CN112070001A - Flood area extraction method and system based on satellite-borne synthetic aperture radar - Google Patents
Flood area extraction method and system based on satellite-borne synthetic aperture radar Download PDFInfo
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Abstract
The invention relates to a flood area extraction method and system based on a satellite-borne synthetic aperture radar. Acquiring an SAR image before a flood disaster and an SAR image after the flood disaster in an area to be extracted; respectively preprocessing the SAR image before the flood and the SAR image after the flood; carrying out subtraction change detection processing on the preprocessed SAR image before the flood and the preprocessed SAR image after the flood, and determining an image after the subtraction change detection processing; determining a segmentation threshold value by adopting an iterative threshold value segmentation method according to the image subjected to the subtraction change detection processing; extracting the flood area of the image subjected to the subtraction change detection processing by using the segmentation threshold value; the flood area extraction method and system based on the satellite-borne synthetic aperture radar can rapidly extract the flood area.
Description
Technical Field
The invention relates to the field of signal processing, in particular to a flood area extraction method and system based on a satellite-borne synthetic aperture radar.
Background
Satellite-borne Synthetic Aperture Radars (SAR) are increasingly widely used in geographic research due to the characteristics that the SAR works all day long and all weather, and is not affected by day and night. In the SAR image, the backscattering coefficients of different earth surfaces have large differences. For a water body, the roughness of the surface of the water body is weaker and is approximate to a flat surface, radar signals are mainly reflected by a mirror surface on the surface, and the signals are difficult to be received by an antenna of the SAR again, so that the reflectivity of the corresponding unit sectional area is lower, and the backscattering coefficient is correspondingly lower; for a land area, the surface is rough, the radar signal is mainly scattered on the rough surface, and a part of the signal is correspondingly received by the antenna of the radar, so that the backward scattering coefficient is high. From this, a distinction can be made between water and land.
Through the change detection of the image, the change trend of the same image in a period of time can be clearly seen. The change detection technology of the image is combined with the extraction technology of the image, and the extraction of the flood area can be realized by utilizing the image of the SAR.
Most of traditional flood area extraction methods are characterized in that after preprocessing, water body extraction is carried out on images before and after disasters in the modes of Otsu threshold segmentation algorithm, unsupervised learning and the like, and then the images are processed through intersection and operation to obtain flood area images. The extraction effect of the algorithm is stable and reliable, but the calculation amount is large, the time consumption is long, the influence of the mountain shadow and the like on the extraction result is caused, the influence of the mountain shadow needs to be eliminated in the extraction process, and the processing time is further prolonged. Therefore, it is necessary to provide a new flood area extraction method based on the satellite-borne SAR.
Disclosure of Invention
The invention aims to provide a flood area extraction method and system based on a satellite-borne synthetic aperture radar, which can be used for rapidly extracting a flood area.
In order to achieve the purpose, the invention provides the following scheme:
a flood area extraction method based on a satellite-borne synthetic aperture radar comprises the following steps:
acquiring an SAR image before a flood disaster and an SAR image after the flood disaster in an area to be extracted;
respectively preprocessing the SAR image before the flood and the SAR image after the flood; the pretreatment comprises the following steps: cutting, multi-view processing, radiation correction, geometric correction and image conversion;
carrying out subtraction change detection processing on the preprocessed SAR image before the flood and the preprocessed SAR image after the flood, and determining an image after the subtraction change detection processing;
determining a segmentation threshold value by adopting an iterative threshold value segmentation method according to the image subjected to the subtraction change detection processing;
extracting the flood area of the image subjected to the subtraction change detection processing by using the segmentation threshold value; the extracted flood area is an area where the pixel value is smaller than the segmentation threshold.
