CN117893439A - Method and device for inverting sea surface wind direction according to SAR image - Google Patents

Abstract

The invention discloses a method, a device, equipment and a storage medium for inverting sea surface wind direction according to SAR images. The method comprises the following steps: smoothing the acquired SAR image; downsampling the smoothed SAR image, the downsampling comprising successive low pass filtering and/or increasing the sampling interval; dividing the downsampled SAR image into N rectangular SAR sub-images, and calculating a gradient value of each pixel of each rectangular SAR sub-image; and calculating dominant wind directions according to gradient values of each pixel of the rectangular SAR sub-images, wherein the dominant wind directions of the rectangular SAR sub-images form sea surface wind directions. According to the technical scheme, the sea surface wind direction can be inverted according to the wind stripe information in the SAR image, the error is further reduced through calculating the gradient value of the pixels in the image, the technical effect of more accurate wind direction assessment is achieved, and a reliable basis is provided for the design planning of the arrangement of the wind turbines of the sea surface wind power plant.

Description

Method and device for inverting sea surface wind direction according to SAR image

Technical Field

The invention relates to the technical field of wind power generation, in particular to a method, a device, equipment and a storage medium for inverting sea surface wind direction according to SAR images.

Background

The sea surface wind farm has important significance for design planning, construction, operation and maintenance of the offshore wind farm. The defects of detecting the sea surface wind field by the traditional means such as an offshore anemometer tower, a floating laser radar, a ocean buoy, a ship and the like are mainly that: typically "point" observations, no long term history, no observations in certain sea areas, or very few. The application of the satellite-borne microwave scatterometer greatly changes the situation, so that the observation of the global sea surface wind field becomes realistic, but the scatterometer has lower resolution and can not meet the requirements of the offshore engineering on the high-resolution sea surface wind field. Furthermore, scatterometers cannot measure sea surface wind fields within 10 km near shore. The Synthetic Aperture Radar (SAR) with high spatial resolution is suitable for detecting local sea surface wind fields in the sea areas such as open sea, offshore, islands and the like, can make up for the defect of satellite measurement of a scatterometer to a great extent, and is receiving more and more attention in the field of offshore engineering application. The method for inverting the sea surface wind field based on SAR data is mainly adopted at present. The method utilizes known wind direction, backscattering section, radar azimuth angle, incidence angle and other information to invert wind speed through a scatterometer geophysical model function. The main problem with this approach is that the wind direction needs to be specified in advance. The existing methods mainly comprise the following steps: the wind direction is specified by using the wind direction measured by the buoy instead of the wind direction of the whole SAR image, or by using the wind direction output by the numerical mode, or by using the wind direction measured by the scatterometer. The disadvantages of the above method are also evident: less float data, lower resolution of the numerical analog output, lower resolution of the wind direction measured by the scatterometer, and larger errors are introduced. How to properly solve the above problems is a problem to be solved in the industry.

Disclosure of Invention

The invention provides a method, a device, equipment and a storage medium for inverting sea surface wind direction according to SAR images, which are used for inverting the sea surface wind direction according to wind stripe information in the SAR images so as to evaluate the direction more accurately.

According to a first aspect of the present invention, there is provided a method of inverting sea surface wind direction from a SAR image, the method of inverting sea surface wind direction from a SAR image comprising:

smoothing the acquired SAR image;

downsampling the smoothed SAR image, the downsampling comprising successive low pass filtering and/or increasing the sampling interval;

dividing the downsampled SAR image into N rectangular SAR sub-images, and calculating a gradient value of each pixel of each rectangular SAR sub-image;

and calculating dominant wind directions according to gradient values of each pixel of the rectangular SAR sub-images, wherein the dominant wind directions of the rectangular SAR sub-images form sea surface wind directions.

In an embodiment, the smoothing the acquired SAR image further includes:

smoothing the acquired SAR image comprises removing SAR speckle noise; or (b)

Enhancing the monitoring of wind fringes of the SAR image.

