CN117690028B - Target detection method and system based on remote sensing sensor - Google Patents
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Abstract
The invention provides a target detection method and a target detection system based on a remote sensing sensor, which relate to the technical field of data processing, and the method comprises the following steps: the invention solves the technical problem of inaccurate detection targets caused by lack of control in the process of detecting the targets in the prior art, realizes accurate detection by a remote sensing sensor, and improves the accuracy of the detection targets.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a target detection method and system based on a remote sensing sensor.
Background
In recent years, the object detection technology is vigorously developed, the land optical image resolution is higher, the information quantity is more abundant, and the method has outstanding advantages in short-distance land object detection tasks. However, due to the limitations of the special imaging environment, which is affected by the land topography, the image often has problems such as noise interference, blurred texture features, and the like. Meanwhile, due to the lack of control in the process of detecting the target in the prior art, the technical problem of inaccurate target detection is caused.
Disclosure of Invention
The application provides a target detection method and a target detection system based on a remote sensing sensor, which are used for solving the technical problem in the prior art that the detected target is inaccurate due to the lack of control in the process of detecting the target in the prior art.
In view of the above problems, the present application provides a target detection method and system based on a remote sensing sensor.
In a first aspect, the present application provides a method for detecting an object based on a remote sensing sensor, the method comprising: determining a target image set based on the spectrum images in the target area acquired by the panoramic camera; acquiring an influence spectrum feature set, wherein the influence spectrum feature set is obtained by extracting spectrum features of the target image set through the resolution imaging spectrometer; calculating statistics of the target image set based on the influence spectrum feature set, and obtaining N image histograms, wherein the N image histograms have a corresponding relation with the target image set, and N is an integer greater than 1; extracting spectral change characteristics in a target area according to the N image histograms, and drawing a spectral change curve chart according to the spectral change characteristics; and obtaining a target spectrum value through the spectrum change curve graph, and locking a detection target based on the target spectrum value.
In a second aspect, the present application provides a remote sensor based object detection system, the system comprising: the image acquisition module is used for acquiring a spectrum image in a target area based on the panoramic camera and determining a target image set; the characteristic extraction module is used for obtaining an influence spectrum characteristic set, wherein the influence spectrum characteristic set is obtained by extracting spectrum characteristics of the target image set through the resolution imaging spectrometer; the first calculation module is used for calculating statistics of the target image set based on the influence spectrum feature set to obtain N image histograms, wherein the N image histograms have a corresponding relation with the target image set, and N is an integer larger than 1; the curve drawing module is used for extracting spectral change characteristics in a target area according to the N image histograms and drawing a spectral change curve according to the spectral change characteristics; and the target locking module is used for obtaining a target spectrum value through the spectrum change curve graph and locking a detection target based on the target spectrum value.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
the target detection method and system based on the remote sensing sensor relate to the technical field of data processing, and solve the technical problem that in the prior art, due to lack of control in the process of detecting targets, the detected targets are inaccurate, so that accurate detection through the remote sensing sensor is realized, and the accuracy of the detected targets is improved.
Drawings
FIG. 1 is a schematic flow chart of a target detection method based on a remote sensing sensor;
FIG. 2 is a schematic diagram of determining a target image flow in a target detection method based on a remote sensing sensor;
fig. 3 is a schematic structural diagram of an object detection system based on a remote sensing sensor.
Reference numerals illustrate: the device comprises an image acquisition module 1, a feature extraction module 2, a first calculation module 3, a first calculation module 4 and a target locking module 5.
Detailed Description
The target detection method and system based on the remote sensing sensor are used for solving the technical problem that in the prior art, due to the fact that management and control in the target detection process are lacked in the prior art, the detected target is inaccurate.
