A side-scan sonar image correction method and a side-scan sonar mosaic imaging system

Abstract

The present invention discloses a side-scan sonar image correction method and a side-scan sonar mosaic image system. The method includes: obtaining a DEM model of underwater terrain; obtaining a side-scan sonar side-scan image, wherein the side-scan image includes a plurality of unit images, each of which corresponds to a track line and attitude data; constructing a virtual side-scan image from the plurality of unit images based on the track line, attitude data, and DEM model; iteratively retrieving the track line and attitude data of the unit images in the virtual side-scan image based on the track line of the unit image to obtain corrected coordinates; and calibrating the track line and attitude data of the unit images in the side-scan image based on the corrected coordinates to obtain a calibrated side-scan image. By combining the track line and attitude data of the side-scan sonar with the DEM model to construct a virtual image, the side-scan sonar image is corrected to obtain a high-precision side-scan sonar mosaic image, thereby solving the problem of excessive misalignment in the splicing of adjacent survey lines caused by low positioning and attitude accuracy in traditional side-scan sonar data.

Description

Technical Field

[0001] The present invention relates to a side-scan sonar image technology, and in particular to a technology for correcting side-scan sonar images based on a DEM model. Background Art

[0002] Side-scan sonar technology can acquire high-resolution underwater acoustic images and is commonly used for geomorphological data collection and underwater obstacle detection. However, this technology cannot produce high-precision underwater topographic data. Side-scan sonar technology typically uses a towed fish method to collect underwater geomorphological data. Data processing primarily consists of five steps: data import, bottom tracking, image preprocessing, trajectory homing, and data interpretation.

[0003] Track homing is a comprehensive assessment based on the length of the towline, combined with the ship's GNSS positioning system and the towfish's attitude measurement system. Towing operations are affected by various factors, such as ship speed and currents, and the towfish's underwater depth can vary significantly, resulting in inaccurate track and attitude data. Excessive errors in track homing calculations can cause significant shifts in the position of the same underwater object between sonar images, making it impossible to accurately determine the object's true underwater location or accurately restore the underwater topography, increasing the difficulty of subsequent work. Summary of the Invention

[0004] In order to solve the problem of inaccurate underwater terrain images obtained by side-scan sonar, the present application provides a method for correcting side-scan sonar images.

[0005] A method for correcting a side-scan sonar image comprises the following steps:

[0006] Obtain the DEM model of underwater terrain;

[0007] Acquire a side-scan image of a side-scan sonar, wherein the side-scan image includes a plurality of unit images, and the unit images correspond to track lines and attitude data;

[0008] Constructing a plurality of unit images into a virtual side-scan image according to the track line, the attitude data and the DEM model;

[0009] Iteratively retrieve the track line and posture data of the unit image in the virtual side-scan image according to the track line of the unit image to obtain corrected coordinates;

[0010] The track line and posture data of the unit image in the side-scan image are calibrated according to the corrected coordinates to obtain a calibrated side-scan image.

[0011] Furthermore, iteratively retrieving the track line and posture data of the unit image in the virtual side-scan image according to the track line of the unit image specifically includes:

[0012] Extracting a calibration image corresponding to the unit image from the virtual side scan image according to the track line of the unit image, wherein the range of the calibration image is larger than the range of the unit image;

[0013] extracting feature points of the unit image and the calibration image respectively;

[0014] Matching the feature points of the unit image with the feature points of the calibration image to obtain a plurality of matching point pairs, and eliminating incorrect matching point pairs;

[0015] Obtain translation parameters and rotation parameters according to the translation and rotation relationship of the matching point pair;

[0016] Calibrate the track line and attitude data of the unit image according to the translation parameter and the rotation parameter;

[0017] The range of the calibration image is narrowed according to the track line of the unit image after calibration, and the above steps are repeated to obtain the final track line and attitude data.

[0018] Furthermore, the translation and rotation relationship of the matching point pair is expressed as:

[0019]

[0020] Among them, X and Y are the coordinates of the matched feature points in the virtual side scan image, XCS and YCS are the coordinates of the feature points of the unit image, T1 and T2 are translation parameters, and R1 and R2 are rotation parameters.

