CN111610001A - Wide remote sensing image MTF ground simulation testing device - Google Patents
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Abstract
A wide remote sensing image MTF ground simulation test device relates to the technical field of wide remote sensing system imaging quality evaluation, solves the technical blank problem, and comprises an image simulation source acquisition unit, a wide image preprocessing unit and an MTF measurement display unit, wherein the image simulation source acquisition unit acquires a simulated wide remote sensing image, compresses and stores the acquired wide remote sensing image, and decompresses the compressed wide remote sensing image to the wide image preprocessing unit; the wide-width image preprocessing unit sequentially carries out denoising, full-field division and effective ROI (region of interest) extraction on the wide-width remote sensing image and transmits the wide-width remote sensing image to the MTF measurement display unit; the MTF measurement display unit measures and displays an MTF curve of the effective ROI area. The invention relates to a MTF ground simulation test device specially aiming at wide remote sensing images, which can simulate the imaging process of a wide remote sensing camera, analyze the imaging quality of the wide remote sensing camera by testing the on-orbit dynamic MTF of the wide remote sensing camera, and ensure the MTF test precision.
Description
Technical Field
The invention relates to the technical field of imaging quality evaluation of wide remote sensing systems, in particular to a ground simulation test device for MTF (modulation transfer function) of a wide remote sensing image.
Background
In recent years, wide remote sensing images acquired by wide remote sensing cameras have high application value due to the fact that the wide remote sensing images contain massive data, and meanwhile, serious degradation of image quality is brought. Modulation Transfer Function (MTF) is an image quality evaluation method which is most widely applied to evaluating the imaging quality of a remote sensing system; the accurate test of MTF of the wide remote sensing image is also the key for improving the image quality of the wide remote sensing image by applying the MTFC-based image restoration method.
The MTF on-orbit measurement method can reflect the comprehensive degradation function of all links of the remote sensing imaging whole link, has low cost and wide application, and can be divided into the following steps according to different ground feature characteristics in the remote sensing image: point pulse method, line pulse method, edge method, periodic target method, and the like. The linear pulse method has higher precision when the ground target meets the calibration condition, and the knife edge method has higher algorithm stability and small influence by the environment, so the two methods are more applied. In order to ensure the MTF testing precision, the line pulse method and the edge method have higher requirements on the image quality of the remote sensing image, are more suitable for the high-resolution remote sensing image, and are mainly focused on the MTF testing device based on the high-resolution remote sensing image in domestic and foreign relevant research works. Due to the characteristics of large difference of imaging quality of each field of view, serious image quality degradation, lack of typical ground objects in the image and the like, the direct application of the conventional MTF testing device often results in that a correct and stable testing result cannot be obtained. At present, the signal-to-noise ratio of a wide remote sensing image is low, and the image quality is reduced; the size is large, and the difference of imaging quality of each field of view is large; the problem that typical objects in an image are few and the like causes difficulty in directly applying an existing MTF testing device or guaranteeing MTF testing precision when the MTF testing device is directly applied is solved, and a MTF ground simulation testing device specially aiming at a wide remote sensing image is not provided at present, so that powerful guidance can not be provided for analysis of imaging quality of the wide remote sensing camera.
Disclosure of Invention
In order to solve the problems, the invention provides a wide remote sensing image MTF ground simulation test device.
The technical scheme adopted by the invention for solving the technical problem is as follows:
a ground simulation test device for MTF of a wide remote sensing image comprises an image simulation source acquisition unit, a wide image preprocessing unit and an MTF measurement display unit, wherein the image simulation source acquisition unit acquires a simulated wide remote sensing image, compresses and stores the acquired wide remote sensing image, and decompresses the compressed wide remote sensing image to the wide image preprocessing unit; the wide-width image preprocessing unit sequentially carries out denoising, full-field division and effective ROI (region of interest) extraction on the wide-width remote sensing image decompressed on the wide-width image preprocessing unit and transmits the wide-width remote sensing image to the MTF measurement display unit; and the MTF measurement display unit measures the effective ROI area to obtain an MTF curve and displays the obtained MTF curve.
