CN114283318B - Ocean front scale characteristic parameter inversion method and system based on SAR image - Google Patents
Ocean front scale characteristic parameter inversion method and system based on SAR image Download PDFInfo
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Abstract
The invention discloses a method and a system for inverting ocean front scale characteristic parameters based on SAR images, which relate to the application field of ocean mesoscale phenomenon remote sensing technology and comprise the following steps: collecting ocean front SAR images, extracting ocean front area images, and filtering interference information; acquiring a sea front belt binary image, wherein the sea front belt binary image is used for extracting sea front scale characteristic parameters; extracting ocean front lines and space distribution images of the ocean front bands according to the ocean front band binarization images, and obtaining ocean front scale characteristic parameters; the inversion method provided by the invention effectively solves the problem that the ocean front characteristics are not obvious and are difficult to directly obtain on the SAR image by utilizing the bright line or dark line characteristics of the ocean front on the SAR image, and lays a technical foundation for the application of the full-time, all-weather and high-resolution SAR image in the ocean front characteristic research.
Description
Technical Field
The invention relates to the field of application of ocean mesoscale phenomenon remote sensing technology, in particular to a ocean front scale characteristic parameter inversion method and system based on SAR images.
Background
Ocean fronts are narrow transition zones between two or more bodies of water that differ significantly in characteristics, so that their spatial distribution has characteristics of a frontal line length and a frontal zone width, which are also indicated by the horizontal gradients based on environmental elements such as temperature, salinity, density, velocity, chlorophyll, color, etc., or their higher order derivatives. However, with the development of aerospace technology, SAR satellite data resources are more abundant, and the advantages of full-day, all-weather and high resolution play an important role in marine environment research. Because the radiation aggregation and the shearing of the ocean front flow field interact with surface waves, the back scattering of the front is obviously different from other places, the front is expressed as a bright line or a dark line on the SAR image, the position of the ocean front can be obtained by adopting an edge feature detection technology generally, further the length information of the ocean front is obtained, and the width feature of the front is not obvious or insufficient on the image, so that the method is difficult to directly obtain. The sea surface temperature distribution data of the corresponding region indicate that the method can obtain the ocean front scale characteristic information with high precision, and provides a technical basis for application of the ocean SAR image in ocean front characteristic research.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a sea front scale characteristic parameter inversion method based on SAR images, which is characterized by comprising the following steps:
Collecting ocean front SAR images, extracting ocean front area images, and filtering interference information;
acquiring a sea front belt binary image, wherein the sea front belt binary image is used for extracting sea front scale characteristic parameters;
extracting ocean front lines and space distribution images of the ocean front bands according to the ocean front band binarization images, and obtaining ocean front scale characteristic parameters.
Preferably, in the process of extracting the ocean front area image, the ocean front area image is extracted according to the bright line or dark line characteristics of the ocean front SAR image, and the speckle noise, the stripe noise and the high-frequency information of sea waves of the ocean front area image are eliminated through median filtering and empirical mode decomposition.
Preferably, in the process of filtering the interference information, the expression of median filtering is:
gi,j＝MedA{fi,j}＝Med{fi+r,j+s,(r,s)∈A,(i,j)∈I2}
Where a is a filter window, f i,j is input data, and g i,j is output data.
Preferably, in the process of filtering interference information, the expression of empirical mode decomposition is:
EMD(I)＝I1+…+Ik+…+In+T
wherein I is an original signal, I k is a decomposed mode, and T is a change trend of the original signal.
Preferably, in the process of acquiring the ocean front belt binarization image, acquiring a gradient distribution image by acquiring a backscattering coefficient gradient of the ocean front SAR image;
Based on the gradient distribution image, performing image gradient threshold segmentation by a maximum inter-class variance method to obtain a binary image of the ocean front, wherein the pixel value of a suspected front signal is 1, and the pixel value of a non-front signal is 0;
the expression of the maximum inter-class variance method is:
g＝w0×w1+w1×(μ0-μ1)2
Wherein ,w0＝N0/(M×N),w1＝N1/(M×N),N0+N1＝×N,w0+w1＝1,g denotes an inter-class variance, μ 0 is a target average gray scale, μ 1 is a background average gray scale, the image size of the gradient distribution image is mxn, the initialization threshold is T, the number of pixels in the image whose gray scale value is smaller than the initialization threshold T is denoted as N 0, and the number of pixels larger than the initialization threshold T is denoted as N 1.
