CN111781146B - Wave parameter inversion method using high-resolution satellite optical image - Google Patents
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Abstract
The invention relates to a wave parameter inversion method by using a high-resolution satellite optical image, belonging to the technical field of ocean wave parameter extraction. The invention comprises the following steps: the method comprises the following steps: preprocessing an original optical image: step two: acquiring a gray value over the ocean; step three: segmenting an image window; step four: strengthening and identifying image characteristics; step five: acquiring an energy spectrum; step six: acquiring the propagation direction of sea waves; step seven: obtaining a radial wave number spectrum; step eight: acquiring a dominant wavelength lambda; step nine: calculating a main wave frequency f and a period T; step ten: obtaining wave information: and sliding the window to obtain the wave propagation direction, wavelength and period of other sub-windows, thereby obtaining wave information in any region in the satellite observation range. The invention can avoid artificial interference calculation by using a two-dimensional Fourier window segmentation sliding technology, obtain accurate wave direction and further obtain information such as wavelength, period and the like.
Description
Technical Field
The invention relates to a wave parameter inversion method by using a high-resolution satellite optical image, belonging to the technical field of ocean wave parameter extraction.
Background
Ocean wave information is important content in ocean service observation, ocean observation in China is mainly developed through a wave buoy of an anchor system at present, the wave buoy can provide information such as wave period, wave direction and wave height once per hour, in addition, two-dimensional near-shore wave information can be observed through a shore-based X-band wave measuring radar, but the observation cost is high, the potential of large-scale popularization is not provided, a microwave scatterometer carried by a satellite can also observe sea surface wave height, but the resolution ratio is low, and coastal areas are often easily interfered by land signals. The applicant knows that wave information is inverted by using satellite remote sensing images such as resource III and the like at present, but manual intervention is needed to start calculation data when wave direction is calculated, namely, the calculation of the wave direction is determined by visual direction, so that the calculation of the wave direction is not accurate. But the main defects of the prior art are as follows: 1) Buoy fixed-point observation belongs to time domain measurement, and wave information extraction in a space domain cannot be realized; 2) The inversion accuracy of the sea wave under small wind waves is low; 3) The shore-based wave-measuring radar has high cost; 4) The satellite microwave sensor has low resolution.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a wave parameter inversion method by using a high-resolution satellite optical image, and a two-dimensional Fourier window segmentation sliding technology is used to avoid artificial interference pre-calculation, obtain an accurate wave direction and further obtain information such as wavelength, period and the like.
The invention relates to a wave parameter inversion method by using a high-resolution satellite optical image, which comprises the following steps:
the method comprises the following steps: preprocessing an original optical image: the method comprises the following steps:
the first step is as follows: calculating DN value difference: because different earth surfaces have gray DN value differences in four channels of red, green, blue and near infrared, the method is used for sea-land separation, finds out the most obvious wave band combination capable of effectively separating land and sea through spectral analysis, and respectively calculates the DN value differences of blue light, near infrared and green light;
the second step is that: calculating a mask matrix M: synthesizing two difference values to obtain a mask matrix M of a sea-land mask, wherein 1 represents sea and 0 represents land;
step two: obtaining a gray value above the ocean: performing convolution operation on the mask matrix M and the image after four-channel fusion to obtain a gray value above the ocean, indicating that ocean information in a blue light channel of the GF-1 optical satellite image is stored most completely, and finally selecting the blue light channel to perform wave inversion;
step three: segmentation of image window: carrying out image window segmentation, and setting the size of a sub-window to be 1km;
step four: image feature enhancement and identification: gradient vector information of the ocean surface reflectivity is obtained through sober operator calculation, and image feature strengthening and identification of wave crests and wave troughs of the sea waves are achieved;
G＝(S x +iS y )*I (3)
in the formula: s x Representing the image with the detection of the transverse edges, S y An image representing longitudinal edge detection, G representing a gradient vector of sea surface reflectivity; i denotes the coefficients of the longitudinal edge detected image, i =1.. N, n being the number of image elements; i represents an original image matrix;
step five: acquisition of energy spectrum: performing two-dimensional Fourier transform on the sub-window gradient vector information to obtain an energy spectrum;
step six: obtaining the wave propagation direction: obtaining the propagation direction of sea waves by performing statistical analysis on the energy spectrum;
step seven: obtaining a radial wave number spectrum: obtaining a radial wave number spectrum by performing radial one-dimensional Fourier transform on the sub-window;
step eight: acquisition of dominant wavelength λ: obtaining a dominant wave wavelength lambda by counting wave numbers corresponding to energy peaks of the radial wave number spectrum;
step nine: calculation of dominant wave frequency f and period T: calculating a dominant wave frequency f and a period T by using a dispersion relation of wave fluctuation;
in the formula: f represents the wave frequency, T represents the period, lambda represents the wavelength, and g represents the acceleration of gravity;
step ten: obtaining wave information: and sliding the window to obtain the wave propagation direction, wavelength and period of other sub-windows, thereby obtaining wave information in any region in the satellite observation range.
