CN110988908B - Quantitative analysis method for imaging influence of spectral shift of optical filter on space optical remote sensor - Google Patents
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Abstract
A quantitative analysis method of the imaging influence of optical filter spectral shift on a space optical remote sensor relates to the technical field of optical remote sensing, and the method comprises the following steps: designing or acquiring spectral characteristic parameters of spectral range, center wavelength and bandwidth of each spectral range of the space optical remote sensor; acquiring a surface reflectivity curve of a typical object; calculating equivalent reflectivities of different typical features in the spectral bandwidth range of each spectral band of the space optical remote sensor according to the optical characteristic parameters of each spectral band of the space optical remote sensor and the surface reflectivity curve of the typical features; simulating solar radiance at the entrance pupil of the space optical remote sensor corresponding to different typical object equivalent reflectivities under typical illumination conditions by using an atmospheric radiation transmission model; calculating an image gray value according to the solar radiation brightness and the space optical remote sensor radiation conversion model; and shifting the center wavelength or bandwidth of each spectrum of the space optical remote sensor, and calculating the corresponding image gray response deviation of different ground objects.
Description
Technical Field
The patent relates to the technical field of optical remote sensing, in particular to a quantitative analysis method for imaging influence of spectral shift of an optical filter on a space optical remote sensor.
Background
The imaging process of the space optical remote sensor is to convert input radiation into image output, and DN value of the image is the result of the combined action of the optical system, the optical filter, the focal plane detector and the input radiation. The optical filter is used as a key device in a remote sensing image imaging link and plays a role of band filtering, and the spectral response performance of the remote sensing imaging system is directly affected.
In practical engineering applications, the filtering type of the optical filter is generally realized through coating, however, based on the current coating technology, errors exist between the spectral characteristics of the optical filter and the design value thereof in actual processing. Therefore, how to determine a reasonable error range so as to ensure that the requirements of spectral performance of remote sensor imaging can be met, and simultaneously, the processing difficulty and cost of the optical filter can be reduced as much as possible, which is an unavoidable technical problem in the development process of a remote sensor imaging system.
Currently, in the performance analysis of a space optical remote sensing imaging system, a clear quantitative relation is difficult to establish between the performance indexes of each link of an imaging link and the final image radiation quality, and researches on the spectral characteristics of an optical filter of a space optical remote sensor are concentrated on the aspects of a design method and development technical means of the optical filter, testing, analyzing and checking the spectral characteristics of the existing optical filter, and the like. In practical engineering application, after the spectral band design of the optical filter is completed, how to determine the film plating technical requirement of the optical filter and how to quantitatively analyze the influence of the spectral characteristic deviation of the optical filter on the imaging of the remote sensor is not a standard or literature basis for reference.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a quantitative analysis method for the imaging influence of spectral shift of an optical filter on a space optical remote sensor, solves the problem of error distribution of spectral characteristics of the optical filter in the design stage of the space optical remote sensor, and can provide a certain reference basis for setting technical requirements of spectral characteristics of the optical filter in the design stage.
The technical scheme adopted for solving the technical problems is as follows:
a method for quantitatively analyzing the imaging effect of spectral shift of a light filter on a space optical remote sensor, the method comprising the steps of:
step one: designing or acquiring spectral characteristic parameters of spectral range, center wavelength and bandwidth of each spectral range of the space optical remote sensor;
step two: acquiring a surface reflectivity curve of a typical object;
step three: according to the optical characteristic parameters of each spectral band of the space optical remote sensor obtained in the first step and the surface reflectivity curve of the typical object obtained in the second step, calculating the equivalent reflectivity of different typical objects in the spectral bandwidth range of each spectral band of the space optical remote sensor;
step four: simulating the radiance at the entrance pupil of the space optical remote sensor corresponding to the equivalent reflectivities of different typical objects under typical illumination conditions by using an atmospheric radiation transmission model;
step five: calculating an image gray value according to the radiance and the space optical remote sensor radiation conversion model obtained in the step four;
step six: and shifting the center wavelength or bandwidth of each spectrum of the space optical remote sensor, and calculating the corresponding image gray response deviation of different ground objects.