Optionally, the preprocessing is performed on the SAR image before the flood and the SAR image after the flood respectively, and specifically includes:
respectively clipping the SAR image before the flood and the SAR image after the flood;
performing multi-view processing on the clipped SAR image before the flood and the clipped SAR image after the flood respectively;
respectively carrying out radiation correction on the SAR image before the flood after the multi-view processing and the SAR image after the flood after the multi-view processing;
respectively carrying out geometric correction on the SAR image before the flood after the radiation correction and the SAR image after the flood after the radiation correction;
and respectively carrying out image conversion on the SAR image before the flood after the geometric correction and the SAR image after the flood after the geometric correction.
Optionally, determining a segmentation threshold by using an iterative threshold segmentation method according to the image subjected to the subtraction change detection processing includes:
dividing all pixel points in the image subjected to the subtraction change detection processing into N grades according to pixel values;
sequencing all pixel points in the image after the subtraction change detection processing according to the amplitudes of the pixel points;
determining an initial segmentation threshold according to all the sorted pixel points;
segmenting the image subjected to the subtraction change detection processing according to the initial segmentation threshold value;
respectively calculating the average value of the pixel point difference values in each segmented image;
determining an updated segmentation threshold value according to the average value of pixel point difference values in all the segmented images;
judging whether the updated segmentation threshold is equal to the initial segmentation threshold;
if so, determining the updated segmentation threshold as the segmentation threshold;
and if not, replacing the initial segmentation threshold value with an updated segmentation threshold value, and returning to the step of segmenting the image subjected to subtraction change detection processing according to the initial segmentation threshold value.
Optionally, the extracting, by using the segmentation threshold, a flood area of the image after the subtraction change detection processing, and then further includes:
processing the extracted flood area with morphological filtering.
A flood area extraction system based on a satellite-borne synthetic aperture radar comprises:
the SAR image acquisition module is used for acquiring an SAR image before a flood disaster and an SAR image after the flood disaster in an area to be extracted;
the SAR image preprocessing module is used for respectively preprocessing the SAR image before the flood and the SAR image after the flood; the pretreatment comprises the following steps: cutting, multi-view processing, radiation correction, geometric correction and image conversion;
the SAR image subtraction change detection processing module is used for carrying out subtraction change detection processing on the preprocessed SAR image before the flood and the preprocessed SAR image after the flood to determine an image after the subtraction change detection processing;
a segmentation threshold determination module, configured to determine a segmentation threshold by using an iterative threshold segmentation method according to the image subjected to the subtraction change detection processing;
the flood area extraction module is used for extracting the flood area from the image subjected to the subtraction change detection processing by using the segmentation threshold value; the extracted flood area is an area where the pixel value is smaller than the segmentation threshold.
Optionally, the SAR image preprocessing module specifically includes:
the SAR image clipping unit is used for clipping the SAR image before the flood and the SAR image after the flood respectively;
the SAR image multi-view processing unit is used for respectively carrying out multi-view processing on the SAR image before the cut flood and the SAR image after the cut flood;
the SAR image radiation correction unit is used for respectively carrying out radiation correction on the SAR image before the flood after the multi-view processing and the SAR image after the flood after the multi-view processing;
the SAR image geometric correction unit is used for respectively carrying out geometric correction on the SAR image before the flood after the radiation correction and the SAR image after the flood after the radiation correction;
and the SAR image conversion unit is used for respectively carrying out image conversion on the SAR image before the flood after the geometric correction and the SAR image after the flood after the geometric correction.
