CN108154479A - A kind of method that remote sensing images are carried out with image rectification - Google Patents
A kind of method that remote sensing images are carried out with image rectification Download PDFInfo
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Abstract
The present invention provides a kind of method that remote sensing images are carried out with image rectification, including：Obtain the remote sensing images I captured by the satellite for carrying CCD camera0And its image parameter, and obtain and shoot the satellite of the remote sensing images and the parameter of CCD camera；Radiant correction is carried out to image：The grey value difference between odd even column data is counted, removal odd even pixel is poor；Aberration between ccd array is removed, the remote sensing images I that finally obtains that treated1.A kind of method that remote sensing images are carried out with image rectification of the present invention, picture quality can be efficiently modified, effectively removed the aberration in fringes noise and piece between piece, image relative detector calibration precision is improved, and can obtain complete, accurate, objective inspection to image rectification effect.
Description
Technical field
The present invention relates to field of remote sensing image processing, and in particular, to a kind of side that remote sensing images are carried out with image rectification
Method.
Background technology
Remote sensing images due to by imaging mode, photoelectric cell performance and imaging when environmental parameter (such as temperature) influence,
The often existing defects in terms of radiation quality and almost T-stable, aberration, Banded improvement for example there is image.Aberration and band are made an uproar
Sound there are problems that so that remote sensing images exist in qualitative and quantitative use, in qualitatively remote Sensing Interpretation and interpretation, color
Difference and Banded improvement seriously affect identification and extraction of the operating personnel to type of ground objects；In various remote sensing quantitative inversions, band
Noise can cause to distort to radiation information, the quantitative target of this degreeof tortuosity can be objectively responded due to lacking, to inverting
As a result influence just can not be assessed.Simultaneously as the way of output of some CCD devices is exported for sequence of parity, to sequence of parity
Processing respectively inevitably introduce the inconsistency of parity signal, this also has the generation of the banding of image data
Certain influence.In addition, when each CCD or a piece of CCD is exported by different electronic links in device, each can be equally introduced
The inconsistency of signal between piece, the response nonuniformity between image data piece affect.
Due to the influence of various factors, when having resulted in camera identical atural object being imaged, different detections
Member may export different DN values so that the image fault of generation.This is it is difficult to be avoided in Satellite Payloads manufacture production.
Therefore, relative detector calibration is normalized to raw image data in Ground Data Processing System, eliminates the distortion of original image,
Restore true cartographic feature, the original DN values for obtaining image to each detection member are adjusted correction, by each detection member
Output valve is adjusted on same benchmark so that each detection member has identical output DN values to identical atural object.Only
Image after relative detector calibration, the image of different payload detection member generation just has comparativity, homogeneity, whole
Scape image is just consistent, and is only the true picture of reflection atural object.On the other hand, relative detector calibration is to be based on effectively carrying on star
Lotus imaging basis on, be on star payload be imaged it is perfect.
At present, various disappear on band algorithm, and offset band is nearly all concentrated on to the research of Banded improvement both at home and abroad
The evaluation of effect also more is limited to qualitatively visual comparison or based between gradation of image mean value, variance, clarity, quality factor etc.
It connects index and carries out quantitative assessment.There is researcher to propose that a kind of method of " visiting first coincident indicator " carrys out quantitative assessment band and makes an uproar recently
Sound, but the principle without describing this method, and the Banded improvement severity of index description can be with stretching in some cases
Image afterwards generates the phenomenon that inconsistent.Existing image processing method existing defects, there are still apparent after image procossing
Phenomena such as striped or aberration.It is therefore desirable to which the image for passing through relative detector calibration is further processed, to obtain
The higher image of quality, preferably meets user demand.Meanwhile for the treatment effect of the remote sensing images after image procossing
It examines, the test rating that existing method uses is excessive or very few, index does not have versatility or index cannot very imperfectly
Summarize the aspect to be examined, cause test effect inaccurate.