Example 1
As shown in fig. 1, an embodiment of the present application provides a target detection method based on a remote sensing sensor, where the method is applied to a target detection system based on a remote sensing sensor, where the system is connected to a user receiving end and a service sensing end, the service sensing end includes a remote sensing sensor, and a panorama camera and a resolution imaging spectrometer are embedded in the service sensing end, and the method includes:
step A100: determining a target image set based on the spectrum images in the target area acquired by the panoramic camera;
further, as shown in fig. 2, step a100 of the present application further includes:
step A110: defining a region boundary based on a target detection range, and determining the target region according to the region boundary;
step A120: selecting an acquisition path of the panoramic camera according to the target area, recording image spectrum distribution data through the acquisition path, and obtaining spectrum distribution uniformity;
step a130: and sequentially determining a plurality of target images according to the spectrum distribution uniformity, and determining the target image set through the plurality of target images.
In the application, the target detection method based on the remote sensor provided by the embodiment of the application is applied to a target detection system based on the remote sensor, the system is connected with a user receiving end and a service sensing end, the service sensing end comprises the remote sensor, a panorama camera and a resolution imaging spectrometer are embedded in the service sensing end, and the panorama camera embedded in the remote sensor is used for collecting spectrum image parameters in a target area.
The panoramic camera projects an optical image generated by a target area through a mirror onto the surface of an image sensor, then converts the optical image into an electric signal, converts the electric signal into a digital image signal after analog-to-digital conversion, sends the digital image signal to a digital signal processing chip for processing, then transmits the digital image signal to a computer for processing through a USB interface, and can acquire spectral image parameters in the target area through a display.
And meanwhile, image acquisition is carried out on a target area according to the determined acquisition path, image spectrum distribution data corresponding to the acquired image data is recorded, and spectrum distribution uniformity is obtained, wherein the spectrum distribution uniformity is that reflection brightness distribution or fluorescence brightness distribution of a plurality of narrow-band monochromatic lights which are densely and uniformly distributed on an object to be inspected in a certain spectrum range is recorded through an imaging spectrometer, so that a spectrum image set formed by a plurality of monochromatic light images is formed, a plurality of target images corresponding to the formed spectrum image set are sequentially determined on the basis, the plurality of target images are summarized and integrated and then recorded as a target image set, and target detection based on a remote sensing sensor is realized for later stage as an important reference basis.
Step A200: acquiring an influence spectrum feature set, wherein the influence spectrum feature set is obtained by extracting spectrum features of the target image set through the resolution imaging spectrometer;
further, step a200 of the present application further includes:
step a210: extracting emission spectrum information in the target area by the resolution imaging spectrometer;
step A220: constructing an image gray scale mean function based on the emission spectrum information;
step A230: and carrying out spectral analysis on the target image set according to the image gray level average function, and determining the influence spectrum characteristic set.
In the application, the resolution imaging spectrometer embedded in the remote sensing sensor is used for collecting parameters of spectral features, further, the emission spectrum information is extracted in a target area through the resolution imaging spectrometer, the resolution imaging spectrometer is used for obtaining almost continuous spectrum data of each pixel while obtaining a large number of ground object target narrow-band continuous spectrum images, and each atom has a characteristic spectral line, so that substances can be identified and chemical compositions of the substances can be determined according to the spectrum data obtained by the resolution imaging spectrometer, the extraction of the spectrum information emitted in the target area is completed, and further, an image gray average function is constructed according to pixel points corresponding to spectrum elements in the emission spectrum information, and the constructed image gray average function is as follows:
wherein,the image gray average value is M is the Mth image in the target image set, N is the Nth image in the target image set, M is not equal to N, and i is the Mth imageThe gray value of the pixel point in the image is i the gray value of the pixel point in the Nth image.
Further, spectral analysis is performed on the target image set according to the image gray level average function, namely, each image in the target image set is substituted into the image gray level average function in sequence to perform image gray level conversion, so that spectral analysis is completed, the content of the element in the substance reaches 10 minus 10 times square grams through image gray level conversion, the characteristic spectral line affecting the image can be extracted from the spectrum, the spectral characteristic set is determined, and further, the purpose of realizing target detection based on the remote sensing sensor is ensured.
