CN111380836A - Black and odorous water positioning method and device based on remote sensing image and related equipment - Google Patents
Black and odorous water positioning method and device based on remote sensing image and related equipment Download PDFInfo
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Abstract
The invention relates to the technical field of pollutant traceability, and provides a remote sensing image-based black and odorous water positioning method, a remote sensing image-based black and odorous water positioning device and related equipment, wherein the remote sensing image-based black and odorous water positioning method comprises the following steps: obtaining a target remote sensing image from the original remote sensing image; obtaining the reflectivity of an object in the target remote sensing image, and calculating the reflectivity to obtain a normalized index of the object corresponding to each color; when the normalization index is within a preset first monitoring threshold range, an object corresponding to the normalization index is confirmed as a target water body; acquiring spectral reflectances of target water bodies in the target remote sensing images in red, green and blue wave bands; calculating to obtain black odorous water body indexes according to the spectral reflectivity; and when the black and odorous water body index is within the preset second monitoring threshold range, determining that the target water body in the range corresponding to the black and odorous water body index is determined to be the black and odorous water body. By implementing the method and the device, the problems of low accuracy and large calculated amount in positioning of the black and odorous water in the prior art can be solved.
Description
Technical Field
The invention relates to the technical field of pollutant traceability, in particular to a method and a device for positioning a black and odorous water body based on remote sensing images and related equipment.
Background
In recent years, with the increasing awareness of environmental protection, water pollution becomes a key concern of people, and effective reduction of black and odorous water emission has become a key task of government departments. In order to enable the emission of the black and odorous water not to exceed the standard, the pollution source with the excessive emission needs to be quickly positioned, otherwise, a good constraint mechanism cannot be formed. At present, two existing black and odorous water positioning methods are generally adopted, the first method is to monitor black and odorous water by arranging black and odorous water monitoring stations at various water body points in an encrypted manner, and the second method is to identify the position of black and odorous water in a remote sensing image.
Although the two methods can realize black and odorous water positioning, the first method depends on a large amount of manpower and material resources, a concentration value monitored by a black and odorous water monitoring site is caused by a plurality of black and odorous water pollution sources together, and is not caused by only a single potential black and odorous water pollution source closest to the black and odorous water pollution source, the second method is used for directly identifying the black and odorous water in the remote sensing image, a large amount of calculation is needed, and meanwhile, the accuracy of identifying the black and odorous water is low.
In summary, the positioning of the black and odorous water in the prior art has the problems of low accuracy and large calculation amount.
Disclosure of Invention
The invention provides a remote sensing image-based black and odorous water positioning method and device and related equipment, and aims to solve the problems of low accuracy and large calculation amount of positioning of black and odorous water in the prior art.
The first embodiment of the present invention provides a black and odorous water positioning method based on remote sensing images, including:
obtaining a target remote sensing image from the original remote sensing image;
obtaining the reflectivity of each color of an object in the target remote sensing image, and calculating the normalization index of the object corresponding to each color according to the reflectivity of each color;
when the normalization index is within a preset first monitoring threshold range, an object corresponding to the normalization index is confirmed as a target water body;
acquiring spectral reflectances of target water bodies in the target remote sensing images in red, green and blue wave bands;
calculating to obtain black and odorous water body indexes of the target water body according to the spectral reflectivity;
and when the black and odorous water body index is within the preset second monitoring threshold range, determining that the target water body in the range corresponding to the black and odorous water body index is determined to be the black and odorous water body.
A second embodiment of the present invention provides a black and odorous water positioning device based on remote sensing images, including:
the target remote sensing image acquisition module is used for acquiring a target remote sensing image from the original remote sensing image;
the normalization index acquisition module is used for acquiring the reflectivity of each color of the object in the target remote sensing image and calculating the normalization index of the object corresponding to each color according to the reflectivity of each color;
the target water body confirmation module is used for confirming that the object corresponding to the normalization index is the target water body when the normalization index is within the preset first monitoring threshold range;
the spectral reflectivity acquisition module is used for acquiring the spectral reflectivities of the target water body in the target remote sensing image in red, green and blue wave bands;
the black and odorous water body index acquisition module is used for calculating and acquiring a black and odorous water body index of the target water body according to the spectral reflectivity;
and the black and odorous water body confirmation module is used for determining that the target water body in the range corresponding to the black and odorous water body index is confirmed to be the black and odorous water body when the black and odorous water body index is within the preset second monitoring threshold range.
A third embodiment of the present invention provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the steps of the method for locating black and odorous water based on remote sensing images according to the first embodiment of the present invention.
