Sonar multi-opening-angle amplification method and system based on image processing

Abstract

The invention relates to the technical field of underwater sonar, in particular to a sonar multi-opening-angle amplification method and a sonar multi-opening-angle amplification system based on image processing, and the method comprises the steps: 1, obtaining a first sonar image corresponding to a first sonar signal and a second sonar image corresponding to a second sonar signal; step 2, classifying the first sonar image and the second sonar image according to image feature information of the first sonar image and the second sonar image, and determining an overall sonar image category of the first sonar image and the second sonar image, the overall sonar image category including a static sonar image and a dynamic sonar image; and step 3, according to the total sonar image category, carrying out image splicing processing on the first sonar image and the second sonar image to obtain a target sonar image.

Description

Technical Field

[0001] The present application relates to the field of underwater sonar technology, and in particular to a sonar multi-angle amplification method and a sonar multi-angle amplification system based on image processing. Background Art

[0002] The working process of sonar mainly includes: 1. The sonar transmitting device transmits sound waves; 2. The sonar receiving device receives the reflected echo; 3. The signal processing device processes the reflected echo to generate a sonar image. In this process, the sonar transmitting device transmits a sound wave in a fan-shaped direction, and the reflected sound waves at different angles are received by the sonar receiving device and processed by the signal processing device to generate a sonar image. The reflected sound waves in different directions are synchronously generated through beamforming technology based on the sound wave signals received by each array element on the transducer array in the sonar transmitting device. Therefore, a complete fan-shaped sonar image can be generated through a single transmission and reception.

[0003] The sonar transmitter receives underwater acoustic signals in parallel through a transducer array, and its field of view is limited by the beam characteristics of the transducer array. Figure 1 As shown, the transducer array will produce grating lobes and side lobes, which will cause the array to receive interference signals, such as hydroacoustic signals in undesired directions, resulting in false targets appearing in the final sonar image.

[0004] The spacing of the transducers, the size of the transducers, the frequency and bandwidth will all have an impact on the grating lobe and side lobe phenomenon. Therefore, once the parameters of the receiving array are determined, the effective field of view of the sonar is limited to a fixed range. The grating lobe limits the field of view of the transducer array. If the field of view needs to be increased, the spacing between the transducers needs to be reduced. This requires a higher level of transducer technology, and more transducers need to be invested in the same size array, resulting in increased costs.

[0005] At present, in order to expand the field of view of sonar, the following methods are mainly used, but these methods all have certain limitations: 1. Reduce the size and spacing of the transducer: Although this method can effectively increase the detection range of the sonar, it requires an increase in the investment in transducers and sampling circuits, resulting in a significant increase in system costs. 2. Mechanical rotation mechanism: Although it is technically feasible to widen the field of view through mechanical rotation, it inevitably sacrifices the image update rate. In addition, the introduction of rotating parts also brings challenges in mechanical reliability, increasing maintenance costs and potential failure risks. 3. Deployment of multiple sonar systems: Although the use of multiple sonar systems can significantly increase the detection range, the system complexity of this solution is extremely high. Not only does it require a precise synchronization mechanism to ensure the coordinated operation of the systems, it may also lead to resource redundancy and increased costs. Summary of the invention

[0006] In view of this, the purpose of this application is to provide a sonar multi-opening angle amplification method and system based on image processing to solve the above problems.

[0007] To solve the above technical problems, this application adopts the following technical solutions:

[0008] In a first aspect, this application provides a sonar multi-opening angle amplification method based on image processing, which is applied to a sonar system. The sonar system includes: a first sonar transmitting device, a second sonar transmitting device, and a sonar receiving device. The transmitting angles of the first sonar transmitting device and the second sonar are complementary. The first sonar transmitting device transmits a first sonar signal, and the second sonar transmitting device transmits a second sonar signal. The first sonar signal and the first sonar signal are transmitted at different times. The sonar receiving device receives the first sonar signal and the second sonar signal. The sonar multi-opening angle amplification method includes: Step 1: Obtain a first sonar image corresponding to the first sonar signal and a second sonar image corresponding to the second sonar signal; Step 2: Classify the first sonar image and the second sonar image according to the image feature information of the first sonar image and the second sonar image, and determine the overall sonar image category of the first sonar image and the second sonar image. The overall sonar image category includes a static sonar image and a dynamic sonar image; Step 3: Perform image stitching processing on the first sonar image and the second sonar image according to the overall sonar image category to obtain a target sonar image.