In one embodiment, the downsampling the smoothed SAR image further comprises successive low pass filtering and/or increasing the sampling interval, including:

by downsampling, including successive low pass filtering and increasing the sampling interval, an image sequence is obtained with progressively lower resolution by half, as follows:

wherein the symbols areRepresenting the operation of reducing resolution by half, symbol +.>For the q-th reduced resolution image, the symbol +.>For passing->The q+1th reduced resolution image after the operation.

In one embodiment, said calculating a gradient value for each pixel of the respective rectangular SAR sub-image further comprises:

according to a convolution template in the preset x-axis direction and a convolution template in the y-axis direction in the Sobel operator, convolving the rectangular SAR sub-image to obtain a gradient matrix in the x-axis direction and a gradient matrix in the y-axis direction of the rectangular SAR sub-image;

and calculating the gradient value of each pixel of the gradient matrix in the x-axis direction and the gradient matrix in the y-axis direction of each rectangular SAR sub-image according to a finite difference Sobel operator method, wherein the Sobel operator comprises a position weighting coefficient of an isotropic Sobel operator.

In one embodiment, said calculating the dominant wind direction from the gradient values of each pixel of said rectangular SAR sub-image further comprises:

calculating the gradient direction of the overall intensity of the rectangular SAR sub-image according to the gradient value of each pixel of the rectangular SAR sub-image;

and analyzing the gradient direction according to the integral intensity of the rectangular SAR sub-image to obtain the dominant wind direction.

In one embodiment, further comprising:

after the dominant wind direction of each pixel of the rectangular SAR sub-image is calculated, noise is eliminated for the dominant direction by setting an acceptance threshold.

According to a second aspect of the present invention, there is provided an apparatus for inverting sea surface wind direction from SAR images, comprising:

the processing module is used for carrying out smoothing processing on the acquired SAR image;

the downsampling module is used for downsampling the SAR image after the smoothing processing, and the downsampling comprises successive low-pass filtering and/or increasing sampling intervals;

the separation module is used for dividing the downsampled SAR image into N rectangular SAR sub-images and calculating the gradient value of each pixel of each rectangular SAR sub-image;

the calculation module is used for calculating dominant wind directions according to the gradient value of each pixel of the rectangular SAR sub-images, and the dominant wind directions of the rectangular SAR sub-images form sea surface wind directions;

according to a third aspect of the present invention, there is provided an electronic device comprising: a processor and a memory storing computer program instructions;

and when the processor executes the computer program instructions, the method for inverting the sea surface wind direction according to the SAR image is realized.

According to a fourth aspect of the present invention there is provided a computer readable storage medium having stored thereon computer program instructions which when executed by a processor implement any of the methods described above for inverting sea surface wind direction from SAR images.

In summary, the invention provides a method and a device for inverting sea surface wind direction according to SAR images, wherein the method comprises the following steps: smoothing the acquired SAR image; downsampling the smoothed SAR image, the downsampling comprising successive low pass filtering and/or increasing the sampling interval; dividing the downsampled SAR image into N rectangular SAR sub-images, and calculating a gradient value of each pixel of each rectangular SAR sub-image; and calculating dominant wind directions according to gradient values of each pixel of the rectangular SAR sub-images, wherein the dominant wind directions of the rectangular SAR sub-images form sea surface wind directions. According to the technical scheme of the embodiment, the sea surface wind direction can be inverted according to the wind stripe information in the SAR image, the error is further reduced through calculating the gradient value of the pixels in the image, the technical effect of more accurate wind direction assessment is achieved, and a reliable basis is provided for the design planning of the wind distribution of the wind power plant on the sea surface.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.