The invention has the beneficial effects that:
the invention provides a special MTF ground simulation testing device for wide remote sensing images, which can simulate wide remote sensing imaging and analyze the imaging quality of a wide remote sensing camera, and ensure the MTF testing precision. And a wide remote sensing image simulation data source with characteristics similar to those of an actual wide remote sensing image can be obtained during testing. The wide-width image preprocessing unit is used for denoising and full-field division preprocessing of the simulated wide-width image, an effective ROI area is automatically and quickly obtained, and the problem that the wide-width remote sensing image is difficult to directly apply the MTF on-orbit measurement method is solved. An improved line pulse method MTF measuring module and an improved inclined edge method MTF measuring module are transplanted into an FPGA processor, so that the effective ROI output by the image processor can be directly processed and operated to obtain a wide remote sensing image full-field MTF curve, and satellite on-orbit test MTF can be conveniently realized.
Drawings
FIG. 1 is a flow chart of the operation of a wide remote sensing image MTF ground simulation test device according to the present invention;
FIG. 2 is a system diagram of a wide remote sensing image MTF ground simulation test device according to the present invention;
FIG. 3 is a schematic view of the full field of view division of a wide remote sensing image according to the present invention;
FIG. 4 is a flow chart of an improved line pulse MTF measurement algorithm of the present invention;
FIG. 5 is a flow chart of an improved inclined edge method MTF measurement algorithm of the present invention.
In the figure: 1. the system comprises a three-axis air-flotation rotary table, 2, a TDI CCD camera, 3, an atmospheric environment simulation device, 4, a large-range combined target, 5, a memory, 6, a graphic processor, 7, an FPGA processor, 8 and a computer.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings.
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 specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
A wide remote sensing image MTF ground simulation test device comprises an image simulation source obtaining unit, a wide image preprocessing unit and an MTF measurement display unit, as shown in figures 1 and 2.
The image simulation source obtaining unit obtains a simulated wide remote sensing image, specifically obtains a simulated wide remote sensing image with characteristics similar to those of an actual wide remote sensing image, and compresses and decompresses the obtained simulated wide remote sensing image to the wide image preprocessing unit.
The image simulation source acquisition unit comprises a three-axis air-flotation turntable 1, a camera, an atmospheric environment simulation device 3, a target and a memory 5. The camera is a TDI CCD camera 2. The TDI CCD camera 2 is installed on the triaxial air-floating rotary table 1, the triaxial air-floating rotary table 1 controls the TDI CCD camera 2 located on the triaxial air-floating rotary table to rotate and slightly vibrate, and the triaxial air-floating rotary table 1 simulates the wide remote sensing camera on a satellite to rotate and image and the satellite platform to vibrate. The target is arranged corresponding to the TDI CCD camera 2 and is arranged in front of the TDI CCD camera 2, the target simulates a large-view-field wide-range imaging target, and the target is a combined target, namely a large-range combined target 4 and can be formed by splicing a plurality of standard resolution test board images after being amplified. The atmospheric environment simulation device 3 is positioned between the camera and the combined target and simulates an atmospheric degradation link when the camera images the target. The target is arranged right in front of the camera and the atmospheric environment simulation device 3 and keeps a certain distance from the camera. Through the atmospheric environment simulation device 3 and the large-range combined target 4, the complex atmospheric conditions under each view field and complex imaging targets in the large view field can be simulated when the wide remote sensing camera images, and further, wide remote sensing images with characteristics similar to those of actual wide remote sensing images can be obtained. The TDI CCD camera 2 is connected with a memory 5 through a first data line, and the memory 5 is connected with a wide-width image preprocessing unit through a second data line. The TDI CCD camera 2 shoots the target to obtain a simulated wide remote sensing image, and the simulated wide remote sensing image is transmitted to the memory 5. And the data line compresses the simulated wide remote sensing image, stores the compressed wide remote sensing image in the memory 5, and decompresses the compressed wide remote sensing image to the wide image preprocessing unit. Compressing the wide remote sensing image through a data line I, and simulating an image lossy compression link in which the remote sensing image is actually downloaded to the ground; and decompressing the compressed wide compressed image data source to a wide image preprocessing unit through a data line II, and simulating a loss decompression link before ground image processing in practice.
The wide-width image preprocessing unit is used for denoising the wide-width remote sensing image decompressed on the wide-width image preprocessing unit, dividing the denoised wide-width remote sensing image into a full view field, selecting an effective ROI (region of interest) in the view field divided from the full view field and sending the effective ROI region to the MTF (modulation transfer function) measurement display unit.
The wide-width image preprocessing unit adopts a graphics processor 6, and the graphics processor 6 comprises a denoising module, a full-view field dividing module and an ROI selecting module. The graphics processor 6 is a GPU. The denoising module denoises the wide remote sensing image decompressed to the wide image preprocessing unit, the full-field division module performs field division on the denoised wide remote sensing image, and the ROI selection module extracts an image area which is divided by the full-field division module and contains an effective MTF test target in a field and transmits the image area to the FPGA processor 7. The region of the image containing the valid MTF test object is also called the valid ROI region.