[0009] Furthermore, the image feature information includes at least one of the following: image gray-scale contrast feature, image boundary feature, and difference feature between consecutive frames of the image.

[0010] Furthermore, when the overall sonar image category is a static sonar image, Step 3 specifically includes: Step A1: Determine the edge parts of the first sonar image and the second sonar image; Step A2: Perform stitching processing on the first sonar image and the second sonar image according to the edge parts of the first sonar image and the second sonar image to obtain a target sonar image.

[0011] Furthermore, when the overall sonar image category is a dynamic sonar image, Step 3 specifically includes: Step B1: Based on the feature point extraction algorithm, extract the first feature point information corresponding to the first sonar image and the second feature point information corresponding to the second sonar image respectively; Step B2: Match the first feature point information and the second feature point information to determine the overlapping area image and the non-overlapping area image corresponding to the first sonar image and the second sonar image; Step B3: Perform image fusion processing on the overlapping area image and image stitching processing on the non-overlapping area image to obtain a target sonar image.

[0012] Further, step B2 specifically includes: step B2-1: Based on the nearest neighbor ratio matching strategy, match the first feature point information and the second feature point information to obtain the nearest neighbor distance ratios corresponding to multiple feature matching point pairs; step B2-2: Determine whether the nearest neighbor distance ratio is greater than a preset distance ratio threshold: if so, determine that the images corresponding to the feature matching point pairs are overlapping region images.

[0013] Further, step B3 includes: step B3-1: Process the feature matching point pairs according to the RANSAC algorithm to calculate the target feature matching point pairs; step B3-2: Calculate the transformation matrix based on the target feature matching point pairs; step B3-3: Based on the transformation matrix, perform image registration on the first sonar image and the second sonar image; step B3-4: Based on the weighted average algorithm, perform gray value fusion processing on the overlapping region images to obtain the target sonar image.

[0014] Further, the overall sonar image category is a dynamic sonar image, and step 3 specifically includes: step C1: Obtain the first emission angle information of the first sonar emission device and the second emission angle information of the second sonar emission device; step C2: Based on the first emission angle information and the second emission angle information, perform perspective correction on the first sonar image and the second sonar image to determine the target sonar image.

[0015] Further, step C2 specifically includes: step C2-1: Calculate the emission angle difference information according to the first emission angle information and the second emission angle information; step C2-2: Rotate and align the second sonar image to the first sonar image according to the emission angle difference information; step C2-3: Perform image fusion and stitching processing on the first sonar image and the rotated second sonar image to determine the target sonar image.

[0016] In a second aspect, the present application provides a sonar multi-opening angle amplification system, including: a first sonar transmitting device, a second sonar transmitting device, a sonar receiving device, and a signal processing device. The transmitting angles of the first sonar transmitting device and the second sonar are complementary. The first sonar transmitting device transmits a first sonar signal, and the second sonar transmitting device transmits a second sonar signal. The first sonar signal and the second sonar signal are transmitted at different times. The sonar receiving device receives the first sonar signal and the second sonar signal. The signal processing device includes an acquisition module, a classification module, and a processing module. The acquisition module is used to acquire a first sonar image corresponding to the first sonar signal and a second sonar image corresponding to the second sonar signal; the classification module is used to classify the first sonar image and the second sonar image according to the image feature information of the first sonar image and the second sonar image, and determine the overall sonar image category of the first sonar image and the second sonar image. The overall sonar image category includes a static sonar image and a dynamic sonar image; the processing module is used to perform image stitching processing on the first sonar image and the second sonar image according to the overall sonar image category to obtain a target sonar image.

[0017] In a third aspect, the present application provides a non-volatile readable storage medium storing computer-readable instructions. When the computer-readable instructions are executed by a processor, the processor is caused to execute the sonar multi-opening angle amplification method based on image processing as described in the first aspect above.