The technical scheme of the invention is further described in detail through the drawings and the embodiments.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a method for inverting sea surface wind direction from SAR images provided by an embodiment of the present invention;

FIG. 2 is a flowchart of step S11 of a method for inverting sea surface wind direction from SAR images according to an embodiment of the present disclosure;

FIG. 3 is a flowchart of step S13 of a method for inverting sea surface wind direction according to SAR image provided by an embodiment of the present invention;

FIG. 4 is a flowchart of step S14 of a method for inverting sea surface wind direction from SAR images according to an embodiment of the present disclosure;

FIG. 5 is a flow chart of yet another method for inverting sea surface wind direction from SAR images provided by an embodiment of the present invention;

FIG. 6 is a block diagram of an apparatus for inverting sea surface wind direction from SAR images according to an embodiment of the present invention;

fig. 7 is a block diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

Features and exemplary embodiments of various aspects of the present application are described in detail below to make the objects, technical solutions and advantages of the present application more apparent, and to further describe the present application in conjunction with the accompanying drawings and the detailed embodiments. It should be understood that the specific embodiments described herein are intended to be illustrative of the application and are not intended to be limiting. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by showing examples of the present application.

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.

As shown in fig. 1, the present invention provides a method for inverting sea surface wind direction according to SAR images, which comprises:

in step S11, smoothing the acquired SAR image;

in step S12, downsampling the smoothed SAR image, the downsampling including successive low pass filtering and/or increasing the sampling interval;

in step S13, the downsampled SAR image is divided into N rectangular SAR sub-images, and a gradient value of each pixel of each rectangular SAR sub-image is calculated;

in step S14, a dominant wind direction is calculated according to the gradient value of each pixel of the rectangular SAR sub-image, and the dominant wind directions of the respective rectangular SAR sub-images constitute sea surface wind directions.

In one embodiment, synthetic aperture radar (SAR, synthetic Aperture Radar, SAR) is a radar technology that creates high resolution radar images by combining echo data of radar sensors at multiple locations in motion. This technique is commonly used in the fields of earth observation, military applications, environmental monitoring, and the like. SAR has a high resolution image: SAR can provide high resolution surface images with the ability to observe under different terrain and meteorological conditions. This makes it widely used in earth observation, topography mapping and environmental monitoring. SAR is independent of weather conditions: unlike optical telemetry, SAR operation is not affected by weather conditions. It can be observed under cloud cover, so that it can provide reliable data under the condition of severe weather. The SAR has motion blur correction: the SAR can collect radar data of a plurality of positions during movement, and the data are used for processing, so that the movement blurring can be corrected, and the image quality can be improved. The SAR comprises the following components: SAR plays an important role in monitoring earth's crust movement, earth's surface subsidence, and seismic activity. It can be used for monitoring urban subsidence, earth surface deformation caused by earthquake, etc.

At present, wind direction is specified by directly utilizing wind stripe information of SAR images, and due to instability of an atmospheric ocean boundary layer, the atmospheric boundary layer is vortex acted on the sea surface to enable the sea surface to generate scattering and radial aggregation, so that the roughness of the sea surface is changed, and black-white alternate stripes are formed on the SAR images. Theoretical research and numerical simulation show that the wind stripe direction caused by boundary layer vortex on the SAR image is basically consistent with the sea surface wind direction, so that the wind stripe direction on the SAR image can represent the wind direction. The solving of the wind stripe direction mainly comprises the following steps: frequency domain-based analysis method and spatial domain-based analysis method. The frequency domain analysis method is to assign wind direction by using the vertical direction of the two-dimensional wave number spectrum peak value connecting line of the wind stripe on the SAR image; the spatial domain based analysis method uses edge detection in digital image processing theory to find fringe edges and assigns wind direction in the gradient maximum direction. The analysis method based on the frequency domain needs to set the pixel number of the concerned sub-image as much as possible to be the power of N of 2, otherwise, the operation times are rapidly increased from O (Nlog 2N) to O (N2), so that the operation time is rapidly increased, and the calculation accuracy is greatly reduced. The spatial analysis method has the advantage of higher spatial resolution. The technical scheme of the application provides an improved local gradient method, and sea surface wind direction can be inverted through SAR images by applying the method. This approach, in contrast to standard gradient methods, is able to extract the local dominant wind direction directly from a set of available local wind directions, avoiding the time consuming histogram analysis operations (i.e., histogram binning, weighting and smoothing) typically required to perform such analysis. Furthermore, the proposed method provides the accuracy associated with each wind direction estimate by exploiting the basic result of the direction statistics.