The denoising module adopts a wavelet packet denoising module, and the wavelet packet denoising module performs wavelet packet denoising on the wide remote sensing image decompressed to the graphic processor 6 to obtain a denoised wide remote sensing image. And improving the signal-to-noise ratio of the wide remote sensing image through wavelet packet denoising operation. Other denoising algorithms can be selected according to the actual application requirements.
And the full-view-field dividing module is used for performing full-view-field nonlinear gradient stripe division on the denoised wide remote sensing image. According to the imaging principle of 'vertical rail scanning + along rail splicing' of the wide remote sensing camera, the wide remote sensing image is divided into full fields of view of nonlinear gradient rectangular strips from the center to two sides along the vertical rail direction, and MTF testing precision errors in two side fields of the vertical rail are reduced. And aiming at different wide remote sensing images, the field of view division with different shapes and different quantities can be carried out according to specific conditions.
The ROI selection module extracts an effective ROI area in the field of view divided by the full field of view division module and transmits the effective ROI area to the FPGA processor 7. The effective ROI area is an effective line pulse area or an effective edge area.
The MTF measurement display unit receives the effective ROI area sent by the wide image preprocessing unit, measures the effective ROI area to obtain an MTF curve and displays the obtained MTF curve. The MTF measuring and displaying unit comprises an FPGA processor 7 and a display, the display adopts a computer 8, the FPGA processor 7 is uploaded with an improved line pulse method MTF measuring module and an improved inclined edge method MTF measuring module, the FPGA processor 7 receives an effective ROI area sent by the wide image preprocessing unit, the effective ROI area is measured by the improved line pulse method MTF measuring module or the improved inclined edge method MTF measuring module to obtain an MTF curve, and the obtained MTF curve is displayed by the computer 8. When the effective ROI is an effective line pulse area, the FPGA processor 7 measures by adopting an improved line pulse method MTF measuring module to obtain an MTF curve; when the effective ROI area is the effective edge area, the FPGA processor 7 measures the MTF curve by using the improved oblique edge MTF measurement module. The computer 8 is used for displaying MTF curves of all fields of the wide remote sensing image output by the FPGA processor 7, and the computer 8 can also perform image quality evaluation and subsequent MTFC-based image restoration processing on the MTF curves obtained by the FPGA processing.
A simulation test process of a wide remote sensing image MTF ground simulation test device comprises the following steps:
s1, obtaining the simulated wide remote sensing image
The large-range combined target 4 is spliced by amplifying images of 4 standard resolution test boards and serves as a large-field-of-view imaging target object (the large-range combined target 4 is arranged in the figure 1), a large-range imaging complex atmospheric environment (the complex atmospheric environment simulation in the figure 1) is provided by an atmospheric environment simulation device 3, the TDI CCD camera 2 is controlled by the three-axis air-flotation turntable 1 to vibrate slightly and scan and image rotationally (the TDI CCD camera 2 in the figure 1 rotates and images), a simulated wide remote sensing image is obtained, and a wide remote sensing image simulation data source is obtained. The wide remote sensing image shot by the TDI CCD camera 2 is compressed to the memory 5 for storage through the first data line, and the wide remote sensing image stored in the memory 5 is decompressed to the graphics processor 6 through the second data line (the wide image simulation source of the image compression and decompression in the figure 1).
S2 preprocessing wide-width image
And then the wide remote sensing image is subjected to wavelet packet denoising, full-field nonlinear gradient stripe division and effective ROI area discrimination selection in sequence through the graphic processor 6. The relevant description is as follows:
s2.1, denoising the wavelet packet: the invention provides a denoising link, aims to add a preprocessing link according to the MTF measurement requirement of the wide remote sensing image, and selects an applicable denoising algorithm. In practical application, other reasonable denoising algorithms can be selected according to the image characteristics. Wavelet packet denoising implementation steps: decomposing the wavelet packet; calculating a wavelet packet decomposition optimal tree according to a given entropy standard; threshold quantization of wavelet packet decomposition coefficients; and (5) wavelet packet reconstruction.
