CN103398799A - Fabry-Perot interference ring image processing method - Google Patents
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Abstract
The invention discloses a Fabry-Perot interference ring image processing method, and belongs to a processing method for a spectral measurement image. The method is used for converting a Fabry-Perot interference ring image into an accurate and low-noise Fabry-Perot interference spectral image. The method sequentially comprises a circle center coordinate determination step, a data folding step and a smoothing noise reduction step. In the data folding step, the information of all pixels on the Fabry-Perot interference ring image is fully utilized, not all distances between the pixels on a non-X' axis on the Fabry-Perot interference ring image and an origin O' are integers, so that the accuracy of the obtained Fabry-Perot interference spectral image reaches a sub-pixel level; and after the smoothing noise reduction step, the noise of the image is reduced, and the signal-to-noise ratio of the image is high.
Description
Technical field
The invention belongs to the disposal route of spectral measurement image, be specifically related to a kind of Fabry Perot interference circle image processing method, for by Fabry Perot interference circle image transitions, being accurate, low noise Fabry Perot Interferogram.
Background technology
The Brillouin scattering of laser is the important tool of measuring some physical parameters, and it has obtained application at optical fiber and atmosphere field.the Brillouin lidar system has been used Fabry Perot etalon and Intensified Charge Coupled Device (intensified charge-coupled device, ICCD), in recent years, the Brillouin lidar system has been applied to as ocean temperature, the measurement of some ocean wave parameters such as speed of sound, laser echo signal is by forming Fabry Perot interference annulus after the Fabry Perot etalon, by Intensified Charge Coupled Device, record Fabry Perot interference doughnut picture, Fabry Perot interference circle image is processed, obtain the Fabry Perot Interferogram, by the Fabry Perot Interferogram is processed, obtain Brillouin's frequency spectrum parameter, by these frequency spectrum parameters, calculated again the parameters such as temperature of seawater.
At present, Fabry Perot interference circle image is converted into to the Fabry Perot Interferogram and mainly contains two kinds of methods.A kind of is the method that directly reads, namely by a radius choosing the Fabry Perot interference pattern, directly measure Brillouin shift, this method is fairly simple, but utilize an integer pixel on radius to calculate, make the pixel outside this radius be not used on the one hand, this also makes the precision of the result of calculating can not reach sub-pix on the other hand; Another kind method is to utilize circle-line interferometer optics system and post lens method, the method is again by a reflection cone by the echoed signal by after the Fabry Perot etalon, reflected signal afterwards presents interference fringe on ICCD, but realize the optical device complexity of the method, can additionally introduce extra optical system noise, thereby its accuracy there is limitation.
Summary of the invention
The invention provides a kind of Fabry Perot interference circle image processing method, purpose is improve Fabry Perot interference circle image to the conversion accuracy of Fabry Perot Interferogram and reduce picture noise.
A kind of Fabry Perot interference circle image processing method provided by the present invention, order comprise determines central coordinate of circle step, the downhill race of the data folding step peace step of making an uproar, and it is characterized in that:
(1) determine the central coordinate of circle step, choose annulus in Fabry Perot interference circle image, by annulus centre coordinate in the human eye observability estimate, interior annulus is divided into again to upper and lower part and left and right part centered by it, calculate respectively the mean value of the maximum gradation value point respective coordinates of the mean value of maximum gradation value point respective coordinates of upper and lower part and left and right part, as annulus centre coordinate in actual;
(2) data folding step, set up coordinate system X ' O ' Y ' take annulus centre coordinate in described reality as initial point, and Fabry Perot interference circle image array is converted into to the secondary array in coordinate system X ' O ' Y '; Set up interference spectum image rectangular coordinate system XOY, by the element on non-X ' axle in described secondary array, by the X-axis coordinate of its distance to coordinate system X ' O ' Y ' initial point as interference spectum image rectangular coordinate system XOY, the value of corresponding element, as the Y-axis coordinate of interference spectum image rectangular coordinate system XOY, finally obtains elementary Fabry Perot Interferogram gray-scale value array Y1 (t);
(3) level and smooth noise reduction step, described elementary Fabry Perot Interferogram gray-scale value array Y1 (t) is carried out to Fast Fourier Transform (FFT), at Fourier by the noise contribution filtering of high frequency and carry out inverse transformation, obtain Fabry Perot Interferogram gray-scale value array Y2 (t) after filtering, by the final Fabry Perot Interferogram of Y2 (t) structure.
