CN116630204B - Remote sensing image online analysis processing system - Google Patents
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Abstract
The invention relates to the technical field of remote sensing images, in particular to an online analysis processing system of remote sensing images, which comprises an acquisition unit, a basic database, an analysis unit and a processing unit. According to the invention, a plurality of basic databases of original remote sensing images are established for a target area for remote sensing image acquisition, more accurate correction basic data can be provided for real-time remote sensing images acquired by an acquisition unit, position information and image size of the real-time remote sensing data acquired by the acquisition unit are judged in multiple aspects through an analysis unit, an accurate reference remote sensing image is selected in the basic databases, and meanwhile, a correction reference line in the original remote sensing image and a real-time correction curve in the real-time remote sensing image are respectively determined through a processing unit to carry out linear correction, so that the real-time remote sensing image is accurately corrected and the definition of the corrected real-time remote sensing image is improved on the premise that the accurate reference remote sensing image is used as basic data for supporting.
Description
Technical Field
The invention relates to the technical field of remote sensing images, in particular to an online analysis processing system for remote sensing images.
Background
The remote sensing image is a film or a photo for recording the electromagnetic wave sizes of various ground objects, and can be divided into a ground remote sensing image, an aerial remote sensing image and an aerospace remote sensing image, wherein the remote sensing image processed by a computer is a digital image; analog images acquired in a photographic manner must be analog-to-digital converted with an image scanner or the like; the digital data obtained in the scanning mode must be transferred to a general carrier such as CCT which can be read by a general digital computer; computer image processing is to be performed in an image processing system; the image processing system is composed of hardware such as a computer, a display, a digitizer, a tape drive and the like and functional software with data input, output, correction, transformation, classification and the like, and the image processing content mainly comprises correction, transformation and classification.
Chinese patent publication No.: CN105631818A discloses a batch automatic geometric correction method and device for remote sensing images; constructing a planar element vector diagram through a remote sensing image, and obtaining a base diagram corresponding to each planar diagram according to the correlation between each planar diagram and a track diagram; according to the central longitude and latitude distance of the base image corresponding to the remote sensing image to be corrected and the planar image, geometric correction is carried out on the remote sensing image, so that in the remote sensing image in the prior art, the acquired remote sensing image is deformed to different degrees due to the instability of the platform height, longitude and latitude, speed and posture of the sensor, the corresponding reference points are needed to be adopted for calculation in the existing data no matter whether the geometric correction is carried out on the remote sensing image through real coordinates or the geometric correction is carried out on the remote sensing image through the reference image, the reference points are always selected uniformly in the whole image, larger operation amount is generated, the matching precision of the reference image used for correction and the real-time remote sensing image is not determined, the definition difference after the correction of the real-time remote sensing image is finally caused, and the image display cannot be accurately and clearly carried out.
Disclosure of Invention
Therefore, the invention provides an on-line analysis processing system for remote sensing images, which is used for solving the problem of lower definition after correction caused by insufficient correction processing precision of the remote sensing images in the prior art.
In order to achieve the above object, the present invention provides an on-line analysis processing system for remote sensing images, comprising,
the acquisition unit is used for acquiring real-time remote sensing data in a target area and converting the real-time remote sensing data to form a real-time remote sensing image;
the basic database is internally stored with a plurality of original remote sensing images of the target area, and each original remote sensing image comprises image position corresponding coordinate information;
the analysis unit is respectively connected with the acquisition unit and the basic database, can screen each original remote sensing image in the basic database according to the position information of the real-time remote sensing image acquired by the acquisition unit, determines an original remote sensing image according to the screening result and the image size of the real-time remote sensing image, and takes the superposition area of the original remote sensing image after the original remote sensing image is sheared as a reference remote sensing image after the processing unit is used for superposition processing and shearing of the original remote sensing image and the real-time remote sensing image;
The processing unit is respectively connected with the acquisition unit, the basic database and the analysis unit, can determine a datum point in the selected reference remote sensing image by using a geometric center, determine a correction reference line after the datum point and a second correction reference line perpendicular to the correction reference line, determine a real-time transverse correction curve in the real-time remote sensing image according to the gray scale conversion rate of each pixel on the correction reference line in the reference remote sensing image, determine a real-time longitudinal correction curve in the real-time remote sensing image according to the gray scale conversion rate of each pixel on the second correction reference line in the reference remote sensing image, transversely stretch the real-time remote sensing image by using the fitting of the correction reference line and the real-time transverse correction curve, and longitudinally stretch the real-time remote sensing image by using the fitting of the second correction reference line and the real-time longitudinal correction curve, thereby completing the correction of the real-time remote sensing image.
Further, the analysis unit can acquire the position information of the real-time remote sensing image acquired by the acquisition unit, the position information comprises coordinate information corresponding to the edge of the real-time remote sensing image, the analysis unit matches the acquired coordinate information corresponding to the edge of the real-time remote sensing image with all the coordinate information corresponding to the position of any one of the original remote sensing images in the basic database,
If the coordinate information corresponding to the edge of the real-time remote sensing image is all in the coordinate information corresponding to the original remote sensing image with current contrast, the analysis unit takes the original remote sensing image with current contrast as a screening item;
if the coordinate information corresponding to the edge of the real-time remote sensing image exists in the part which is in the coordinate information corresponding to the original remote sensing image with current contrast, the analysis unit takes the original remote sensing image with current contrast as an alternative;
if the coordinate information corresponding to the edge of the real-time remote sensing image does not have a part in the coordinate information corresponding to the original remote sensing image with current contrast, the analysis unit judges that the original remote sensing image with current contrast is an invalid reference image and does not select the original remote sensing image with current contrast;
and the analysis unit sequentially carries out matching judgment on each original remote sensing image in the basic database and the real-time remote sensing image until all original remote sensing images in the basic database are matched.