Optionally, the segmentation threshold determining module specifically includes:
the grade division unit is used for equally dividing all pixel points in the image subjected to the subtraction change detection processing into N grades according to pixel values;
the sorting unit is used for sorting all pixel points in the image after the subtraction change detection processing according to the amplitudes of the pixel points;
an initial segmentation threshold determination unit, configured to determine an initial segmentation threshold according to all the sorted pixel points;
a segmentation unit, configured to segment the image after the subtraction change detection processing according to the initial segmentation threshold;
the average value determining unit of the pixel point difference value is used for respectively calculating the average value of the pixel point difference value in each segmented image;
the updating and dividing threshold determining unit is used for determining an updating and dividing threshold according to the average value of pixel point difference values in all the divided images;
a judging unit configured to judge whether the updated segmentation threshold is equal to the initial segmentation threshold;
a division threshold determination unit configured to determine, if equal, an updated division threshold as the division threshold;
and the iteration unit is used for replacing the initial segmentation threshold value with an updated segmentation threshold value if the initial segmentation threshold value is not equal to the updated segmentation threshold value, and returning to the step of segmenting the image subjected to subtraction change detection processing according to the initial segmentation threshold value.
Optionally, the method further includes:
and the morphological filtering processing module is used for processing the extracted flood area by using morphological filtering.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
according to the flood area extraction method and system based on the satellite-borne synthetic aperture radar, an iterative threshold segmentation algorithm is adopted in the extraction of the flood area, compared with a common Otsu algorithm, unsupervised learning and the like, the extraction effect is similar, but the extraction rate is greatly improved. And the flow of subtracting change detection and then threshold segmentation is firstly carried out, so that the influence of the mountain shadow in the SAR image before and after disaster is mutually counteracted, the step of eliminating the mountain shadow in the conventional extraction method is omitted, and the extraction efficiency is further improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a flood area extraction method based on a satellite-borne synthetic aperture radar provided by the invention;
fig. 2 is a schematic diagram of an SAR image before a flood disaster and an SAR image after the flood disaster in an area to be extracted, which are provided by the present invention;
FIG. 3 is a schematic diagram of the flood area for extraction provided by the present invention;
fig. 4 is a schematic structural diagram of a flood area extraction system based on a satellite-borne synthetic aperture radar provided by 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.
The invention aims to provide a flood area extraction method and a flood area extraction system based on a satellite-borne synthetic aperture radar,
in order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Fig. 1 is a schematic flow chart of a flood area extraction method based on a satellite-borne synthetic aperture radar provided by the present invention, and as shown in fig. 1, the flood area extraction method based on the satellite-borne synthetic aperture radar provided by the present invention includes:
s101, acquiring an SAR image before a flood and an SAR image after the flood in an area to be extracted.
S102, preprocessing the SAR image before the flood and the SAR image after the flood respectively; the pretreatment comprises the following steps: cropping, multi-view processing, radiation correction, geometric correction, and image translation.
S102 specifically comprises the following steps:
and respectively clipping the SAR image before the flood and the SAR image after the flood. In the clipping process, the flood area is included, and meanwhile, the area of the area which is not affected by the flood is reduced as much as possible, so that the extraction result is more obvious, and the size of the image is reduced to improve the processing rate.
The specific method comprises the following steps: and simultaneously cutting the SAR images before and after the disaster, removing redundant parts as much as possible, and simultaneously ensuring that the flood area is completely positioned in the middle of the images, thereby facilitating subsequent operation and observation.
And respectively carrying out multi-view processing on the SAR image before the flood after clipping and the SAR image after the flood after clipping. For remote sensing images, the monoscopic images have the highest spatial resolution, but have a large amount of speckle noise which is difficult to avoid. The multi-view processing can achieve the effect of reducing speckle noise by averaging the azimuth direction and the distance direction of the single-view image.
The specific method comprises the following steps: performing multi-view processing on images before and after a disaster, setting the distance direction quantity and the direction quantity to be the same, performing multiple imaging on a target area by using different frequency bands, and overlapping obtained results to obtain a result.
And respectively carrying out radiation correction on the SAR image before the flood after the multi-view processing and the SAR image after the flood after the multi-view processing. Through radiation correction, radiation distortion and distortion introduced by various external factors and the characteristics of the sensor in the SAR image are eliminated.
The specific method comprises the following steps: and associating the pixels of the SAR image with a backscattering system by utilizing platform software related to the SAR satellite, and correcting the original image by means of remote sensing auxiliary information data and a related error correction model under the support of a related system, thereby eliminating radiation distortion and distortion.