Invention content
Recognized based on above-mentioned background how the relative detector calibration of image rectification, particularly CCD camera is changed
Into being the key point for breaking through existing remote sensing image processing bottleneck.
Technological deficiency based on this field, the present invention provides it is a kind of to remote sensing images carry out image rectification method,
It is characterized in that, includes the following steps：
Step 1, the remote sensing images I captured by the satellite for carrying CCD camera is obtained0And its image parameter, and obtain shooting
The satellite of the remote sensing images and the parameter of CCD camera；
Step 2, the gain coefficient of relative calibration coefficient is filtered, obtains improved calibration coefficient model；
Step 3, relative detector calibration is carried out to image using the improved calibration coefficient model, eliminates tiny striped and make an uproar
Sound：
Step 4, after relative detector calibration in image data, the grey value difference between odd even column data is counted, by this
Grey value difference is respectively overlay in again on odd even column data, and removal odd even pixel is poor；
Step 5, the luminance difference of intermediate ccd array subgraph and left and right piece ccd array subgraph is obtained using image statistics,
That is the fluctuating of left and right ccd array bottom level compensates the deviant of left and right ccd array with the fluctuating, removes CCD gusts of three pieces
Aberration between row, the remote sensing images I that finally obtains that treated1；
Step 6, it obtains and treated remote sensing images I is carried out to original remote sensing images1And its image parameter；
Step 7, image rectification testing model is established, is tested to the image rectification effect of remote sensing images.
Preferably, the step 2 is filtered the gain coefficient of relative calibration coefficient, the filter function of use
For low-pass filter, the high frequency section of data is filtered out, and the low frequency part of retention data.
Preferably, the cutoff frequency of the low-pass filter is 1 to the two/10ths 1/10th of highest frequency.
Preferably, the step 2 is filtered the gain coefficient of relative calibration coefficient, and filtering algorithm selection is high
The curve of number is fitted.
Preferably, the filtering algorithm includes one of wavelet filtering, Wiener filtering, Kalman filtering.
Preferably, the step 4 after relative detector calibration in image data, counts the gray scale between odd even column data
Value difference is different, which is respectively overlay in again on odd even column data, and removal odd even pixel is poor, specially：Odd column and
Even column regards an entirety as respectively, and odd column and even column are then carried out Histogram Matching respectively, respectively obtain different tonal gradations
Then the deviant is added separately in odd column data and even column data by the deviant that should be added and subtracted down.
Preferably, the step 5 is specially：
A, B, C is enabled to represent left, middle and right linear array of ccd array respectively, and sub-image area a, b1 are represented as a left side
The adjacent part of piece linear array and middle linear array；Sub-image area b2, c are the adjacent part of middle linear array and right linear array, to four
A subgraph a, b1, b2, c carry out statistics with histogram respectively, histogram low side and high-end each 20% data are removed, to centre
60% data ask for mean value, are set as a, b1, b2, c, then Δ a, and Δ c is that left and right piece linear array needs the DN values compensated, Δ a, Δ
C is calculated respectively by following formula：Δ a=b1-a, Δ c=b2-c.
The present invention solves directly carries out real image opposite spoke using by the relative calibration coefficient that calibration data obtain
Penetrate some problems being still had after correction, such as odd even pixel difference, fringes noise, aberration.Utilize the technical side of the present invention
Case can be efficiently modified picture quality, be effectively removed the aberration in fringes noise and piece between piece, image relative radiation
Correction accuracy is improved, and can obtain complete, accurate, objective inspection to image rectification effect.
Description of the drawings
Method flow diagram proposed by the invention Fig. 1.
Specific embodiment
For a better understanding of the present invention, with reference to the description of the embodiment of the accompanying drawings, the method for the present invention is carried out
Further instruction.
In order to fully understand the present invention, numerous details are referred in the following detailed description.But art technology
Personnel are it should be understood that the present invention may not need these details and realize.In embodiment, it is not described in detail well known side
Method, process, component, circuit, in order to avoid unnecessarily make embodiment cumbersome.
