CN109584155A - A kind of method that unmanned aerial vehicle remote sensing image quickly splices - Google Patents
A kind of method that unmanned aerial vehicle remote sensing image quickly splices Download PDFInfo
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- CN109584155A CN109584155A CN201710902463.0A CN201710902463A CN109584155A CN 109584155 A CN109584155 A CN 109584155A CN 201710902463 A CN201710902463 A CN 201710902463A CN 109584155 A CN109584155 A CN 109584155A
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- 238000000034 method Methods 0.000 title claims abstract description 26
- 238000012952 Resampling Methods 0.000 claims abstract description 4
- 238000000605 extraction Methods 0.000 claims abstract description 4
- 230000005855 radiation Effects 0.000 claims description 5
- 230000004927 fusion Effects 0.000 claims description 3
- 238000003702 image correction Methods 0.000 claims description 2
- 230000007704 transition Effects 0.000 abstract description 5
- 230000009286 beneficial effect Effects 0.000 abstract description 2
- 230000000116 mitigating effect Effects 0.000 abstract description 2
- 238000007500 overflow downdraw method Methods 0.000 abstract description 2
- 230000009466 transformation Effects 0.000 description 4
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
- G06T3/4038—Image mosaicing, e.g. composing plane images from plane sub-images
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- 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
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- 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
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- 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
- G06T2207/20—Special algorithmic details
- G06T2207/20212—Image combination
- G06T2207/20221—Image fusion; Image merging
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
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- Theoretical Computer Science (AREA)
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Abstract
The invention discloses a kind of methods that unmanned aerial vehicle remote sensing image quickly splices, unmanned aerial vehicle remote sensing image is acquired first, radiant correction is carried out followed by remote sensing images of the histogram matching to acquisition, geometric correction is carried out to remote sensing images using image resampling method, then matching treatment is carried out to pretreated remote sensing images, it is rejected including characteristics of image classification, image characteristics extraction, characteristic matching, erroneous matching characteristic point, finally the remote sensing images after matching are merged using weighted average fusion method, obtain spliced image.Compared with prior art, the invention has the following beneficial effects: the methods quickly spliced by unmanned aerial vehicle remote sensing image, can accurately be registrated image, reduce stitching error, accomplish seamless spliced, and transition is naturally, scientific basis can be provided for mitigation drop calamity and emergency command.
Description
Technical field
The present invention relates to field of image processings, have especially invented a kind of method that unmanned aerial vehicle remote sensing image quickly splices.
Background technique
Unmanned plane as a kind of emerging air remote sensing platform, have the characteristics that efficiently, flexibly, quickly, it is inexpensive, on machine
The available high resolution image of digital camera, DV of carrying.Unmanned aerial vehicle remote sensing is a kind of new remote sensing, is answered
It is extensive with field, including agricultural, forestry, electric power, land resources, urban planning etc..
But it since unmanned aerial vehicle remote sensing platform is during taking photo by plane, is limited, is obtained by flying height and camera focus etc.
The image taken haves the characteristics that flying height is low, film size is small, can not reflect the overall condition of shooting area, tends not to contentedly face
When the demand and application, especially emergency disaster relief of information.Therefore, more with regard to what need to be will acquire to obtain entire target area information
It opens remote sensing images splicing and is fused into a width panoramic picture.The purpose of the quick splicing of image is quick and more accurately obtains
Stitching image is obtained, its technological difficulties are how to be accurately registrated image and reduce stitching error.
Summary of the invention
Goal of the invention: in view of the above shortcomings of the prior art, proposing a kind of method that unmanned aerial vehicle remote sensing image quickly splices,
To be accurately registrated image and reduce stitching error.
Technical solution: the invention discloses a kind of method that unmanned aerial vehicle remote sensing image quickly splices, this method includes following
Step:
Step 1: unmanned aerial vehicle remote sensing Image Acquisition；
Step 2: the correction of unmanned aerial vehicle remote sensing image radiation；
Step 3: the unmanned aerial vehicle remote sensing geometric correction of imagery；
Step 4: unmanned aerial vehicle remote sensing images match；
Step 5: unmanned aerial vehicle remote sensing image co-registration.
Specifically, unmanned aerial vehicle remote sensing image radiation bearing calibration is histogram matching in step 2.
Unmanned plane is at interval of taking photo by plane twice, and since intensity of illumination and incidence angle change, adjacent two width image may be generated
It is inconsistent etc. to show as brightness of image, saturation degree for larger color difference, therefore, it is necessary to radiant correction be carried out to image, to eliminate image
Influence of the color difference to splicing.
Specifically, unmanned aerial vehicle remote sensing geometric image correction method is image resampling in step 3.
It is light-weight since unmanned plane is small in size, it is affected by air-flow, stability and wind loading rating are poor, flight attitude
Inclination, jitter phenomenon are difficult to avoid that these can all generate direct influence to the remote sensing images of acquisition, cause image to occur abnormal
Become.Geometric correction is carried out to fault image by picpointed coordinate transformation, image resampling etc., to eliminate geometric distortion to image
It influences, meets the needs of image registration.
Specifically, unmanned aerial vehicle remote sensing image matching method is characteristics of image classification, image characteristics extraction, feature in step 4
Matching, erroneous matching characteristic point are rejected.
Image registration refers to two width for carry out shooting acquisition to same Target scalar or several images on spatial position
Alignment transforms to the process under unified coordinate system by finding optimal registration parameter for several images.Image registration is image
The core of splicing, the quality of the direct image joint of the precision of registration.
Specifically, unmanned aerial vehicle remote sensing image interfusion method is weighted average fusion in step 5.