S2.2, dividing a full view field: the wide image is divided into rectangular strips from the center to two sides along the vertical rail direction, and the width of the rectangular division strip adopted from the central view field of the subsatellite point to the view fields at two sides of the vertical rail deviated from the subsatellite point is gradually reduced (the full view field nonlinear gradual change strip division of fig. 1). The schematic diagram of dividing the full field of view of the wide remote sensing image in this embodiment is as shown in fig. 3, where the field of view from the center field of view to both sides of the vertical rail are sequentially marked as ± 0.3 field of view, ± 0.5 field of view, ± 0.7 field of view, ± 0.8 field of view, ± 0.9 field of view, ± 1 field of view, and-0.3- +0.3 field of view as the center field of view, the 0 point of the center field of view is positive from the left to the right, the divided field of view is K field of view, and K is ± 0.3, ± 0.5, ± 0.7, ± 0.8, ± 0.9. In practical application, the MTF test can be performed on each divided field in sequence to obtain a full field MTF curve, or the MTF test can be performed on a divided part of the designated field to obtain a specific field MTF curve, that is, the field is reselected to correspond to the field in fig. 1.
S2.3, ROI selection: the ROI selection module performs effective ROI area selection on the (whole/partial) field of view after the full field of view is divided. The specific process is as follows, firstly, the linear edge and the knife edge in each view field of the wide image are extracted by adopting an image edge detection algorithm. Then automatically distinguishing the edge target and the line pulse target according to the characteristics of the edge target and the line pulse target: the gray value difference of the pixels at the two sides of the edge target is larger; the gray values of the pixels on both sides of the line pulse target are basically the same. Finally, the active ROI region (active line pulse region or active edge region) is selected. The selection of the effective edge area follows: the height of the edge is more than 20 pixel units; selecting a knife edge region with high edge contrast (> 20%); the angle of the edge is 5-10 degrees. The active line pulse area selection follows: the linear ground object has obvious contrast (the contrast is more than 20 percent) with the background and the background brightness is uniform; a line feature of 2-5 pixel width is selected. To ensure reliability of the MTF calculation, the effective line pulse area and the effective edge area are selected according to the above criteria.
Selecting which one meets the measurement requirement according to the characteristics of the ground objects in each field, for example, selecting which one meets the measurement requirement in a 0.7 field by using a line pulse target and a knife edge target, wherein the line pulse target meets the measurement characteristic requirement, and then using the line pulse target area as an effective ROI area and adopting a subsequent improved line pulse MTF measurement algorithm to measure the MTF of the 0.7 field. If the edge target characteristics are better in the-0.9 field of view, the MTF for the-0.9 field of view can be measured using the region where the edge target is located as the effective ROI and using the modified oblique edge MTF measurement algorithm that follows. And in some fields, the ground object can only be a line object or only a blade object, and only one of the line pulse target and the blade object is obtained.
S3, MTF measurement display
And an FPGA processor 7 implanted with an improved oblique edge method MTF measurement algorithm and an improved line pulse MTF measurement algorithm program is used for processing and operating effective ROI areas of each field of view output by the image processor 6 to obtain a full-field MTF curve of the wide remote sensing image, and the full-field MTF curve is output to a computer 8 for display. According to the actual application requirements, the image quality of the remote sensing image can be further analyzed in the computer 8 by utilizing the full-field MTF curve of the wide remote sensing image, and the image restoration operation is carried out.
The algorithm flow chart of the improved line pulse method MTF measurement module is shown in FIG. 4, which is specifically described as follows:
s3.11, line feature extraction and straight line fitting: performing edge detection and least square straight line fitting on the effective line pulse area to obtain the corresponding position of the linear pulse ground object in the image, and determining the sampling point of each row according to the positioned edge point;
s3.12, LSF construction and interpolation: performing curve fitting on the sampling point with sub-pixel precision obtained in S3.11 to obtain LSF corresponding to the output pulse, namely LSFOutput of；
S3.13, setting an input pulse signal and fitting the LSF: setting the width of an input square wave pulse by combining a target sampling interval of a camera detector according to the width of an actual linear ground object, namely finishing the setting of an input pulse signal, and fitting to obtain an input signal LSF (local pulse frequency), namely the LSFInput device(ii) a The target sampling interval of the camera detector is the shooting resolution size of the large-range combined target 4 corresponding to the pixel resolution size of the camera detector.
S3.14, discrete Fourier transform and MTF calculation: and respectively carrying out Fourier transform on the LSF obtained in the S3.12 and the LSF obtained in the S3.13, calculating the ratio of corresponding positions to obtain an MTF curve, and carrying out normalization processing on the MTF curve.