Further, the analysis unit judges the number of the selected screening items after completing all matching of the original remote sensing images in the basic database,
if the number of the selected screening options is zero, the analysis unit judges the number of the selected alternatives to determine whether to select the reference remote sensing image;
If the number of the selected screening items is one, the analysis unit performs coordinate information superposition processing on the original remote sensing image corresponding to the selected screening items and the real-time remote sensing image through the processing unit to form superposition areas, the processing unit cuts out the superposition areas in the original remote sensing image, and the superposition areas of the cut original remote sensing image are used as reference remote sensing images;
if the number of the selected screening items is greater than one, the analysis unit acquires the image size of the real-time remote sensing image, and selects an original remote sensing image from the original remote sensing images corresponding to the selected screening items to determine the reference remote sensing image.
Further, when the number of the selected options is zero, the analysis unit acquires the number of the selected options and determines,
if the number of the selected alternatives is zero, the analysis unit judges that the reference remote sensing image of the real-time remote sensing image is not selected in the basic database, sends out an artificial GPS correction prompt, and stores the real-time remote sensing image corrected by the GPS in the basic database as an original remote sensing image in a target area;
if the number of the selected alternatives is one, the analysis unit judges that the original remote sensing image corresponding to the selected alternatives and the real-time remote sensing image are subjected to coordinate information superposition processing through the processing unit, and judges the image area of the superposition area so as to determine whether to select the reference remote sensing image;
If the number of the selected alternatives is greater than one, the analysis unit judges that the coordinate information superposition processing is sequentially carried out on the original remote sensing images corresponding to the selected alternatives through the processing unit to form superposition areas, and the superposition area with the most value area is selected from the superposition areas to judge so as to determine whether the reference remote sensing image is selected.
Further, a standard reference area occupation ratio is arranged in the analysis unit, when the processing unit performs coordinate information superposition processing on the original remote sensing image corresponding to the selected candidate item and the real-time remote sensing image to determine a superposition area, the analysis unit acquires the area value of the superposition area, calculates the occupation ratio of the area value of the superposition area to the total area value of the real-time remote sensing image, and compares the real-time reference area occupation ratio with the standard reference area occupation ratio as the real-time reference area occupation ratio,
if the real-time reference area occupation ratio is smaller than the standard reference area occupation ratio, the analysis unit judges that the reference remote sensing image of the real-time remote sensing image is not selected in the basic database, sends out an artificial GPS correction prompt, and stores the real-time remote sensing image corrected by the GPS into the basic database as an original remote sensing image in a target area;
And if the real-time reference area occupation ratio is larger than or equal to the standard reference area occupation ratio, the processing unit cuts the overlapped area part in the corresponding original remote sensing image, and takes the overlapped area of the cut original remote sensing image as the reference remote sensing image.
Further, the analysis unit can obtain the image size of the real-time remote sensing image, calculate the real-time pixel number of the real-time remote sensing image according to the image size of the real-time remote sensing image, when the number of the selected screening items is larger than one, the analysis unit cuts out the image size of the original remote sensing image corresponding to each selected screening item, and calculates the pixel number difference value of the pixel number of the real-time pixel number and the pixel number of each original remote sensing image according to the pixel number corresponding to each original remote sensing image, and the original remote sensing image corresponding to the minimum value of the pixel number difference value is selected, coordinate information superposition is carried out on the original remote sensing image and the real-time remote sensing image through the processing unit, so that each superposition area is formed, the processing unit cuts out the superposition area part in the original remote sensing image, and the superposition area of the cut original remote sensing image is used as a reference remote sensing image.
Further, when the analysis unit selects the reference remote sensing image, the processing unit can acquire a geometric center point of the reference remote sensing image as a reference point, make any straight line in the reference remote sensing image after passing the reference point, make the straight line intersect with the edge of the reference remote sensing image as a node of the straight line, take a straight line segment between the two nodes as a correction reference line, acquire gray values of pixels penetrated by the correction reference line, take the gray value of the reference point as a standard gray value, and calculate the gray conversion rate of pixels adjacent to the reference point on the correction reference line as a reference gray conversion rate;
the gray scale change rate VG= |Gi-Gj|/Gj, gj is the gray scale value corresponding to the pixel where the datum point is located, gi is the gray scale value of the calculated adjacent pixel, and when the gray scale conversion rate of the pixel adjacent to the datum point on the correction reference line is calculated, the two adjacent pixels on two sides of the datum point are respectively calculated.