The wind stripe information in the SAR image can invert the sea surface wind direction, but because the SAR image contains a large amount of errors such as noise and interference factors, the traditional gradient method is difficult to consider the observation errors and inevitably introduces huge errors, and the patent proposes a method for further improving wind direction evaluation, which is superior to the traditional method and further reduces the errors. The accurate wind direction assessment is extremely important for offshore numerical simulation and offshore wind farm fan arrangement design planning, wake flow can be further reduced, generating capacity is improved, and more investment benefits are brought.

According to the technical scheme, the sea surface wind direction can be inverted according to the wind stripe information in the SAR image, the error is further reduced through calculating the gradient value of the pixels in the image, the technical effect of more accurate wind direction assessment is achieved, and a reliable basis is provided for the design planning of the wind distribution of the wind power plant on the sea surface.

In one embodiment, as shown in FIG. 2, step S11 includes the following steps S21-S22:

in step S21, smoothing the acquired SAR image includes removing SAR speckle noise;

in step S22, wind fringes of the monitored SAR image are enhanced.

In one embodiment, SAR image smoothing includes operations to remove SAR speckle noise of an input calibration image and enhance detection of wind fringe patterns on the SAR image. This smoothing operation should preserve the image edges to preserve the directional information of the SAR detected wind field structure.

The spatial resolution of the SAR image is different from a few meters to tens of meters, the spatial resolution of the sea surface wind field is often in kilometer level by utilizing the SAR image to invert, and the SAR image needs to be subjected to downsampling treatment based on the consideration of improving the operation efficiency and being more suitable for detecting quasi-periodic and quasi-linear wind stripe characteristics, so that the spatial resolution of the image is reduced to a hundred meters level, and the resolution is generally controlled to be about 500 meters finally. The increasing of the adoption interval is mainly based on the resolution of the SAR satellite map, if the resolution of the SAR satellite image in a certain area is 10m (one pixel), the unit of the sampling minimum interval can be 10 m; increasing the sampling interval can reduce the sampling rate by selecting every nth pixel in each direction, and the area size is controlled to be around 500m by 500m as described above, and if 1 pixel represents 10m, 50 pixels by 50 pixels are equivalent to a rectangle. By downsampling, including successive low pass filtering and increasing the sampling interval, an image sequence is obtained with progressively lower resolution by half, as follows:

wherein the symbols areRepresenting the operation of reducing resolution by half, symbol +.>For the q-th reduced resolution image, the symbol +.>For passing->The q+1th reduced resolution image after the operation.

In one embodiment, as shown in FIG. 3, step S13 includes the following steps S31-S32:

in step S31, the rectangular SAR sub-image is convolved according to a convolution template in the preset x-axis direction and a convolution template in the y-axis direction in the Sobel operator, so as to obtain a gradient matrix in the x-axis direction and a gradient matrix in the y-axis direction of the rectangular SAR sub-image;

in step S32, a gradient value of each pixel of the gradient matrix in the x-axis direction and the gradient matrix in the y-axis direction of each rectangular SAR sub-image is calculated according to a finite difference Sobel operator method, where the Sobel operator includes a position weighting coefficient of an isotropic Sobel operator.