Preferably, the typical features are water, soil, vegetation.
The beneficial effects of the invention are as follows: the quantitative analysis method for the imaging influence of the spectral shift of the optical filter on the space optical remote sensor can intuitively measure the difference of gray values of output images caused by the spectral characteristic change of the imaging system of the space optical remote sensor, is beneficial to solving the problem of error distribution of the spectral characteristic of the optical filter in the design stage of the space optical remote sensor, and can reasonably reduce the difficulty and cost of device processing on the premise that the remote sensor meets the imaging performance requirement. The connection between the input radiation of the space optical remote sensor and the gray value of the output image is established by using the atmospheric radiation transmission model and the remote sensor radiation conversion model, the simulation analysis method can be used as a simulation analysis means for the influence of performance indexes of each link of the space optical remote sensor imaging link on the system imaging, and the simulation result can provide a certain reference basis for the design of the remote sensor.
Drawings
FIG. 1 is a graph of the spectral response of a remote sensor using the method of quantitatively analyzing the effect of spectral shift of a filter on imaging of a spatial optical remote sensor according to the present invention.
FIG. 2 is a plot of typical surface reflectance for a method of quantitatively analyzing the effect of spectral shift of an optical filter on imaging of a spatial optical remote sensor in accordance with the present invention.
FIG. 3 is a graph of radiance at the entrance pupil of a remote sensor for a quantitative analysis of the effect of spectral shift of an optical filter on imaging of a spatial optical remote sensor in accordance with the present invention.
Detailed Description
The invention will be described in further detail with reference to the drawings and examples.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
A quantitative analysis method for the imaging influence of optical filter spectral shift on a space optical remote sensor comprises the following steps:
step one: the spectral characteristic parameters (design values) of the space optical remote sensor are designed or obtained, taking a certain model of space optical remote sensor as an example, the design values of the spectral ranges of the space optical remote sensor are shown in table 1, and the simplified spectral response curves are shown in fig. 1 for the convenience of analysis.
TABLE 1 spectral design Range for certain model of spatial optical remote sensor
| Spectrum segment | Spectral range/nm | Center wavelength/nm | Bandwidth/nm |
| Panchromatic Pan | 450～800 | 625 | 350 |
| Band1(Blue) | 450～510 | 480 | 60 |
| Band2(Green) | 510～580 | 545 | 70 |
| Band3(Red) | 630～690 | 660 | 60 |
| Band4(NIR) | 770～895 | 832.5 | 125 |
Step two: using ENVI ground object spectrum library, surface reflectance curves for typical ground objects such as water, soil, vegetation, etc., are obtained as shown in fig. 2.
Step three: calculating equivalent reflectivities rho of different typical objects in spectral bandwidth ranges of each spectral band of the space optical remote sensor according to the spectral characteristic parameters of the space optical remote sensor provided in the first step and the typical object reflectivity curve obtained in the second step i The method comprises the following steps:
wherein ρ (λ) is the surface reflectance of a typical object; s is S i (lambda) is the spectral response function of the space optical remote sensor in the wave band i, and the wave band response range is lambda 1 And lambda (lambda) 2 Responses outside this range are equal to 0.
Step four: and (3) calculating the radiance at the entrance pupil of the space optical remote sensor corresponding to the equivalent reflectances of different typical features under a certain solar altitude angle by using an atmospheric radiation transmission model Modtran4 according to the typical feature equivalent reflectances obtained by the calculation in the step (three).
As shown in fig. 3, when the solar altitude angle is 60 °, and the typical equivalent reflectivity is 0.3, the solar radiation energy in summer in the middle latitude area of the earth is obtained through simulation by using Modtran4, and is reflected by the ground, and then is reflected on the top of the atmosphere.