Step A300: calculating statistics of the target image set based on the influence spectrum feature set, and obtaining N image histograms, wherein the N image histograms have a corresponding relation with the target image set, and N is an integer greater than 1;
further, step a300 of the present application further includes:
step a310: the statistics of the target image set comprises gray variance and gray standard deviation of the target image set;
step A320: judging a plurality of brightness values in the target image set based on the gray variance and the gray standard deviation;
step a330: and carrying out statistical distribution according to the pixel numbers of the brightness values to obtain the N image histograms.
Further, step a330 of the present application includes:
step A331: constructing a ground coordinate system based on the target area;
step a332: constructing an acquisition position coordinate system and an instantaneous acquisition coordinate system of the remote sensor based on the acquisition position of the panoramic camera;
step a333: establishing a correlation factor of the ground coordinate system and the instantaneous acquisition coordinate system by using a collineation condition;
step A334: performing real-time auxiliary adjustment on the acquisition position coordinate system based on the correlation factor to acquire a plurality of pixel coordinate points of the brightness values;
step a335: and determining the number of the plurality of pixels according to the coordinate points of the plurality of pixels.
In the present application,
the statistics of the target image set comprises the gray variance and the gray standard deviation of the target image set, wherein the gray variance and the gray standard deviation of the target image set are obtained by calculation through the following standard deviation formula:
wherein,is the standard deviation of the gray scale,the image gray average value is M is the Mth image in the target image set, N is the Nth image in the target image set, M is not equal to N, i is the gray value of the pixel point in the Mth image, and i is the gray value of the pixel point in the Nth imageIs the gray variance.
Further, judging a plurality of brightness values in the target image set based on gray variance and gray standard deviation, when the gray standard deviation of the image is small, the brightness values are concentrated, the image contrast is small, when the gray standard deviation of the image is large, the brightness values are scattered, the image contrast is large, so that the brightness values in the image are sequentially recorded, finally, according to the number of a plurality of pixels of the brightness values, the statistical distribution is performed, namely, respectively, constructing a ground coordinate system based on a target area, constructing an acquisition position coordinate system of a remote sensing sensor based on an acquisition position of a panoramic camera, and an instantaneous acquisition coordinate system, wherein the ground coordinate system is used for constructing an x-axis according to the north-south orientation of the ground, constructing a y-axis according to the east-west orientation of the ground, constructing a z-axis perpendicular to the ground at an original point where the x-axis and the y-axis intersect, so as to finish the construction of the ground maximum play, the acquisition position coordinate system and the instantaneous acquisition coordinate system of the remote sensor are both the space coordinate system layout based on the space position of the remote sensor, the instantaneous acquisition coordinate system is the coordinate system under the instant moment of the acquisition position, the acquisition position coordinate system and the instantaneous acquisition coordinate system can be the same coordinate system, further, the collineation condition is utilized to establish the association factors of the ground coordinate system and the instantaneous acquisition coordinate system, the collineation condition refers to the collineation of the projection center, the object point and the three points of the image point, the association factors are determined according to the association mapping coordinate points between the ground coordinate system and the instantaneous acquisition coordinate system, the association mapping coordinate points are stronger, the obtained association factors are taken as the basis, the real-time auxiliary adjustment of the remote sensor is carried out on the acquisition position coordinate system, and therefore the accuracy of the remote sensor during data sensing acquisition is improved, and then determining a plurality of pixel coordinate points corresponding to a plurality of brightness values in a coordinate system after real-time adjustment, recording a plurality of pixel numbers according to the pixel coordinate points in the coordinate system, finally acquiring N image histograms corresponding to the pixel numbers in the coordinate system according to statistical distribution among the recorded pixel numbers, wherein the abscissa in the N image histograms represents gray level change of an image, and the ordinate identifies the frequency of occurrence of any gray level in the image, so as to realize the target detection tamping foundation based on a remote sensing sensor.