A fourth embodiment of the present invention provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the remote sensing image-based black and odorous water localization method provided by the first embodiment of the present invention.
In the remote sensing image-based black and odorous water positioning method, device and related equipment, firstly, a target remote sensing image is obtained from an original remote sensing image, then, the reflectivity of each color of an object in the target remote sensing image is obtained, the normalization index of the object corresponding to each color is obtained through the reflectivity calculation of each color, then, when the normalization index is within a preset first monitoring threshold range, the object corresponding to the normalization index is determined as a target water body, the spectral reflectivity of the target water body in red, green and blue wave bands in the target remote sensing image is obtained again, finally, the black and odorous water body index of the target water body is obtained through calculation according to the spectral reflectivity, and when the black and odorous water body index is within a preset second monitoring threshold range, the target water body in the range corresponding to the black and odorous water body index is determined as the black and odorous water body. The method comprises the steps of firstly obtaining a target water body in a target remote sensing image, and then obtaining black odorous water according to the target water body in the remote sensing image.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
Fig. 1 is a schematic view of an application environment of a black odorous water localization method based on remote sensing images according to a first embodiment of the present invention;
fig. 2 is a flowchart of a black odorous water localization method based on remote sensing images according to a first embodiment of the present invention;
fig. 3 is a flowchart of step 15 in the remote sensing image-based black odorous water localization method according to the first embodiment of the present invention;
fig. 4 is still another flowchart of the black odorous water localization method based on remote sensing images according to the first embodiment of the present invention;
fig. 5 is still another flowchart of the black odorous water localization method based on remote sensing images according to the first embodiment of the present invention;
fig. 6 is a block diagram of a black odorous water locating device based on remote sensing images according to a second embodiment of the present invention;
fig. 7 is a block diagram of a computer device according to a third embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The black and odorous water positioning method based on remote sensing images provided by the first embodiment of the invention can be applied to an application environment as shown in fig. 1, wherein a client (computer device) communicates with a server through a network. The server side obtains a target remote sensing image from an original remote sensing image sent by the client side, obtains the reflectivity of each color of an object in the target remote sensing image, and calculates the normalization index of the object corresponding to each color according to the reflectivity of each color; when the normalization index is within a preset first monitoring threshold range, an object corresponding to the normalization index is confirmed as a target water body; acquiring spectral reflectances of target water bodies in the target remote sensing images in red, green and blue wave bands; calculating to obtain black and odorous water body indexes of the target water body according to the spectral reflectivity; when the black and odorous water body index is within the preset second monitoring threshold range, determining that the target water body in the range corresponding to the black and odorous water body index is confirmed to be the black and odorous water body, and sending the black and odorous water body in the target remote sensing image to the client. Among them, the client (computer device) may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices. The server can be implemented by an independent server or a server cluster composed of a plurality of servers.
In a first embodiment of the present invention, as shown in fig. 2, a method for locating black odorous water based on remote sensing images is provided, which is described by taking the method as an example applied to a server in fig. 1, and includes the following steps 11 to 15.
Step 11: and obtaining a target remote sensing image from the original remote sensing image.
The original remote sensing image comprises a remote sensing image shot by a satellite. For example, the original remote sensing image may be GF-2 image data or other high resolution satellite image obtained from a national geographic information public service platform, a remote sensing market, or the like.
Step 12: and obtaining the reflectivity of each color of the object in the target remote sensing image, and calculating the normalization index of the object corresponding to each color according to the reflectivity of each color.
The normalization index specifically comprises a normalization water body index and a normalization vegetation index.
In the step 12, specifically, the reflectivity of the object in the target remote sensing image in three bands of green, red and near infrared is obtained, and the normalized water body index is obtained by calculating according to the following formula (1):
the NDWI represents the normalized water body index, the Green represents the reflectivity of an object in a Green wave band in the target remote sensing image, and the NIR represents the reflectivity of the object in a near-infrared wave band in the target remote sensing image.
Obtaining a normalized vegetation index by calculating according to the following formula (2):
the NDVI represents a normalized vegetation index, the Red represents the reflectivity of an object in a Red wave band in the target remote sensing image, and the NIR represents the reflectivity of the object in a near infrared wave band in the target remote sensing image.
Step 13: when the normalization index is within the preset first monitoring threshold range, the object corresponding to the normalization index is determined as the target water body.
The normalization index includes a normalized water body index and a normalized vegetation index, and the preset first monitoring threshold also includes two thresholds, namely a first threshold and a second threshold. The first threshold corresponds to a normalized water body index, and the second threshold corresponds to a normalized vegetation index. It should be noted that the setting of the first threshold and the second threshold may be artificially set according to the distribution of the surface features in the actual remote sensing image, or the segmentation threshold may be determined according to the maximum inter-class variance using the greater amount of money algorithm.