Preferably, in the process of extracting the ocean front, extracting an ocean front skeleton according to the ocean front binary image to obtain the ocean front;
And connecting and shearing burrs on the intermittent parts of the ocean fronts to obtain smooth and continuous ocean fronts, wherein the length of the ocean fronts is obtained according to the sum of the distances among all the points of the ocean fronts.
Preferably, in the process of acquiring the length of the ocean front, the expression of the length of the ocean front is:
wherein N represents the number of points on the ocean front line, lon i and lat i represent the longitude and latitude of the ith point.
Preferably, in the process of extracting the space distribution image of the ocean front, a new ocean front binary image is obtained by adjusting an initialization threshold value;
filtering non-frontal information by setting a regional threshold value, and reserving the frontal information with obvious characteristics;
By setting the thresholds of various morphological structural elements, closing operations of structural elements with different parameters are performed for closing narrow discontinuities and elongated ravines, eliminating small holes and filling cracks in the contour lines.
Preferably, in the process of acquiring the ocean front scale characteristic parameters, carrying out edge extraction on the ocean front binary image to obtain the edge position of the ocean front;
according to the trend of the ocean front, acquiring the width information of the ocean front along longitude or latitude, wherein,
The front width is:
front_w＝|lona-lonb|×100.0
The front width when the longitudes are equal is:
front_w＝|lata-latb|×111.32
wherein, (lon a,lona)、(lonb,latb) is the longitude and latitude of the a and b points of the ocean front.
An SAR image-based ocean front scale feature parameter inversion system, comprising:
the data extraction unit is used for collecting the ocean front SAR image, extracting the ocean front area image and filtering interference information;
The binarization image extraction unit is used for obtaining a sea front belt binarization image which is used for extracting sea front scale characteristic parameters;
The characteristic extraction unit is used for extracting the ocean front line and the space distribution image of the ocean front band according to the ocean front band binarization image to obtain ocean front scale characteristic parameters.
The invention discloses the following technical effects:
According to the invention, by utilizing the bright line or dark line characteristics of the ocean front on the SAR image, the SAR image ocean front scale characteristic parameter inversion method based on the multi-parameter threshold is provided, the problem that the ocean front belt characteristics are not obviously and difficultly obtained directly on the SAR image is effectively solved, and a technical foundation is laid for the application of the full-time, all-weather and high-resolution SAR image in ocean front characteristic research.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an inversion method according to the present invention;
FIG. 2 is a SAR image comprising ocean front phenomenon according to an embodiment of the present invention;
FIG. 3 is a sea frontal area SAR image according to an embodiment of the present invention;
FIG. 4 is a graph showing the gradient of the back scattering coefficient of the ocean frontal zone according to the embodiment of the invention.
FIG. 5 is a view of an ocean front detection result image according to an embodiment of the present invention;
FIG. 6 is a view of a marine front skeleton image according to an embodiment of the present invention;
FIG. 7 is a view of an ocean front image according to an embodiment of the present invention;
FIG. 8 is a view of a marine front image for multi-parameter threshold detection according to an embodiment of the present invention;
FIG. 9 is a schematic view of the width of the ocean front according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
As shown in fig. 1-9, the invention provides a marine front scale characteristic parameter inversion method based on a SAR image, which is characterized by comprising the following steps:
Collecting ocean front SAR images, extracting ocean front area images, and filtering interference information;
acquiring a sea front belt binary image, wherein the sea front belt binary image is used for extracting sea front scale characteristic parameters;
extracting ocean front lines and space distribution images of the ocean front bands according to the ocean front band binarization images, and obtaining ocean front scale characteristic parameters.
Further preferably, in the process of extracting the ocean front area image, the ocean front area image is extracted according to the bright line or dark line characteristics of the ocean front SAR image, and the speckle noise, the stripe noise and the high-frequency information of sea waves of the ocean front area image are eliminated through median filtering and empirical mode decomposition.