Step A400: extracting spectral change characteristics in a target area according to the N image histograms, and drawing a spectral change curve chart according to the spectral change characteristics;
in this application, in order to better identify the detection target, the spectral variation characteristics in the target area are extracted by using the N image histograms obtained as the basis reference data, the spectrum is a pattern in which the dispersed monochromatic light is sequentially arranged according to the wavelength after the monochromatic light is split by the dispersion system, the light waves are generated by electrons moving inside atoms, and the movement conditions of the electrons inside atoms of various substances are different, so that the emitted light waves are different. The spectrum directly produced by the luminescence of an object in the emission spectrum is called the emission spectrum: continuous spectrum and open line spectrum. The spectrum of light which is continuously distributed and contains various colors of light ranging from red light to purple light is called a continuous spectrum. The emission spectrum of incandescent solids, liquids and high pressure gases is a continuous spectrum. The spectrum containing only some discontinuous bright lines is called bright line spectrum, the bright lines in the bright line spectrum are called spectral lines, each spectral line corresponds to light with different wavelengths, the emission spectrum of thin gas or metal vapor is the bright line spectrum, the spectrum change characteristic in a target area is determined on the basis, further, the spectrum change characteristic is drawn, namely, the light with different wavelengths is subjected to the drawing, the photoelectric sensitivity of a camera tube is different, namely, the relative sensitivity of a photoelectric element changes along with the change of the wavelength of light waves when the illumination of incident light is fixed, one photoelectric element is only sensitive to the incident light with a certain wavelength range, meanwhile, the corresponding sensitivity of the camera tube is measured by the light with different wavelengths, the spectrum sensitivity curve of the camera tube can be obtained, and the spectrum change characteristic is recorded as a spectrum change curve, so that the target detection based on a remote sensing sensor has a limiting effect.
Step A500: and obtaining a target spectrum value through the spectrum change curve graph, and locking a detection target based on the target spectrum value.
Further, step a500 of the present application further includes:
step A510: configuring an image spectrum verification period;
step A520: performing spectral image verification on the target spectral value in the image spectral period to obtain an image spectral verification result;
step a530: locking a detection target by taking the image spectrum verification result as an additional detection feature, and acquiring locking target data;
step a540: and sending the locking target data to the user receiving end.
In the application, on the basis of the drawn spectrum change curve graph, determining a spectrum value contained in a target area, marking the spectrum value as a target spectrum value, further, correspondingly configuring an image spectrum verification period according to the change fluctuation range of the target spectrum value in the spectrum change curve graph, namely defining the verification period in the fluctuation critical value of the target spectrum value, further, performing spectrum image verification on the target spectrum value in the image spectrum period, namely comparing the target spectrum value in the image spectrum period with the spectrum value in the same period of a history period, when the difference between the target spectrum value and the spectrum value is within a preset spectrum error threshold, the preset spectrum error threshold can be set to be 10%, the verification is regarded as passing, and marking the verification result as an image spectrum verification result, further, performing target detection by taking the image spectrum verification result as an additional detection feature, namely performing target detection by taking the verified target spectrum value as a detection reference value, thereby more accurately locking target data, finally sending the locked target data to a user receiving end to complete target detection, and improving the accuracy of target detection performed on a remote sensor in a later stage.
In summary, the target detection method based on the remote sensing sensor provided by the embodiment of the application at least includes the following technical effects, so that accurate detection by the remote sensing sensor is realized, and the accuracy of detecting the target is improved.