In one embodiment, the spatial analysis method is to equally divide the SAR image into N rectangular sub-images, calculate the vertical direction of the overall intensity gradient direction of each sub-image, and then calculate the spatial gradient direction of each sub-imageIn the sub-image, the pixel intensity gradient direction is calculated. The intensity gradient of the image may indicate the direction in which the brightness of the image varies the most, which is often associated with certain physical properties, such as the direction of wind, which may affect the texture of the sea surface and thus the reflected intensity of the SAR image. After the overall intensity gradient directions for each sub-image are obtained, the next step in the analysis is to consider the perpendicular directions of these gradient directions. Physically, for SAR pictures, the wind direction on the sea surface tends to be in a perpendicular relationship with the gradient direction of the radar reflection intensity on the sea surface. Thus, by estimating the perpendicular direction of the intensity gradient direction, local wind direction information can be derived. Because the observed image intensity contains noise, the difficulty of gradient solving is increased, and the method is mainly based on a Sobel operator method of finite difference at present. The Sobel operator is a common operator used for edge detection in image processing, and an image edge is found by calculating a first derivative, and an edge point is at the maximum value of an image gradient. The method adopts the position weighting coefficient of the isotropic Sobel operator in the Sobel operators, which is more accurate compared with the common Sobel operator, and the gradient amplitude is consistent when detecting the edges in different directions. Two convolution templates are used in the Sobel operator, one reflecting the degree of change D of the X-axis direction _x A degree D reflecting the change in the y-axis direction _y The method is characterized in that the method is an omnidirectional differential operator of an odd template (3*3), the up, down, left and right of a detection point are weighted, when the Sobel operator is used for detecting the edge, the templates are used for convoluting images to obtain gradient matrixes in the X-axis direction and the Y-axis direction, the templates in the X-axis direction (horizontal direction) highlight brightness changes in the horizontal direction, and the templates in the Y-axis direction (vertical direction) highlight brightness changes in the vertical direction; the Sobel operator takes into account the brightness variations in all directions in the image, which is achieved by combining two mutually perpendicular templates that detect the brightness variations in the horizontal and vertical directions, respectively, i.e. the X-axis direction and the Y-axis direction we refer to. The two templates are used to perform convolution operations with the original image respectively to produce two result matrices, one reflecting the gradient in the X-axis direction (horizontal edge) and one reflecting the gradient in the Y-axis direction (vertical edge). For each point in the imageThe total gradient matrix for that point can be calculated from the gradient matrices in the X-axis direction and the Y-axis direction. The total gradient matrix reflects the edge intensity of each pixel point on the image. When the total gradient exceeds a certain threshold, the point can be considered to be located on the edge. From these two gradient matrices, a gradient matrix for each point in the image can be calculated.

In one embodiment, as shown in FIG. 4, step S14 includes the following steps S41-S42:

in step S41, calculating a gradient direction of the overall intensity of the rectangular SAR sub-image according to the gradient value of each pixel of the rectangular SAR sub-image;

in step S42, the dominant wind direction is obtained by analyzing the gradient direction of the overall intensity of the rectangular SAR sub-image.

In one embodiment, the gradient value of each pixel point of the SAR sub-image can be obtained by the method of solving the gradient in the previous step, and the gradient of each pixel point in the sub-image is likely to be different due to the existence of noise and the like, and how to calculate the gradient direction of the integral intensity of the sub-image according to the gradient of each pixel point is a key step of solving and extracting the main wind direction. A modified local gradient method is used herein. For each sub-image (here denoted ROI), its dominant wind direction can be extracted directly from the overall set of wind directions estimated by the gradient method, and when a gradient operator (Sobel operator) is applied to each pixel in the image, each pixel will obtain a gradient value, with components in the X-direction and Y-direction. These components can be further analyzed to determine the gradient direction of the various local regions in the image. After analyzing a sufficient number of pixels, an overall distribution of wind direction can be established, the dominant wind direction being identified as it is in the overall wind direction distributionSignificant or statistically dominant. The improved local gradient method provides an accuracy measure of the result of the assessment of each wind direction by orienting the base result of the statistics. Especially in local wind directionsIn opposite direction->In circles it is equivalent, that is, wind blowing in one direction is statistically the same as wind blowing in the opposite direction, since wind direction is generally considered to have an uncertainty of 180 degrees. The local angle used for estimation should therefore be regarded essentially as axial data rather than circular data, and the standard method of processing axial data is to convert it into circular data by "doubling the angle", referring to a complete circle period of 0-360 degrees. Algorithmically, we consider that this data is not evenly distributed across the circle. One standard method of processing such 180 degree periodic data is "double angle". For example, one north wind (set to 0 degrees) and one south wind (set to 180 degrees) are doubled and mapped to 0 degrees. I.e.)>Conversion to->And ignoring ambiguity in direction means that we map each angle to twice it, which is done to ignore the original 180 degree uncertainty in the statistical analysis, making the statistical distribution more explicit. Thus given set of observations and available local gradient wind directionAverage angle->(in the statistics and probability theory,<X>representing the expected value of the variable x, i.e. the weighted average of the values of x) and the associated accuracy +.>Respectively from the following formula

