CN105787952B - A kind of appraisal procedure that micro-vibration influences in-orbit picture quality - Google Patents
A kind of appraisal procedure that micro-vibration influences in-orbit picture quality Download PDFInfo
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Abstract
The invention discloses the appraisal procedures that a kind of micro-vibration influences in-orbit picture quality, include the following steps:In-orbit image is obtained using TDICCD acquisitions, the scenery that length runs through area-of-interest is chosen according to evaluation requirement in in-orbit image;To scenery region, center line is extracted, following process is performed both by for each pixel point on center line:Acquisition energy curve is fitted to adjacent picture elements energy using the Energy distribution of its adjacent picture elements;The distance of the relatively current pixel point of center of energy point of energy curve is that the camera optical axis of current pixel point shakes amplitude;The optical axis of all pixel points is shaken into the curve that the amplitude composition camera optical axis changes over time;Fourier transformation is carried out to the curve, obtains the frequency energy distribution curve of camera optical axis shaking;By the optical axis for being more than setting numerical value in energy distribution curve shake the corresponding decimation in frequency of amplitude come out and star on micro-vibration source vibration frequency comparison, thus know the contribution that the camera optical axis is shaken in micro-vibration source on each star.
Description
Technical field
The invention belongs to art of image analysis, and in particular to a kind of assessment side that micro-vibration influences in-orbit picture quality
Method.
Background technology
Micro-vibration refer to spacecraft in orbit during, due to carrying equipment (such as momenttum wheel high-speed rotating component, the sun
The walking members such as wing driving mechanism, infrared camera pendulum mirror etc. tilting members) smaller past of spacecraft amplitude caused by normal work
Multiple movement.The equipment that micro-vibration has been guided in micro-vibration source.Micro-vibration energy very little, is answered compared to caused by transmitter section mechanical environment
Become, micro-vibration will not cause structure to destroy to when young 1 magnitude.In addition to amplitude is smaller, the frequency range of micro-vibration is very wide, appearance
State control system is difficult to measure, also can not full frequency band control.Micro-vibration mainly influences that optical camera etc. is sensitive to micro-vibration to be set
Standby, being High Resolution Remote Sensing Satellites must solve the problems, such as.
For the image quality of remote sensing satellite, foreign countries have carried out numerous studies, but focus on comprehensive picture quality
Assessment, without the method that individually assessment micro-vibration influences picture quality.
At present both at home and abroad to the evaluation goal of picture quality be evaluation be image " fidelity " and " intelligibility ".From method
It is upper to be broadly divided into objective evaluation and subjective estimate method to divide.
The objective evaluation of picture quality is to constitute the related physics of image to measuring gained according to given measurement standard
Characteristic parameters are evaluated.Generally by two different quality views.One is without reference to image, emphasize that physical characteristic is joined
The direct effect to image is measured, includes mainly image moisture in the soil, image power spectrum etc.;It is another then original image is provided, it emphasizes to be based on
The difference of parameter evaluates the loss of picture quality and deterioration degree between image, and this measurement includes mean square error
(MSE), peak value mean square error (PMSE), average relative error (MAE), Y-PSNR (PSNR), Laplace fidelity, fuzzy entropy
Deng.There are reference waveform method and test pattern to test block-regulations the test of display.The major defect of objective evaluation be with regarding
Feel that same effect is poor.
The subjective assessment of picture quality is that people directly observes image, according to the evaluation criterion of regulation and opinion scale and people
Eye is given a mark to picture quality and is evaluated to the visual experience of image, and the statistics given a mark to image according still further to each observer is flat
Provide last evaluation result.
Railway Project is needed to pay attention to when subjective assessment:
(1) selection of observer
To keep the subjective assessment of picture quality statistically significant, the observer's number for participating in scoring is no less than 20 people.
Observer should include two kinds of people:One is untrained " layman " observers;Another kind is specially trained, to figure
As " expert " being skillful at, they can be noted that the crucial performance and slight change of image deterioration, are carried out to picture quality
Stringent judgement.
