CN102867184B - Extraction method for sea ice motion features in SAR (synthetic aperture radar) images - Google Patents
Extraction method for sea ice motion features in SAR (synthetic aperture radar) images Download PDFInfo
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Abstract
The invention discloses an extraction method for sea ice motion features in SAR (synthetic aperture radar) images. The method comprises the following steps of: reading two SAR images repeatedly observed, smoothing and downsampling the images respectively, selecting a plurality of image blocks from the images, and forming image pairs; estimating the global motion velocity of sea ice from the image pairs by a Fourier transform method; subtracting the global motion of the sea ice from the second SAR image, estimating local motion velocity fields of the sea ice in the first SAR image and the second SAR image removed with the global motion by an optical flow method and a least square method; and finally, visualizing the local motion velocity fields of the sea ice into the first SAR image by a vector diagram method. The extraction method has the characteristics of higher accuracy, visualized display of the local motion velocity fields and the like and can be used for the extraction of the sea ice motion features in the SAR images.
Description
Technical Field
The invention belongs to the technical field of microwave marine remote sensing, and particularly relates to a method for extracting sea ice motion characteristics in an SAR image.
Background
Sea ice is salt water ice formed by directly freezing sea water, and is a mixture of solid ice, brine, bubbles containing salt and the like. Sea ice is also one of important influencing factors in the research fields of sea hydrology, atmospheric circulation, climate and the like, and particularly, the thin sea ice plays a key role in the research of ocean surface heat flow, water vapor flow and salinity flow. Meanwhile, the drift and diffusion movement of the sea ice can cause serious threats to offshore oil platforms, ship transportation and the like.
At present, an observation station, an offshore monitoring platform, an icebreaker and satellite remote sensing are main methods for sea ice monitoring. Light waves, infrared rays and microwaves are commonly used radiation sources of active/passive satellite remote sensors, belong to indirect measurement methods, and have the characteristic of wide observation range. Compared with light waves and infrared rays, microwaves are not limited by weather conditions such as sunlight, clouds, fog and rain, and play an important role in sea ice observation. Such as Synthetic Aperture Radars (SAR) mounted on satellites such as ENVISAT, ERS, and RADARSAT-2. Different types of sea ice, such as primary ice, initial ice, annual ice, perennial ice and the like, can be identified from the SAR image; the motion characteristics of the sea ice can also be extracted by adopting two SAR images.
At sea ice and its discontinuous structures (such as water channels, cracks, ice ridges, etc.), there are complex forms of motion, such as rigid motion, stretching, bending, shearing, dispersing, joining, plastic flow, elastic flow, viscous flow, etc. The method comprises the steps of roughly dividing sea ice movement into global movement and local movement in an SAR image, wherein the global movement refers to large-scale rigid movement of the sea ice, is expressed as translation or rotation of the SAR image and is irrelevant to pixel points, namely irrelevant to the space position of the sea ice; the local motion refers to local and segmented continuous motion in the near-rigid motion, and is related to pixel points, namely the sea ice spatial position. Since the SAR satellite operates in polar orbit, it is limited by a low time sampling rate (typically 0.5-3 days). The global motion of sea ice is usually dozens of kilometers away, and can reach 100-200 pixel distances.
The difference method, the area method and the feature method are commonly used for detecting motion in images. In the face of global motion of the SAR image, the methods have the defects of low efficiency, poor precision and the like, and simultaneously influence the extraction of the local motion characteristics of the sea ice.
Disclosure of Invention
The purpose of the invention is as follows: in order to solve the problems and the defects in the prior art, the invention provides the method for extracting the sea ice motion characteristics in the SAR image, which has high efficiency and high precision.
The technical scheme is as follows: a method for extracting sea ice motion characteristics in an SAR image comprises the following steps:
step 1, reading in 2 SAR images with the size of M multiplied by N which are repeatedly observed, wherein the time interval for observing the 2 SAR images is delta t, and the azimuth resolution of the SAR images is recorded as rhoxDistance resolution is denoted as ρyRespectively recording 2 SAR images as I1(m, n) and I2(M, N), wherein M is 1,2, 1, N is 1,2, N, x is an azimuth direction, and y is a distance direction; the time interval delta t refers to the time difference of observing two SAR images in the same area, and is usually 1-3 days; based on the 2 SAR images, the movement of the sea ice during this period is extracted.