And respectively carrying out geometric correction on the SAR image before the flood after the radiation correction and the SAR image after the flood after the radiation correction. And correcting the image by using a large amount of geographic data and a geometric model through geometric correction, so that the difference between the remote sensing image and the real earth surface in the aspects of shape, size, direction and the like is eliminated.
The specific method comprises the following steps: and establishing a conversion relation between the image and the corresponding geographic coordinates by using platform software related to the SAR satellite, and respectively corresponding and correcting each pixel point in the image, so that the image after geometric correction is obtained, and the purpose of eliminating geometric distortion is achieved.
And respectively carrying out image conversion on the SAR image before the flood after the geometric correction and the SAR image after the flood after the geometric correction. Because the difference of backscattering coefficients of the water body and the land is large, the value distribution range is wide, and the image is converted into a dB form in order to process the image.
The specific method comprises the following steps: and converting the backscattering coefficient value of each pixel point of the preprocessed SAR image. Reading in the backscattering coefficient value x of each pixel point, and then converting the backscattering coefficient value x into a dB form y: y isi＝10lgxi。
And S103, carrying out subtraction change detection processing on the preprocessed SAR image before the flood and the preprocessed SAR image after the flood, and determining the image after the subtraction change detection processing. After the processing, in the image after the subtraction change detection processing, the difference value of the backscattering coefficient of the area suffering from the flood is large, and the difference value of the backscattering coefficient of the area not suffering from the flood is small, and through the step, the flood area can be roughly seen.
The specific method comprises the following steps: and subtracting the preprocessed SAR image after the flood from the preprocessed SAR image before the flood, wherein the value of each pixel point is the backscattering coefficient value before the corresponding point disaster minus the backscattering coefficient value after the corresponding point disaster.
And S104, determining a segmentation threshold value by adopting an iterative threshold value segmentation method according to the image subjected to the subtraction change detection processing.
S104 specifically comprises the following steps:
and equally dividing all pixel points in the image subjected to the subtraction change detection processing into N grades according to pixel values.
And sequencing all pixel points in the image after the subtraction change detection processing according to the amplitudes of the pixel points. The value of the backscattering coefficient y is quantized to z and the proportion p occupied by each level is counted.
And determining an initial segmentation threshold according to all the sorted pixel points. I.e. the initial segmentation threshold t1Is composed of
And segmenting the image after the subtraction change detection processing according to the initial segmentation threshold value. The first part is the front n1One level, the second part being the remaining levels.
And respectively calculating the average value of the pixel point difference values in each segmented image. Namely, the average value of the pixel point difference values of the two parts is calculated respectively
And
and determining an updated segmentation threshold value according to the average value of the pixel point difference values in all the segmented images. I.e. updating the segmentation threshold t2Comprises the following steps:
determining whether the updated split threshold is equal to the initial split threshold.
If so, determining the updated segmentation threshold as the segmentation threshold.
And if not, replacing the initial segmentation threshold value with an updated segmentation threshold value, and returning to the step of segmenting the image subjected to subtraction change detection processing according to the initial segmentation threshold value. Until the two thresholds are equal or the difference value of the two thresholds is smaller than the set value.
S105, extracting a flood area of the image subjected to the subtraction change detection processing by using the segmentation threshold; the extracted flood area is an area where the pixel value is smaller than the segmentation threshold.
After S105, further comprising:
processing the extracted flood area with morphological filtering. After threshold segmentation, due to the influence of terrain and the like, part of speckle noise still exists, and scattered speckle noise is removed through morphological filtering, so that the interference of other factors on the extraction result is avoided.
The specific method comprises the following steps: and performing morphological filtering on the extracted flood area, selecting proper structural elements, performing corrosion operation firstly, and performing expansion operation secondly to suppress noise points. The obtained result is the final flood area extraction result.