In step 13, when the normalized water body index is greater than the first threshold and the normalized vegetation index is smaller than the second threshold, the object corresponding to the normalized index is determined as the target water body. Specifically, when the first threshold value is 0, the second threshold value may be 0.3.
Step 14: and acquiring the spectral reflectivities of the target water body in the red, green and blue wave bands in the target remote sensing image.
In particular, the spectral reflectance is obtained by a measurement device capable of measuring the spectrum of the object, for example, a spectrophotometer, a spectrometer, a reflectance meter, and the like. And acquiring the color of the target water body in the target remote sensing image by using the measuring equipment, and expressing the color of the target water body by using the reflectivity of each color. It should be noted that the reflectance wavelength band in the target remote sensing image has: red, green, blue and near infrared are 4 wave bands. Here, the spectral reflectance in the red band may be represented by R, the spectral reflectance in the green band may be represented by G, and the spectral reflectance in the blue band may be represented by B.
Step 15: and calculating to obtain the black and odorous water body index of the target water body according to the spectral reflectivity.
The black and odorous water body indexes specifically comprise a chromaticity index, a wave band difference index and a wave band ratio index of a target water body in a target remote sensing image.
Step 16: and when the black and odorous water body index is within the preset second monitoring threshold range, determining that the target water body in the range corresponding to the black and odorous water body index is determined to be the black and odorous water body.
The black and odorous water body comprises a chromaticity index, a band difference index and a band ratio index, so the preset second monitoring threshold also comprises three thresholds, namely a third threshold, a fourth threshold and a fifth threshold, wherein the third threshold corresponds to the chromaticity index, the fourth threshold corresponds to the band difference index, and the fifth threshold corresponds to the band ratio index.
Through the implementation of the steps 11 to 16, the target water body in the target remote sensing image is obtained firstly, and then the black and odorous water is obtained according to the target water body in the remote sensing image, so that the problems of low accuracy and large calculation amount existing in the positioning of the black and odorous water in the prior art are solved.
In addition, in this embodiment, after the original remote sensing image is captured by the capturing device, the original remote sensing image is sent to the server, and the server processes the original remote sensing image according to the above steps 11 to 16 to obtain the position of the black and odorous water body, and sends the position of the black and odorous water body to the client.
Further, as an implementation manner of this embodiment, the step 11 specifically includes: and respectively carrying out radiometric calibration processing, geometric correction processing, atmospheric correction processing and image fusion processing on the original remote sensing image to obtain a target remote sensing image.
Specifically, the radiometric calibration processing of the original remote sensing image is specifically based on a quantitative relationship between a spectral radiance value of the original remote sensing image and a digital quantization value output by the imaging spectrometer. The general term of the pixel value in the remote sensing image is a digital quantization value (DN value), and further, DN is a remote sensing pixel brightness value, records the gray value of the ground object target, is an integer value related to the sensor, the ground object target and the transmission path, and does not really reflect the gray value of the ground object. The DN image is converted into an image of radiance value, and is calculated by the following formula (3):
Lλ＝K·DN+C (3)
wherein L isλThe method comprises the steps of representing the radiance value of a wave band lambda, K representing gain, C representing offset, DN representing the digital quantization value of a pixel value in an original remote sensing image, and obtaining the offset C and the gain K from a remote sensing image metadata file. In this embodiment, since DN is the remote sensing pixel brightness value, the recorded gray value of the ground object target is an integer value related to the sensor, the ground object target, and the transmission path, and does not really reflect the gray value of the ground object, by performing the radiometric calibration process on the original remote sensing image,the digital quantization value of the original remote sensing image is converted into a real radiation value, and the brightness gray value of the image is converted into absolute radiation brightness so as to reduce interference generated by radiation when the satellite shoots the remote sensing image.
Specifically, the geometric correction processing is carried out on the original remote sensing image subjected to the radiometric calibration processing according to a correction function in a geometric correction model, geodetic coordinates of ground points of the actual ground object target are associated with corresponding image point coordinates in the original remote sensing image by a ratio polynomial through the geometric correction model, and the coordinate positions of the image points in the whole remote sensing image are obtained by using the known geodetic coordinates of the ground points of the actual ground object target. And then, a geometric fine correction model is used, and polynomial space transformation and pixel interpolation operation between the real position and the original remote sensing image are established by collecting the accurate geographic position of the ground point of the actual ground object target, so that accurate registration of the original remote sensing image and the actual geographic target is realized.