A kind of method that remote sensing images are carried out with image rectification shown in Figure 1, proposed by the invention, feature exist
In including the following steps：
Step 1, the remote sensing images I captured by the satellite for carrying CCD camera is obtained0And its image parameter, and obtain shooting
The satellite of the remote sensing images and the parameter of CCD camera；
Step 2, the gain coefficient of relative calibration coefficient is filtered, obtains improved calibration coefficient model；
Step 3, relative detector calibration is carried out to image using the improved calibration coefficient model, eliminates tiny striped and make an uproar
Sound：
Step 4, after relative detector calibration in image data, the grey value difference between odd even column data is counted, by this
Grey value difference is respectively overlay in again on odd even column data, and removal odd even pixel is poor；
Step 5, the luminance difference of intermediate ccd array subgraph and left and right piece ccd array subgraph is obtained using image statistics,
That is the fluctuating of left and right ccd array bottom level compensates the deviant of left and right ccd array with the fluctuating, removes CCD gusts of three pieces
Aberration between row, the remote sensing images I that finally obtains that treated1；
Step 6, it obtains and treated remote sensing images I is carried out to original remote sensing images1And its image parameter；
Step 7, image rectification testing model is established, is tested to the image rectification effect of remote sensing images.
Preferably, the step 2 is filtered the gain coefficient of relative calibration coefficient, the filter function of use
For low-pass filter, the high frequency section of data is filtered out, and the low frequency part of retention data.
Preferably, the cutoff frequency of the low-pass filter is 1 to the two/10ths 1/10th of highest frequency.
Preferably, the step 2 is filtered the gain coefficient of relative calibration coefficient, and filtering algorithm selection is high
The curve of number is fitted.
Preferably, the filtering algorithm includes one of wavelet filtering, Wiener filtering, Kalman filtering.
Preferably, the step 4 after relative detector calibration in image data, counts the gray scale between odd even column data
Value difference is different, which is respectively overlay in again on odd even column data, and removal odd even pixel is poor, specially：Odd column and
Even column regards an entirety as respectively, and odd column and even column are then carried out Histogram Matching respectively, respectively obtain different tonal gradations
Then the deviant is added separately in odd column data and even column data by the deviant that should be added and subtracted down.
Preferably, the step 5 is specially：
A, B, C is enabled to represent left, middle and right linear array of ccd array respectively, and sub-image area a, b1 are represented as a left side
The adjacent part of piece linear array and middle linear array；Sub-image area b2, c are the adjacent part of middle linear array and right linear array, to four
A subgraph a, b1, b2, c carry out statistics with histogram respectively, histogram low side and high-end each 20% data are removed, to centre
60% data ask for mean value, are set as a, b1, b2, c, then Δ a, and Δ c is that left and right piece linear array needs the DN values compensated, Δ a, Δ
C is calculated respectively by following formula：Δ a=b1-a, Δ c=b2-c.
Preferably, wherein, the step 1 obtains the satellite of the shooting remote sensing images and the parameter of CCD camera,
The satellite parametric reduction includes：Satellite designation, pointing accuracy, orbit altitude, panchromatic resolution ratio, multispectral resolution rate,
It is imaged breadth；
The CCD camera parameter includes：Camera title, focal length, f-number, pixel, items MTF parameters.
Preferably, it wherein, handles further including image gray processing.
Preferably, wherein, the I of acquisition0, I1Image parameter include resolution ratio.
Preferably, wherein, the step 7 establishes image rectification testing model, further includes and calculates remote sensing images correction inspection
Index, the index includes：Signal-to-noise ratio index, MTF indexs, information content index, dependent degeneration degree index.
Preferably, wherein, the signal-to-noise ratio index S/N is specially：
Wherein, f is camera focus, and F is camera aperture value, and B is the radiance of camera inlet, τopticsFor optical system
Unite transmitance, η be optical system cover bar ratio, NtdiSeries, t are integrated for TDICCDintFor TDICCD row integration periods, RCCDFor CCD
Responsiveness, PefFor camera valid pixel, Nshot、Ndark、Nread、NFPNThere are shots in respectively CCD and signal processing circuit to make an uproar
Sound, reads noise, fixed pattern noise at dark current noise.
