speed is fast, and registration accuracy is high.
Above-mentioned general introduction is merely to illustrate that the purpose of book, it is not intended to limited in any way.Except foregoing description
Schematical aspect, embodiment and feature outside, by reference to accompanying drawing and the following detailed description, the present invention is further
Aspect, embodiment and feature would is that what is be readily apparent that.
Brief description of the drawings
In the accompanying drawings, unless specified otherwise herein, otherwise represent same or analogous through multiple accompanying drawing identical references
Part or element.What these accompanying drawings were not necessarily to scale.It should be understood that these accompanying drawings depict only according to the present invention
Some disclosed embodiments, and should not serve to limit the scope of the present invention.
Fig. 1 is the waveband registration method flow chart of the high spectrum image of the embodiment of the present invention.
Fig. 2 is the wave band registration system construction drawing of the high spectrum image of the embodiment of the present invention.
Embodiment
Hereinafter, some exemplary embodiments are simply just described.As one skilled in the art will recognize that
Like that, without departing from the spirit or scope of the present invention, described embodiment can be changed by various different modes.
Therefore, accompanying drawing and description are considered essentially illustrative rather than restrictive.
As shown in figure 1, the waveband registration method of the high spectrum image of the present embodiment, comprises the following steps：
Step S100, chooses some wave band as benchmark wave band, the image of the wave band is respectively then expanded into M up and down
Individual pixel, generates new image and is used as benchmark image.
Wave band registration is on the basis of some wave band of high spectrum image, to carry out registration.Therefore, elder generation is needed before registration
Suitable wave band is selected as benchmark wave band, the principle of selection be the registering success rate and accuracy rate of other wave bands and the wave band more
Height, choosing method can be analyzed by each spectral range, actual progress determines that this is common knowledge, no longer with quasi-experiment etc.
Repeat.
Original high spectrum image is the same in the size of each wave band, according to practical application needs, after registration, each wave band
Image size also must be the same.But, because imaging time is inconsistent, cause the areas imaging of benchmark wave band and other wave bands not
Unanimously, if be directly registrable, and ensure that images after registration size is constant, the missing image partial data after registration can be caused, because
This, chooses after benchmark wave band, the image of benchmark wave band is respectively expanded into M pixel up and down, forms new image and makees
On the basis of image.M value determines that M values are more than maximum by the maximum offset between other wave bands and benchmark wave band
Offset.
Step S200, characteristic point is extracted on band image subject to registration, and each characteristic point is extracted centered on characteristic point
Template window.
Before characteristic point is extracted, enhancing operation is carried out to band image subject to registration, prominent contrast makes the spy of extraction
Levy a little more.
In this step, it can be usedOr SIFT (Scale-invariant feature transform, yardstick
Invariant features are changed) or Harris or SURF (Speeded-Up Robust Features accelerate robust feature) conduct extraction
The operator of characteristic point, the present embodiment is preferredOperator, by the Robert ladders for calculating each pixel of band image subject to registration
The gray scale covariance matrix of degree and a window centered on pixel (c, r), finds as far as possible in band image subject to registration
The point of the error ellipse of small and close circle is used as characteristic point.
Step S300, to each characteristic point, selection and the characteristic point identical coordinate are on benchmark image
The heart, extracts search window, and then completing thick matching using normalizated correlation coefficient obtains thick match point.
After thick matching is completed, there may be some Mismatching points, use stochastical sampling coherence method (Random
Sample Consensus, RANSAC) and least square method rejecting Mismatching point, obtain correct thick match point.
Step S400, the thick conversion for setting up band image subject to registration and benchmark image based on above-mentioned correct thick match point is closed
System, to each characteristic point, calculates match point of the characteristic point on benchmark image, with institute according to the thick transformation relation
State and extract search window centered on match point, completing essence matching using normalizated correlation coefficient obtains smart match point.
Compared to thick matching, essence matching uses smaller search window, and higher normalizated correlation coefficient threshold value is found more smart
True smart match point.After the completion of accurate matching, Mismatching point is rejected using RANSAC and least square method, correct essence is obtained
With point.
Step S500, the essence conversion for setting up band image subject to registration and benchmark image based on above-mentioned correct smart match point is closed
System, then completes the correction of band image subject to registration using the smart transformation relation.
Calibration model uses multinomial model, the exponent number of multinomial model according to match point quantity and anamorphose situation come
It is determined that.Multinomial model needs match point distribution than more uniform.Match point is homogenized before correction, specific method
For：Mesh generation is pressed to image, match point is assigned to different grids, for there is the grid of match point, retains matching degree most
A big control point, then builds model using the match point after homogenization.
Step S600, repeat step S200~S500, complete the registration of next wave band.
In order to improve registering efficiency, after one wave band of registration, offset of the wave band relative to benchmark wave band is calculated,
In step S300 to next wave band using characteristic point coordinate add offset after coordinate centered on extract search window.