[0018] As can be seen from the above technical solutions, the advantages and positive effects of a sonar multi-opening angle amplification method and system based on image processing proposed by the present application are as follows:

[0019] First of all, in the present application, the sonar transmitting device is divided into two parts, namely a first sonar transmitting device and a second sonar transmitting device, which emit sound waves in different directions respectively. The receiving transducer array of the same sonar receiving device receives the sonar echoes in two directions at different times to avoid the occurrence of grating lobes and side lobes in the transducer array and improve the sonar image quality.

[0020] Secondly, in the present application, the viewing angle of the sonar is amplified through image processing. According to the categories of the two sonar images, the corresponding image processing method is selected, and after processing, the two images are stitched to form a complete sonar image with a larger field of view. Compared with the prior art, the present invention can significantly expand the viewing angle opening of the sonar without adding a sonar receiving device, and reduce the system cost.

[0021] In addition, the present application is applicable to existing sonar systems. Only simple modifications need to be made to the existing sonar systems to apply the sonar opening angle amplification method provided by the present application. The system cost is significantly reduced compared with the traditional scheme. There are no mechanical moving parts, and the image update rate is only slightly lower than that of the traditional single-transmission scheme. The system structure is simple, easy to implement and maintain, and the beamforming algorithm requires half the computing power and can be implemented using low-cost chips, further reducing the system cost. Description of the Drawings

[0022] The above content of the present application and the following detailed implementation manners will be better understood when read in conjunction with the accompanying drawings. It should be noted that the drawings are only examples of the claimed technical solutions.

[0023] Figure 1 It is a diagram of the grating lobe radiation phenomenon received by the transducer array;

[0024] Figure 2 It is a block diagram of the sonar multi-opening angle amplification system provided by the present application;

[0025] Figure 3 It is a flowchart of the sonar multi-opening angle amplification method based on image processing provided by the present application;

[0026] Figure 4 It is the overall flowchart of the sonar multi-opening angle amplification method provided by the present application;

[0027] Figure 5 It is a flowchart of the first implementation manner for obtaining the target sonar image provided by the present application;

[0028] Figure 6 It is a schematic diagram of the splicing of static images provided by the present application;

[0029] Figure 7 It is a flowchart of the second implementation manner for obtaining the target sonar image provided by the present application;

[0030] Figure 8 It is a schematic diagram of the splicing of dynamic images provided by the present application;

[0031] Figure 9 It is a flowchart of the third implementation manner for obtaining the target sonar image of the present application.

[0032] Among them, the reference numerals are explained as follows:

[0033] The first sonar transmitting device: 10;

[0034] The second sonar transmitting device: 20;

[0035] The sonar receiving device: 30;

[0036] The signal processing device: 40. Detailed Implementation Manner

[0037] The following details the detailed features and advantages of the present application in the detailed implementation manner. The content is sufficient for any person skilled in the art to understand the technical content of the present application and implement it accordingly. According to the specification, claims and drawings disclosed in this specification, those skilled in the art can easily understand the related purposes and advantages of the present application.

[0038] It should be noted that in this specification, similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0039] In the description of this embodiment, it should be noted that the orientation or positional relationship indicated by the terms "upper", "lower", "inner", "bottom", etc. is based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the product is usually placed during use. It is only for the convenience of describing this application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to this application.

[0040] To make the objectives, technical solutions, and advantages of this application clearer, the following will further describe the embodiments of this application in detail with reference to the drawings.

[0041] Please refer to Figure 2 As shown, this application provides a sonar multi-opening angle amplification system, which includes: a first sonar transmitting device 10, a second sonar transmitting device 20, a sonar receiving device 30, and a signal processing device 40.

[0042] Among them, the first sonar transmitting device 10 and the second sonar transmitting device 20 are respectively installed at different positions, and their installation angles can be specifically and flexibly adjusted according to the actual application scenario. Their transmitting angles can be complementary. In actual situations, the transmitting angles of the first sonar transmitting device 10 and the second sonar transmitting device 20 can partially overlap to ensure that the detection areas corresponding to the two transmitting angles are fully covered.

[0043] Exemplarily, the transmitting direction of the first sonar transmitting device 10 is from -θ to α degrees, and the transmitting direction of the second sonar transmitting device 20 is from -α to θ degrees, forming complementary transmitting angles of the two sonar transmitting devices.