[0021] Furthermore, the method also includes grayscale processing of the DEM model.

[0022] Furthermore, obtaining the DEM model of the underwater terrain includes: measuring the underwater terrain using a multi-beam bathymetric system to form an image lattice of the measurement object, outputting three-dimensional coordinates of the image area, and establishing a DEM model according to the three-dimensional coordinates.

[0023] Furthermore, it also includes preprocessing the unit images of the side scan image, specifically including slant range correction and bottom tracking.

[0024] Furthermore, the attitude data is attitude change data of the side scan sonar at each moment in the water, including roll, pitch, bow roll and heave.

[0025] A side-scan sonar mosaic image system is obtained according to any of the above-mentioned side-scan sonar image correction methods.

[0026] The beneficial effects of the present invention are:

[0027] A virtual image is constructed by combining the side-scan sonar track and attitude data with the DEM model and compared with the actual side-scan image. The track and attitude data are corrected to make the virtual image data consistent with the actual side-scan image, and the real side-scan sonar underwater positioning and attitude data are obtained. This is used to correct the side-scan sonar image to obtain a high-precision side-scan sonar mosaic image, which solves the problem of excessive misalignment in the splicing of adjacent survey lines caused by the low positioning and attitude accuracy of traditional side-scan sonar data. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0029] Figure 1 It is a schematic diagram of the overall flow of the correction method. DETAILED DESCRIPTION

[0030] In order to make the purpose, features, and advantages of this application more obvious and easy to understand, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the embodiments described below are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0031] The present invention will be further explained below with reference to the accompanying drawings and specific embodiments.

[0032] Example 1

[0033] This embodiment provides a method for correcting side-scan sonar images. Figure 1 As shown, the following steps are included:

[0034] S1, obtain the DEM model of the underwater terrain.

[0035] The multi-beam bathymetry system is used to measure underwater terrain, form an image matrix of the measured object, and output the three-dimensional coordinates of the image area. A DEM model is established based on the three-dimensional coordinates. The DEM model is then grayscale processed to obtain a grayscale image of the underwater terrain.

[0036] Multi-beam bathymetry technology can obtain high-resolution and accurately positioned underwater terrain data, and then generate a high-precision DEM model that can express the elevation fluctuations.

[0037] S2. Acquire a side-scan sonar image. The side-scan image consists of several unit images. A unit is a segmentation unit of the side-scan image and is not specifically limited. For example, a ping image can be considered a unit image. Each unit image is associated with a trackline and attitude data. The attitude data is the attitude change data of the side-scan sonar at each moment in the water, including roll, pitch, heading, and depth data.

[0038] Preprocess the unit images of the side scan image, including slant range correction and bottom tracking.

[0039] Bottom tracking includes: side scan sonar imaging based on time-series echoes. For the first transmitting beam, its echo is received after a period of time spent in round-trip propagation in the vertical direction. Therefore, a blank section from the middle line to the image area appears in 1 Ping scan line, which is the water column area. For the first echo received from directly below the towed fish, due to the short propagation distance and small energy loss, its echo intensity is the strongest, and it is represented as the seabed point of the Ping in the image; the echoes received subsequently are arranged in sequence to form a Ping scan line (Scanline). With the movement of the measuring carrier and the continuous emission and reception beams of the transducer, the Ping scan line is recorded in sequence, and the line is the seabed line. At the same time, the height H of the towed fish to the seabed can also be known.

[0040] H=T×V

[0041] Where T is the one-way time of the first echo received from directly below the towed fish, and V is the speed of sound waves in water.

[0042] Slope range corrections include:

[0043] The side scan sonar image is calculated from left to right based on the time it takes for the sound waves to return. Therefore, the side scan sonar image reflects the slant distance from the transducer to the seabed, resulting in uneven lateral scale on the sonar image and causing the target to be laterally deformed. Slant range is defined as the straight-line distance from the side scan sonar head to a certain point on the terrain (generally ignoring microscopic terrain fluctuations). Therefore, we will find that in order to ensure that the lateral reflection is the lateral distance and the sonar image is not deformed, slant range correction must be performed. Generally speaking, this can be achieved using the following formula:

[0044]

[0045] L is the slant distance, and H is the height from the side scan sonar to the seabed.