（1）

The amplitude of the resulting vector is averaged to calculate an average vector (i.e., the sum of all vectors divided by the number of vectors), whose amplitude is the length of this vector, expressed as:

（2）

average composite lengthIs a dimensionless parameter that represents a measure of directional alignment within the ROI, measured from the mean wind direction.

In one embodiment, as shown in fig. 5, the method further includes the following step S51:

in step S51, a dominant wind direction is obtained by analyzing a gradient direction of the overall intensity of the rectangular SAR sub-image.

In one embodiment, reliable estimates are selected and the relevant improved local gradient method results are determined directly. Regardless of the statistical distribution of the available direction (axial) data, for each direction's estimate,a confidence interval of (1-a) may be manually specified, e.g., a 95% confidence interval may be determined, which may be adjusted in practice,it represents a level of significance that is used to determine the confidence level of the statistical conclusion. For example, α=0.05, the confidence level is 95%, and the assignment can be made according to the following expression:

（3）

wherein the method comprises the steps ofIs a standard normal distribution of (1/2) up->Number of digits (decibel)>A second central triangular moment representing the ROI doubled local direction. Expression (3) is effective for ROIs with large sample sizes.

Thus, an improved local gradient method can be achieved by estimating the wind directionSetting a suitable acceptance threshold->To eliminate noise, suitably depending on the confidence interval mentioned above, which is determined, then the subsequent values are also determined. In practical terms, when the wind direction inversion is performed by adopting the method, the acceptable risk level of the user is generally adjusted by combining expertise, practical engineering experience and experimental purposes:

（4）

in one embodiment, FIG. 6 is a block diagram illustrating an apparatus for inverting sea surface wind direction from SAR images, according to an exemplary embodiment. As shown in fig. 6, the device for inverting the sea surface wind direction according to the SAR image includes a processing module 61, a downsampling module 62, a separating module 63, and a calculating module 64.

The processing module 61 is configured to perform smoothing processing on the acquired SAR image;

the downsampling module 62 is configured to downsample the smoothed SAR image, where the downsampling includes successive low-pass filtering and/or increasing a sampling interval;

the separation module 63 is configured to divide the downsampled SAR image into N rectangular SAR sub-images, and calculate a gradient value of each pixel of each rectangular SAR sub-image;

the calculation module 64 is configured to calculate a dominant wind direction according to a gradient value of each pixel of the rectangular SAR sub-image, where the dominant wind direction of each rectangular SAR sub-image forms a sea surface wind direction.

The processing module 61, the downsampling module 62, the separating module 63 and the calculating module 64 included in the block diagram of the apparatus for inverting sea surface wind direction according to the SAR image are controlled to execute the method for inverting sea surface wind direction according to the SAR image set forth in any of the above embodiments.