Step five: the method comprises the steps of establishing a radiation conversion model of a space optical remote sensor, and specifically comprises the following steps:
in the imaging process of the space optical remote sensor, the radiance at the camera entrance pupil is irradiated on a detector after passing through an optical system, the detector converts a received optical signal into an electronic signal through photoelectric conversion, and then the electronic signal is amplified and processed through a signal processing circuit, and finally the electronic signal is quantized and output as a gray scale (DN) value of an image pixel.
The spectral flux Φ (λ) received by each detector element can be expressed as:
wherein A is d For the detector pixel area, F is the relative aperture of the optical system, L (lambda) is the radiance at the entrance pupil of the remote sensor, τ 0 Is the transmittance of the optical system.
The number of electrons Se accumulated in each probe element during the photoelectric conversion process during the imaging exposure time can be expressed as:
wherein R (lambda) is the spectral response function of the detector, t int For exposure time, η is quantum efficiency, λ is wavelength, h= 6.626 ×10 -34 J·s is planck constant, c=3×10 8 m/s is the speed of light.
The DN value of an image can be expressed as:
DN＝gain×Se
to sum up, the relation between DN value and input radiance of an image can be expressed as:
wherein,,
step six: the center wavelength and the bandwidth of each spectrum band of the space optical remote sensor are respectively shifted, the image gray level deviation corresponding to different ground objects is calculated, and the calculation formula is as follows:
the quantitative analysis method of the influence of the spectral shift of the optical filter on the imaging of the space optical remote sensor is realized.
Wherein R is δ Center wavelength pair for spatial optical remote sensorOr spectral characteristic parameters after bandwidth shift, DN (R δ ) For calculating DN value of image according to spectral characteristic parameter of space optical remote sensor with deviation, R 0 For the design value of spectral characteristic parameters of a space optical remote sensor, DN (R 0 ) And calculating an obtained image DN value according to the design value of the spectral characteristic parameter of the space optical remote sensor.
1) Spectral band center wavelength shift impact analysis
And (3) keeping the bandwidths of all the spectral bands unchanged, shifting the central wavelengths by +/-10 nm respectively, and calculating the gray scale deviation of the images corresponding to different typical objects. The calculation results are shown in tables 2 to 6, taking Coarse Granular Snow (coarse snow), giant wild (grass), grayish brown loam (bare earth), sandstone (Sandstone), seawater_open_ocean (sea water) as examples.
TABLE 2 coarse snow Coarse Granular Snow center wavelength offset Effect
TABLE 3 influence of the offset of the center wavelength of the grass Giant Wildrye
TABLE 4 influence of bare soil Grayishbrown loam center wavelength shift
TABLE 5 Sandstone Sandstone center wavelength shift effect
TABLE 6 Seawater SeaWater_Open_Ocean center wavelength offset Effect
2) Spectral band offset impact analysis
The central wavelength of each spectrum is kept unchanged, the bandwidth is shifted to the short wavelength and the long wavelength by 0 nm-10 nm, and the image gray level deviation corresponding to different typical objects is calculated. The calculation results are shown in tables 8 to 12, taking Coarse Granular Snow (coarse snow), giant wild (grass), grayish brown loam (bare earth), sandstone (Sandstone), seawater_open_ocean (sea water) as examples.