Specifically, the atmospheric correction processing is carried out on the original remote sensing image subjected to geometric correction processing, namely, the remote sensing image reflecting the target position of a real ground object is obtained firstly, pixel-level correction is carried out through a radiation transmission model, the image of atmospheric molecules and aerosol is eliminated, and the real reflectivity of the earth surface in the original remote sensing image is obtained. In this embodiment, since the total radiance of the surface feature target in the obtained original remote sensing image is not a reflection of the real reflectivity of the surface, including the radiant quantity error caused by atmospheric absorption, especially scattering, the radiation error caused by the atmospheric influence can be eliminated by the geometric correction processing, and the real reflectivity of the surface in the original remote sensing image is obtained.
Specifically, the image fusion of the original remote sensing image subjected to geometric correction processing is to perform image fusion on a multispectral image by using a high-resolution panchromatic image, realize pixel-level image fusion after feature extraction, pixel association and resampling, and take the remote sensing image after image fusion as a target remote sensing image, so that the purpose of improving the spatial resolution of the target remote sensing image while ensuring the spectral resolution is achieved. In addition, a full-color image refers to a black-and-white image over the entire visible light band.
In this embodiment, by performing the radiometric calibration process, the geometric correction process, the atmospheric correction process, and the image fusion process on the original remote sensing image, the resolution of the original remote sensing image can be improved, and the interference of radiation and atmosphere on the original remote sensing image can be reduced, so as to obtain the target remote sensing image.
Further, as an implementation manner of this embodiment, as shown in fig. 3, the step 15 specifically includes the following steps 151 to 154:
step 151: and calculating according to the spectral reflectivity to obtain the tristimulus values.
Wherein, the tristimulus values can be obtained by calculation of the following formula (4):
wherein X represents the red primary color stimulus amount, Y represents the green primary color stimulus amount, Z represents the blue primary color stimulus amount, R represents the spectral reflectance of the color of the target water body in a red band, G represents the spectral reflectance of the color of the target water body in a green band, and B represents the spectral reflectance of the color of the target water body in a blue band.
Step 152: and converting the tristimulus values into chromaticity coordinates, and calculating according to the chromaticity coordinates to obtain a chromaticity index.
Specifically, the chromaticity coordinates can be obtained by calculation using the following formula (5):
wherein, each chromaticity coordinate (x, y) corresponds to a color with different saturation, i.e. the corresponding chromaticity index. The chromaticity coordinates (x, y) are coordinates in the color coordinates (CIE-xy coordinate system).
Further, the chromaticity index can be calculated from the chromaticity coordinates calculated by the above equation (5) and the following equation (6):
α＝Arctan2(y-0.3333，x-0.3333) (6)
wherein α represents a rotation angle value, the rotation angle value α has a positive correlation with the dominant wavelength of a pixel corresponding to a color in a target water body, and the dominant wavelength of the corresponding color increases from 380nm to 700nm in the whole range (-2 pi to 2 pi).
It is to be noted that the value of the rotation angle α obtained by the above formula (6) is defined as the color Index1。
Step 153: and calculating according to the spectral reflectances of the target water body in the green and blue wave bands to obtain a wave band difference index.
Specifically, the band difference index may be obtained by calculation according to the following formula (7):
Index2＝Rgreen-Rblue(7)
therein, Index2Representing the band difference index, RgreenSpectral reflectance, R, in the green band representing the color of a target body of waterblueRepresenting the spectral reflectance of the color of the target body of water in the blue band.
Step 154: and calculating according to the spectral reflectivities of the target water body in green and red wave bands to obtain a wave band ratio index.
Specifically, the band ratio index can be obtained by calculation according to the following formula (8):
therein, Index3Representing the band ratio index, RgreenSpectral reflectance, R, in the green band representing the color of a target body of waterredRepresenting the spectral reflectance of the color of the target body of water in the red band.
Through the implementation of the above steps 151 to 154, the chromaticity index, the band difference index and the band ratio index of the target water body can be respectively obtained according to the spectral reflectivity calculation, so as to provide a basis for obtaining the black and odorous water body position in the target water body subsequently.
Further, as an implementation manner of this embodiment, after the step 16, the method further includes performing post-processing on the black and odorous water body to obtain a filtered target remote sensing image.