Described Fabry Perot interference circle image processing method is characterized in that:
(1) described definite central coordinate of circle step comprises following sub-step:
(1.1) by Fabry Perot interference circle image construction image array, in the image array, each element is the gray-scale value of Fabry Perot interference circle image respective pixel, and the capable sequence number of each element, row sequence number are respectively row-coordinate, the row coordinate of Fabry Perot interference circle image respective pixel;
(1.2) in eye-observation Fabry Perot interference circle image, whether having bright spot of view-field center, is to remove this bright spot of view-field center, rotor step (1.3), otherwise direct rotor step (1.3);
(1.3) human eye is chosen in Fabry Perot interference circle image and is connect paracentral interior annulus most, the estimation row-coordinate X at the human eye described interior circle ring center of estimation place
0, estimation row coordinate Y
0, then with this estimation row-coordinate X
0The center of classifying as at place, be divided into left and right two parts by the element in described image array;
(1.4) in Fabry Perot interference circle image, the described interior circle diameter D of human eye estimation, round and obtain n D/3, as statistics mid point number, from (Y described image array
0-n) row starts until (Y
0+ n) row, find out respectively in delegation two elements corresponding to maximum gradation value in left and right two parts array element, records the row at these two element places
Then calculate the row X at these two element mid point places
Oi ':
I=X
0-n～X
0+ n;
(1.5) calculate the row at described interior circle ring center place
(1.6) with estimation row coordinate Y
0The behavior center at place, be divided into up and down two parts by the element in this image array, from (X described image array
0-n) row start until (X
0+ n) row, find out respectively in row two elements corresponding to maximum gradation value in two parts array element of up and down, records the row at these two element places
Then calculate the capable Y at these two element mid point places
Oi ':
i＝Y
0-n～Y
0+n；
(1.7) calculate the row at described interior circle ring center place
Described
Be described interior annulus central coordinate of circle O ' (
);
(2) described data folding step comprises following sub-step:
(2.1) with interior annulus central coordinate of circle O ' (
) be initial point, X ' axle is transverse axis, and Y ' axle is the longitudinal axis, sets up rectangular coordinate system X ' O ' Y ', by the row-coordinate of each element in described image array, row coordinate respectively corresponding conversion be ordinate and the horizontal ordinate in rectangular coordinate system X ' O ' Y ', form the secondary image array;
(2.2) set up interference spectum image rectangular coordinate system XOY, its initial point O and described interior annulus central coordinate of circle O ' (
) overlap, X-axis represent in the secondary image array element to initial point O ' (
) distance, Y-axis represents in the secondary image array corresponding element value;
Calculate the element on all non-X ' axles in described secondary image array to initial point apart from d, it is mapped on X-axis, by different elements to initial point O ' (
) apart from the ascending arrangement of d, arrange sequence number t=0,1,2 ..., m-1, wherein m is for arranging total number of sequence number; Corresponding element value is mapped as to corresponding Y coordinate, for the identical a plurality of elements of d, calculate their mean value, be mapped as the Y coordinate, form elementary Fabry Perot Interferogram gray-scale value array Y1 (t), its arrangement of elements sequence number is t, and element value is the mean value of corresponding element value or element in described secondary image array;
(3) described level and smooth noise reduction step comprises following sub-step:
(3.1) described elementary Fabry Perot Interferogram gray-scale value array Y1 (t) is carried out to the fast discrete Fourier conversion, obtain array
Element sequence number k=0,1,2 ..., h-1, wherein, h is array
Total number of middle element;
(3.2) find and make
Smallest positive integral i, and make array
In, its element sequence number is eligible: the element value of i<k<h-i-1 is set to zero, obtains the noise reduction array
(3.3) to the noise reduction array
Carry out discrete inversefouriertransform, obtain Fabry Perot Interferogram gray-scale value array Y2 (t) after filtering, its arrangement of elements sequence number is t;
In described interference spectum image rectangular coordinate system XOY, t is corresponding apart from d according to the arrangement of elements sequence number, using each element of Fabry Perot Interferogram gray-scale value array Y2 (t) after described filtering as corresponding Y coordinate, obtain final Fabry Perot interference spectrum picture.