Further preferably, in filtering the interference information, the expression of median filtering is:
gi,j＝MedA{fi,j}＝Med{fi+r,j+s,(r,s)∈A,(i,j)∈I2}
Where a is a filter window, f i,j is input data, and g i,j is output data.
Further preferably, in the process of filtering interference information, the expression of empirical mode decomposition is:
EMD(I)＝I1+…+Ik+…+In+T
wherein I is an original signal, I k is a decomposed mode, and T is a change trend of the original signal.
Further preferably, in the process of acquiring the ocean front binary image, acquiring a gradient distribution image by acquiring a backscattering coefficient gradient of the ocean front SAR image;
Based on the gradient distribution image, performing image gradient threshold segmentation by a maximum inter-class variance method to obtain a binary image of the ocean front, wherein the pixel value of a suspected front signal is 1, and the pixel value of a non-front signal is 0;
the expression of the maximum inter-class variance method is:
g＝w0×w1+w1×(μ0-μ1)2
Wherein ,w0＝N0/(M×N),w1＝N1/(M×N),N0+N1＝×N,w0+w1＝1,g denotes an inter-class variance, μ 0 is a target average gray scale, μ 1 is a background average gray scale, the image size of the gradient distribution image is mxn, the initialization threshold is T, the number of pixels in the image whose gray scale value is smaller than the initialization threshold T is denoted as N 0, and the number of pixels larger than the initialization threshold T is denoted as N 1.
Further preferably, in the process of extracting the ocean front, extracting an ocean front skeleton according to the ocean front binary image to obtain the ocean front;
And connecting and shearing burrs on the intermittent parts of the ocean fronts to obtain smooth and continuous ocean fronts, wherein the length of the ocean fronts is obtained according to the sum of the distances among all the points of the ocean fronts.
Further preferably, in the process of acquiring the length of the ocean front, the expression of the length of the ocean front is:
wherein N represents the number of points on the ocean front line, lon i and lat i represent the longitude and latitude of the ith point.
Further preferably, in the process of extracting the spatial distribution image of the ocean front, a new binary image of the ocean front is obtained by adjusting an initialization threshold value;
filtering non-frontal information by setting a regional threshold value, and reserving the frontal information with obvious characteristics;
By setting the thresholds of various morphological structural elements, closing operations of structural elements with different parameters are performed for closing narrow discontinuities and elongated ravines, eliminating small holes and filling cracks in the contour lines.
Further preferably, in the process of acquiring the ocean front scale characteristic parameters, edge extraction is carried out on the ocean front binary image to obtain the edge position of the ocean front;
according to the trend of the ocean front, acquiring the width information of the ocean front along longitude or latitude, wherein,
The front width is:
front_w＝|lona-lonb|×100.0
The front width when the longitudes are equal is:
front_w＝|lata-latb|×111.32
wherein, (lon a,lona)、(lonb,latb) is the longitude and latitude of the a and b points of the ocean front.
An SAR image-based ocean front scale feature parameter inversion system, comprising:
the data extraction unit is used for collecting the ocean front SAR image, extracting the ocean front area image and filtering interference information;
The binarization image extraction unit is used for obtaining a sea front belt binarization image which is used for extracting sea front scale characteristic parameters;
The characteristic extraction unit is used for extracting the ocean front line and the space distribution image of the ocean front band according to the ocean front band binarization image to obtain ocean front scale characteristic parameters.
Example 1: the invention provides a sea front scale characteristic parameter inversion method, which comprises the following steps:
S1, reading SAR images, intercepting ocean frontal area domain images, and filtering interference information;
S2, a sea front belt binarization image is preliminarily obtained by adopting a sea front SAR image back scattering coefficient gradient threshold method;
S3, extracting a sea front skeleton, obtaining a sea front by cutting burrs through connection of discontinuous parts, and calculating the length of the sea front according to the longitude and latitude of all points on the front;
S4, obtaining a spatial distribution image of the ocean front by adopting a multi-parameter threshold method;
S5, acquiring the width information of the ocean front according to the edge position of the ocean front.
The step S1 specifically comprises the following steps:
s11, the bright line or dark line features of the selected ocean front SAR image are obvious, as shown in figure 2;
s12, intercepting an ocean frontal area image, as shown in FIG. 3;
s13, eliminating speckle noise, stripe noise and high-frequency information of sea waves in the data through preprocessing such as median filtering and empirical mode decomposition.