And the post-processing of the black and odorous water body comprises small patch removal, category color adjustment and vectorization output of results. Specifically, the removal of small patches of the black and odorous water body of the target water body in the target remote sensing image comprises convolution filtering, clustering processing or filtering processing and the like, and is used for removing some patches which are very small in area or are classified by mistake in the black and odorous water body of the target water body; the black and odorous water body and the normal water body can be more obviously distinguished by adjusting the category color of the black and odorous water body of the target water body in the target remote sensing image; the vectorization output result of the black and odorous water body of the target water body in the target remote sensing image can enable the data structure of the output result of the black and odorous water body recognized by the target remote sensing image to be more compact, redundancy is reduced, and subsequent graphic display, network and retrieval analysis are facilitated.
Through carrying out aftertreatment with black and odorous water in the target water for the black and odorous water that demonstrates in the remote sensing image is more clear, is favorable to the observer to observe the position of black and odorous water in the target water more clearly from the remote sensing image.
Further, as an implementation manner of this embodiment, as shown in fig. 4, in order to accurately obtain the position of the target water body in the target remote sensing image, a preset first monitoring threshold needs to be obtained. Obtaining the preset first monitoring threshold further comprises the following steps 21 to 26:
step 21: respectively obtaining target remote sensing images from a plurality of original remote sensing images;
step 22: respectively obtaining the reflectivity of each color of an object in the target remote sensing image, and calculating the normalization index of the object corresponding to each color according to the reflectivity of each color;
step 23: inputting normalization indexes of a plurality of target water bodies into a pre-constructed target water body inversion model, and setting a first monitoring threshold;
step 24: when the normalization index is within the range of the first monitoring threshold value, determining an object corresponding to the normalization index as a predicted target water body, and respectively outputting the predicted positions of the target water body in the target remote sensing image;
step 25: respectively comparing the predicted target water body position in the multiple target remote sensing images with the actual target water body position;
step 26: and when the predicted positions of the target water bodies in the multiple target remote sensing images do not accord with the actual position of the target water body, re-adjusting the size of the first monitoring threshold until the predicted positions of the target water bodies in the multiple target remote sensing images accord with the actual position of the target water body, and taking the set first monitoring threshold as a preset first monitoring threshold.
Since the method of steps 21 to 23 is similar to the method of steps 11 to 13, the description is omitted here. In addition, since the first monitoring threshold includes a first threshold and a second threshold, when the predicted positions of the target water bodies in the plurality of target remote sensing images do not coincide with the actual position of the target water body, at least one of the first monitoring thresholds should be adjusted until the predicted positions of the target water bodies in the plurality of target remote sensing images coincide with the actual position of the target water body.
Through the implementation of the steps 21 to 26, the first monitoring threshold adapted to different environments can be obtained, so that the prediction of the target water body position in the target remote sensing image is more accurate.
Further, as an implementation manner of this embodiment, as shown in fig. 5, it is necessary to obtain a preset second monitoring threshold value to accurately obtain the position of the black odorous water body in the target water body. Obtaining the preset second monitoring threshold further comprises the following steps 31 to 39:
step 31: respectively obtaining target remote sensing images from a plurality of original remote sensing images;
step 32: respectively obtaining the reflectivity of each color of an object in the target remote sensing image, and calculating the normalization index of the object corresponding to each color according to the reflectivity of each color;
step 33: when the normalization index is within a preset first monitoring threshold range, an object corresponding to the normalization index is confirmed as a target water body;
step 34: acquiring spectral reflectances of target water bodies in the target remote sensing images in red, green and blue wave bands;
step 35: calculating and respectively obtaining black and odorous water body indexes of the target water body according to the spectral reflectivity;
step 36: respectively inputting black and odorous water body indexes of a target water body into a pre-constructed black and odorous water body inversion model, and setting a second monitoring threshold;
step 37: when the black and odorous water body index is within the second monitoring threshold range, determining that the target water body in the range corresponding to the black and odorous water body index is determined as the predicted black and odorous water body, and respectively outputting the predicted positions of the black and odorous water body;
step 38: respectively comparing the predicted black and odorous water body position in the multiple target remote sensing images with the actual black and odorous water body position;
step 39: and when the predicted position of the black and odorous water body in the multiple target remote sensing images does not accord with the actual position of the black and odorous water body, re-adjusting the size of the second monitoring threshold value until the predicted position of the black and odorous water body in the multiple target remote sensing images accords with the actual position of the black and odorous water body, and taking the set second monitoring threshold value as the preset second monitoring threshold value.
Since the method of steps 31 to 37 is similar to the method of steps 11 to 16, the description is omitted here. In addition, since the second monitoring threshold includes the third threshold, the fourth threshold, and the fifth threshold, when the predicted position of the black odorous water body does not coincide with the actual position of the target water body, at least one of the second monitoring thresholds should be adjusted until the predicted position of the black odorous water body in the plurality of target remote sensing images coincides with the actual position of the black odorous water body.