[0046] S3, constructing a virtual side-scan image from the plurality of unit images according to the track line and attitude data obtained in step S2 and the DEM model obtained in step S1.

[0047] S4, based on the unit image's trackline, i.e., the unit image's coordinate information in the side-scan image, iteratively retrieves the unit image's trackline and posture data in the virtual side-scan image obtained in step S3 to obtain corrected coordinate information. This specifically includes steps S41 to S46, and is illustrated using a ping image as an example.

[0048] S41, extracting the corresponding calibration image B from the virtual side scan image based on the track line of a ping image A. Image B and image A are in the same location area, and the range of calibration image B extends 50 meters around image A to ensure that image A is included in image B.

[0049] S42, using the sift algorithm to extract feature points of image A and image B respectively.

[0050] S43, using the nearest neighbor method to match the feature points of image A with the feature points of image B to obtain a number of matching point pairs; using the random sampling consensus (RANSAC) algorithm to eliminate incorrect matching point pairs for the matched feature points.

[0051] S44, obtaining translation parameters and rotation parameters based on the translation and rotation relationship of the matching point pair. The translation and rotation relationship of the matching point pair is expressed as follows:

[0052]

[0053] Among them, X and Y are the coordinates of the feature points matched in the virtual side scan image, X CS 、Y CS are the coordinates of the feature points of the unit image, T1 and T2 are the translation parameters, and R1 and R2 are the rotation parameters.

[0054] Then we have:

[0055]

[0056] make:

[0057]

[0058] but:

[0059] p=(X T X) -1 X t a

[0060] Then the translation parameters and rotation parameters are obtained. The translation parameters correspond to the track line, and the rotation parameters correspond to the attitude data.

[0061] S45 , calibrating the trajectory and posture data of the unit image according to the translation parameter and the rotation parameter.

[0062] S46, narrowing the range of the calibration image according to the track line of the calibrated unit image, and repeating the above steps to obtain the final track line and attitude data.

[0063] S5 , calibrating the track line and attitude data of the unit image in the side-scan image according to the corrected coordinate information obtained in step S4 to obtain a calibrated side-scan image.

[0064] The side-scan sonar image correction method according to this embodiment can obtain a high-precision side-scan sonar mosaic image with more accurate track line and attitude accuracy, and the side-scan sonar mosaic image also falls within the protection scope of the present invention.

[0065] Example 2

[0066] This embodiment discloses a side-scan sonar image correction system, which is used to implement the side-scan sonar correction in Example 1, and includes:

[0067] The DEM unit is used to store and process the DEM model of the underwater terrain. It also performs grayscale processing on the DEM model to obtain the underwater terrain grayscale impact map.

[0068] The side-scan sonar unit is used to store the side-scan images produced by the sonar. The side-scan images include a number of unit images, each of which corresponds to a track line and attitude data. The unit images are pre-processed, including slant range correction and bottom tracking.

[0069] The image construction unit is used to construct a plurality of unit images into a virtual side-scan image according to the track line and attitude data stored in the side-scan unit and the DEM model stored in the DEM unit.

[0070] The retrieval unit is used to iteratively retrieve the track line and posture data of the unit image in the virtual side-scan image according to the track line of the unit image to obtain the corrected coordinates. The specific operation is:

[0071] Extracting a calibration image corresponding to the unit image from the virtual side scan image according to the track line of the unit image, wherein the range of the calibration image is larger than the range of the unit image;

[0072] extracting feature points of the unit image and the calibration image respectively;

[0073] Matching the feature points of the unit image with the feature points of the calibration image to obtain a plurality of matching point pairs, and eliminating incorrect matching point pairs;

[0074] Obtain translation parameters and rotation parameters according to the translation and rotation relationship of the matching point pair;

[0075] Calibrate the track line and attitude data of the unit image according to the translation parameter and the rotation parameter;

[0076] The range of the calibration image is narrowed according to the track line of the unit image after calibration, and the above steps are repeated to obtain the final track line and attitude data.