(1) Median filtering
gi,j＝MedA{fi,j}＝Med{fi+r,j+s,(r,s)∈A,(i,j)∈I2}
Where a is a filter window, f i,j is input data, and g i,j is output data.
(2) Empirical mode decomposition
EMD(I)＝I1+…+Ik+…+In+T
In the formula, I is an original signal, I k represents a decomposed mode, and T is a change trend of the original signal. The background signal is removed from the original signal to obtain a new signal I new:
Inew＝I1+…+Ik+…+In
The step S2 specifically comprises the following steps:
S21, calculating a backward scattering coefficient gradient of the SAR image to obtain a gradient distribution image;
S22, performing image gradient threshold segmentation by using a maximum inter-class variance method to obtain a sea front binary image.
Step S21 specifically comprises the steps of performing back scattering coefficient gradient calculation on the ocean frontal area image to obtain an ocean frontal area back scattering coefficient gradient distribution image, as shown in FIG. 4;
step S22 specifically comprises obtaining a sea front binary image through maximum inter-class variance method image gradient threshold segmentation, as shown in FIG. 5.
Assuming that the image size is m×n, the initialization threshold is T, the number of pixels in the image with gray values smaller than the initialization threshold T is denoted as N 0, and the number of pixels with gray values larger than the initialization threshold T is denoted as N 1, the ratio w 0 of the target pixel to the whole image is:
w0＝N0/(M×N)
the proportion w 1 of background pixels to the whole image is:
w1＝N1/(M×N)
Wherein N 0+N1＝×N,w0+w1 = 1.
The total average gray level of the image is mu, the target average gray level is mu 0, the background average gray level is mu 1, and the inter-class variance is g, if
μ＝w0×μ0+w1×μ1
g＝w0×(μ0-μ)2+w1×(μ1-μ)2
Two formulas are available:
g＝w0×w1+w1×(μ0-μ1)2
the threshold peak k which maximizes the inter-class variance g is obtained by a traversal method, and the difference between the target and the background is considered to be the largest at the moment, and the gray level T at the moment is the optimal threshold.
And carrying out binary value on the image by utilizing the threshold k, wherein the pixel point value of the suspected frontal signal is 1, and the pixel point value of the non-frontal signal is 0, so as to obtain a binary image.
The step S3 specifically comprises the following steps:
s31, extracting a sea front band skeleton to obtain a sea front line, as shown in fig. 6;
S32, connecting the intermittent parts of the ocean fronts and shearing burrs to obtain smooth and continuous ocean fronts, as shown in fig. 7;
S33, calculating the sum of the distances among all points on the front as the length (in km) of the ocean front.
Wherein N represents the number of points on the ocean front line, lon i and lat i represent the longitude and latitude of the ith point.
The step S4 specifically comprises the following steps:
S41, adjusting the binarization threshold in the S2, and obtaining a sea front binary image again;
s42, filtering non-frontal information by setting a regional threshold value, and retaining the frontal information with obvious characteristics;
Let the area of the region be A, then there are:
In the method, in the process of the invention, The small signal is filtered out for the area a smaller than the set area threshold.
S43, by setting the thresholds of various structural elements of morphology, closing the structural elements with different parameters, closing narrow discontinuities and elongated ravines, eliminating small holes and filling cracks in the contour lines, as shown in fig. 8.
The set a is closed using the structural element B, defined as:
the expansion operation is performed on A by B, and then the corrosion operation is performed on the result by B.
The step S5 specifically comprises the following steps:
S51, extracting the edge of the binary image of the ocean front to obtain the edge position of the ocean front;
S52, determining width information of the ocean front along longitude or latitude according to the trend of the ocean front. A schematic diagram of the width of the blade at equal latitude and longitude is shown in fig. 9.
The front width is (in km) at equal latitudes:
front_w＝|lona-lonb|×100.0
The front width is (in km) when the longitudes are equal:
front_w＝|lata-latb|×111.32
Wherein, (lon a,lata)、(lonb,latb) is the longitude and latitude of the a and b points of the ocean front.