Through the implementation of the above steps 31 to 39, the second monitoring threshold adapted to different environments can be obtained, so that the prediction of the position of the black odorous water body in the target water body is more accurate.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
A second embodiment of the present invention provides a remote-sensing-image-based black odorous water positioning device, which corresponds to the remote-sensing-image-based black odorous water positioning method provided in the first embodiment one by one.
Further, the remote sensing image-based black and odorous water positioning device comprises a target remote sensing image acquisition module 41, a normalization index acquisition module 42, a target water body confirmation module 43, a spectral reflectance acquisition module 44, a black and odorous water body index acquisition module 45 and a black and odorous water body confirmation module 46. The functional modules are explained in detail as follows:
a target remote sensing image obtaining module 41, configured to obtain a target remote sensing image from an original remote sensing image;
the normalization index acquisition module 42 is configured to acquire the reflectivity of each color of the object in the target remote sensing image, and calculate a normalization index of the object corresponding to each color according to the reflectivity of each color;
a target water body confirmation module 43, configured to confirm that the object corresponding to the normalization index is the target water body when the normalization index is within the preset first monitoring threshold range;
the spectral reflectivity acquisition module 44 is used for acquiring the spectral reflectivities of the target water body in the target remote sensing image in red, green and blue wave bands;
the black and odorous water body index obtaining module 45 is used for calculating and obtaining the black and odorous water body index of the target water body according to the spectral reflectivity;
and a black and odorous water body confirmation module 46, configured to determine, when the black and odorous water body index is within a preset second monitoring threshold range, that the target water body in the range corresponding to the black and odorous water body index is confirmed to be the black and odorous water body.
Further, as an implementation manner of the present embodiment, the target remote sensing image acquisition module 41 includes a preprocessing unit. The detailed functions of the preprocessing unit are as follows:
and the preprocessing unit is used for respectively carrying out radiometric calibration processing, geometric correction processing, atmospheric correction processing and image fusion processing on the original remote sensing image to obtain a target remote sensing image.
Further, as an implementation manner of this embodiment, the black and odorous water index obtaining module 45 includes a tristimulus value obtaining unit, a chromaticity index obtaining unit, a band difference index obtaining unit, and a band ratio index obtaining unit. The detailed functions of the functional units are as follows:
the tristimulus value acquisition unit is used for calculating according to the spectral reflectivity to obtain a tristimulus value;
the chromaticity index obtaining unit is used for converting the tristimulus values into chromaticity coordinates and calculating the chromaticity index according to the chromaticity coordinates;
the band difference index acquisition unit is used for calculating according to the spectral reflectances of the target water body in green and blue bands to obtain a band difference index;
and the wave band ratio acquisition unit is used for calculating to obtain a wave band ratio index according to the spectral reflectivity of the target water body in green and red wave bands.
Further, as an implementation manner of this embodiment, the black odorous water localization apparatus based on remote sensing images further includes a post-processing module, and detailed functions of the post-processing module are as follows:
and the post-processing module is used for performing post-processing on the black and odorous water body to obtain a filtered target remote sensing image.
Further, as an implementation manner of this embodiment, the black and odorous water positioning device based on remote sensing images further includes a remote sensing image acquisition module, a first normalization processing module, a first monitoring threshold setting module, a target water body position output module, a target water body position comparison module, and a first monitoring threshold determination module. The detailed functions of the functional modules are as follows:
the first remote sensing image acquisition module is used for respectively acquiring a target remote sensing image from a plurality of original remote sensing images;
the first normalization processing module is used for respectively obtaining the reflectivity of each color of an object in the target remote sensing image and calculating the normalization index of the object corresponding to each color according to the reflectivity of each color;
the first monitoring threshold setting module is used for inputting the normalization indexes of a plurality of target water bodies into a pre-constructed target water body inversion model and setting a first monitoring threshold;
the target water body position output module is used for determining an object corresponding to the normalized index as a predicted target water body when the normalized index is within the range of the first monitoring threshold value, and respectively outputting the predicted positions of the target water body in the target remote sensing image;
the target water body position comparison module is used for comparing the predicted target water body positions in the multiple target remote sensing images with the actual target water body positions respectively;
and the first monitoring threshold determining module is used for readjusting the size of the first monitoring threshold when the predicted positions of the target water bodies in the target remote sensing images are not consistent with the actual position of the target water body until the predicted positions of the target water bodies in the target remote sensing images are consistent with the actual position of the target water body, and taking the set first monitoring threshold as a preset first monitoring threshold.