(2) quality yardstick and interference (obstruction) scale
The scale of image subjective assessment is often to select according to the observation being in the push for image technique.To ordinary people
For mostly use quality yardstick, and to image professional's multiple users interference scale.
(3) observed image condition
Test condition should match with the use condition of standard as far as possible.Following table gives the observation condition number of various countries' proposition
Value and CCIR recommendations.
The observation condition CCIR (OSIO 1966) of 1 image quality evaluation of table
Subjective evaluation method is divided into absolute evaluation and relative evaluation.Absolute evaluation is provided in advance according to some by observer
Opinion scale or the experience of oneself, to be evaluated image propose Quality estimation.In some cases, one group of standard can also be provided
Image as reference, help observer suitable evaluation is made to picture quality.The common opinion scale of absolute evaluation is known as
" all-round excellent degree scale ", such as following table.
The all-round excellent degree scale of 2 absolute evaluation of table
Extraordinary image | 5 points |
Good image | 4 points |
Medium image | 3 points |
The image of difference | 2 points |
Excessively poor image | 1 point |
Relative evaluation is that a collection of image is classified by good to bad by observer, that is, is compared to each other to image
It obtains quality and provides score.Relative evaluation is commonly used so-called " group's goodness scale " such as following table.
Group's goodness scale of 3 relative evaluation of table
Best image in a batch | 7 points |
The image better than the average level of this batch | 6 points |
It is slightly better than the image of this batch of average level | 5 points |
The image of this batch of average level | 4 points |
Slightly it is inferior to the image of this batch of average level | 3 points |
Than the image of the average water adjustment of this batch | 2 points |
Worst image in a batch | 1 point |
The more subjective evaluation method used in the world at present mostly uses CCIR Pyatyis scoring quality yardstick and obstruction
Scale.Quality yardstick is mostly used for ordinary people, and it is more preferable using obstruction scale for image professional.
CCIR500 standards are as shown in the table:
Table 4CCIR500 proposed standards
NIIRS (National Imagery Interpretability Rating Scale National Imagery interpretation degree etc.
Grade standard) it is U.S. government's image resolution ratio evaluation and reporting standard association (Image Resolution Assessment and
Reporting Standards Committee (IRARS)) lead a set of standard for evaluation image quality developed.
The first edition of NIIRS is published on 1974, is completed within 1991 primary larger revision, is completed again within 1994 primary small-scale
It revises and issues.NIIRS is the subjective criterion of a task-driven.
NIIRS is related to task height first.NIIRS standards are mainly used in military surveillance field, for military surveillance,
Resolution ratio has vital meaning.Therefore, just a priori there is a theory in the developer of NIIRS standards:" image interpretation
Personnel should have completes more interpretation tasks using the ability of high-definition picture." in NIIRS standards " interpretation " substantially may be used
Be understood to typical military target (such as su-27 flank guard's opportunity of combat, T-72 tanks, launching silo state) " it was found that "
(Detect), " differentiation " (Distinguish) and " confirmation " (Identify).To sum up, NIIRS and with resolution ratio be lead
To task especially military mission it is inseparable.
Secondly, NIIRS is a subjective criterion.NIIRS is made of 10 ranks (0 grade to 9 grades), and each rank has several
Interpretation task or standard are constituted.These standards indicate the information that this level image should be able to be extracted.For example, for one
A NIIRS2 grades of full-colour image, decipherer should be able to have found the large-scale hangar on airport, for NIIRS6 grades of image, they
Large-scale or Medium Helicopter should be able to be distinguished.The development process of NIIRS by means of military information circle interpretation expert couple
The interpretation of great amount of images.It is simultaneously accurate using NIIRS by qualified image interpretation personnel to the process of image grading using NIIRS
It is then compared to complete to be classified image with image.