Preferably, in the second step, the GF-1 optical satellite image adopts an optimal band combination technique for inverting the ocean waves.
Preferably, in the second step, the GF-1 optical satellite image is preprocessed to provide information of wave crests and wave troughs of the ocean surface.
Preferably, in the fifth step, two-dimensional Fourier transform is performed on the wave information after GF-1 optical satellite image preprocessing, 180-degree blurring is eliminated by combining with the actual wind direction, and the wave direction is obtained and is consistent with the wave buoy result.
Preferably, in the seventh step, the sea power density spectrum calculated in the x, y and radial directions by the one-dimensional fourier transform is used for judging the radial wavelength from the peak value, and the wave period is obtained through the dispersion relation and is consistent with the wave buoy and the GNSS buoy.
Preferably, in the step ten, the acquisition of the wave information needs to use a satellite remote sensing image and adopt a two-dimensional fourier and a one-dimensional radial fourier to perform a combined inversion of the wave direction and wavelength technology.
The beneficial effects of the invention are: 1) Sea wave information extraction considering spatial characteristics; 2) Extracting wave information under a low sea condition; 3) The wave observation cost is reduced, the acquisition cost of the existing GF-1 optical image data is low, the data can be freely used for public purposes such as scientific research and the like, and the traditional sensors such as buoys and the like have high price and are difficult to acquire data; 4) The space coverage range is improved, the high-resolution satellite can monitor most of the global sea area including open sea areas, the traditional methods such as buoy measurement and the like nearly provide the measurement of limited points, and the space distribution is very limited; 5) The resolution of the observation can be improved, the resolution of the GF-1 optical image is 2m, and the coverage range of each scene can reach 50 kilometers.
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FIG. 1 is a schematic flow diagram of the invention as a whole.
FIG. 2 is a schematic flow chart of steps one to four of the present invention.
FIG. 3 is a schematic flow chart of steps five to six of the present invention.
Fig. 4 is a schematic flow chart of steps seven to ten 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 only a part of the embodiments of the present invention, and not all of the embodiments. 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.
Example 1:
at present, the number of on-orbit operation of high-resolution satellites in China is increased day by day, the observation coverage range of oceans in China is enlarged day by day, ocean observation modes can be enriched by utilizing the high-resolution optical satellite images to invert ocean waves, ocean observation and scientific research are facilitated, and the popularization of the application of the high-resolution optical satellites in China is facilitated. Compared with the prior art, the invention has the following characteristics:
according to the invention, sea wave element information can be obtained by high-resolution satellite optical image inversion. The observation capability of the traditional wave buoy on the calm sea state is limited by the sensitivity of an instrument system, and an effective signal is usually submerged by noise. Through the invention, the wave length, period and direction information of the sea waves can be obtained. The coverage area of the satellite optical image is wider, and the space distribution state of sea waves can be effectively reflected. Compared with the offshore business wave buoy, the satellite optical image can be implemented in the global sea area without being limited by regions.
A wave test of national high resolution No. 1 (GF-1) optical image inversion is developed in Shandong coastal areas, accuracy verification is carried out by using a wave buoy of an ocean station and a GNSS height measurement buoy, and comparison shows that the wave information obtained by the method is high in accuracy and has good applicability under the condition of small wind waves.