Step 2, respectively carrying out comparison on SAR images I1(m, n) and I2(m, n) smoothing and downsampling, selecting K image blocks with L × L size to form K image pairs
With Gaussian kernel separately from SAR image I1(m, n) and I2(m, n) is convoluted and downsampled to obtain a smoothed imageAndnamely, it is <math>
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</math> wherein, represents the convolution operation,representing discrete Gaussian kernels of variance σ and size qxq, q usually being equal {3,5,7,9,11}, Sp↓ represents p times of downsampling, and p is usually 2 or 4;
from the smoothed imageAnd an imageSelecting K image blocks with the size of L multiplied by L at the corresponding positions to form K image pairs which are respectively marked asWherein, m '1, 2, L, n' 1,2, L,k, K ranges from 5 to 10, and L is typically equal to 64, 128, or 256.
Step 3, adopting a Fourier transform method to obtain the image pairAnd estimating the global motion speed of the sea ice, and recording the global motion speed
Using Fourier transform method to obtain ith image pairIs related toWherein, F [ ·]Representing a two-dimensional Fourier transform, F-1{. represents two-dimensional inverse Fourier transform, and the pixel point corresponding to the maximum value of the correlation function is marked asThe azimuthal component of the global velocity of movement of the sea iceComponent in the upward direction of distance <math>
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Step 4, from SAR image I2Subtracting the global motion of sea ice in (m, n), i.e.Wherein,represents a lower rounding operation;
step 5, utilizing an optical flow method and a least square method to obtain the SAR image I1(m, n) and I'2(m, n) estimating the local motion velocity field of the sea ice, notedAnd the local motion velocity field of the sea ice is obtained by adopting a vector diagram methodVisualized in SAR image I1(m, n);
according to the optical flow method, the local movement speed of the sea ice isWherein f is an image gray scale function, x is an azimuth direction, y is a distance direction, t is time, and V islxComponent of local velocity in azimuth, VlyIs the component of the local motion velocity in the distance direction;
scanning the image I with a 3 × 3 window centered on the pixel point (m, n)1(m, n) and I'2(m, n)), the partial differentiation is replaced by a difference method, and the parameter V in the formula (a) is estimated by a least square methodlxAnd VlyIs marked asFinally, the local motion speed field of the sea ice is processed by adopting a vector diagram methodVisualized in SAR image I1(m, n).
Has the advantages that: compared with the prior art, the method for extracting the sea ice motion characteristics in the SAR image provided by the invention has the advantages that the SAR image is firstly subjected to smoothing and downsampling, the overall motion speed of the sea ice is estimated from the image block based on a Fourier transform method, and the operation efficiency is higher. The local motion of the sea ice is estimated by adopting an optical flow method and a least square method, and the local motion velocity field of the sea ice is visualized by adopting a line integral convolution method, so that the method has the characteristics of high precision, visual display and the like.
Drawings
FIG. 1 is a flow chart of an embodiment of the present invention.
Detailed Description
The present invention is further illustrated by the following examples, which are intended to be purely exemplary and are not intended to limit the scope of the invention, as various equivalent modifications of the invention will occur to those skilled in the art upon reading the present disclosure and fall within the scope of the appended claims.
As shown in fig. 1, the method for extracting sea ice motion characteristics in an SAR image includes the following steps:
reading in 2 repeatedly observed SAR images with the size of M multiplied by N, wherein the time interval for observing the 2 SAR images is delta t, and the azimuth resolution of the SAR images is recorded as rhoxDistance resolution is denoted as ρyRespectively recording 2 SAR images as I1(m, n) and I2(M, N), wherein M1, 2, 1., M, N1, 2., N;
2, respectively aiming at the SAR image I1(m, n) and I2(m, n) smoothing and downsampling, selecting K image blocks with L × L size to form K image pairs
With Gaussian kernel separately from SAR image I1(m, n) and I2(m, n) is convoluted and downsampled to obtain a smoothed imageAndnamely, it is <math>
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</math> wherein, represents the convolution operation,representing discrete Gaussian kernels of variance σ and size qxq, q usually being equal {3,5,7,9,11}, Sp↓ represents p times of downsampling, and p is usually 2 or 4;
from the smoothed imageAnd an imageSelecting K image blocks with the size of L multiplied by L at the corresponding positions to form K image pairs which are respectively marked asWherein, m '1, 2, L, n' 1,2, L, i1, 2, K is 5~10, and L usually takes 64, 128 or 256 values.