Further, after calculating the reference gray level conversion rate of the pixels adjacent to the reference point on the correction reference line, the processing unit selects the same coordinate information in the real-time remote sensing image according to the reference point coordinate information of the reference remote sensing image and determines the same coordinate information as the reference point of the reference remote sensing image, calculates each gray level conversion rate of the pixels where the reference point is located and the pixels adjacent to the reference point in the real-time remote sensing image as each correction gray level conversion rate, and selects the pixel corresponding to the correction gray level conversion rate with the smallest difference value of the reference gray level conversion rate from each correction gray level conversion rate as the correction pixel;
After the process unit finishes marking of the correction pixels once, the process unit takes the selected adjacent pixels in the reference remote sensing image as the next reference point of the reference remote sensing image, takes the gray conversion rate of the adjacent pixels on the other side of the next reference point on the correction reference line as the reference gray conversion rate, takes the marked correction pixels as the next reference point of the real-time remote sensing image in the real-time remote sensing image, and selects the next correction pixels from the adjacent pixels of the next reference point of the real-time remote sensing image according to the reference gray conversion rate until all pixels on the correction reference line in the reference remote sensing image are calculated, a plurality of marked correction pixels are obtained in the real-time remote sensing image, and the center points of the correction pixels are subjected to line fitting to form a real-time transverse correction curve of the real-time remote sensing image.
Further, the processing unit makes a straight line perpendicular to the correction reference line at the reference point passing through the geometric center point in the reference remote sensing image as a second correction reference line, and repeats the operation of determining the real-time transverse correction curve of the real-time remote sensing image according to the correction reference line in the reference remote sensing image, and determines the real-time longitudinal correction curve in the real-time remote sensing image according to the second correction reference line in the reference remote sensing image.
Further, the processing unit can mark a correction reference line in the reference remote sensing image in the real-time remote sensing image by an image position, fit a real-time transverse correction curve of the real-time remote sensing image to the correction reference line of the image position mark, transversely stretch the real-time remote sensing image in the direction of the vertical and correction reference lines according to the fitting distance of the real-time transverse correction curve, mark a second correction reference line in the reference remote sensing image in the real-time remote sensing image by the image position, fit a real-time longitudinal correction curve of the real-time remote sensing image to the second correction reference line of the image position mark, longitudinally stretch the real-time remote sensing image in the direction of the vertical and second correction reference line according to the fitting distance of the real-time longitudinal correction curve, and finish correction of the real-time remote sensing image.
Compared with the prior art, the method has the advantages that through establishing a basic database storing a plurality of original remote sensing images in a target area for remote sensing image acquisition, more accurate correction basic data can be provided for the real-time remote sensing image acquired by the acquisition unit, the position information and the image size of the real-time remote sensing data acquired by the acquisition unit in real time are judged in multiple aspects through the analysis unit, an accurate reference remote sensing image is selected in the basic database, meanwhile, a correction reference line is determined in the reference remote sensing image through the processing unit, a real-time transverse correction curve is determined in the real-time remote sensing image by the gray level conversion rate of each pixel in the correction reference line, a second correction reference line is determined in the reference remote sensing image, a real-time longitudinal correction curve is determined in the real-time remote sensing image by the gray level conversion rate of each pixel in the second correction reference line, the real-time remote sensing image is corrected in a linear mode, the real-time remote sensing image is corrected accurately on the premise that the accurate reference remote sensing image is used as basic data support, and the definition of the corrected real-time remote sensing image is improved.
Further, the analysis unit judges according to the coordinate information corresponding to the edge of the real-time remote sensing image, determines whether the selected original remote sensing image comprises the acquisition area of the real-time remote sensing image, takes the original remote sensing image as a screening item when the analysis unit judges that the actual coordinate range of the original remote sensing image comprises the acquisition area of the whole real-time remote sensing image, takes the original remote sensing image as a candidate item when the analysis unit judges that the actual coordinate range of the original remote sensing image comprises the acquisition area of a part of the real-time remote sensing image, and realizes intelligent classification of the original remote sensing image so as to ensure accurate selection of the reference remote sensing image.
Further, when the analysis unit finishes the judgment of the coordinate information of all original remote sensing images in the basic database, the original remote sensing images corresponding to the screening items are preferentially selected to serve as the basis for selecting the reference remote sensing images according to the number of the selected screening items and the number of the candidate items, and when the selected screening items do not exist, the number of the candidate items is judged to determine whether the reference remote sensing images are selected or not, or the analysis correction processing is abandoned, and the accuracy of real-time remote sensing image correction is further ensured by prompting the manual GPS correction processing.
In particular, when the analysis unit selects the reference remote sensing image from the original remote sensing image corresponding to the candidate, the analysis unit judges according to the area ratio occupied by the overlapping area of the images, and selects the overlapping part of the original remote sensing image with the largest real-time reference area occupation ratio as the reference remote sensing image on the basis that the overlapping part accords with the standard reference area occupation ratio, thereby guaranteeing the referential of the reference remote sensing image, improving the correction quality of the real-time remote sensing image and guaranteeing the correction definition of the real-time remote sensing image.
Further, when the reference remote sensing image is selected for each screening item, the original remote sensing image closest to the image size of the real-time remote sensing image is selected by comparing the acquired image sizes, so that the characteristic points in the standard image can be more accurately calibrated, and the correction effect of the real-time remote sensing image can be further improved.
Further, by cutting the overlapping area of the original remote sensing image and determining the reference remote sensing image, the image of the image pair correction effect outside the non-real-time remote sensing image area can be effectively avoided, and the real-time remote sensing image correction effect is further improved.