NIIRS and GRD (ground resolution) have certain correspondence, see the table below:
The correspondence of table 5NIIRS and GRD
NIIRS grades | GRD |
NIIRS 0 | N/A (not applicable) |
NIIRS 1 | More than 9m |
NIIRS 2 | 4.5~9m |
NIIRS 3 | 2.5~4.5m |
NIIRS 4 | 1.2~2.5m |
NIIRS5 | 0.75~1.2m |
NIIRS 6 | 40~75cm |
NIIRS 7 | 20~40cm |
NIIRS 8 | 10~20cm |
NIIRS 9 | Less than 10cm |
NIIRS standards are gradually generalized to some other quick to image resolution ratio by some fruitful work at present
The civil field of sense.The current system of NIIRS standards is:
Table 6NIIRS standards systems
General Image-Quality Equation (GIQE equations) are from late 1980s in IRARS
It is developed under leader.Its original purpose is exactly one for establishing a bridge block and linking up NIIRS standards and remote sensing system performance
Index subset.Third edition GIQE is formally announced within 1994, discloses fourth edition GIQE again through revision after this, fourth edition GIQE includes
It is respectively applied to visible light and infrared two equations.
GIQE, which is described in research, thinks on some influential factors of image NIIRS grades be how to influence image
NIIRS grades.They are to indicate imaging scale and the ground pixel resolution of resolution capability respectively;Indicate image acuity
Relative edge along response;Indicate the signal-to-noise ratio of signal and noise amplitude relationship;Since letter is transmitted in modulation in photo electric imaging system
The generally use of number compensation (MTFC), effect show as the promotion at edge and the increase of noise, (are adjusted to consider MTFC
Modulation trnasfer function compensates) influence, add edge response overshoot item and noise gain item.
Third edition GIQE forms are as follows:
NIIRS=11.82+3.32log10RERGM-3.32log10GSDGM-1.48HGM- G/SNR is noted:Subscript GM indicates water
Square to the geometric average with vertical direction
Here every meaning is as follows
GSD:Ground sampled distance in inches
RER:Relative edge is along response
H:Modulation transfer function compensates response overshoot in edge caused by (MTFC)
SNR:Signal noise ratio (snr) of image
Fourth edition visible light GIQE equation forms:
NIIRS=10.251-alog10GSDGM+blog10RERGM-0.656·HGM-0.344·G/SNR
A=3.32, b=1.559 as RER >=0.9
A=3.16, b=2.817 as RER < 0.9
The computational methods of H can be summarized as:In the direction of motion or scanning direction, when standard edge is a monotonic function along response
When, H is equal to the value of standardization edge response at 1.25 away from edge pixels, and otherwise, H is equal to 1~3 away from edge pixel coverage
The maximum value of interior normalization edge response, utilizes the geometric average of both direction in GIQE equations.
Revised GIQE may (λ be wavelength, F system F numbers, the spatial sampling of P devices to the system in effective of λ F/p < 1
Distance).Use scope such as following table of the GIQE equations by verification simultaneously:
Table 7GIQE parameter areas
NIIRS standards gem-pure can be included into task orientation by the analysis according to front to picture quality concept
Image quality criteria.Task involved by NIIRS standards is all the task of resolution ratio sensitivity, and typical task is panchromatic visible light
Military surveillance.Therefore, NIIRS standards cannot expand the scope of application by " accidentally ".
In NIIRS using in field, NIIRS standards are a very outstanding standards, possess following some characteristics:
The increase of linear criterion rating number and the interpretation degree of image are consistent.
The interpretation degree difference of discreteness image can be often clearly distinguished open when reaching a NIIRS rank.
The classification of device independence image and sensor are unrelated, and such NIIRS can be used to handle different imaging systems and obtain
The image obtained.
Availability standard is easy to be read personnel's use.Furtherly, interpretation personnel can apply standard to handle out stable
As a result.
The interpretation degree of the content for the NIIRS grades and figure itself that criterion equivalence piece image comes out by criterion interpretation
It is consistent.
These characteristics ensure that NIIRS standards become the image criterion of the task orientation of current west information mainstream
One of.
From NIIRS standards from the point of view of the intension of picture quality, it can be found that NIIRS systems are more laid particular emphasis in specific area
Image " can be understood "." can understand " is related to task, and only required by task information can extract image from image and just talk
Can effectively it understand.Leonardesque " Mona Lisa " intelligibility is very high, for find fighter plane military information imagery interpreter he
It can understand, but his task can be sayed without effective " can understand " degree.