Further, as an implementation manner of this embodiment, the black and odorous water positioning device based on remote sensing images further includes a second remote sensing image acquisition module, a second normalization processing module, a target water body determination module, a reflectivity acquisition module, a black and odorous water body index processing module, a second monitoring threshold setting module, a black and odorous water body position output module, a black and odorous water body position comparison module, and a second monitoring threshold determination module. The detailed functions of the functional modules are as follows:
the second remote sensing image acquisition module is used for respectively acquiring a target remote sensing image from the plurality of original remote sensing images;
the second normalization index processing module is used for respectively obtaining the reflectivity of each color of the object in the target remote sensing image and calculating the normalization index of the object corresponding to each color according to the reflectivity of each color;
the target water body judging module is used for confirming that the object corresponding to the normalized index is the target water body when the normalized index is within the range of a preset first monitoring threshold value;
the reflectivity acquisition module is used for acquiring the spectral reflectivities of the target water body in the target remote sensing image in red, green and blue wave bands;
the black and odorous water body index processing module is used for calculating and respectively obtaining black and odorous water body indexes of the target water body according to the spectral reflectivity;
the second monitoring threshold setting module is used for inputting black and odorous water body indexes of the target water body into the pre-constructed black and odorous water body inversion model respectively and setting a second monitoring threshold;
the black and odorous water body position output module is used for determining the target water body in the range corresponding to the black and odorous water body index as the predicted black and odorous water body when the black and odorous water body index is within the second monitoring threshold range, and respectively outputting the predicted position of the black and odorous water body;
the black and odorous water body position comparison module is used for respectively comparing the predicted black and odorous water body position in the multiple target remote sensing images with the actual black and odorous water body position;
and the second monitoring threshold value determining module is used for readjusting the size of the second monitoring threshold value when the predicted positions of the black and odorous water bodies in the multiple target remote sensing images do not accord with the actual position of the black and odorous water body until the predicted positions of the black and odorous water bodies in the multiple target remote sensing images accord with the actual position of the black and odorous water body, and taking the set second monitoring threshold value as the preset second monitoring threshold value.
For specific limitation of the remote sensing image-based black and odorous water positioning device, reference may be made to the above limitation on the remote sensing image-based black and odorous water positioning method, and details are not repeated here. All or part of the modules in the black and odorous water positioning device based on the remote sensing image can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
A third embodiment of the present invention provides a computer device, which may be a server, and the internal structure diagram of which may be as shown in fig. 7. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing data related to the black and odorous water positioning method based on the remote sensing image. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement the remote sensing image-based black and odorous water positioning method provided by the first embodiment of the invention.
A fourth embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the remote sensing image-based black odorous water localization method provided by the first embodiment of the present invention, such as step 11 to step 16 shown in fig. 2, step 151 to step 154 shown in fig. 3, step 21 to step 26 shown in fig. 4, and step 31 to step 39 shown in fig. 5. Alternatively, the computer program, when executed by the processor, implements the functions of the modules/units of the remote sensing image-based black and odorous water localization method provided in the first embodiment. To avoid repetition, further description is omitted here.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. A black and odorous water positioning method based on remote sensing images is characterized by comprising the following steps:
obtaining a target remote sensing image from the original remote sensing image;
obtaining the reflectivity of each color of the object in the target remote sensing image, and calculating to obtain a normalization index of the object corresponding to each color according to the reflectivity of each color;
when the normalization index is within a preset first monitoring threshold range, determining that the object corresponding to the normalization index is a target water body;
acquiring the spectral reflectances of the target water body in the target remote sensing image in red, green and blue wave bands;
calculating to obtain the black and odorous water body index of the target water body according to the spectral reflectivity;
and when the black and odorous water body index is within a preset second monitoring threshold range, determining that the target water body in the range corresponding to the black and odorous water body index is confirmed to be the black and odorous water body.
2. The remote sensing image-based black odorous water positioning method according to claim 1, wherein the step of obtaining the target remote sensing image from the original remote sensing image comprises:
and respectively carrying out radiometric calibration processing, geometric correction processing, atmospheric correction processing and image fusion processing on the original remote sensing image to obtain the target remote sensing image.
3. The remote sensing image-based black and odorous water positioning method according to claim 1, wherein the black and odorous water body index includes a chromaticity index, a band difference index and a band ratio index, and the calculating the black and odorous water body index according to the spectral reflectance includes:
calculating according to the spectral reflectivity to obtain a tristimulus value;
converting the tristimulus values into chromaticity coordinates, and calculating according to the chromaticity coordinates to obtain the chromaticity index;
calculating to obtain the band difference index according to the spectral reflectances of the target water body in green and blue bands;
and calculating to obtain the band ratio index according to the spectral reflectivities of the target water body in green and red bands.