[0044] The transmitted signals of the first sonar transmitting device 10 and the second sonar transmitting device 20 are time-division multiplexed and alternately transmitted to avoid being affected by the grating lobe phenomenon and the side lobe phenomenon.

[0045] It can be understood that if the gain of the grating lobe or side lobe is relatively large compared to the main lobe, the sound wave reflected from the grating lobe or side lobe direction back to the receiving array of the sonar receiving device 30 will be treated as a target on the main lobe, and the receiving array cannot distinguish whether this echo signal comes from the main lobe (the direction where detection is desired) or from the grating lobe / side lobe direction. Therefore, one method is to control the direction in which the transmitting array emits sound so that it does not emit sound waves in the grating lobe direction. However, this inevitably limits the field of view opening angle of the sonar system.

[0046] Compared with the common situation in the current existing technologies where multiple sonars simultaneously transmit sonar signals, which easily causes grating lobe phenomena and sidelobe phenomena, the present application innovatively proposes to alternately transmit signals through the first sonar transmitting device 10 and the second sonar transmitting device 20, so that the receiving array of the sonar receiving device 30 only receives the sonar signal of one sonar transmitting device at a single time, and determines that the sonar signal is the signal coming from the main lobe direction, so as to improve the grating lobe problem and the sidelobe problem.

[0047] The first sonar transmitting device 10 transmits a first sonar signal, and the second sonar transmitting device 20 transmits a second sonar signal. The first sonar signal and the first sonar signal are transmitted at different times to achieve time-division multiplexing transmission.

[0048] The sonar receiving device 30 can use a single receiving transducer array to receive the first sonar signal and the second sonar signal in two directions. Among them, the beam coverage range of the receiving transducer array can meet the irradiation range of the transmitting transducer of a single sonar transmitting device.

[0049] The signal processing device 40 processes the sonar echo signals in two directions in a time-division multiplexing manner, and independently performs beamforming and image generation on the echo signals in each direction, and then realizes seamless splicing of the two images by designing an image splicing algorithm.

[0050] Specifically, the signal processing device 40 includes an acquisition module, a classification module, and a processing module. Among them, the acquisition module is used to acquire the first sonar image corresponding to the first sonar signal and the second sonar image corresponding to the second sonar signal; the classification module is used to classify the first sonar image and the second sonar image according to the image feature information of the first sonar image and the second sonar image, and determine the overall sonar image category of the first sonar image and the second sonar image. The overall sonar image category includes static sonar images and dynamic sonar images; the processing module is used to perform image splicing processing on the first sonar image and the second sonar image according to the overall sonar image category to obtain a target sonar image.

[0051] It can be understood that the sonar multi-opening angle amplification system proposed in the present application realizes a significant expansion of the field of view opening angle without increasing the number of receiving transducers. Compared with the traditional scheme, this system greatly reduces the cost, and at the same time abandons mechanical moving parts, thus ensuring a high degree of reliability. In terms of the image update rate, this system is slightly inferior to the traditional single-transmission scheme, but still maintains high efficiency. Structurally, this system is simple and clear, which is not only easy to implement and maintain, but also can easily realize the opening angle amplification by simply modifying the existing sonar. In addition, the beamforming algorithm adopted halves the computing power requirements, which means that a chip with lower cost can be used to implement it, further reducing the overall cost of the system.

[0052] Please refer to Figure 3 and Figure 4 , based on the above sonar multi-opening angle amplification system, the present application also provides a sonar multi-opening angle amplification method based on image processing. The specific steps of this method are as follows:

[0053] Step 1: Obtain the first sonar image corresponding to the first sonar signal and the second sonar image corresponding to the second sonar signal.

[0054] Step 2: Classify the first sonar image and the second sonar image according to the image feature information of the first sonar image and the second sonar image, and determine the overall sonar image category of the first sonar image and the second sonar image.

[0055] Among them, the overall sonar image category includes static sonar images and dynamic sonar images, and the image feature information includes at least one of the following: image gray contrast feature, image boundary feature, and difference feature between consecutive frames of the image.

[0056] It can be understood that a static sonar image refers to a situation where the position and attitude of the sonar do not change significantly between the left and right frame imaging operations. This static situation means that the sonar does not change between the left frame imaging and the right frame imaging, rather than the position of the detected target not changing.