MTF＝DFT(LSFOutput of)/DFT(LSFInput device)
Where DFT denotes the discrete fourier transform.
The flow chart of the algorithm of the improved inclined edge method MTF measurement module is shown in FIG. 5, which is specifically described as follows:
s3.21, edge point detection: and carrying out simple difference on the gray value (normalization) of each row of the effective edge area, wherein the maximum difference point is the position of the edge point.
S3.22, fitting edge points: fitting the edge points by adopting a nonlinear least square method to obtain an edge fitting line.
S3.23, distance-gray level data acquisition: the vertical distance between each pixel point in the effective edge area and the edge fitting line is taken as an x value (the x values corresponding to the pixel points on the two sides of the edge are marked as "-" and "+", respectively), and each pixel value after normalization is taken as a y value.
S3.24, fitting of an ESF curve: and fitting according to the x value and the y value of S3.23 to obtain an ESF curve. Fitting an ESF curve by adopting a Fermi function with stronger noise suppression capacity; and solving the unknown coefficients in the Fermi function by using a nonlinear least squares iterative algorithm:
wherein: x is the vertical distance between the pixel point and the edge fitting line; f (x) is a normalized pixel value of the pixel point corresponding to the x position obtained by Fermi fitting; g1、g2、g3、g4、g5、g6、g7、g8、g9And g10All are Fermi fitting coefficients.
Assume that the expression of the fitted curve is F (x)i，gj) The sum of the squared errors is:
wherein: s is each xiFermi fitting pixel value F (x) at pixel point correspondencei) And the actual sampled pixel value yiThe sum of squared errors between; i is 1, 2, …, n is the number of actual sampling points, j is 1, 2, …, 10 is the number of Fermi fitting coefficients to be solved, gjFitting coefficients for Fermi.
According to the principle of least square method：
With the smallest sum of squares of errors
Then g is0A set of Fermi fitting coefficients.
S3.25, fitting of an LSF curve: and directly deriving the ESF curve obtained in S3.24 to obtain an LSF curve.
S3.26, calculation of MTF: discretizing the LSF obtained in S3.25 in a space containing peaks and sufficient width, then performing discrete Fourier transform to obtain an MTF curve of the image with respect to frequency, normalizing the curve,
MTF curve: MTF (n) ═ FFT (LSF (n)) > electrically non-conducting
MTF normalization: normaize _ MTF (n) ═ MTF (n)/MTF (0)
Where FFT denotes fast fourier transform.
The normalized MTF curve obtained at S3.14 and the normalized MTF curve obtained at S3.26 are displayed by computer 8.
The invention provides a ground simulation test device for MTF of a wide remote sensing image. During testing, the rotation of the camera is controlled through the air flotation rotary table, micro vibration is provided, and the rotary imaging process of the wide remote sensing camera and the micro vibration process of the satellite platform can be simulated; through the atmospheric environment simulation device 3 and the large-range combined target 4, complex atmospheric conditions under each view field and complex imaging targets in the large view field can be simulated when the wide remote sensing camera images, and further a wide remote sensing image simulation data source similar to the actual wide remote sensing image characteristics can be obtained. The compression and decompression processes of satellite downloading and ground processing of remote sensing images can be simulated more truly through the links of image data compression and decompression between the memory 5 and the camera and between the memory 5 and the image processor 6. The image processor 6 is used for innovatively conducting denoising and full-view-field division preprocessing on the analog wide-width image, automatically and quickly obtaining an effective ROI (region of interest), and the problem that the wide-width remote sensing image is difficult to directly apply the MTF on-track measurement method is solved. The improved line pulse method MTF measuring module and the improved inclined edge method MTF measuring module are innovatively transplanted into the FPGA processor 7, so that the effective ROI output by the graphic processor 6 can be directly processed and operated to obtain a wide remote sensing image full-field MTF curve, and the on-satellite on-track MTF test can be conveniently realized. The output of the computer 8 shows the MTF curve, which can be further used for image quality evaluation and the subsequent image restoration processing based on MTFC. The invention provides a special MTF ground simulation testing device for wide remote sensing images, which can simulate wide remote sensing imaging and analyze the imaging quality of a wide remote sensing camera, and ensure the MTF testing precision.