Further, the geometric center point of the selected reference remote sensing image, namely the center of gravity position of the reference remote sensing image in the plane, can be flexibly set according to the setting of correction times, and when the unit correction is carried out, the geometric center point is selected as a datum point, and a correction reference line is determined through the datum point, so that the integral gray level change condition of the reference remote sensing image can be expressed, and the correction of the real-time remote sensing image is facilitated.
Further, a correction reference line is determined in a reference remote sensing image through a processing unit, a real-time transverse correction curve is determined in a real-time remote sensing image according to the gray level conversion rate of each pixel in the correction reference line, a second correction reference line is determined in the reference remote sensing image, a real-time longitudinal correction curve is determined in the real-time remote sensing image according to the gray level conversion rate of each pixel in the second correction reference line, the real-time transverse correction curve is fitted to the correction reference line of the image position mark through transverse stretching fitting of the real-time image, and the real-time longitudinal correction curve is fitted to the second correction reference line of the image position mark through longitudinal stretching fitting of the real-time image, so that linear correction of the real-time remote sensing image is realized, and the correction effect of the real-time remote sensing image is improved.
Drawings
FIG. 1 is a schematic diagram of an online remote sensing image analysis system according to the present embodiment;
FIG. 2 is a schematic diagram of a basic database according to the present embodiment;
fig. 3 is a schematic diagram of a reference point adjacent pixel according to the present embodiment.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1, which is a schematic diagram of an on-line analysis processing system for remote sensing images according to the present embodiment, the present embodiment discloses an on-line analysis processing system for remote sensing images, which includes,
the acquisition unit is used for acquiring real-time remote sensing data in a target area and converting the real-time remote sensing data to form a real-time remote sensing image;
the basic database is internally stored with a plurality of original remote sensing images of the target area, and each original remote sensing image comprises image position corresponding coordinate information;
the analysis unit is respectively connected with the acquisition unit and the basic database, can screen each original remote sensing image in the basic database according to the position information of the real-time remote sensing image acquired by the acquisition unit, determines an original remote sensing image according to the screening result and the image size of the real-time remote sensing image, and takes the superposition area of the original remote sensing image after the original remote sensing image is sheared as a reference remote sensing image after the processing unit is used for superposition processing and shearing of the original remote sensing image and the real-time remote sensing image;
the processing unit is respectively connected with the acquisition unit, the basic database and the analysis unit, can determine a datum point in the selected reference remote sensing image by using a geometric center, determine a correction reference line after the datum point and a second correction reference line perpendicular to the correction reference line, determine a real-time transverse correction curve in the real-time remote sensing image according to the gray scale conversion rate of each pixel on the correction reference line in the reference remote sensing image, determine a real-time longitudinal correction curve in the real-time remote sensing image according to the gray scale conversion rate of each pixel on the second correction reference line in the reference remote sensing image, transversely stretch the real-time remote sensing image by using the fitting of the correction reference line and the real-time transverse correction curve, and longitudinally stretch the real-time remote sensing image by using the fitting of the second correction reference line and the real-time longitudinal correction curve, thereby completing the correction of the real-time remote sensing image.
With continued reference to fig. 2, a schematic diagram of the basic database according to this embodiment is shown, by establishing a basic database storing a plurality of original remote sensing images for a target area where remote sensing image acquisition is performed, more accurate correction basic data can be provided for a real-time remote sensing image acquired by an acquisition unit, and multiple aspects of position information and image size of the real-time remote sensing data acquired by the acquisition unit are determined by an analysis unit, an accurate reference remote sensing image is selected in the basic database, meanwhile, a correction reference line is determined in a reference remote sensing image by a processing unit, a real-time transverse correction curve is determined in the real-time remote sensing image by a gray-scale conversion rate of each pixel in the correction reference line, a second correction reference line is determined in the reference remote sensing image, and a real-time longitudinal correction curve is determined in the real-time remote sensing image by a gray-scale conversion rate of each pixel in the second correction reference line, so that linear correction of the real-time remote sensing image is realized, and the real-time remote sensing image is accurately corrected and the definition of the corrected real-time remote sensing image is improved on the premise that the accurate reference remote sensing image is supported by the basis data.
Specifically, the analysis unit can acquire the position information of the real-time remote sensing image acquired by the acquisition unit, the position information comprises coordinate information corresponding to the edge of the real-time remote sensing image, the analysis unit matches the acquired coordinate information corresponding to the edge of the real-time remote sensing image with all the coordinate information corresponding to the position of any one of the original remote sensing images in the basic database,
If the coordinate information corresponding to the edge of the real-time remote sensing image is all in the coordinate information corresponding to the original remote sensing image with current contrast, the analysis unit takes the original remote sensing image with current contrast as a screening item;
if the coordinate information corresponding to the edge of the real-time remote sensing image exists in the part which is in the coordinate information corresponding to the original remote sensing image with current contrast, the analysis unit takes the original remote sensing image with current contrast as an alternative;
if the coordinate information corresponding to the edge of the real-time remote sensing image does not have a part in the coordinate information corresponding to the original remote sensing image with current contrast, the analysis unit judges that the original remote sensing image with current contrast is an invalid reference image and does not select the original remote sensing image with current contrast;
and the analysis unit sequentially carries out matching judgment on each original remote sensing image in the basic database and the real-time remote sensing image until all original remote sensing images in the basic database are matched.