As shown in Fig. 2 the present embodiment also provides a kind of system of the waveband registration method for above-mentioned high spectrum image, bag
Include：
Benchmark image generation module 100, for choosing some wave band as benchmark wave band, then by the image of the wave band
Respectively expand several pixels up and down, generate new image and be used as benchmark image；
Template window extraction module 200, for extracting characteristic point on band image subject to registration, is carried centered on characteristic point
Take the template window of each characteristic point；
Thick matching module 300, for each characteristic point, selection to be sat with the characteristic point identical on benchmark image
Centered on being denoted as, search window is extracted, thick match point is obtained using template matching method；
Smart matching module 400, the thick change for setting up band image subject to registration and benchmark image based on the thick match point
Relation is changed, to each characteristic point, match point of the characteristic point on benchmark image is calculated according to the thick transformation relation,
Search window is extracted centered on the match point, smart match point is obtained using template matching method
Geometric correction module 500, the essence for setting up band image subject to registration and benchmark image based on the smart match point
Transformation relation, then completes the correction of band image subject to registration using the smart transformation relation.
The wave band registration system of the present embodiment, in addition to image enhancement module, for before characteristic point is extracted, treating and matching somebody with somebody
Quasi- band image protrude the enhancing operation of contrast.
The wave band registration system of the present embodiment, in addition to Mismatching point reject module, for using stochastical sampling uniformity
Method and least square method reject Mismatching point.
The wave band registration system of the present embodiment, in addition to offset computing module, for after a registering wave band, counting
Calculate offset of the wave band relative to benchmark wave band.
The wave band calibration method and system for the high spectrum image that the present embodiment is provided can be automatically performed unmanned plane EO-1 hyperion
The wave band registration of image, makes all wave bands of unmanned plane high spectrum image have Space Consistency, and processing speed is fast, registration accuracy
It is high.
The foregoing is only a specific embodiment of the invention, but protection scope of the present invention is not limited thereto, any
Those familiar with the art the invention discloses technical scope in, its various change or replacement can be readily occurred in,
These should all be included within the scope of the present invention.Therefore, protection scope of the present invention should be with the guarantor of the claim
Shield scope is defined.
Claims (9)
1. a kind of waveband registration method of high spectrum image, it is characterised in that including：
Step S100, chooses some wave band as benchmark wave band, the image of the wave band is respectively then expanded to some up and down
Individual pixel, generates new image and is used as benchmark image；
Step S200, characteristic point is extracted on band image subject to registration, and the template of each characteristic point is extracted centered on characteristic point
Window；
Step S300, to each characteristic point, selection is carried with the characteristic point identical coordinate as center on benchmark image
Search window is taken, thick match point is obtained using template matching method；
Step S400, the thick transformation relation of band image subject to registration and benchmark image is set up based on the thick match point, to each
Individual characteristic point, calculates match point of the characteristic point on benchmark image, with the match point according to the thick transformation relation
Centered on extract search window, obtain smart match point using template matching method；
Step S500, the smart transformation relation of band image subject to registration and benchmark image is set up based on the smart match point, is then made
The correction of band image subject to registration is completed with the smart transformation relation；
Step S600, repeat step S200~S500, complete the registration of next wave band.
2. waveband registration method according to claim 1, it is characterised in that before characteristic point is extracted, to ripple subject to registration
Section image protrude the enhancing operation of contrast.
3. waveband registration method according to claim 1, it is characterised in that the thick match point described in step S400 is to make
The later thick match point of Mismatching point, the essence described in step S500 are rejected with stochastical sampling coherence method and least square method
Match point is to reject the later smart match point of Mismatching point using stochastical sampling coherence method and least square method.
4. waveband registration method according to claim 1, it is characterised in that after one wave band of registration, calculate the ripple
Section uses next wave band the coordinate of characteristic point plus after offset relative to the offset of benchmark wave band in step S300
Coordinate centered on extract search window.
5. waveband registration method according to claim 1, it is characterised in that in step s 200, is usedOr
SIFT or Harris or SURF is used as the operator for extracting characteristic point.
6. a kind of wave band registration system of high spectrum image, it is characterised in that including：
Benchmark image generation module, for choosing some wave band as benchmark wave band, then by bottom left on the image of the wave band
Respectively expand several pixels on the right side, generates new image and is used as benchmark image；
Template window extraction module, for extracting characteristic point on band image subject to registration, extracts each centered on characteristic point
The template window of characteristic point；
Thick matching module, for each characteristic point, being selected and the characteristic point identical coordinate conduct on benchmark image
Center, extracts search window, thick match point is obtained using template matching method；
Smart matching module, the thick transformation relation for setting up band image subject to registration and benchmark image based on the thick match point,
To each characteristic point, match point of the characteristic point on benchmark image is calculated according to the thick transformation relation, with described
Search window is extracted centered on match point, smart match point is obtained using template matching method
Geometric correction module, the essence conversion for being set up band image subject to registration and benchmark image based on the smart match point is closed
System, to each characteristic point, according to the smart transformation relation, geometric correction is carried out using multinomial model.
7. wave band registration system according to claim 6, it is characterised in that also including image enhancement module, for carrying
Take before characteristic point, the enhancing that band image subject to registration protrude contrast is operated.
8. wave band registration system according to claim 6, it is characterised in that also reject module including Mismatching point, be used for
Mismatching point is rejected using stochastical sampling coherence method and least square method.
9. wave band registration system according to claim 6, it is characterised in that also including offset computing module, for
After a registering wave band, offset of the wave band relative to benchmark wave band is calculated.
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