GIQE equations are a good bridges, and NIIRS standards contacted with certain design objectives of remote sensing system
Come, while also denoting the relationship between these indexs.NIIRS standards determine GIQE, therefore GSD (in GIQE equations
Surface sample distance) weight that accounts for should be most heavy.This point also determines the scope of application of GIQE.But GIQE and GRD are
Multivalue correspondence, that is to say, that in some section, GIQE is not to the variation extrasensitivity of GRD, some other shadow at this time
The effect of the factor of sound can show especially out.Therefore, the Δ NIIIRS that is calculated using GIQE is used for Δ NIIIRS itself
Illustrate that a certain range of variation of remote sensing system performance is still very convictive.The other parts of this paper have and can apply Δ
NIIIRS illustrates influence of some links of some remote sensing systems to imaging capability.
Invention content
In view of this, the present invention provides the appraisal procedure that a kind of micro-vibration influences in-orbit picture quality, can be derived that
The visual evaluation that micro-vibration influences in-orbit picture quality.
In order to achieve the above object, the technical scheme is that:A kind of micro-vibration is commented what in-orbit picture quality influenced
Estimate method, includes the following steps:
Step (1) obtains in-orbit image using the TDICCD acquisitions of time delay integration image controller, in in-orbit image
The scenery that length runs through area-of-interest is chosen according to evaluation requirement.
Step (2) extracts center pel point, organization center line line by line to scenery region.
Step (3) is traversed each pixel point on center line, following step is performed both by for each pixel point centered on center line
Suddenly (4)~step (5):
Step (4) is directed to current pixel point, in its left and right or the adjacent picture elements symmetrical above and below for choosing setting quantity, utilizes phase
The Energy distribution of adjacent pixel is fitted adjacent picture elements energy, the energy curve after being fitted.
Step (5) is directed to current pixel point, extracts the center of energy point of the energy curve after the fitting of its adjacent picture elements energy
The distance of relatively current pixel point, the distance are that the camera optical axis of current pixel point shakes amplitude.
Step (6) connects the optical axis shaking amplitude of all pixel points to change over time to the camera optical axis
Curve obtains at the time of each pixel point corresponds in curve according to the auxiliary data of TDICCD.
Step (7) carries out Fourier transformation to above-mentioned curve, and the frequency energy distribution curve of camera optical axis shaking can be obtained.
The optical axis for being more than setting numerical value in energy distribution curve is shaken the corresponding decimation in frequency of amplitude and come out by step (8),
With the vibration frequency comparison in micro-vibration source on star, the contribution that the camera optical axis is shaken in micro-vibration source on each star is thus known.
Advantageous effect:
(1) present invention relies primarily on MTF, NIIRS and GIQE etc. to assess picture quality compared to conventional method, can not differentiate
The influence of micro-vibration, the present invention can provide the visual evaluation that micro-vibration influences in-orbit picture quality.
(2) present invention can not only assess the relative amplitude of camera optical axis shaking, can also assess the frequency of camera optical axis shaking
Characteristic is directly the impact evaluation service in micro-vibration source;
(3) conventional method is compared, the present invention does not need the particular arrangements such as particular image or ground target, it is only necessary on image
With the characteristic information convenient for analysis.
Description of the drawings
Fig. 1 is a kind of estimation flow that micro-vibration influences in-orbit picture quality of the present invention;
Fig. 2 is the railway image that the satellite in the embodiment of the present invention obtains;
Fig. 3 is the feature information extraction for the railway image that the satellite in the embodiment of the present invention obtains;
Fig. 4 is the result in time domain that the optical axis shakes;
Fig. 5 is the frequency-domain result that the optical axis shakes.
Specific implementation mode
The present invention will now be described in detail with reference to the accompanying drawings and examples.
Embodiment 1
Step (1) obtains in-orbit image using the TDICCD acquisitions of time delay integration image controller, in in-orbit image
The scenery that length runs through area-of-interest is chosen according to evaluation requirement.