The analysis unit judges whether the selected original remote sensing image comprises a real-time remote sensing image acquisition area or not according to the coordinate information corresponding to the edge of the real-time remote sensing image, when the analysis unit judges that the actual coordinate range of the original remote sensing image comprises the whole real-time remote sensing image acquisition area, the real coordinate range of the original remote sensing image is used as a screening item, and when the actual coordinate range of the original remote sensing image comprises a part of real-time remote sensing image acquisition area, the real coordinate range of the original remote sensing image is judged to be used as an alternative item, so that the original remote sensing image is intelligently classified, and the accuracy of selecting the reference remote sensing image is guaranteed.
Specifically, the analysis unit judges the number of the selected screening items after all the original remote sensing images in the basic database are matched,
if the number of the selected screening options is zero, the analysis unit judges the number of the selected alternatives to determine whether to select the reference remote sensing image;
if the number of the selected screening items is one, the analysis unit performs coordinate information superposition processing on the original remote sensing image corresponding to the selected screening items and the real-time remote sensing image through the processing unit to form superposition areas, the processing unit cuts out the superposition areas in the original remote sensing image, and the superposition areas of the cut original remote sensing image are used as reference remote sensing images;
if the number of the selected screening items is greater than one, the analysis unit acquires the image size of the real-time remote sensing image, and selects an original remote sensing image from the original remote sensing images corresponding to the selected screening items to determine the reference remote sensing image.
Specifically, when the number of the selected options is zero, the analysis unit acquires the number of the selected options and determines,
If the number of the selected alternatives is zero, the analysis unit judges that the reference remote sensing image of the real-time remote sensing image is not selected in the basic database, sends out an artificial GPS correction prompt, and stores the real-time remote sensing image corrected by the GPS in the basic database as an original remote sensing image in a target area;
if the number of the selected alternatives is one, the analysis unit judges that the original remote sensing image corresponding to the selected alternatives and the real-time remote sensing image are subjected to coordinate information superposition processing through the processing unit, and judges the image area of the superposition area so as to determine whether to select the reference remote sensing image;
if the number of the selected alternatives is greater than one, the analysis unit judges that the coordinate information superposition processing is sequentially carried out on the original remote sensing images corresponding to the selected alternatives through the processing unit to form superposition areas, and the superposition area with the most value area is selected from the superposition areas to judge so as to determine whether the reference remote sensing image is selected.
When the analysis unit finishes the judgment of the coordinate information on all original remote sensing images in the basic database, the original remote sensing images corresponding to the screening items are preferentially selected to serve as the basis for selecting the reference remote sensing images according to the number of the selected screening items and the number of the candidate items, and when the selected screening items do not exist, the number of the candidate items is judged to determine whether the reference remote sensing images are selected or not, or the analysis correction processing is abandoned, and the manual GPS correction processing is carried out through prompting, so that the accuracy of real-time remote sensing image correction is further ensured.
Specifically, a standard reference area occupation ratio is arranged in the analysis unit, when the processing unit performs coordinate information superposition processing on the original remote sensing image corresponding to the selected candidate item and the real-time remote sensing image to determine a superposition area, the analysis unit acquires the area value of the superposition area, calculates the occupation ratio of the area value of the superposition area to the total area value of the real-time remote sensing image, takes the occupation ratio as the real-time reference area occupation ratio, compares the real-time reference area occupation ratio with the standard reference area occupation ratio,
if the real-time reference area occupation ratio is smaller than the standard reference area occupation ratio, the analysis unit judges that the reference remote sensing image of the real-time remote sensing image is not selected in the basic database, sends out an artificial GPS correction prompt, and stores the real-time remote sensing image corrected by the GPS into the basic database as an original remote sensing image in a target area;
and if the real-time reference area occupation ratio is larger than or equal to the standard reference area occupation ratio, the processing unit cuts the overlapped area part in the corresponding original remote sensing image, and takes the overlapped area of the cut original remote sensing image as the reference remote sensing image.
When the analysis unit selects the reference remote sensing image from the original remote sensing image corresponding to the alternative, the analysis unit judges according to the area ratio occupied by the overlapping area of the images, selects the overlapping part of the original remote sensing image with the largest real-time reference area occupation ratio as the reference remote sensing image on the basis of conforming to the standard reference area occupation ratio, ensures the referential of the reference remote sensing image, improves the correction quality of the real-time remote sensing image, and ensures the correction definition of the real-time remote sensing image.
Specifically, the analysis unit can obtain the image size of the real-time remote sensing image, calculate the real-time pixel number of the real-time remote sensing image according to the image size of the real-time remote sensing image, when the number of the selected screening items is greater than one, the analysis unit cuts out the image size of the original remote sensing image corresponding to each selected screening item, and calculates the pixel number difference value of the pixel number of the real-time pixel number and the pixel number of each original remote sensing image according to the pixel number corresponding to each original remote sensing image, and the original remote sensing image corresponding to the minimum value of the pixel number difference value is selected, coordinate information superposition is carried out on the original remote sensing image and the real-time remote sensing image through the processing unit, so as to form each superposition area, the processing unit cuts out the superposition area part in the original remote sensing image, and takes the superposition area of the cut original remote sensing image as the reference remote sensing image.