Example two
Based on the same inventive concept as the target detection method based on the remote sensing sensor in the foregoing embodiment, as shown in fig. 3, the present application provides a target detection system based on the remote sensing sensor, where the system includes:
the image acquisition module 1 is used for determining a target image set based on the spectrum image in the target area acquired by the panoramic camera;
the feature extraction module 2 is used for obtaining an influence spectrum feature set, wherein the influence spectrum feature set is obtained by extracting spectrum features of the target image set through the resolution imaging spectrometer;
the first calculating module 3 is configured to calculate statistics of the target image set based on the influence spectrum feature set, and obtain N image histograms, where N is an integer greater than 1, where the N image histograms have a correspondence with the target image set;
the graph drawing module 4 is used for extracting spectral change characteristics in a target area according to the N image histograms, and drawing a spectral change graph according to the spectral change characteristics;
and the target locking module 5 is used for obtaining a target spectrum value through the spectrum change curve graph, and locking a detection target based on the target spectrum value.
Further, the system further comprises:
the area determining module is used for defining an area boundary based on the target detection range and determining the target area according to the area boundary;
the recording module is used for selecting an acquisition path of the panoramic camera according to the target area, recording image spectral distribution data through the acquisition path and obtaining spectral distribution uniformity;
the image determining module is used for sequentially determining a plurality of target images according to the spectrum distribution uniformity and determining the target image set through the plurality of target images.
Further, the system further comprises:
the spectrum extraction module is used for extracting emission spectrum information in the target area through the resolution imaging spectrometer;
the function construction module is used for constructing an image gray level mean function based on the emission spectrum information;
and the spectrum analysis module is used for carrying out spectrum analysis on the target image set according to the image gray level average function and determining the influence spectrum characteristic set.
Further, the system further comprises:
the statistic of the target image set comprises a gray variance and a gray standard deviation of the target image set;
the brightness value acquisition module is used for judging a plurality of brightness values in the target image set based on the gray variance and the gray standard deviation;
and the statistical distribution module is used for carrying out statistical distribution according to the pixel numbers of the brightness values to obtain the N image histograms.
Further, the system further comprises:
the first coordinate system construction module is used for constructing a ground coordinate system based on the target area;
the second coordinate system construction module is used for constructing an acquisition position coordinate system and an instantaneous acquisition coordinate system of the remote sensing sensor based on the acquisition position of the panoramic camera;
the association module is used for establishing association factors of the ground coordinate system and the instantaneous acquisition coordinate system by using a collineation condition;
the auxiliary adjustment module is used for carrying out real-time auxiliary adjustment on the acquisition position coordinate system based on the association factors, and acquiring a plurality of pixel coordinate points of the brightness values;
and the pixel determining module is used for determining the number of the pixels according to the coordinate points of the pixels.
Further, the system further comprises:
the period configuration module is used for configuring the image spectrum verification period;
the image verification module is used for carrying out spectrum image verification on the target spectrum value in the image spectrum period to obtain an image spectrum verification result;
the detection locking module is used for locking a detection target by taking the image spectrum verification result as an additional detection characteristic to acquire locking target data;
and the data sending module is used for sending the locking target data to the user receiving end.
The foregoing detailed description of the method for detecting an object based on a remote sensor will clearly be known to those skilled in the art, and the device disclosed in this embodiment is relatively simple to describe, and the relevant places refer to the method section for description, since it corresponds to the method disclosed in the embodiment.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. The target detection method based on the remote sensing sensor is characterized in that the method is applied to a target detection system based on the remote sensing sensor, the system is connected with a user receiving end and a service sensing end, the service sensing end comprises the remote sensing sensor, a panoramic camera and a resolution imaging spectrometer are embedded in the service sensing end, and the method comprises the following steps:
determining a target image set based on the spectrum images in the target area acquired by the panoramic camera;
acquiring an influence spectrum feature set, wherein the influence spectrum feature set is obtained by extracting spectrum features of the target image set through the resolution imaging spectrometer;
calculating statistics of the target image set based on the influence spectrum feature set, and obtaining N image histograms, wherein the N image histograms have a corresponding relation with the target image set, and N is an integer greater than 1;
extracting spectral change characteristics in a target area according to the N image histograms, and drawing a spectral change curve chart according to the spectral change characteristics;
and obtaining a target spectrum value through the spectrum change curve graph, and locking a detection target based on the target spectrum value.