The invention is further illustrated by the following specific example. The data used in the example is from the Sentinel-1A satellite of the european office, the research area is located in northwest of mainma, the watershed of the chandun river, all provinces, the SAR original image is shown in fig. 2, and the specific image information is shown in tables 1 and 2. Tables 1 and 2 are as follows:
TABLE 1 Pre-disaster image information
TABLE 2 post-disaster image information
The embodiment specifically comprises the following steps:
the method comprises the following steps: determining an area, and downloading SAR images before and after flood in the corresponding area; in this example, the data corresponding to the Sentinel-1A satellite is downloaded, and the specific parameters are as shown in the table above.
Step two: and preprocessing the SAR image, namely, cutting the original image in a first step. In this example, the Sentinel Application Platform (SNAP) is used to perform the clipping process on the original image, and during the clipping process, the clipping ranges of the image before and after the disaster should be consistent, so as to facilitate the subsequent processing.
Step three: and a second step of SAR image preprocessing, namely performing multi-view processing on the cut images. In this example, the specific method is: and performing multi-view processing on the images before and after the disaster respectively. And imaging the target region for multiple times by using different frequency bands through SNAP software, and averaging the images after imaging to obtain the processed images. The multi-view processing can inhibit the speckle noise by sacrificing the spatial resolution, so an appropriate value should be selected during operation, and the speckle noise is inhibited as much as possible on the premise that the spatial resolution meets the requirement.
In this example, when both the number of distance directions and the number of azimuth directions are set to 3, speckle noise can be suppressed well while the spatial resolution also satisfies the extraction requirement, and therefore, both the number of distance directions and the number of azimuth directions are set to 3.
Step four: and in the third step of SAR image preprocessing, performing radiation correction on the image after multi-view processing, in the example, performing radiation correction on the image after the processing in the third step by using SNAP software and by means of remote sensing auxiliary information data and a correction model, and directly associating the pixel value of each point with a backscattering coefficient through radiation correction to inhibit radiation distortion and distortion.
The image used in this example is of Level-1 type, and SNAP provides four calibration look-up tables for Sentinel-1: respectively generate
γiAnd a number DN, performing radiometric calibration according to the following formula:
where a is any one of the four parameters described above, and value (i) is a corrected value.
Step five: and fourthly, preprocessing the SAR image, geometrically correcting the image after radiation correction, in the example, downloading geographic information of a corresponding region by using SNAP software, then corresponding the image after processing in the fourth step, correcting according to the geographic information of the corresponding region, and inhibiting geometric distortion and distortion.
Step six: reading in the preprocessed image data, including the backscattering coefficient value x of each pixel point, converting the preprocessed image into a dB form to obtain the converted value y of each pixel point, and obtaining the converted image.
Step seven: and (4) carrying out subtraction change detection processing on the image processed in the sixth step, and subtracting the image after disaster processed in the sixth step from the image before disaster processed in the sixth step, wherein the value of each pixel point is obtained by subtracting the pixel point value of the image after disaster from the pixel point value of the image before disaster corresponding to the corresponding point.
Step eight: and calculating a threshold value by using an iterative threshold value segmentation method, and performing threshold value segmentation on the image.
(a) And equally dividing all pixel points into N grades according to the pixel values, wherein N is 500 in the example, then quantizing the backscattering coefficient value y into z, and counting the proportion p of each grade.
(b) Ordering pixel points in the picture according to the amplitude values of the pixel points, and calculating an initial segmentation threshold value t1。
(c) According to an initial threshold t1Dividing the original image into two parts, the first part is the front n1One level, the second part being the remaining levels. Respectively calculating the average value of the pixel point difference values of the two parts
And
(d) compute update partitioningThreshold value t2。
(e) The updated segmentation threshold is compared to the initial segmentation threshold. If t2And t1Are the same, then t2Is the calculated threshold; if not, the calculation is continued, and iteration is continued until the difference value of the two thresholds is equal or smaller than the set value.