When the reference remote sensing image is selected for each screening item, the original remote sensing image closest to the image size of the real-time remote sensing image is selected by comparing the acquired image sizes, so that the characteristic points in the standard image can be more accurately calibrated, and the correction effect of the real-time remote sensing image can be further improved.
In this embodiment, by clipping the overlapping area of the original remote sensing image and determining the reference remote sensing image, an image with a correction effect of an image outside the non-real-time remote sensing image area can be effectively avoided, and the correction effect of the real-time remote sensing image is further improved.
With continued reference to fig. 3, a schematic diagram of adjacent pixels of the reference point according to the present embodiment includes a reference point 1, a pixel 2 where the reference point is located, a correction reference line 3, a first adjacent pixel 4 and a second adjacent pixel 5,
specifically, when the analysis unit selects the reference remote sensing image, the processing unit can acquire the geometric center point of the reference remote sensing image as a reference point, make any straight line in the reference remote sensing image through the reference point, make the straight line intersect with the edge of the reference remote sensing image to form a node of the straight line, take the straight line segment between the two nodes as a correction reference line, acquire the gray value of each pixel penetrated by the correction reference line, take the gray value of the reference point as a standard gray value, and calculate the gray conversion rate of the pixel adjacent to the reference point on the correction reference line as a reference gray conversion rate;
the gray scale change rate VG= |Gi-Gj|/Gj, gj is the gray scale value corresponding to the pixel where the datum point is located, gi is the gray scale value of the calculated adjacent pixel, and when the gray scale conversion rate of the pixel adjacent to the datum point on the correction reference line is calculated, the two adjacent pixels on two sides of the datum point are respectively calculated.
The geometric center point of the selected reference remote sensing image, namely the center of gravity position of the reference remote sensing image in the plane, can be flexibly set according to the setting of correction times, the geometric center point is selected as a datum point when unit correction is carried out, and a correction reference line is determined through the datum point, so that the integral gray scale change condition of the reference remote sensing image can be represented, the correction of the real-time remote sensing image is facilitated, and in the embodiment, 8 pixels around any pixel are all adjacent pixels of the pixel.
Specifically, after calculating the reference gray level conversion rate of the pixels adjacent to the reference point on the correction reference line, the processing unit selects the same coordinate information in the real-time remote sensing image according to the reference point coordinate information of the reference remote sensing image and determines the same coordinate information as the reference point of the reference remote sensing image, calculates each gray level conversion rate of the pixels where the reference point is located and the pixels adjacent to the reference point in the real-time remote sensing image as each correction gray level conversion rate, and selects the pixel corresponding to the correction gray level conversion rate with the smallest difference value of the reference gray level conversion rate from each correction gray level conversion rate as the correction pixel;
after the process unit finishes marking of the correction pixels once, the process unit takes the selected adjacent pixels in the reference remote sensing image as the next reference point of the reference remote sensing image, takes the gray conversion rate of the adjacent pixels on the other side of the next reference point on the correction reference line as the reference gray conversion rate, takes the marked correction pixels as the next reference point of the real-time remote sensing image in the real-time remote sensing image, and selects the next correction pixels from the adjacent pixels of the next reference point of the real-time remote sensing image according to the reference gray conversion rate until all pixels on the correction reference line in the reference remote sensing image are calculated, a plurality of marked correction pixels are obtained in the real-time remote sensing image, and the center points of the correction pixels are subjected to line fitting to form a real-time transverse correction curve of the real-time remote sensing image.
Specifically, the processing unit makes a straight line perpendicular to the correction reference line at a reference point passing through the geometric center point in the reference remote sensing image as a second correction reference line, and repeats the operation of determining the real-time transverse correction curve of the real-time remote sensing image according to the correction reference line in the reference remote sensing image, and determines the real-time longitudinal correction curve in the real-time remote sensing image according to the second correction reference line in the reference remote sensing image.
In this embodiment, the real-time remote sensing image is corrected by determining the real-time transverse correction curve and the real-time longitudinal correction curve, and multiple sets of real-time correction curves can be determined in the real-time remote sensing image for multiple corrections according to the actual correction conditions and requirements, but when the determined correction direction of the real-time correction curves is not vertical, the mutual images between the real-time correction curves under the correction conditions need to be considered, and the affected positions are filtered or averaged.
Specifically, the processing unit can mark a correction reference line in a reference remote sensing image in a real-time remote sensing image by an image position, fit a real-time transverse correction curve of the real-time remote sensing image to the correction reference line of the image position mark, transversely stretch the real-time remote sensing image in the direction of the vertical and correction reference lines according to the fitting distance of the real-time transverse correction curve, mark a second correction reference line in the reference remote sensing image in the real-time remote sensing image by the image position, fit a real-time longitudinal correction curve of the real-time remote sensing image to the second correction reference line of the image position mark, and longitudinally stretch the real-time remote sensing image in the direction of the vertical and second correction reference lines according to the fitting distance of the real-time longitudinal correction curve to finish correction of the real-time remote sensing image.