First have to analyze in-orbit image data, select to have longer more straight feature scenery (such as airport, railway,
River etc.) image, to carry out further assessment.
Step (2) extracts center pel point, organization center line line by line to above-mentioned scenery region;
Step (3) is traversed each pixel point on center line, following step is performed both by for each pixel point centered on center line
Suddenly (4)~step (5);When it is implemented, TDICCD acquired image features are directed to, it is corresponding from the first row of center line
Pixel point starts, and executes step (4)~step (5), and subsequent line number adds 1, removes a line and correspond to pixel point, repeat step
(4)~step (5) is until all the points are finished.Flow is specifically as shown in Figure 1.
Step (4) is directed to current pixel point, in its left and right or the adjacent picture elements symmetrical above and below for choosing setting quantity, utilizes phase
The Energy distribution of adjacent pixel is fitted adjacent picture elements energy, the energy curve after being fitted;
Step (5) is directed to current pixel point, extracts the center of energy point of the energy curve after the fitting of its adjacent picture elements energy
The distance of relatively current pixel point, the distance are that the camera optical axis of current pixel point shakes amplitude;
Step (6) connects the optical axis shaking amplitude of all pixel points to change over time to the camera optical axis
Curve obtains at the time of each pixel point corresponds in curve according to the auxiliary data of TDICCD;
Step (7) carries out Fourier transformation to above-mentioned curve, and the frequency energy distribution curve of camera optical axis shaking can be obtained;
The optical axis for being more than setting numerical value in energy distribution curve is shaken the corresponding decimation in frequency of amplitude and come out by step (8),
With the vibration frequency comparison in micro-vibration source on star, the contribution that the camera optical axis is shaken in micro-vibration source on each star is thus known.
Embodiment 2
Select a width that there is the image of longer, more straight feature scenery, such as Fig. 2 in step1, the in-orbit image obtained from satellite
It is shown, for the image on the airport that certain satellite obtains;
There are a longer and generally more straight railway, therefore the extraction pair characterized by the railway on step 2, the image
As.Input initial value:1,14162, gray scale 109;
Step 3, feature information extraction cycle:
(1) line number adds 1, i.e. line number=2, columns=14162;
(2) from image analysis it is found that the width of railway is about 7 pixels, therefore left and right respectively takes 3 pixels, i.e. abscissa
=2, ordinate=14159,14160,14161,14162,14163,14164,14165;
(3) found in longitudinal 7 pixels with 109 immediate gray scales, be 14161, gray value 107;
(4) related data of the 2nd row is recorded, line number adds 1, repeats (2)~(3), until reach the boundary of characteristic information, this
It is the boundary of image in example.
Finally obtained the results are shown in Figure 3, if obtained coordinate is respectively x, y.
Step 4, the center for having obtained railway in image at this time, can carry out according to the center to characteristic information
Central energy position fitting cycle.
(1) first by respectively taking three pixels, i.e. abscissa=1 at 1,14162 position or so, ordinate=14159,
14160,14161,14162,14163,14164,14165;
(2) center of energy for being fitted to obtain at this using ceiling capacity is:14162.2585;
(3) it is 0.2585 pixel to subtract the optical axis shaking amplitude that its center 14162 obtains at the point;
(4) it is shaken if necessary to calculate longitudinal optical axis, can take three points (if line number is big downwards by 1,14162 position
In 3,3 points can be respectively taken up and down), i.e. abscissa=1,2,3,4, ordinate=14162.
(5) (2)~(3) are repeated, longitudinal optical axis shaking amplitude is obtained;
(6) line number is added 1, i.e. line number is 2;
(7) according to i.e. repeatable (1)~(6) of the second of y element, until reaching the last one value of y.
It is finally obtained that the results are shown in Figure 4.
Step 5, the result in time domain for having obtained the shaking of the camera optical axis at this time.When can be obtained according to the camera single stage integration time
Domain curve, as shown in Figure 5.