According to the ocean front scale characteristic parameter inversion method disclosed by the invention, the length information of the ocean front is obtained by extracting the bright line or the dark line characteristic of the ocean front on the SAR image, then the spatial distribution image of the ocean front is obtained through multi-parameter threshold joint adjustment such as a back scattering coefficient gradient threshold, a morphological multi-structural element threshold, a regional filtering threshold and the like, further the width information of the ocean front is obtained, and finally the scale characteristic parameters such as the length of the ocean front, the width of the front and the like are obtained.
Claims (2)
1. The ocean front scale characteristic parameter inversion method based on the SAR image is characterized by comprising the following steps of:
Collecting ocean front SAR images, extracting ocean front area images, and filtering interference information;
Acquiring an ocean front belt binary image, wherein the ocean front belt binary image is used for extracting ocean front scale characteristic parameters;
extracting ocean front lines and space distribution images of the ocean front bands according to the ocean front band binarization images, and obtaining the ocean front scale characteristic parameters;
In the process of extracting the ocean front area image, extracting the ocean front area image according to the bright line or dark line characteristics of the ocean front SAR image, and eliminating the speckle noise, the stripe noise and the high-frequency information of sea waves of the ocean front area image through median filtering and empirical mode decomposition;
In the process of filtering interference information, the expression of the median filtering is as follows:
gi,j＝MedA{fi,j}＝Med{fi+r,j+s,(r,s)∈A,(i,j)∈I2}
Wherein A is a filter window, f i,j is input data, and g i,j is output data;
In the process of filtering interference information, the expression of the empirical mode decomposition is as follows:
EMD(I)＝I1+…+Ik+…+In+T
Wherein I is an original signal, I k is a decomposed mode, and T is a change trend of the original signal;
In the process of acquiring a binary image of the ocean front, acquiring a gradient distribution image by acquiring a backscattering coefficient gradient of the ocean front SAR image;
based on the gradient distribution image, performing image gradient threshold segmentation by a maximum inter-class variance method to obtain the ocean front binary image, wherein the pixel value of a suspected front signal is 1, and the pixel value of a non-front signal is 0;
The expression of the maximum inter-class variance method is as follows:
g＝w0×(μ0-μ)2+w1×(μ1-μ)2
μ＝W0×μ0+W1×μ1
Wherein ,w0＝N0/(M×N),w1＝N1/(M×N),N0+N1＝M×N,w0+w1＝1,g represents an inter-class variance, μ is a total average gray scale, μ 0 is a target average gray scale, μ 1 is a background average gray scale, the image size of the gradient distribution image is mxn, the initialization threshold is T, the number of pixels in the image whose gray scale value is smaller than the initialization threshold T is denoted as N 0, and the number of pixels larger than the initialization threshold T is denoted as N 1;
in the process of extracting the ocean front, extracting an ocean front skeleton according to the ocean front binary image to obtain an ocean front;
Connecting and shearing burrs at the intermittent parts of the ocean fronts to obtain smooth and continuous ocean fronts, wherein the length of the ocean fronts is obtained according to the sum of the distances among all the points of the ocean fronts;
In the process of acquiring the length of the ocean front, the expression of the length of the ocean front is:
Wherein N represents the number of points on the ocean front line, lon i and lat i represent the longitude and latitude of the ith point;
In the process of extracting the space distribution image of the ocean front, a new ocean front binary image is obtained by adjusting the initialization threshold value;
filtering non-frontal information by setting a regional threshold value, and reserving the frontal information with obvious characteristics;
By setting the thresholds of various morphological structural elements, closing operations of structural elements with different parameters are performed for closing narrow discontinuities and elongated ravines, eliminating small holes and filling cracks in the contour lines.
2. The SAR image-based ocean front scale feature parameter inversion method of claim 1, wherein:
In the process of acquiring the ocean front scale characteristic parameters, carrying out edge extraction on the ocean front belt binarization image to obtain the edge position of the ocean front belt;
according to the trend of the ocean front, acquiring the width information of the ocean front along longitude or latitude, wherein,
The front width is:
front_w＝|lona-lonb|×100.0
The front width when the longitudes are equal is:
front_w＝|lata-latb|×111.32
Wherein, (lon a,lata)、(lonb,latb) is the longitude and latitude of the a and b points of the ocean front.
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