The processing unit is used for determining a correction reference line in the reference remote sensing image, determining a real-time transverse correction curve in the real-time remote sensing image according to the gray level conversion rate of each pixel in the correction reference line, determining a second correction reference line in the reference remote sensing image, determining a real-time longitudinal correction curve in the real-time remote sensing image according to the gray level conversion rate of each pixel in the second correction reference line, fitting the real-time transverse correction curve to the correction reference line of the image position mark through transverse stretching fitting of the real-time image, fitting the real-time longitudinal correction curve to the second correction reference line of the image position mark through longitudinal stretching fitting of the real-time image, and realizing linear correction of the real-time remote sensing image and improving the correction effect of the real-time remote sensing image.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
The foregoing description is only of the preferred embodiments of the invention and is not intended to limit the invention; various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A remote sensing image on-line analysis processing system is characterized by comprising,
the acquisition unit is used for acquiring real-time remote sensing data in a target area and converting the real-time remote sensing data to form a real-time remote sensing image;
the basic database is internally stored with a plurality of original remote sensing images of the target area, and each original remote sensing image comprises image position corresponding coordinate information;
the analysis unit is respectively connected with the acquisition unit and the basic database, can screen each original remote sensing image in the basic database according to the position information of the real-time remote sensing image acquired by the acquisition unit, determines an original remote sensing image according to the screening result and the image size of the real-time remote sensing image, and takes the superposition area of the original remote sensing image after the original remote sensing image is sheared as a reference remote sensing image after the processing unit is used for superposition processing and shearing of the original remote sensing image and the real-time remote sensing image;
The processing unit is respectively connected with the acquisition unit, the basic database and the analysis unit, can determine a datum point in the selected reference remote sensing image by using a geometric center, determine a correction reference line after the datum point and a second correction reference line perpendicular to the correction reference line, determine a real-time transverse correction curve in the real-time remote sensing image according to the gray scale conversion rate of each pixel on the correction reference line in the reference remote sensing image, determine a real-time longitudinal correction curve in the real-time remote sensing image according to the gray scale conversion rate of each pixel on the second correction reference line in the reference remote sensing image, transversely stretch the real-time remote sensing image by using the fitting of the correction reference line and the real-time transverse correction curve, and longitudinally stretch the real-time remote sensing image by using the fitting of the second correction reference line and the real-time longitudinal correction curve, thereby completing the correction of the real-time remote sensing image.
2. The system of claim 1, wherein the analysis unit is capable of acquiring the position information of the real-time remote sensing image acquired by the acquisition unit, the position information includes coordinate information corresponding to an edge of the real-time remote sensing image, the analysis unit matches the acquired coordinate information corresponding to the edge of the real-time remote sensing image with coordinate information corresponding to all image positions included in any one of the original remote sensing images in the base database,
If the coordinate information corresponding to the edge of the real-time remote sensing image is all in the coordinate information corresponding to the original remote sensing image with current contrast, the analysis unit takes the original remote sensing image with current contrast as a screening item;
if the coordinate information corresponding to the edge of the real-time remote sensing image exists in the part which is in the coordinate information corresponding to the original remote sensing image with current contrast, the analysis unit takes the original remote sensing image with current contrast as an alternative;
if the coordinate information corresponding to the edge of the real-time remote sensing image does not have a part in the coordinate information corresponding to the original remote sensing image with current contrast, the analysis unit judges that the original remote sensing image with current contrast is an invalid reference image and does not select the original remote sensing image with current contrast;
and the analysis unit sequentially carries out matching judgment on each original remote sensing image in the basic database and the real-time remote sensing image until all original remote sensing images in the basic database are matched.
3. The system of claim 2, wherein the analysis unit determines the number of selected screening terms after all the original remote sensing images in the base database are matched,
If the number of the selected screening options is zero, the analysis unit judges the number of the selected alternatives to determine whether to select the reference remote sensing image;
if the number of the selected screening items is one, the analysis unit performs coordinate information superposition processing on the original remote sensing image corresponding to the selected screening items and the real-time remote sensing image through the processing unit to form superposition areas, the processing unit cuts out the superposition areas in the original remote sensing image, and the superposition areas of the cut original remote sensing image are used as reference remote sensing images;
if the number of the selected screening items is greater than one, the analysis unit acquires the image size of the real-time remote sensing image, and selects an original remote sensing image from the original remote sensing images corresponding to the selected screening items to determine the reference remote sensing image.
4. The system of claim 3, wherein the analysis unit obtains the number of candidates to be selected and determines when the number of candidates to be selected is zero,
if the number of the selected alternatives is zero, the analysis unit judges that the reference remote sensing image of the real-time remote sensing image is not selected in the basic database, sends out an artificial GPS correction prompt, and stores the real-time remote sensing image corrected by the GPS in the basic database as an original remote sensing image in a target area;
If the number of the selected alternatives is one, the analysis unit judges that the original remote sensing image corresponding to the selected alternatives and the real-time remote sensing image are subjected to coordinate information superposition processing through the processing unit, and judges the image area of the superposition area so as to determine whether to select the reference remote sensing image;
if the number of the selected alternatives is greater than one, the analysis unit judges that the coordinate information superposition processing is sequentially carried out on the original remote sensing images corresponding to the selected alternatives through the processing unit to form superposition areas, and the superposition area with the most value area is selected from the superposition areas to judge so as to determine whether the reference remote sensing image is selected.