Step 6, Fourier transformation is carried out to above-mentioned time domain data, obtains the frequency domain characteristic of camera optical axis shaking.
To sum up, the above is merely preferred embodiments of the present invention, it is not intended to limit the scope of the present invention.It is all
Within the spirit and principles in the present invention, any modification, equivalent replacement, improvement and so on should be included in the protection of the present invention
Within the scope of.
Claims (1)
1. the appraisal procedure that a kind of micro-vibration influences in-orbit picture quality, which is characterized in that include the following steps:
Step (1) acquires in-orbit image, the basis in the in-orbit image using time delay integration image controller TDICCD
Evaluation requirement chooses the scenery that length runs through area-of-interest;
Step (2) extracts center pel point, organization center line line by line to the scenery region;
Step (3) is traversed each pixel point on center line, following step is performed both by for each pixel point centered on the center line
Suddenly (4)~step (5)
Step (4) is directed to current pixel point, in its left and right or the adjacent picture elements symmetrical above and below for choosing setting quantity, utilizes adjacent picture
The Energy distribution of member is fitted adjacent picture elements energy, the energy curve after being fitted;
Step (5) is directed to current pixel point, and the center of energy point for extracting the energy curve after the fitting of its adjacent picture elements energy is opposite
The distance of current pixel point, the distance are that the camera optical axis of current pixel point shakes amplitude;
The optical axis of all pixel points is shaken amplitude and connected to get the curve changed over time to the camera optical axis by step (6),
It is obtained according to the auxiliary data of TDICCD at the time of each pixel point corresponds in curve;
Step (7) carries out Fourier transformation to above-mentioned curve, and the frequency energy distribution curve of camera optical axis shaking can be obtained;
The optical axis for being more than setting numerical value in the energy distribution curve is shaken the corresponding decimation in frequency of amplitude and come out by step (8),
With the vibration frequency comparison in micro-vibration source on star, the contribution that the camera optical axis is shaken in micro-vibration source on each star is thus known.
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6084989A (en) * | 1996-11-15 | 2000-07-04 | Lockheed Martin Corporation | System and method for automatically determining the position of landmarks in digitized images derived from a satellite-based imaging system |
CN102013100A (en) * | 2010-11-26 | 2011-04-13 | 北京空间机电研究所 | Image quality discrimination method based on remote sensing image phase correlation |
CN102063558A (en) * | 2010-09-10 | 2011-05-18 | 航天东方红卫星有限公司 | Determination method of imaging condition of agile satellite |
CN102156990A (en) * | 2011-04-02 | 2011-08-17 | 北京理工大学 | Automatic identification method for blur parameters of TDI-CCD aerial remote sensing image |
CN103983343A (en) * | 2014-05-29 | 2014-08-13 | 武汉大学 | Satellite platform chattering detection method and system based on multispectral image |
Family Cites Families (1)
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US9396531B2 (en) * | 2013-12-23 | 2016-07-19 | Tufts University | Systems and methods for image and video signal measurement |
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- 2016-03-28 CN CN201610180605.2A patent/CN105787952B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6084989A (en) * | 1996-11-15 | 2000-07-04 | Lockheed Martin Corporation | System and method for automatically determining the position of landmarks in digitized images derived from a satellite-based imaging system |
CN102063558A (en) * | 2010-09-10 | 2011-05-18 | 航天东方红卫星有限公司 | Determination method of imaging condition of agile satellite |
CN102013100A (en) * | 2010-11-26 | 2011-04-13 | 北京空间机电研究所 | Image quality discrimination method based on remote sensing image phase correlation |
CN102156990A (en) * | 2011-04-02 | 2011-08-17 | 北京理工大学 | Automatic identification method for blur parameters of TDI-CCD aerial remote sensing image |
CN103983343A (en) * | 2014-05-29 | 2014-08-13 | 武汉大学 | Satellite platform chattering detection method and system based on multispectral image |
Non-Patent Citations (1)
Title |
---|
某遥感卫星平台的微振动试验研究;王泽宇等;《航天器环境工程》;20150630;第32卷(第3期);278-285 * |
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