Preferably, wherein, MTF is system modulation transmission function, and the MTF indexs are specially：
MTF=MTFIt is static·MTFDynamically
MTFIt is static=MTFOptical design·MTFOptical manufacturing·MTFOptics adjustment·MTFCCD device·MTFCircuit
Wherein, N is TDICCD integration series, and Δ p is improper as shifting amount, fNormalizationIt is normalized spatial frequency.
Preferably, wherein, described information content's index C is specially：
Wherein, the gray scale value set of each pixel i is { S in imagei, i=1,2 ..., n }, correspond to the probability occurred
For { Ai, i=1,2 ..., n }, W is imaging breadth；
Preferably, wherein, after dependent degeneration degree refers to image procossing, compared with original remote sensing images, picture quality is moved back
The degree of change, the dependent degeneration degree index RL are specially：
Wherein, S0、S1The gray value of pixel in respectively original remote sensing images and treated remote sensing images,
The mean value of pixel gray value in respectively original remote sensing images and treated remote sensing images, the ash of each pixel i in image
Angle value collection is combined into { Si, i=1,2 ..., n }, R0And R1The resolution of respectively original remote sensing images and treated remote sensing images
Rate.
Preferably, wherein, the step 7, image rectification testing model is specially：
Wherein, wiFor quality inspection parameters weighting input by user, ∑ wi=1,For quality inspection parameters weighting wi
Fitting function, as the coefficient of quality inspection model indices, IQT scoring output areas are 0-100 points, wherein 100 points
Most satisfied for picture quality, 0 point least satisfied for picture quality, preferably using substar high quality graphic as 100 points with reference to mark
It is accurate.
As it can be seen that a kind of method that remote sensing images are carried out with image rectification of the present invention, can be efficiently modified picture quality, make
Aberration in fringes noise and piece between piece is effectively removed, and image relative detector calibration precision is improved, and can be with
Complete, accurate, objective inspection is obtained to image rectification effect.
Here the preferred embodiment of the present invention is only illustrated, but its meaning is not intended to limit the scope of the invention, applicability and is matched
It puts.On the contrary, detailed explanation of the embodiments can be implemented by those skilled in the art.It will be understood that without departing from appended power
In the case of the spirit and scope of the invention that sharp claim determines, changes and modifications may be made to details.
Claims (7)
- A kind of 1. method that remote sensing images are carried out with image rectification, which is characterized in that include the following steps：Step 1, the remote sensing images I captured by the satellite for carrying CCD camera is obtained0And its image parameter, and it is described distant to obtain shooting Feel the satellite of image and the parameter of CCD camera；Step 2, the gain coefficient of relative calibration coefficient is filtered, obtains improved calibration coefficient model；Step 3, relative detector calibration is carried out to image using the improved calibration coefficient model, eliminates fine stripe noise：Step 4, after relative detector calibration in image data, the grey value difference between odd even column data is counted, by the gray scale Value difference is different to be respectively overlay in again on odd even column data, and removal odd even pixel is poor；Step 5, the luminance difference of intermediate ccd array subgraph and left and right piece ccd array subgraph is obtained using image statistics, i.e., it is left The fluctuating of right ccd array bottom level compensates the deviant of left and right ccd array with the fluctuating, removal three pieces ccd array it Between aberration, the remote sensing images I that finally obtains that treated1；Step 6, it obtains and treated remote sensing images I is carried out to original remote sensing images1And its image parameter；Step 7, image rectification testing model is established, is tested to the image rectification effect of remote sensing images.
- 2. the method for claim 1, wherein step 2 is filtered place to the gain coefficient of relative calibration coefficient Reason, the filter function used filters out the high frequency section of data for low-pass filter, and the low frequency part of retention data.