The thought for being weighted and averaged fusion method is that the pixel value of the lap of two images is first weighted, so
It is overlapped again afterwards.The purpose of image co-registration is exactly that the image after registration is merged into a width newly based on certain transformation model
Image splicing trace should not occur in overlapping region, that is, accomplish seamless spliced, transition nature.
Compared with prior art, the invention has the following beneficial effects:
The method quickly spliced by unmanned aerial vehicle remote sensing image can accurately be registrated image, reduce stitching error, accomplish seamless spelling
It connects, transition is naturally, scientific basis can be provided for mitigation drop calamity and emergency command.
Specific embodiment
With specific embodiment, the present invention is described in further detail below, it should be noted that above embodiments are only
Limited to illustrate technical solution of the present invention, those of ordinary skill in the art technical solution of the present invention is done its
He modifies or equivalent replacement should all cover without departing from the spirit and principle of technical solution of the present invention in right of the invention
In claimed range.
Unmanned aerial vehicle remote sensing Image Acquisition.High-definition digital camera is carried on six rotor wing unmanned aerial vehicles, acquires 20 minutes images.
The correction of unmanned aerial vehicle remote sensing image radiation.Relative detector calibration is carried out using histogram matching, by adjusting reference
The histogram of image is allowed to match with image histogram to be spliced；Image and image to be spliced after correction is in brightness and tone
Substantially it reaches unanimity, realizes the smooth transition of two images well, eliminate influence of the image color difference to splicing.
The unmanned aerial vehicle remote sensing geometric correction of imagery.Geometric correction is carried out to fault image by picpointed coordinate transformation, is eliminated several
What influence of the distortion to image, meets the needs of image registration.
Unmanned aerial vehicle remote sensing images match.Unmanned aerial vehicle remote sensing image matching method be characteristics of image classification, image characteristics extraction,
Characteristic matching, erroneous matching characteristic point are rejected.Image registration, which refers to, carries out shooting two width of acquisition or more to same Target scalar
Alignment of the width image on spatial position is transformed to several images under unified coordinate system by finding optimal registration parameter
Process.Image registration is the core of image joint technology, the quality of the direct image joint of the precision of registration.
Unmanned aerial vehicle remote sensing image interfusion method is weighted average fusion.To the pixel value of the lap of two images, first
It is weighted, is then overlapped again.Image after registration is merged into the new figure of a width based on certain transformation model
Picture splicing trace should not occur in overlapping region, accomplish seamless spliced, transition nature.Endlap rate reaches 70%, side
Reach 40% to Duplication.
Claims (5)
1. a kind of method that unmanned aerial vehicle remote sensing image quickly splices, which comprises the following steps:
Step 1: unmanned aerial vehicle remote sensing Image Acquisition；
Step 2: the correction of unmanned aerial vehicle remote sensing image radiation；
Step 3: the unmanned aerial vehicle remote sensing geometric correction of imagery；
Step 4: unmanned aerial vehicle remote sensing images match；
Step 5: unmanned aerial vehicle remote sensing image co-registration.
2. a kind of method that unmanned aerial vehicle remote sensing image quickly splices according to claim 1, it is characterised in that: the step
In 2, unmanned aerial vehicle remote sensing image radiation bearing calibration is histogram matching.
3. a kind of method that unmanned aerial vehicle remote sensing image quickly splices according to claim 1, it is characterised in that: the step
In 3, unmanned aerial vehicle remote sensing geometric image correction method is image resampling.
4. a kind of method that unmanned aerial vehicle remote sensing image quickly splices according to claim 1, it is characterised in that: the step
In 4, unmanned aerial vehicle remote sensing image matching method is characteristics of image classification, image characteristics extraction, characteristic matching, erroneous matching characteristic point
It rejects.
5. a kind of method that unmanned aerial vehicle remote sensing image quickly splices according to claim 1, it is characterised in that: the step
In 5, unmanned aerial vehicle remote sensing image interfusion method is weighted average fusion.
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| CN201710902463.0A CN109584155A (en) | 2017-09-29 | 2017-09-29 | A kind of method that unmanned aerial vehicle remote sensing image quickly splices |
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| CN201710902463.0A CN109584155A (en) | 2017-09-29 | 2017-09-29 | A kind of method that unmanned aerial vehicle remote sensing image quickly splices |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112634186A (en) * | 2020-12-25 | 2021-04-09 | 江西裕丰智能农业科技有限公司 | Image analysis method of unmanned aerial vehicle |
| CN116228539A (en) * | 2023-03-10 | 2023-06-06 | 贵州师范大学 | Unmanned aerial vehicle remote sensing image stitching method |
| CN117788351A (en) * | 2024-02-27 | 2024-03-29 | 杨凌职业技术学院 | Agricultural remote sensing image correction method and system |
-
2017
- 2017-09-29 CN CN201710902463.0A patent/CN109584155A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112634186A (en) * | 2020-12-25 | 2021-04-09 | 江西裕丰智能农业科技有限公司 | Image analysis method of unmanned aerial vehicle |
| CN116228539A (en) * | 2023-03-10 | 2023-06-06 | 贵州师范大学 | Unmanned aerial vehicle remote sensing image stitching method |
| CN117788351A (en) * | 2024-02-27 | 2024-03-29 | 杨凌职业技术学院 | Agricultural remote sensing image correction method and system |
| CN117788351B (en) * | 2024-02-27 | 2024-05-03 | 杨凌职业技术学院 | Agricultural remote sensing image correction method and system |
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Application publication date: 20190405 |