The present invention includes and determine central coordinate of circle step, the downhill race of the data folding step peace step of making an uproar, in the data folding step, take full advantage of the information of all pixels on Fabry Perot interference circle image, pixel on Fabry Perot interference circle image on non-X ' axle is not positive integer to the distance of initial point O ' entirely, resulting Fabry Perot Interferogram precision has reached sub-pix, after level and smooth noise reduction step, reduce picture noise, signal noise ratio (snr) of image is high.
The accompanying drawing explanation
Fig. 1 is schematic flow sheet of the present invention;
Fig. 2 is the Fabry Perot interference circle image that ICCD photographs;
Fig. 3 is for determining interference circle central step schematic diagram;
Fig. 4 is data folding step schematic diagram;
Fig. 5 is the Fabry Perot interference spectum that obtains after data fold;
The smooth spectrum of Fig. 6 for obtaining after level and smooth by Fast Fourier Transform (FFT) low pass noise reduction;
Fig. 7 is Fabry Perot interference circle pattern schematic diagram.
Embodiment
The present invention is further described below in conjunction with drawings and Examples.
As shown in Figure 1, the embodiment of the present invention sequentially comprises and determines central coordinate of circle step, the downhill race of the data folding step peace step of making an uproar.
(1) determine the central coordinate of circle step, comprise following sub-step:
(1.1) by Fabry Perot interference circle image construction image array shown in Figure 2, in the image array, each element is the gray-scale value of Fabry Perot interference circle image respective pixel, and the capable sequence number of each element, row sequence number are respectively row-coordinate, the row coordinate of Fabry Perot interference circle image respective pixel;
(1.2) in eye-observation Fabry Perot interference circle image, whether having bright spot of view-field center, is to remove this bright spot of view-field center, rotor step (1.3), otherwise direct rotor step (1.3);
(1.3) human eye is chosen in Fabry Perot interference circle image and is connect paracentral interior annulus (annulus of the white arrow indication on Fig. 2) most, the estimation row-coordinate X at the human eye described interior circle ring center of estimation place
0, estimation row coordinate Y
0, then with this estimation row-coordinate X
0The center of classifying as at place, be divided into left and right two parts by the element in described image array, as shown in Figure 3;
(1.4) in Fabry Perot interference circle image, the described interior circle diameter D of human eye estimation, round and obtain n D/3, as statistics mid point number, from (Y described image array
0-n) row starts until (Y
0+ n) row, find out respectively in delegation two elements corresponding to maximum gradation value in left and right two parts array element, records the row at these two element places
Then calculate the row X at these two element mid point places
Oi ':
I=X
0-n～X
0+ n;
(1.5) calculate the row at described interior circle ring center place
(1.6) with estimation row coordinate Y
0The behavior center at place, be divided into up and down two parts by the element in this image array, from (X described image array
0-n) row start until (X
0+ n) row, find out respectively in row two elements corresponding to maximum gradation value in two parts array element of up and down, records the row at these two element places
Then calculate the capable Y at these two element mid point places
Oi ':
i＝Y
0-n～Y
0+n；
(1.7) calculate the row at described interior circle ring center place
Described
Be described interior annulus central coordinate of circle O ' (
);
(2) data folding step comprises following sub-step:
(2.1) as shown in Figure 4, with interior annulus central coordinate of circle O ' (