Table 8 coarse snow Coarse Granular Snow Bandwidth differential Effect
TABLE 9 grass Giant Wildrye Bandwidth Difference Effect
Table 10 bare soil Grayishbrown loam bandwidth differential impact
Table 11 Sandstone bandwidth difference effects
Table 12 Seawater SeaWater_OpenOcean Bandwidth Difference Effect
According to the simulation calculation result, the influence of the spectrum characteristic deviation of the remote sensor on different ground features on the gray value of the image can be visually seen, and the following conclusion can be further obtained by analysis:
conclusion 1: compared with the shift of the center wavelength, the deviation of the spectral bandwidth has larger influence on the image gray scale;
conclusion 2: the influence effect of spectrum characteristic deviation on the image gray level is not consistent in different spectrum sections, the Blue and NIR spectrum sections are sensitive to the change of the central wavelength, and the Blue, green and Red spectrum sections are sensitive to the change of the bandwidth;
conclusion 3: the influence of the center wavelength deviation on the image gray of different typical features is inconsistent, for example, when the center wavelength deviation is 4nm, the gray deviation of different features is as follows:
| type of ground object | B1(Blue) | B2(Green) | B3(Red) | B4(NIR) | Pan |
| Coarse snow Coarse Granular Snow | 4.43％ | 2.24％ | -0.31％ | -4.15％ | 0.46％ |
| Grass Giant wild eye | 3.54％ | 1.50％ | -0.81％ | -3.20％ | 1.08％ |
| Bare soil Grayish brown loam | 3.56％ | 2.51％ | -0.66％ | -1.66％ | 1.05％ |
| Sand Sandstone | 3.51％ | 1.40％ | -0.70％ | -3.38％ | -0.19％ |
| Seawater seawater_open_ocean | 2.67％ | 1.31％ | -0.87％ | -3.56％ | -0.37％ |
Conclusion 4: the influence of the bandwidth deviation on the image gray of different typical features tends to be consistent, for example, when the bandwidth deviation is-3 nm, the gray deviation of different features is as follows:
| type of ground object | B1(Blue) | B2(Green) | B3(Red) | B4(NIR) | Pan |
| Coarse snow Coarse Granular Snow | -3.20％ | -3.85％ | -4.51％ | -3.13％ | -0.53％ |
| Grass Giant wild eye | -3.53％ | -4.13％ | -4.78％ | -3.13％ | 0.32％ |
| Bare soil Grayish brown loam | -3.53％ | -4.14％ | -4.70％ | -1.57％ | -0.83％ |
| Sand Sandstone | -3.55％ | -4.16％ | -4.73％ | -3.28％ | -0.86％ |
| Seawater seawater_open_ocean | -4.31％ | -4.20％ | -4.81％ | -3.40％ | -0.95％ |
In addition, besides the conclusion, reasonable suggestions can be provided for the technical requirements of spectral characteristics of optical filter processing according to specific performance indexes of remote sensor imaging and in combination with simulation data analysis results. At present, the relative radiation precision of the space optical remote sensor images of various countries can basically reach 3%, and accordingly, combining the simulation calculation results of the image gray response change of the typical object under different spectral characteristic deviations, the processing error range of the spectral characteristics of the optical filter can be suggested as follows: the central wavelength is +/-2 nm and the bandwidth is +/-1 nm.
Claims (2)
1. A method for quantitatively analyzing the imaging effect of spectral shift of an optical filter on a space optical remote sensor, which is characterized by comprising the following steps:
step one: designing or acquiring spectral characteristic parameters of spectral range, center wavelength and bandwidth of each spectral range of the space optical remote sensor;
step two: acquiring a surface reflectivity curve of a typical object;
step three: according to the optical characteristic parameters of each spectral band of the space optical remote sensor obtained in the first step and the surface reflectivity curve of the typical object obtained in the second step, calculating the equivalent reflectivity of different typical objects in the spectral bandwidth range of each spectral band of the space optical remote sensor;
step four: simulating the radiance at the entrance pupil of the space optical remote sensor corresponding to the equivalent reflectivities of different typical objects under typical illumination conditions by using an atmospheric radiation transmission model;
step five: calculating an image gray value according to the radiance and the space optical remote sensor radiation conversion model obtained in the step four;
step six: the center wavelength or bandwidth of each spectrum of the space optical remote sensor is shifted, the image gray scale response deviation corresponding to different ground objects is calculated, and the calculation formula is as follows:
wherein R is δ Spectral characteristics parameters, DN (R) δ ) For calculating DN value of image according to spectral characteristic parameter of space optical remote sensor with deviation, R 0 For the design value of spectral characteristic parameters of a space optical remote sensor, DN (R 0 ) And calculating an obtained image DN value according to the design value of the spectral characteristic parameter of the space optical remote sensor.
2. The method for quantitatively analyzing the imaging influence of spectral shift of optical filter on space optical remote sensor according to claim 1, wherein the typical features are water, soil and vegetation.
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