(f) With the final segmentation threshold tnFor boundary, the area with the pixel value lower than the threshold is extracted to realize the preliminary extraction of the flood area.
Step nine: the images (extracted flood areas) after the threshold segmentation are processed by morphological filtering. The extracted image is morphologically filtered, in this example, by an on operation. In this example, a 2 × 2 rectangle is selected as the processing unit, and the erosion operation is performed first, and then the dilation operation is performed.
(a) And (3) corrosion operation: and moving the processing unit in the original image by taking the central point of the processing unit as an anchor point, and traversing each pixel of the image. And taking the minimum value of all pixels in the corresponding area of the original image covered by the structural element, and replacing the current pixel value with the minimum value to obtain the image subjected to corrosion operation processing.
(b) And (3) expansion operation: and moving the processing unit in the original image by taking the central point of the processing unit as an anchor point, and traversing each pixel of the image. And taking the maximum value of all pixels in the corresponding area of the original image covered by the structural element, and replacing the current pixel value with the maximum value to obtain the image after the expansion operation processing.
And after the opening operation processing, the noise of the image is restrained, and the processed image is the final flood area extraction result.
Through the above steps, the areas of the target area subjected to the flood are extracted, and the extracted image is shown in fig. 3. According to the visual comparison between the original image and the related optical image, the extraction method can basically realize the extraction of the flood area of the target area, 175 points in 200 sampled points are judged correctly through random sampling, comparison and evaluation, the accuracy can reach 87.5%, and the method can realize the quick and accurate extraction of the flood area of the target area according to the evaluation result.
Fig. 4 is a schematic structural diagram of a flood area extraction system based on a satellite-borne synthetic aperture radar, as shown in fig. 4, the flood area extraction system based on the satellite-borne synthetic aperture radar provided by the present invention includes: the SAR image processing method comprises an SAR image acquisition module 401, an SAR image preprocessing module 402, an SAR image subtraction change detection processing module 403, a segmentation threshold determination module 404 and a flood area extraction module 405.
The SAR image acquisition module 401 is configured to acquire a SAR image before a flood disaster and a SAR image after the flood disaster in an area to be extracted.
The SAR image preprocessing module 402 is configured to respectively preprocess the SAR image before the flood and the SAR image after the flood; the pretreatment comprises the following steps: cropping, multi-view processing, radiation correction, geometric correction, and image translation.
The SAR image subtraction change detection processing module 403 is configured to perform subtraction change detection processing on the preprocessed SAR image before the flood and the preprocessed SAR image after the flood, and determine an image after the subtraction change detection processing.
The segmentation threshold determination module 404 is configured to determine a segmentation threshold by using an iterative threshold segmentation method according to the image after the subtraction change detection processing.
The flood area extraction module 405 is configured to extract a flood area from the subtraction change detection-processed image by using the segmentation threshold; the extracted flood area is an area where the pixel value is smaller than the segmentation threshold.
The SAR image preprocessing module 402 specifically includes: the SAR image processing system comprises an SAR image cutting unit, an SAR image multi-view processing unit, an SAR image radiation correction unit, an SAR image geometric correction unit and an SAR image conversion unit.
The SAR image clipping unit is used for respectively clipping the SAR image before the flood and the SAR image after the flood.
The SAR image multi-view processing unit is used for respectively carrying out multi-view processing on the SAR image before the cut flood and the SAR image after the cut flood.
The SAR image radiation correction unit is used for respectively carrying out radiation correction on the SAR image before the flood after the multi-view processing and the SAR image after the flood after the multi-view processing.
The SAR image geometric correction unit is used for respectively carrying out geometric correction on the SAR image before the flood after the radiation correction and the SAR image after the flood after the radiation correction.