5. The on-line analysis processing system for remote sensing images according to claim 4, wherein a standard reference area occupation ratio is arranged in the analysis unit, when the processing unit performs coordinate information superposition processing on the original remote sensing image corresponding to the selected candidate item and the real-time remote sensing image to determine a superposition area, the analysis unit obtains an area value of the superposition area, calculates the occupation ratio of the area value of the superposition area to the total area value of the real-time remote sensing image, and uses the occupation ratio as the real-time reference area occupation ratio, the analysis unit compares the real-time reference area occupation ratio with the standard reference area occupation ratio,
If the real-time reference area occupation ratio is smaller than the standard reference area occupation ratio, the analysis unit judges that the reference remote sensing image of the real-time remote sensing image is not selected in the basic database, sends out an artificial GPS correction prompt, and stores the real-time remote sensing image corrected by the GPS into the basic database as an original remote sensing image in a target area;
and if the real-time reference area occupation ratio is larger than or equal to the standard reference area occupation ratio, the processing unit cuts the overlapped area part in the corresponding original remote sensing image, and takes the overlapped area of the cut original remote sensing image as the reference remote sensing image.
6. The remote sensing image online analysis processing system according to claim 3, wherein the analysis unit can obtain an image size of the real-time remote sensing image, calculate the number of real-time pixels of the real-time remote sensing image according to the image size of the real-time remote sensing image, when the number of the selected screening items is greater than one, the analysis unit cuts out the image size of the original remote sensing image corresponding to each selected screening item, and calculates the number of pixels corresponding to each original remote sensing image, the central control unit calculates the difference value between the number of real-time pixels and the number of pixels of each original remote sensing image, and the original remote sensing image corresponding to the minimum value of the difference value of the number of pixels is subjected to coordinate information coincidence processing on the original remote sensing image and the real-time remote sensing image through the processing unit, so that each coincidence region is formed, the processing unit cuts out the coincidence region part in the original remote sensing image, and takes the coincidence region of the cut-out original remote sensing image as a reference remote sensing image.
7. The remote sensing image online analysis processing system according to claim 1, wherein the processing unit is capable of acquiring a geometric center point of a reference remote sensing image as a reference point when the analysis unit selects the reference remote sensing image, making any straight line in the reference remote sensing image after passing through the reference point, intersecting the straight line with an edge of the reference remote sensing image as a node of the straight line, taking a straight line segment between the two nodes as a correction reference line, acquiring gray values of pixels penetrated by the correction reference line, taking the gray values of the reference point as standard gray values, and calculating gray conversion rates of pixels adjacent to the reference point on the correction reference line as reference gray conversion rates;
the gray scale change rate VG= |Gi-Gj|/Gj, gj is the gray scale value corresponding to the pixel where the datum point is located, gi is the gray scale value of the calculated adjacent pixel, and when the gray scale conversion rate of the pixel adjacent to the datum point on the correction reference line is calculated, the two adjacent pixels on two sides of the datum point are respectively calculated.
8. The system according to claim 7, wherein the processing unit, after calculating the reference gray level conversion rate of the pixels adjacent to the reference point on the corrected reference line, selects the same coordinate information in the real-time remote sensing image according to the reference point coordinate information of the reference remote sensing image and determines the same coordinate information as the reference point of the reference remote sensing image, calculates each gray level conversion rate of the pixels where the reference point is located and the pixels adjacent thereto in the real-time remote sensing image as each corrected gray level conversion rate, and selects the pixel corresponding to the corrected gray level conversion rate having the smallest difference value from the reference gray level conversion rates from among the corrected gray level conversion rates as the corrected pixel;
After the process unit finishes marking of the correction pixels once, the process unit takes the selected adjacent pixels in the reference remote sensing image as the next reference point of the reference remote sensing image, takes the gray conversion rate of the adjacent pixels on the other side of the next reference point on the correction reference line as the reference gray conversion rate, takes the marked correction pixels as the next reference point of the real-time remote sensing image in the real-time remote sensing image, and selects the next correction pixels from the adjacent pixels of the next reference point of the real-time remote sensing image according to the reference gray conversion rate until all pixels on the correction reference line in the reference remote sensing image are calculated, a plurality of marked correction pixels are obtained in the real-time remote sensing image, and the center points of the correction pixels are subjected to line fitting to form a real-time transverse correction curve of the real-time remote sensing image.
9. The system according to claim 8, wherein the processing unit makes a straight line perpendicular to the correction reference line as a second correction reference line at a reference point of the reference remote sensing image that passes through the geometric center point, and the processing unit repeats the above operation of determining the real-time lateral correction curve of the real-time remote sensing image from the correction reference line in the reference remote sensing image, and determines the real-time longitudinal correction curve in the real-time remote sensing image from the second correction reference line in the reference remote sensing image.
10. The remote sensing image online analysis processing system according to claim 9, wherein the processing unit is capable of marking a correction reference line in a reference remote sensing image in an image position in a real-time remote sensing image, fitting a real-time transverse correction curve of the real-time remote sensing image to the correction reference line of the image position mark, transversely stretching the real-time remote sensing image in a direction perpendicular to the correction reference line according to a fitting distance of the real-time transverse correction curve, marking a second correction reference line in the reference remote sensing image in the image position in the real-time remote sensing image, fitting a real-time longitudinal correction curve of the real-time remote sensing image to the second correction reference line of the image position mark, longitudinally stretching the real-time remote sensing image in a direction perpendicular to the second correction reference line according to a fitting distance of the real-time longitudinal correction curve, and completing the correction of the real-time remote sensing image.
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