) be initial point, X ' axle is transverse axis, and Y ' axle is the longitudinal axis, sets up rectangular coordinate system X ' O ' Y ', by the row-coordinate of each element in described image array, row coordinate respectively corresponding conversion be ordinate and the horizontal ordinate in rectangular coordinate system X ' O ' Y ', form the secondary image array;
(2.2) set up interference spectum image rectangular coordinate system XOY, its initial point O and described interior annulus central coordinate of circle O ' (
) overlap, X-axis represent in the secondary image array element to initial point O ' (
) distance, Y-axis represents in the secondary image array corresponding element value;
Calculate the element on all non-X ' axles in described secondary image array to initial point apart from d, it is mapped on X-axis, by different elements to initial point O ' (
) apart from the ascending arrangement of d, arrange sequence number t=0,1,2 ..., m-1, wherein m is for arranging total number of sequence number; Corresponding element value is mapped as to corresponding Y coordinate, for the identical a plurality of elements of d, calculates their mean value, be mapped as the Y coordinate, obtain elementary Fabry Perot Interferogram, as shown in Figure 5; And form elementary Fabry Perot Interferogram gray-scale value array Y1 (t), and its arrangement of elements sequence number is t, element value is the mean value of corresponding element value or element in described secondary image array;
(3) level and smooth noise reduction step comprises following sub-step:
(3.1) described elementary Fabry Perot Interferogram gray-scale value array Y1 (t) is carried out to the fast discrete Fourier conversion, obtain array
Element sequence number k=0,1,2 ..., h-1, wherein, h is array
Total number of middle element;
(3.2) find and make
Smallest positive integral i, and make array
In, its element sequence number is eligible: the element value of i<k<h-i-1 is set to zero, obtains the noise reduction array
(3.3) to the noise reduction array
Carry out discrete inversefouriertransform, obtain Fabry Perot Interferogram gray-scale value array Y2 (t) after filtering, its arrangement of elements sequence number is t;
In described interference spectum image rectangular coordinate system XOY, t is corresponding apart from d according to the arrangement of elements sequence number, using each element of Fabry Perot Interferogram gray-scale value array Y2 (t) after described filtering as corresponding Y coordinate, obtain final Fabry Perot interference spectrum picture, as shown in Figure 6.
In the temperature measuring application of reality, at first by the Fabry Perot interference spectum, calculate Brillouin shift, and then obtain temperature by the Brillouin shift inverting.
Brillouin shift v
BBy following formula, calculated:
Wherein, FSR is the Free Spectral Range of Fabry Perot etalon, according to the selected concrete model of Fabry Perot etalon, determines r
1, r
1', r
2, r
2' be respectively from the inside to the outside the radius of annulus in adjacent four annulus in the Fabry Perot interference spectrum, as shown in Figure 7.
The temperature retrieval formula is as follows:
T(S，v
B)＝t
0+t
1(v
B-7.5)+t
2(v
B-7.5)
2+t
3(v
B-7.5)
3+t
4(v
B-7.5)
6+
S(t
5+t
6(v
B-7.5)+t
7(v
B-7.5)
2+t
8(v
B-7.5)
3)；
Wherein, t
j(j=0,1 ..., 8) be design factor, wherein, t0=23.5, t1=65.5, t2=75, t3=252, t4=1100, t5=-0.402, t6=-0.287, t7=-0.902, t8=-5.5, in the situation that salinity S is known, can calculate temperature according to Brillouin shift.
In order to verify effect of the present invention, in the pure water (salinity is zero) of different temperatures, done 3 experiments, obtain result as shown in table 1.In table, temperature data directly reads method by the present invention and tradition respectively and obtains by the said temperature inversion formula.