2. The method of claim 1, wherein the determining a set of target images based on the panoramic camera capturing spectral images within a target area, the method further comprising:
defining a region boundary based on a target detection range, and determining the target region according to the region boundary;
selecting an acquisition path of the panoramic camera according to the target area, recording image spectrum distribution data through the acquisition path, and obtaining spectrum distribution uniformity;
and sequentially determining a plurality of target images according to the spectrum distribution uniformity, and determining the target image set through the plurality of target images.
3. The method of claim 1, wherein extracting spectral features of the set of target images by the resolution imaging spectrometer obtains a set of influencing spectral features, the method further comprising:
extracting emission spectrum information in the target area by the resolution imaging spectrometer;
constructing an image gray scale mean function based on the emission spectrum information;
and carrying out spectral analysis on the target image set according to the image gray level average function, and determining the influence spectrum characteristic set.
4. A method according to claim 3, wherein the image gray-scale mean function is as follows:
；
wherein,the image gray average value is M is the Mth image in the target image set, N is the Nth image in the target image set, M is not equal to N, and i is the gray value of the pixel point in the Mth imageI is the gray value of the pixel point in the Nth image.
5. The method of claim 1, wherein computing statistics of the set of target images based on the set of impact spectral features, obtaining N image histograms, the method further comprising:
the statistics of the target image set comprises gray variance and gray standard deviation of the target image set;
judging a plurality of brightness values in the target image set based on the gray variance and the gray standard deviation;
and carrying out statistical distribution according to the pixel numbers of the brightness values to obtain the N image histograms.
6. The method of claim 5, wherein the method further comprises:
constructing a ground coordinate system based on the target area;
constructing an acquisition position coordinate system and an instantaneous acquisition coordinate system of the remote sensor based on the acquisition position of the panoramic camera;
establishing a correlation factor of the ground coordinate system and the instantaneous acquisition coordinate system by using a collineation condition;
performing real-time auxiliary adjustment on the acquisition position coordinate system based on the correlation factor to acquire a plurality of pixel coordinate points of the brightness values;
and determining the number of the plurality of pixels according to the coordinate points of the plurality of pixels.
7. The method of claim 1, wherein a target spectral value is obtained from the spectral variation graph, the detection target being locked based on the target spectral value, the method further comprising:
configuring an image spectrum verification period;
performing spectral image verification on the target spectral value in the image spectral period to obtain an image spectral verification result;
locking a detection target by taking the image spectrum verification result as an additional detection feature, and acquiring locking target data;
and sending the locking target data to the user receiving end.
8. Target detection system based on remote sensing sensor, its characterized in that, the system is connected with user's receiving terminal, service sensing end, and the service sensing end contains remote sensing sensor, embedded panoramic camera of service sensing end, resolution imaging spectrometer, the system includes:
the image acquisition module is used for acquiring a spectrum image in a target area based on the panoramic camera and determining a target image set;
the characteristic extraction module is used for obtaining an influence spectrum characteristic set, wherein the influence spectrum characteristic set is obtained by extracting spectrum characteristics of the target image set through the resolution imaging spectrometer;
the first calculation module is used for calculating statistics of the target image set based on the influence spectrum feature set to obtain N image histograms, wherein the N image histograms have a corresponding relation with the target image set, and N is an integer larger than 1;
the curve drawing module is used for extracting spectral change characteristics in a target area according to the N image histograms and drawing a spectral change curve according to the spectral change characteristics;
and the target locking module is used for obtaining a target spectrum value through the spectrum change curve graph and locking a detection target based on the target spectrum value.
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| CN113588592A (en) * | 2021-06-30 | 2021-11-02 | 北京航空航天大学 | Typical target material identification method based on specific spectral band |
| CN113947730A (en) * | 2021-11-26 | 2022-01-18 | 长光禹辰信息技术与装备(青岛)有限公司 | Remote sensing data identification method and device, electronic equipment and readable storage medium |
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