The SAR image conversion unit is used for respectively carrying out image conversion on the SAR image before the flood after the geometric correction and the SAR image after the flood after the geometric correction.
The segmentation threshold determination module 404 specifically includes: the device comprises a grade division unit, a sorting unit, an initial segmentation threshold value determination unit, a segmentation unit, a pixel point difference value average value determination unit, an updating segmentation threshold value determination unit, a judgment unit, a segmentation threshold value determination unit and an iteration unit.
And the grade division unit is used for equally dividing all pixel points in the image subjected to the subtraction change detection processing into N grades according to pixel values.
And the sequencing unit is used for sequencing all the pixel points in the image after the subtraction change detection processing according to the amplitude values of the pixel points.
The initial segmentation threshold determining unit is used for determining an initial segmentation threshold according to all the sorted pixel points.
And the segmentation unit is used for segmenting the image subjected to the subtraction change detection processing according to the initial segmentation threshold value.
The average value determining unit of the pixel point difference value is used for respectively calculating the average value of the pixel point difference value in each segmented image.
And the updating and dividing threshold determining unit is used for determining the updating and dividing threshold according to the average value of the pixel point difference values in all the divided images.
The judging unit is used for judging whether the updated segmentation threshold is equal to the initial segmentation threshold.
The division threshold determination unit is configured to determine the updated division threshold as the division threshold if equal.
And the iteration unit is used for replacing the initial segmentation threshold value with an updated segmentation threshold value if the initial segmentation threshold value is not equal to the updated segmentation threshold value, and returning to the step of segmenting the image subjected to subtraction change detection processing according to the initial segmentation threshold value.
As an embodiment, the flood area extraction system based on the satellite-borne synthetic aperture radar provided by the present invention further includes: and a morphological filtering processing module.
And the morphological filtering processing module is used for processing the extracted flood area by using morphological filtering.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (8)
1. A flood area extraction method based on a satellite-borne synthetic aperture radar is characterized by comprising the following steps:
acquiring an SAR image before a flood disaster and an SAR image after the flood disaster in an area to be extracted;
respectively preprocessing the SAR image before the flood and the SAR image after the flood; the pretreatment comprises the following steps: cutting, multi-view processing, radiation correction, geometric correction and image conversion;
carrying out subtraction change detection processing on the preprocessed SAR image before the flood and the preprocessed SAR image after the flood, and determining an image after the subtraction change detection processing;
determining a segmentation threshold value by adopting an iterative threshold value segmentation method according to the image subjected to the subtraction change detection processing;
extracting the flood area of the image subjected to the subtraction change detection processing by using the segmentation threshold value; the extracted flood area is an area where the pixel value is smaller than the segmentation threshold.
2. The method according to claim 1, wherein the preprocessing is performed on the SAR image before the flood and the SAR image after the flood, specifically including:
respectively clipping the SAR image before the flood and the SAR image after the flood;
performing multi-view processing on the clipped SAR image before the flood and the clipped SAR image after the flood respectively;
respectively carrying out radiation correction on the SAR image before the flood after the multi-view processing and the SAR image after the flood after the multi-view processing;
respectively carrying out geometric correction on the SAR image before the flood after the radiation correction and the SAR image after the flood after the radiation correction;
and respectively carrying out image conversion on the SAR image before the flood after the geometric correction and the SAR image after the flood after the geometric correction.
3. The method according to claim 1, wherein the determining a segmentation threshold by using an iterative threshold segmentation method according to the image after the subtraction change detection processing specifically includes:
dividing all pixel points in the image subjected to the subtraction change detection processing into N grades according to pixel values;
sequencing all pixel points in the image after the subtraction change detection processing according to the amplitudes of the pixel points;
determining an initial segmentation threshold according to all the sorted pixel points;
segmenting the image subjected to the subtraction change detection processing according to the initial segmentation threshold value;
respectively calculating the average value of the pixel point difference values in each segmented image;
determining an updated segmentation threshold value according to the average value of pixel point difference values in all the segmented images;
judging whether the updated segmentation threshold is equal to the initial segmentation threshold;
if so, determining the updated segmentation threshold as the segmentation threshold;
and if not, replacing the initial segmentation threshold value with an updated segmentation threshold value, and returning to the step of segmenting the image subjected to subtraction change detection processing according to the initial segmentation threshold value.