Table 1
As can be seen from Table 1, with adopting the result that directly reads the method measurement, compare, the result that the present invention obtains is more near actual value.
Claims (2)
1. Fabry Perot interference circle image processing method, order comprise determines central coordinate of circle step, the downhill race of the data folding step peace step of making an uproar, and it is characterized in that:
(1) determine the central coordinate of circle step, choose annulus in Fabry Perot interference circle image, by annulus centre coordinate in the human eye observability estimate, interior annulus is divided into again to upper and lower part and left and right part centered by it, calculate respectively the mean value of the maximum gradation value point respective coordinates of the mean value of maximum gradation value point respective coordinates of upper and lower part and left and right part, as annulus centre coordinate in actual;
(2) data folding step, set up coordinate system X ' O ' Y ' take annulus centre coordinate in described reality as initial point, and Fabry Perot interference circle image array is converted into to the secondary array in coordinate system X ' O ' Y '; Set up interference spectum image rectangular coordinate system XOY, by the element on non-X ' axle in described secondary array, by the X-axis coordinate of its distance to coordinate system X ' O ' Y ' initial point as interference spectum image rectangular coordinate system XOY, the gray-scale value of corresponding element, as the Y-axis coordinate of interference spectum image rectangular coordinate system XOY, finally obtains elementary Fabry Perot Interferogram gray-scale value array Y1 (t);
(3) level and smooth noise reduction step, described elementary Fabry Perot Interferogram gray-scale value array Y1 (t) is carried out to Fast Fourier Transform (FFT), at Fourier by the noise contribution filtering of high frequency and carry out inverse transformation, obtain Fabry Perot Interferogram gray-scale value array Y2 (t) after filtering, by the final Fabry Perot Interferogram of Y2 (t) structure.
2. Fabry Perot interference circle image processing method as claimed in claim 1 is characterized in that:
(1) described definite central coordinate of circle step comprises following sub-step:
(1.1) by Fabry Perot interference circle image construction image array, in the image array, each element is the gray-scale value of Fabry Perot interference circle image respective pixel, and the capable sequence number of each element, row sequence number are respectively row-coordinate, the row coordinate of Fabry Perot interference circle image respective pixel;
(1.2) in eye-observation Fabry Perot interference circle image, whether having bright spot of view-field center, is to remove this bright spot of view-field center, rotor step (1.3), otherwise direct rotor step (1.3);
(1.3) human eye is chosen in Fabry Perot interference circle image and is connect paracentral interior annulus most, the estimation row-coordinate X at the human eye described interior circle ring center of estimation place
0, estimation row coordinate Y
0, then with this estimation row-coordinate X
0The center of classifying as at place, be divided into left and right two parts by the element in described image array;
(1.4) in Fabry Perot interference circle image, the described interior circle diameter D of human eye estimation, round and obtain n D/3, as statistics mid point number, from (Y described image array
0-n) row starts until (Y
0+ n) row, find out respectively in delegation two elements corresponding to maximum gradation value in left and right two parts array element, records the row at these two element places
Then calculate the row X at these two element mid point places
Oi ':
I=X
0-n～X
0+ n;
(1.5) calculate the row at described interior circle ring center place
(1.6) with estimation row coordinate Y
0The behavior center at place, be divided into up and down two parts by the element in this image array, from (X described image array
0-n) row start until (X
0+ n) row, find out respectively in row two elements corresponding to maximum gradation value in two parts array element of up and down, records the row at these two element places
Then calculate the capable Y at these two element mid point places
Oi ':
i＝Y
0-n～Y
0+n；