[0077] The image forming unit is used to calibrate the track line and posture data of the unit image in the side-scan image according to the corrected coordinates to obtain a calibrated side-scan image.

[0078] Example 3

[0079] This embodiment discloses a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the side-scan sonar image correction method in Embodiment 1 can be implemented.

[0080] The computer-readable storage medium may be in the form of an electrical connection having one or more wire segments, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0081] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of units is merely a logical functional division. In actual implementation, other division methods may be used, such as combining or integrating multiple units into another device, or ignoring or not implementing certain features.

[0082] The units may or may not be physically separate, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0083] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0084] In this application, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. Furthermore, in this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, electrical, optical, RF, or any suitable combination thereof.

Claims

1. A method for correcting side-scan sonar images, characterized in that: The following steps are involved: Obtain the DEM model of underwater terrain; Acquire a side-scan image of a side-scan sonar, wherein the side-scan image includes a plurality of unit images, and the unit images correspond to track lines and attitude data; Constructing a plurality of unit images into a virtual side-scan image according to the track line, the attitude data and the DEM model; Iteratively retrieving the track line and attitude data of the unit image in the virtual side-scan image according to the track line of the unit image to obtain corrected coordinates, specifically comprising: extracting a calibration image corresponding to the unit image in the virtual side-scan image according to the track line of the unit image, wherein the range of the calibration image is larger than the range of the unit image; extracting feature points of the unit image and the calibration image respectively; matching the feature points of the unit image with the feature points of the calibration image to obtain a plurality of matching point pairs, and eliminating erroneous matching point pairs; obtaining translation parameters and rotation parameters according to the translation and rotation relationships of the matching point pairs; calibrating the track line and attitude data of the unit image according to the translation parameters and rotation parameters; reducing the range of the calibration image according to the track line of the calibrated unit image, and repeating the above steps to obtain final track line and attitude data; The track line and posture data of the unit image in the side-scan image are calibrated according to the corrected coordinates to obtain a calibrated side-scan image.

2. The side scan sonar image correction method according to claim 1, characterized in that: The translation and rotation relationship of the matching point pair is expressed as: ， Among them, X and Y are the coordinates of the feature points matched in the virtual side scan image, X CS 、Y CS are the coordinates of the feature points of the unit image, T1 and T2 are the translation parameters, and R1 and R2 are the rotation parameters.

3. The side scan sonar image correction method according to claim 1, characterized in that: The method also includes grayscale processing of the DEM model.

4. The side scan sonar image correction method according to claim 1, characterized in that: Acquiring a DEM model of underwater terrain includes: measuring the underwater terrain using a multi-beam bathymetric system to form an image matrix of the measurement object, outputting three-dimensional coordinates of the image area, and establishing a DEM model based on the three-dimensional coordinates.

5. The side scan sonar image correction method according to claim 1, characterized in that: The method also includes preprocessing the unit images of the side scan image, specifically including slant range correction and bottom tracking.

6. The side scan sonar image correction method according to claim 1, characterized in that: The attitude data is the attitude change data of the side scan sonar at each moment in the water, including roll, pitch, bow roll and heave.

7. A side-scan sonar mosaic imaging system, characterized in that: The side-scan sonar mosaic image system obtains a side-scan sonar mosaic image according to the side-scan sonar image correction method according to any one of claims 1 to 6.

8. A side-scan sonar image correction system, characterized in that: The side-scan sonar image correction system performs the side-scan sonar image correction method according to any one of claims 1 to 6, comprising: DEM unit, used to store and process DEM models of underwater terrain; A side scan sonar unit, used to store a side scan image of the side scan sonar, wherein the side scan image includes a plurality of unit images, and each unit image corresponds to a track line and attitude data; An image construction unit, configured to construct a plurality of unit images into a virtual side-scan image according to the track line, the attitude data and the DEM model; a retrieval unit, configured to iteratively retrieve the track line and posture data of the unit image in the virtual side-scan image according to the track line of the unit image to obtain a corrected coordinate; The image forming unit is used to calibrate the track line and posture data of the unit image in the side-scan image according to the corrected coordinates to obtain a calibrated side-scan image.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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