4. The method according to claim 1, wherein the extracting the flood area from the subtraction change detection processed image by using the segmentation threshold further comprises:
processing the extracted flood area with morphological filtering.
5. A flood area extraction system based on a satellite-borne synthetic aperture radar is characterized by comprising:
the SAR image acquisition module is used for acquiring an SAR image before a flood disaster and an SAR image after the flood disaster in an area to be extracted;
the SAR image preprocessing module is used for respectively preprocessing the SAR image before the flood and the SAR image after the flood; the pretreatment comprises the following steps: cutting, multi-view processing, radiation correction, geometric correction and image conversion;
the SAR image subtraction change detection processing module is used for carrying out subtraction change detection processing on the preprocessed SAR image before the flood and the preprocessed SAR image after the flood to determine an image after the subtraction change detection processing;
a segmentation threshold determination module, configured to determine a segmentation threshold by using an iterative threshold segmentation method according to the image subjected to the subtraction change detection processing;
the flood area extraction module is used for extracting the flood area from the image subjected to the subtraction change detection processing by using the segmentation threshold value; the extracted flood area is an area where the pixel value is smaller than the segmentation threshold.
6. The flood area extraction system based on the spaceborne synthetic aperture radar according to claim 5, wherein the SAR image preprocessing module specifically comprises:
the SAR image clipping unit is used for clipping the SAR image before the flood and the SAR image after the flood respectively;
the SAR image multi-view processing unit is used for respectively carrying out multi-view processing on the SAR image before the cut flood and the SAR image after the cut flood;
the SAR image radiation correction unit is used for respectively carrying out radiation correction on the SAR image before the flood after the multi-view processing and the SAR image after the flood after the multi-view processing;
the SAR image geometric correction unit is used for respectively carrying out geometric correction on the SAR image before the flood after the radiation correction and the SAR image after the flood after the radiation correction;
and the SAR image conversion unit is used for respectively carrying out image conversion on the SAR image before the flood after the geometric correction and the SAR image after the flood after the geometric correction.
7. The flood area extraction system based on the spaceborne synthetic aperture radar according to claim 5, wherein the segmentation threshold determination module specifically comprises:
the grade division unit is used for equally dividing all pixel points in the image subjected to the subtraction change detection processing into N grades according to pixel values;
the sorting unit is used for sorting all pixel points in the image after the subtraction change detection processing according to the amplitudes of the pixel points;
an initial segmentation threshold determination unit, configured to determine an initial segmentation threshold according to all the sorted pixel points;
a segmentation unit, configured to segment the image after the subtraction change detection processing according to the initial segmentation threshold;
the average value determining unit of the pixel point difference value is used for respectively calculating the average value of the pixel point difference value in each segmented image;
the updating and dividing threshold determining unit is used for determining an updating and dividing threshold according to the average value of pixel point difference values in all the divided images;
a judging unit configured to judge whether the updated segmentation threshold is equal to the initial segmentation threshold;
a division threshold determination unit configured to determine, if equal, an updated division threshold as the division threshold;
and the iteration unit is used for replacing the initial segmentation threshold value with an updated segmentation threshold value if the initial segmentation threshold value is not equal to the updated segmentation threshold value, and returning to the step of segmenting the image subjected to subtraction change detection processing according to the initial segmentation threshold value.
8. The flood area extraction system based on the spaceborne synthetic aperture radar as claimed in claim 5, further comprising:
and the morphological filtering processing module is used for processing the extracted flood area by using morphological filtering.
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