(1.7) calculate the row at described interior circle ring center place
Described
Be described interior annulus central coordinate of circle O ' (
);
(2) described data folding step comprises following sub-step:
(2.1) with interior annulus central coordinate of circle O ' (
) be initial point, X ' axle is transverse axis, and Y ' axle is the longitudinal axis, sets up rectangular coordinate system X ' O ' Y ', by the row-coordinate of each element in described image array, row coordinate respectively corresponding conversion be ordinate and the horizontal ordinate in rectangular coordinate system X ' O ' Y ', form the secondary image array;
(2.2) set up interference spectum image rectangular coordinate system XOY, its initial point O and described interior annulus central coordinate of circle O ' (
) overlap, X-axis represent in the secondary image array element to initial point O ' (
) distance, Y-axis represents in the secondary image array corresponding element value;
Calculate the element on all non-X ' axles in described secondary image array to initial point apart from d, it is mapped on X-axis, by different elements to initial point O ' (
) apart from the ascending arrangement of d, arrange sequence number t=0,1,2 ..., m-1, wherein m is for arranging total number of sequence number; Corresponding element value is mapped as to corresponding Y coordinate, for the identical a plurality of elements of d, calculate their mean value, be mapped as the Y coordinate, form elementary Fabry Perot Interferogram gray-scale value array Y1 (t), its arrangement of elements sequence number is t, and element value is the mean value of corresponding element value or element in described secondary image array;
(3) described level and smooth noise reduction step comprises following sub-step:
(3.1) described elementary Fabry Perot Interferogram gray-scale value array Y1 (t) is carried out to the fast discrete Fourier conversion, obtain array
Element sequence number k=0,1,2 ..., h-1, wherein, h is array
Total number of middle element;
(3.2) find and make
Smallest positive integral i, and make array
In, its element sequence number is eligible: the element value of i<k<h-i-1 is set to zero, obtains the noise reduction array
(3.3) to the noise reduction array
Carry out discrete inversefouriertransform, obtain Fabry Perot Interferogram gray-scale value array Y2 (t) after filtering, its arrangement of elements sequence number is t;
In described interference spectum image rectangular coordinate system XOY, t is corresponding apart from d according to the arrangement of elements sequence number, using each element of Fabry Perot Interferogram gray-scale value array Y2 (t) after described filtering as corresponding Y coordinate, obtain final Fabry Perot interference spectrum picture.
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| WO2016173382A1 (en) * | 2015-04-30 | 2016-11-03 | 清华大学 | Method for measuring focal length and rotating angle using fabry-perot etalon |
| CN107144224A (en) * | 2017-06-16 | 2017-09-08 | 中国计量大学 | A kind of use F P etalons measure the apparatus and method of two-dimensional micro-displacement |
| CN114627178A (en) * | 2022-02-23 | 2022-06-14 | 武汉大学 | Method for automatically determining circle center and radius of Fabry-Perot interference ring |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2016173382A1 (en) * | 2015-04-30 | 2016-11-03 | 清华大学 | Method for measuring focal length and rotating angle using fabry-perot etalon |
| CN106092515A (en) * | 2015-04-30 | 2016-11-09 | 清华大学 | A kind of Fabry-Perot etalon focal length measurement and the method for corner |
| CN106092515B (en) * | 2015-04-30 | 2019-09-20 | 清华大学 | A method of with Fabry-Perot etalon focal length measurement and corner |
| CN107144224A (en) * | 2017-06-16 | 2017-09-08 | 中国计量大学 | A kind of use F P etalons measure the apparatus and method of two-dimensional micro-displacement |
| CN107144224B (en) * | 2017-06-16 | 2019-04-16 | 中国计量大学 | A kind of apparatus and method with F-P etalon measurement two-dimensional micro-displacement |
| CN114627178A (en) * | 2022-02-23 | 2022-06-14 | 武汉大学 | Method for automatically determining circle center and radius of Fabry-Perot interference ring |
| CN114627178B (en) * | 2022-02-23 | 2024-04-02 | 武汉大学 | Method for automatically determining center and radius of Fabry-Perot interference ring |
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