As shown in fig. 1, the wave parameter inversion method using high resolution satellite optical images according to the present invention includes the following steps:
the method comprises the following steps: preprocessing of the original optical image, as shown in fig. 2: the method comprises the following steps:
the first step is as follows: calculating the difference in DN values: because different earth surfaces have gray DN value differences in four channels of red, green, blue and near infrared, the method is used for sea-land separation, finds out the most obvious wave band combination capable of effectively separating land and sea through spectral analysis, and respectively calculates the DN value differences of blue light, near infrared and green light;
the second step is that: calculating a mask matrix M: obtaining a mask matrix M of a sea-land mask by combining the two difference values, wherein 1 represents a sea, and 0 represents a land;
step two: obtaining the gray value over the sea: performing convolution operation on the mask matrix M and the image after four-channel fusion to obtain a gray value above the ocean, indicating that ocean information in a blue light channel of the GF-1 optical satellite image is stored most completely, and finally selecting the blue light channel to perform sea wave inversion;
step three: segmentation of image window: carrying out image window segmentation, and setting the size of a sub-window to be 1km;
step four: image feature enhancement and identification: gradient vector information of the ocean surface reflectivity is obtained through sober operator calculation, and image feature strengthening and identification of wave crests and wave troughs of the sea waves are achieved;
G＝(S x +iS y )*I (3)
in the formula: s. the x Representing the image with the detection of the transverse edges, S y An image representing longitudinal edge detection, G representing a gradient vector of sea surface reflectivity; i denotes the coefficients of the longitudinal edge detected image, i =1.. N, n being the number of image elements; i represents an original image matrix;
step five: acquisition of energy spectrum: performing two-dimensional Fourier transform on the sub-window gradient vector information to obtain an energy spectrum;
step six: obtaining the wave propagation direction: obtaining the propagation direction of sea waves by carrying out statistical analysis on the energy spectrum;
step seven: obtaining a radial wave number spectrum: obtaining a radial wave number spectrum by performing radial one-dimensional Fourier change on the sub-window;
step eight: acquisition of dominant wavelength λ: obtaining a dominant wave wavelength lambda by counting wave numbers corresponding to energy peaks of the radial wave number spectrum;
step nine: calculation of dominant wave frequency f and period T: calculating a dominant wave frequency f and a period T by using a dispersion relation of wave fluctuation;
in the formula: f represents the wave frequency, T represents the period, lambda represents the wavelength, and g represents the acceleration of gravity;
step ten: obtaining wave information: and sliding the window to obtain the wave propagation direction, wavelength and period of other sub-windows, thereby obtaining wave information in any region in the satellite observation range.
In the second step, the GF-1 optical satellite image adopts an optimal wave band combination technology for inverting the sea wave.
And in the second step, preprocessing the GF-1 optical satellite image to provide wave crest and wave trough information of the ocean surface.
As shown in fig. 3, in the fifth step, two-dimensional fourier transform is performed on the wave information after GF-1 optical satellite image preprocessing, and 180-degree blur is eliminated by combining with the actual wind direction, so that a wave direction is obtained, which is consistent with the wave buoy result.
As shown in fig. 4, in the seventh step, the sea power density spectrum calculated in the x, y and radial directions by the one-dimensional fourier transform is used to determine the radial wavelength from the peak value, and the wave period is obtained through the dispersion relation and is consistent with the wave buoy and the GNSS buoy.
In the step ten, the wave information is obtained by using a satellite remote sensing image and adopting a two-dimensional Fourier and a one-dimensional radial Fourier to carry out combined inversion on the wave direction and the wave length technology.
The invention considers the sea wave information extraction of the space characteristics; extracting wave information under a low sea condition; the wave observation cost is reduced, the conventional GF-1 optical image data has low acquisition cost and can be freely used for public use such as scientific research, and the conventional sensors such as a buoy have high price and are difficult to acquire data; the space coverage range is improved, the high-resolution satellite can monitor most of the global sea area including open sea areas, the traditional methods such as buoy measurement and the like nearly provide the measurement of limited points, and the space distribution is very limited; the resolution of the observation can be improved, the resolution of the GF-1 optical image is 2m, and the coverage range of each scene can reach 50 kilometers.