As shown in fig. 5, the present invention provides an electronic device 500, including: a processor 501 and a memory 502 storing computer program instructions;

the processor 501 performs smoothing processing on the acquired SAR image when executing the computer program instructions; downsampling the smoothed SAR image, the downsampling comprising successive low pass filtering and/or increasing the sampling interval; dividing the downsampled SAR image into N rectangular SAR sub-images, and calculating a gradient value of each pixel of each rectangular SAR sub-image; and calculating dominant wind directions according to gradient values of each pixel of the rectangular SAR sub-images, wherein the dominant wind directions of the rectangular SAR sub-images form sea surface wind directions.

The invention provides a computer readable storage medium, which stores computer program instructions that when executed by a processor, smooth acquired SAR images; downsampling the smoothed SAR image, the downsampling comprising successive low pass filtering and/or increasing the sampling interval; dividing the downsampled SAR image into N rectangular SAR sub-images, and calculating a gradient value of each pixel of each rectangular SAR sub-image; and calculating dominant wind directions according to gradient values of each pixel of the rectangular SAR sub-images, wherein the dominant wind directions of the rectangular SAR sub-images form sea surface wind directions.

It is to be understood that the specific features, operations and details described herein before with respect to the method of the invention may also be similarly applied to the apparatus and system of the invention, or vice versa. In addition, each step of the method of the present invention described above may be performed by a corresponding component or unit of the apparatus or system of the present invention.

It is to be understood that the various modules/units of the apparatus of the invention may be implemented in whole or in part by software, hardware, firmware, or a combination thereof. Each module/unit may be embedded in the processor of the computer device in hardware or firmware form or independent of the processor, or may be stored in the memory of the computer device in software form for the processor to call to perform the operations of each module/unit. Each module/unit may be implemented as a separate component or module, or two or more modules/units may be implemented as a single component or module.

In one embodiment, a computer device is provided that includes a memory and a processor, the memory having stored thereon computer instructions executable by the processor, the computer instructions, when executed by the processor, directing the processor to perform the steps of the method of the embodiments of the invention. The computer device may be broadly a server, a terminal, or any other electronic device having the necessary computing and/or processing capabilities. In one embodiment, the computer device may include a processor, memory, network interface, communication interface, etc. connected by a system bus. The processor of the computer device may be used to provide the necessary computing, processing and/or control capabilities. The memory of the computer device may include a non-volatile storage medium and an internal memory. The non-volatile storage medium may have an operating system, computer programs, etc. stored therein or thereon. The internal memory may provide an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface and communication interface of the computer device may be used to connect and communicate with external devices via a network. Which when executed by a processor performs the steps of the method of the invention.

The present invention may be implemented as a computer readable storage medium having stored thereon a computer program which, when executed by a processor, causes steps of a method of an embodiment of the present invention to be performed. In one embodiment, a computer program is distributed over a plurality of computer devices or processors coupled by a network such that the computer program is stored, accessed, and executed by one or more computer devices or processors in a distributed fashion. A single method step/operation, or two or more method steps/operations, may be performed by a single computer device or processor, or by two or more computer devices or processors. One or more method steps/operations may be performed by one or more computer devices or processors, and one or more other method steps/operations may be performed by one or more other computer devices or processors. One or more computer devices or processors may perform a single method step/operation or two or more method steps/operations.

Those of ordinary skill in the art will appreciate that the method steps of the present invention may be implemented by a computer program, which may be stored on a non-transitory computer readable storage medium, to instruct related hardware such as a computer device or a processor, which when executed causes the steps of the present invention to be performed. Any reference herein to memory, storage, database, or other medium may include non-volatile and/or volatile memory, as the case may be. Examples of nonvolatile memory include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), flash memory, magnetic tape, floppy disk, magneto-optical data storage, hard disk, solid state disk, and the like. Examples of volatile memory include Random Access Memory (RAM), external cache memory, and the like.

The technical features described above may be arbitrarily combined. Although not all possible combinations of features are described, any combination of features should be considered to be covered by the description provided that such combinations are not inconsistent.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the 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 scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.