Claims (9)
1. The ground simulation test device for the MTF of the wide remote sensing image is characterized by comprising an image simulation source acquisition unit, a wide image preprocessing unit and an MTF measurement display unit, wherein the image simulation source acquisition unit acquires a simulated wide remote sensing image, compresses and stores the acquired wide remote sensing image, and decompresses the compressed wide remote sensing image to the wide image preprocessing unit; the wide-width image preprocessing unit sequentially carries out denoising, full-field division and effective ROI (region of interest) extraction on the wide-width remote sensing image decompressed on the wide-width image preprocessing unit and transmits the wide-width remote sensing image to the MTF measurement display unit; and the MTF measurement display unit measures the effective ROI area to obtain an MTF curve and displays the obtained MTF curve.
2. The ground simulation test device for MTF of the wide remote sensing image as claimed in claim 1, wherein the image simulation source obtaining unit comprises a three-axis air-floating turntable, a camera, an atmospheric environment simulation device, a target and a memory, the camera is installed on the three-axis air-floating turntable, the target is located in front of the camera, the atmospheric environment simulation device is located between the camera and the atmospheric environment simulation device, the camera is connected with the memory through a data line I, and the memory is connected with the wide image preprocessing unit through a data line II.
3. The ground simulation test device for MTF of the wide remote sensing image as claimed in claim 2, wherein the camera is rotated and vibrated by the three-axis air-floating turntable to simulate the rotation imaging of the wide remote sensing camera on the satellite and the vibration of the satellite platform; simulating an atmospheric degradation link through the atmospheric environment simulation device; compressing the wide remote sensing image shot by the camera through the first data line and sending the compressed wide remote sensing image to a memory; and decompressing the wide remote sensing image stored in the memory through the second data line and sending the decompressed wide remote sensing image to a wide image preprocessing unit.
4. The ground simulation test device for the MTF of the wide remote sensing image as claimed in claim 1, wherein the denoising specifically comprises: and carrying out wavelet packet denoising on the wide remote sensing image decompressed to the wide image preprocessing unit to obtain the denoised wide remote sensing image.
5. The ground simulation test device for the MTF of the wide remote sensing image of claim 1, wherein the division of the full field of view is specifically as follows: and the wide image preprocessing unit divides the denoised wide remote sensing image into full-field rectangular strips with non-linear gradual change from the center to two sides along the vertical rail direction.
6. The ground simulation test device for MTF of the wide remote sensing image of claim 1, wherein the effective ROI area is an effective line pulse area or an effective edge area.
7. The wide remote sensing image MTF ground simulation test device of claim 6, wherein the MTF measurement display unit comprises an FPGA processor and a display, the FPGA processor is uploaded with an improved line pulse method MTF measurement module and an improved inclined edge method MTF measurement module, the FPGA processor receives the effective ROI area sent by the wide image preprocessing unit, the effective ROI area is measured by the improved line pulse method MTF measurement module or the improved inclined edge method MTF measurement module to obtain an MTF curve, and the obtained MTF curve is displayed by the display.
8. The ground simulation test device for MTF of the wide remote sensing image of claim 7, wherein when the effective ROI area is an effective line pulse area, the MTF measuring module measures the effective line pulse area to obtain an MTF curve; the measurement process is as follows:
s3.11, performing edge detection and least square straight line fitting on the effective line pulse area to obtain the corresponding position of the linear pulse ground object in the image, and determining sampling points of each row according to the positioned edge points;
s3.12, performing curve fitting on the sampling points with the sub-pixel precision obtained in the S3.11 to obtain LSFs corresponding to the output pulses;
s3.13, setting an input pulse signal and fitting an LSF of the input pulse signal;
and S3.14, respectively carrying out Fourier transform on the LSF obtained in the S3.12 and the LSF obtained in the S3.13 to obtain an MTF curve, and normalizing the MTF curve.
9. The ground simulation test device for MTF of the wide remote sensing image of claim 7, wherein when the effective ROI area is an effective edge area, the MTF measuring module measures the effective edge area by using an improved inclined edge method to obtain an MTF curve; the measurement process is as follows:
s3.21, obtaining the position of an edge point by differentiating the gray value of each row of the effective edge area;
s3.22, fitting the edge points obtained in the S3.21 to obtain an edge fitting line;
and S3.23, taking the vertical distance between each pixel point in the effective edge area and the edge fitting line as an x value, and taking each pixel value after normalization as a y value.
S3.24, fitting according to the x value and the y value of the S3.23 to obtain an ESF curve;
s3.25, deriving the ESF curve obtained in the S3.24 to obtain an LSF curve;
and S3.26, discretizing the LSF curve obtained in the S3.25, performing discrete Fourier transform to obtain an MTF curve, and normalizing the MTF curve.
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