The method can be widely applied to the occasion of extracting the ocean wave parameters.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (6)
1. A wave parameter inversion method by using a high-resolution satellite optical image is characterized by comprising the following steps:
the method comprises the following steps: preprocessing an original optical image: the method comprises the following steps:
the first step is as follows: calculating DN value difference: because different earth surfaces have gray DN value differences in four channels of red, green, blue and near infrared, the method is used for sea-land separation, finds out the most obvious wave band combination capable of effectively separating land and sea through spectral analysis, and respectively calculates the DN value differences of blue light, near infrared and green light;
the second step: calculating a mask matrix M: synthesizing two difference values to obtain a mask matrix M of a sea-land mask, wherein 1 represents sea and 0 represents land;
step two: obtaining the gray value over the sea: performing convolution operation on the mask matrix M and the image after four-channel fusion to obtain a gray value above the ocean, indicating that ocean information in a blue light channel of the GF-1 optical satellite image is stored most completely, and finally selecting the blue light channel to perform wave inversion;
step three: segmentation of the image window: segmenting an image window, wherein the size of a sub-window is set to be 1km;
step four: image feature enhancement and identification: gradient vector information of the ocean surface reflectivity is obtained through sober operator calculation, and image feature strengthening and identification of wave crests and wave troughs of the sea waves are achieved;
G＝(S x +iS y )*I (3)
in the formula: s x Representing the image subjected to the detection of the transverse edges, S y An image representing longitudinal edge detection, G representing a gradient vector of sea surface reflectivity; i denotes the coefficients of the longitudinal edge detected image, i =1.. N, n being the number of image elements; i represents an original image matrix;
step five: acquisition of energy spectrum: performing two-dimensional Fourier transform on the sub-window gradient vector information to obtain an energy spectrum; step six: obtaining the wave propagation direction: obtaining the propagation direction of sea waves by carrying out statistical analysis on the energy spectrum;
step seven: obtaining a radial wave number spectrum: obtaining a radial wave number spectrum by performing radial one-dimensional Fourier change on the sub-window;
step eight: acquisition of dominant wavelength λ: obtaining a dominant wave wavelength lambda by counting wave numbers corresponding to energy peaks of the radial wave number spectrum; step nine: calculation of dominant wave frequency f and period T: calculating a dominant wave frequency f and a period T by using a dispersion relation of wave fluctuation;
in the formula: f represents the wave frequency, T represents the period, lambda represents the wavelength, and g represents the acceleration of gravity;
step ten: obtaining wave information: and sliding the window to obtain the wave propagation direction, wavelength and period of other sub-windows, thereby obtaining wave information in any region in the satellite observation range.
2. The wave parameter inversion method using high resolution satellite optical images according to claim 1, wherein in the second step, the GF-1 optical satellite images adopt an optimal band combination technique for inverting sea waves.
3. The wave parameter inversion method using high resolution satellite optical images according to claim 1, wherein in the second step, GF-1 optical satellite images are preprocessed to provide wave crest and wave trough information of the ocean surface.
4. The wave parameter inversion method using the high-resolution satellite optical image according to claim 1, wherein in the fifth step, the two-dimensional fourier transform is performed on the wave information after the GF-1 optical satellite image preprocessing, and 180 ° ambiguity is eliminated by combining with an actual wind direction to obtain a wave direction, which is consistent with a wave buoy result.
5. The wave parameter inversion method using high resolution satellite optical images according to claim 1, wherein in the seventh step, the sea power density spectrum calculated in x, y and radial directions by one-dimensional fourier transform determines the radial wavelength from the peak value, and the wave period is obtained by dispersion relation and is consistent with the wave buoy and the GNSS buoy.
6. The wave parameter inversion method using the high-resolution satellite optical image as claimed in claim 1, wherein in the step ten, the sea wave information is acquired by using a satellite remote sensing image and adopting a two-dimensional fourier and a one-dimensional radial fourier to perform a combined inversion sea wave direction and wavelength technology.
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| CN113514833B (en) * | 2021-04-25 | 2023-10-27 | 南京信息工程大学 | Sea surface arbitrary point wave direction inversion method based on sea wave image |
| CN114740550B (en) * | 2022-06-14 | 2022-08-26 | 广东海洋大学 | Intelligent recognition early warning method and system for continuous storm events |
| CN115659131B (en) * | 2022-09-27 | 2023-07-04 | 中国海洋大学 | Near-field wave propagation direction identification method for marine structure |
| CN116258787B (en) * | 2023-05-15 | 2023-10-17 | 自然资源部第一海洋研究所 | Wave direction spectrum algorithm suitable for wave image |
| CN117058532B (en) * | 2023-10-08 | 2023-12-19 | 自然资源部第一海洋研究所 | Method and system for inverting water depth and wave height based on sea wave and solar flare signals |
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