- 3. method as claimed in claim 2, wherein, the cutoff frequency of the low-pass filter is 1/10th of highest frequency To 1/20th.
- 4. the method for claim 1, wherein step 2 is filtered place to the gain coefficient of relative calibration coefficient Reason, the curve of filtering algorithm selection high reps are fitted.
- 5. method as claimed in claim 4, wherein, the filtering algorithm includes wavelet filtering, Wiener filtering, Kalman filtering One of.
- 6. the method for claim 1, wherein step 4, after relative detector calibration in image data, statistics is strange The grey value difference is respectively overlay on odd even column data by the grey value difference between even column data again, removes odd even pixel Difference, specially：Odd column and even column are regarded as an entirety respectively, odd column and even column are then subjected to Histogram Matching respectively, point The deviant that should be added and subtracted under different tonal gradations is not obtained, and the deviant is then added separately to odd column data and even column data On.
- 7. the method for claim 1, wherein the step 5 is specially：A, B, C is enabled to represent left, middle and right linear array of ccd array respectively, and sub-image area a, b1 are represented as left line The adjacent part of battle array and middle linear array；Sub-image area b2, c are the adjacent part of middle linear array and right linear array, to four sons Image a, b1, b2, c carry out statistics with histogram respectively, remove histogram low side and high-end each 20% data, to centre 60% Data ask for mean value, are set as a, b1, b2, c, then Δ a, and Δ c is the DN values that left and right piece linear array needs compensate, and Δ a, Δ c distinguish It is calculated by following formula：Δ a=b1-a, Δ c=b2-c.
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| CN111639543A (en) * | 2020-04-26 | 2020-09-08 | 山东科技大学 | Hyperspectral remote sensing image wetland classification method based on Markov random field |
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| CN110580692B (en) * | 2019-09-11 | 2022-03-25 | 北京空间飞行器总体设计部 | Method for correcting radiation consistency of multi-line time difference scanning image |
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| CN111145118A (en) * | 2019-12-24 | 2020-05-12 | 国家卫星气象中心(国家空间天气监测预警中心) | Remote sensing image stripe removing method and device |
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| CN111639543A (en) * | 2020-04-26 | 2020-09-08 | 山东科技大学 | Hyperspectral remote sensing image wetland classification method based on Markov random field |
| CN112001263A (en) * | 2020-07-28 | 2020-11-27 | 国家卫星气象中心(国家空间天气监测预警中心) | Method and system for selecting reference probe element of linear array scanning remote sensor |
| CN112001263B (en) * | 2020-07-28 | 2024-02-09 | 国家卫星气象中心(国家空间天气监测预警中心) | Method and system for selecting reference probe of linear array scanning remote sensor |
| CN112529807B (en) * | 2020-12-15 | 2022-11-08 | 北京道达天际科技股份有限公司 | Relative radiation correction method and device for satellite image |
| CN112529807A (en) * | 2020-12-15 | 2021-03-19 | 北京道达天际科技有限公司 | Relative radiation correction method and device for satellite image |
| CN112954239A (en) * | 2021-01-29 | 2021-06-11 | 中国科学院长春光学精密机械与物理研究所 | On-board CMOS image dust pollution removal and recovery system and recovery method |
| CN113487547B (en) * | 2021-06-24 | 2023-08-15 | 北京市遥感信息研究所 | Satellite remote sensing image stripe noise positioning method and device |
| CN113487547A (en) * | 2021-06-24 | 2021-10-08 | 北京市遥感信息研究所 | Satellite remote sensing image strip noise positioning method and device |
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| CN114567722B (en) * | 2021-12-20 | 2024-02-20 | 北京空间机电研究所 | Method, device, equipment and medium for quickly synthesizing moving image |
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| CN114596416A (en) * | 2022-05-07 | 2022-06-07 | 武汉天际航信息科技股份有限公司 | Three-dimensional ground object model repairing method, system, equipment and storage medium |
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