Claims (10)

1. A method of inverting sea surface wind direction from SAR images, comprising:

smoothing the acquired SAR image;

downsampling the smoothed SAR image, the downsampling comprising successive low pass filtering and/or increasing the sampling interval;

dividing the downsampled SAR image into N rectangular SAR sub-images, and calculating a gradient value of each pixel of each rectangular SAR sub-image;

and calculating dominant wind directions according to gradient values of each pixel of the rectangular SAR sub-images, wherein the dominant wind directions of the rectangular SAR sub-images form sea surface wind directions.

2. The method for inverting sea surface wind direction according to SAR image according to claim 1, wherein said smoothing the acquired SAR image comprises:

smoothing the acquired SAR image comprises removing SAR speckle noise; or (b)

Enhancing the monitoring of wind fringes of the SAR image.

3. The method of inverting sea surface wind direction from SAR images according to claim 1, wherein said downsampling of the smoothed SAR image comprises successive low pass filtering and/or increasing the sampling interval, comprising:

by downsampling, including successive low pass filtering and increasing the sampling interval, an image sequence is obtained with progressively lower resolution by half, as follows:

wherein the symbols areRepresenting the operation of reducing resolution by half, symbol +.>For the q-th reduced resolution image, the symbol +.>For passing->The q+1th reduced resolution image after the operation.

4. The method of inverting sea surface wind direction from SAR images according to claim 1, wherein said calculating a gradient value for each pixel of the respective rectangular SAR sub-image comprises:

according to a convolution template in the preset x-axis direction and a convolution template in the y-axis direction in the Sobel operator, convolving the rectangular SAR sub-image to obtain a gradient matrix in the x-axis direction and a gradient matrix in the y-axis direction of the rectangular SAR sub-image;

and calculating the gradient value of each pixel of the gradient matrix in the x-axis direction and the gradient matrix in the y-axis direction of each rectangular SAR sub-image according to a finite difference Sobel operator method, wherein the Sobel operator comprises a position weighting coefficient of an isotropic Sobel operator.

5. The method for inverting sea surface wind direction from SAR images according to claim 1, wherein said calculating dominant wind direction from gradient values of each pixel of said rectangular SAR sub-image comprises:

calculating the gradient direction of the overall intensity of the rectangular SAR sub-image according to the gradient value of each pixel of the rectangular SAR sub-image;

and analyzing the gradient direction according to the integral intensity of the rectangular SAR sub-image to obtain the dominant wind direction.

6. The method of inverting sea surface wind direction from SAR images according to claim 1, further comprising:

after the dominant wind direction of each pixel of the rectangular SAR sub-image is calculated, noise is eliminated for the dominant direction by setting an acceptance threshold.

7. An apparatus for inverting sea surface wind direction from SAR images, comprising:

the processing module is used for carrying out smoothing processing on the acquired SAR image;

the downsampling module is used for downsampling the SAR image after the smoothing processing, and the downsampling comprises successive low-pass filtering and/or increasing sampling intervals;

the separation module is used for dividing the downsampled SAR image into N rectangular SAR sub-images and calculating the gradient value of each pixel of each rectangular SAR sub-image;

the calculation module is used for calculating dominant wind directions according to the gradient value of each pixel of the rectangular SAR sub-images, and the dominant wind directions of the rectangular SAR sub-images form sea surface wind directions.

8. The apparatus for inverting sea surface wind direction from SAR images according to claim 7, wherein: the processing module, the downsampling module, the separating module and the computing module are controlled to perform the method of inverting sea surface wind direction from SAR images according to any of claims 1-6.

9. A computing device, comprising:

a communication interface, a processor, a memory;

wherein the memory is for storing program instructions that, when executed by the processor, cause the computing device to implement the method of inverting sea surface wind direction from SAR images of any one of claims 1 to 6.

10. A computer readable storage medium having stored thereon program instructions, which when executed by a computer cause the computer to implement the method of inverting sea surface wind direction from SAR images according to any of claims 1 to 6.