Using Fourier transform to obtain image pairAnd estimating the global motion speed of the sea ice, and recording the global motion speed
Using Fourier transform method to obtain ith image pairIs related toWherein, F [ ·]Representing a two-dimensional Fourier transform, F-1{. represents two-dimensional inverse Fourier transform, and the pixel point corresponding to the maximum value of the correlation function is marked asThe azimuthal component of the global velocity of movement of the sea iceComponent in the upward direction of distance <math>
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From SAR image I2Subtracting the global motion of sea ice in (m, n), i.e.Wherein,represents a lower rounding operation;
using optical flow and least squaresMethod, from SAR image I1(m, n) and I'2(m, n) estimating the local motion velocity field of the sea ice, notedAnd the local motion velocity field of the sea ice is obtained by adopting a vector diagram methodVisualized in SAR image I1(m, n);
according to the optical flow method, the local movement speed of the sea ice isWherein f is an image gray scale function, x is an azimuth direction, y is a distance direction, t is time, and V islxComponent of local velocity in azimuth, VlyIs the component of the local motion velocity in the distance direction;
scanning the image I with a 3 × 3 window centered on the pixel point (m, n)1(m, n) and I'2(m, n)), the partial differentiation is replaced by a difference method, and the parameter V in the formula (a) is estimated by a least square methodlxAnd VlyIs marked asFinally, the local motion speed field of the sea ice is processed by adopting a vector diagram methodVisualized in SAR image I1(m, n).
Claims (2)
1. A method for extracting sea ice motion characteristics in an SAR image is characterized by comprising the following steps:
step 1, reading in 2 SAR images with the size of M multiplied by N which are repeatedly observed, wherein the time interval for observing the 2 SAR images is delta t, and the azimuth resolution of the SAR images is recorded as rhoxDistance resolution is denoted as ρyRespectively recording 2 SAR images as I1(m, n) and I2(M, N), wherein M is 1,2, …, M, N is 1,2, …, N, x is an azimuth direction, and y is a distance direction;
step 2, respectively carrying out comparison on SAR images I1(m, n) and I2(m, n) smoothing and downsampling, selecting K image blocks with L × L size to form K image pairs
The specific process is as follows: with Gaussian kernel separately from SAR image I1(m, n) and I2(m, n) is convoluted and downsampled to obtain a smoothed imageAndnamely, it is <math>
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from the smoothed imageAnd an imageSelecting K image blocks with the size of L multiplied by L at the corresponding positions to form K image pairs which are respectively marked asWherein m ═ 1,2, …, L, n ═ 1,2, …, L, i ═ 1,2, …, K, the value range of K is 5-10, and L is 64, 128 or 256;
step 3, adopting a Fourier transform method to obtain the image pairAnd estimating the global motion speed of the sea ice, and recording the global motion speed
Using Fourier transform method to obtain ith image pairIs related toWherein, F [ ·]Representing a two-dimensional Fourier transform, F-1{. represents two-dimensional inverse Fourier transform, and the pixel point corresponding to the maximum value of the correlation function is marked asThe azimuthal component of the global velocity of movement of the sea iceComponent in the upward direction of distance <math>
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Step 4, from SAR image I2Subtracting the global motion of sea ice in (m, n), i.e.
Wherein,represents a lower rounding operation;
step 5, utilizing an optical flow method and a least square method to obtain the SAR image I1(m, n) and I2' (m, n) estimate the local velocity field of motion of sea ice, notedAnd the local motion velocity field of the sea ice is obtained by adopting a vector diagram methodVisualized in the SAR image I1(m, n).
2. The method for extracting the sea ice motion characteristics in the SAR image according to claim 1, characterized in that the step 5 is performed according to the following process:
according to the optical flow method, the local movement speed of the sea ice isWherein f is an image gray scale function, x is an azimuth direction, y is a distance direction, t is time, and V islxComponent of local velocity in azimuth, VlyIs the component of the local motion velocity in the distance direction;
scanning the image I with a 3 × 3 window centered on the pixel point (m, n)1(m, n) and I'2(m, n)), the partial differentiation is replaced by a difference method, and the parameter V in the formula (a) is estimated by a least square methodlxAnd VlyIs marked asFinally, the local motion speed field of the sea ice is processed by adopting a vector diagram methodVisualized in SAR image I1(m, n).
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| CN107871323A (en) * | 2016-09-23 | 2018-04-03 | 国家海洋环境监测中心 | A kind of sea ice motion information acquisition method based on all solid state radar |
| CN107730549B (en) * | 2017-10-31 | 2020-10-09 | 大连海事大学 | Method for calculating ice age of sea ice |
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