4. The remote sensing image-based black and odorous water positioning method according to claim 1, wherein after determining that the target water body in the range corresponding to the black and odorous water body index is confirmed to be a black and odorous water body when the black and odorous water body index is within a preset second monitoring threshold range, the method comprises:
and carrying out post-treatment on the black and odorous water body to obtain a filtered target remote sensing image.
5. The remote sensing image-based black and odorous water body positioning method according to claim 1, wherein the acquiring of the preset first monitoring threshold value comprises:
respectively obtaining the target remote sensing image from a plurality of original remote sensing images;
respectively obtaining the reflectivity of each color of the object in the target remote sensing image, and calculating the normalization index of the object corresponding to each color according to the reflectivity of each color;
inputting the normalization indexes of a plurality of target water bodies into a pre-constructed target water body inversion model, and setting a first monitoring threshold;
when the normalization index is within the first monitoring threshold range, determining an object corresponding to the normalization index as a predicted target water body, and respectively outputting the predicted positions of the target water body in the target remote sensing image;
respectively comparing the predicted target water body position in the target remote sensing images with the actual target water body position;
when the predicted positions of the target water bodies in the target remote sensing images do not accord with the actual positions of the target water bodies, the size of the first monitoring threshold value is adjusted again until the predicted positions of the target water bodies in the target remote sensing images accord with the actual positions of the target water bodies, and the set first monitoring threshold value is used as the preset first monitoring threshold value.
6. The remote sensing image-based black and odorous water body positioning method according to claim 1, wherein the acquiring of the preset second monitoring threshold value comprises:
respectively obtaining the target remote sensing image from a plurality of original remote sensing images;
respectively obtaining the reflectivity of each color of the object in the target remote sensing image, and calculating to obtain the normalization index of the object corresponding to each color according to the reflectivity of each color;
when the normalization index is within the preset first monitoring threshold range, determining that the object corresponding to the normalization index is a target water body;
acquiring the spectral reflectances of the target water body in the target remote sensing image in red, green and blue wave bands;
calculating and respectively obtaining the black and odorous water body indexes of the target water body according to the spectral reflectivity;
inputting the black and odorous water body indexes of the target water body into a pre-constructed black and odorous water body inversion model respectively, and setting a second monitoring threshold;
when the black and odorous water body index is within the second monitoring threshold range, determining that the target water body in the range corresponding to the black and odorous water body index is determined to be the predicted black and odorous water body, and respectively outputting the predicted position of the black and odorous water body;
respectively comparing the predicted black and odorous water body position in the target remote sensing images with the actual black and odorous water body position;
when the predicted position of the black and odorous water body in the target remote sensing images does not accord with the actual position of the black and odorous water body, the size of the second monitoring threshold value is adjusted again until the predicted position of the black and odorous water body in the target remote sensing images accords with the actual position of the black and odorous water body, and the set second monitoring threshold value is used as the preset second monitoring threshold value.
7. The utility model provides a black smelly water positioner based on remote sensing image which characterized in that includes:
the target remote sensing image acquisition module is used for acquiring a target remote sensing image from the original remote sensing image;
the normalization index acquisition module is used for acquiring the reflectivity of each color of the object in the target remote sensing image and calculating the normalization index of the object corresponding to each color according to the reflectivity of each color;
the target water body confirmation module is used for confirming that the object corresponding to the normalization index is the target water body when the normalization index is within a preset first monitoring threshold range;
the spectral reflectivity acquisition module is used for acquiring the spectral reflectivities of the target water body in the target remote sensing image in red, green and blue wave bands;
the black and odorous water body index obtaining module is used for calculating and obtaining the black and odorous water body index of the target water body according to the spectral reflectivity;
and the black and odorous water body confirmation module is used for determining that the target water body in the range corresponding to the black and odorous water body index is confirmed to be the black and odorous water body when the black and odorous water body index is within a preset second monitoring threshold range.
8. The remote sensing image-based black odorous water positioning device according to claim 7, wherein the target remote sensing image acquisition module includes:
and the preprocessing unit is used for respectively carrying out radiometric calibration processing, geometric correction processing, atmospheric correction processing and image fusion processing on the original remote sensing image to obtain the target remote sensing image.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the remote sensing image-based black and odorous water localization method according to any one of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium storing a computer program, wherein the computer program is executed by a processor to implement the steps of the remote sensing image-based black and odorous water localization method according to any one of claims 1 to 6.
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