[0057] A dynamic sonar image refers to a situation where the position or attitude of the sonar changes significantly between two frame imaging operations. Dynamic compensation corresponds to different imaging of overlapping area objects during the generation of two images. For example, a change in the pitch angle will cause a change in the shape of feature points. At this time, simple stitching will result in a large distortion, which may exceed the allowable limit. The method to repair this distortion is to calculate the coordinate system difference between the left and right frames according to the overlapping area during each stitching, and transform the coordinate systems of the two frames through the calculated coordinate system transformation matrix, and then stitch the two transformed frames.

[0058] Step 3: Perform image stitching processing on the first sonar image and the second sonar image according to the overall sonar image category to obtain a target sonar image.

[0059] As Figure 5 shown in the first embodiment of the present application, step 3 may include: Step A1: Determine the edge part of the first sonar image and the edge part of the second sonar image. Step A2: Perform stitching processing on the first sonar image and the second sonar image according to the edge part of the first sonar image and the edge part of the second sonar image to obtain a target sonar image.

[0060] It can be understood that this embodiment is applicable to scenarios where the sonar emission device is fixedly installed or the object detected by the sonar emission device has a relatively slow moving speed, and the first sonar image and the second sonar image are static sonar images. In this case, within the imaging cycle of the transmitting transducers of the first sonar emission device and the second sonar emission device, parameters such as the position and attitude of the sonar will not change significantly, or the changes that occur are negligible compared to the dimensions of the sonar image. As Figure 6 shown, in this application scenario, a static image stitching algorithm can be used to directly stitch the edge parts of the images in two directions, so that the formed target sonar image has a larger viewing angle.

[0061] As Figure 7 and Figure 8 shown in the second implementation manner of the present application, step 3 may specifically include:

[0062] Step B1: Based on the feature point extraction algorithm, extract the first feature point information corresponding to the first sonar image and the second feature point information corresponding to the second sonar image respectively.

[0063] Specifically, within the overlapping region of the first sonar image and the second sonar image, the SURF (Speeded Up Robust Features) algorithm can be used to extract the feature point information. The selection of feature points can be determined according to the characteristics of the sonar image. Exemplarily, the characteristics include: 1. The mutation points at the target edge; 2. The centroid of the strong reflection region; 3. The region with obvious texture changes. Among them, each feature point in the feature point information generates a 128-dimensional feature descriptor.

[0064] Step B2: Match the first feature point information and the second feature point information to determine the overlapping region image and the non-overlapping region image corresponding to the first sonar image and the second sonar image.

[0065] Step B2 specifically includes: Step B2-1: Based on the nearest neighbor ratio matching strategy, match the first feature point information and the second feature point information to obtain the nearest neighbor distance ratio corresponding to multiple feature matching point pairs; Step B2-2: Determine whether the nearest neighbor distance ratio is greater than the preset distance ratio threshold: if so, determine the image corresponding to the feature matching point pair as the overlapping region image; if not, determine the image corresponding to the feature matching point pair as the non-overlapping region image.

[0066] Specifically, 1. The nearest neighbor ratio matching strategy (NNDR) is adopted for feature point matching. The Euclidean distances between the respective feature descriptors in the first sonar image and the second sonar image are calculated to obtain the nearest neighbor distance and the second nearest neighbor distance between the feature points. 2. Nearest neighbor distance / Second nearest neighbor distance = Nearest distance ratio. 3. When the nearest distance ratio is greater than 0.8, the two feature points are determined to be a reliable matching point pair. The reliable matching point pair can represent an overlapping region image, and the matching points with a nearest distance ratio less than 0.8 can represent a non-overlapping region image.

[0067] Step B3: Perform image fusion processing on the overlapping region image and image stitching processing on the non-overlapping region image to obtain the target sonar image.

[0068] Step B3 includes: Step B3-1: According to the RANSAC algorithm, process the feature matching point pairs to calculate the target feature matching point pairs; Step B3-2: Calculate the transformation matrix based on the target feature matching point pairs; Step B3-3: Based on the transformation matrix, perform image registration on the first sonar image and the second sonar image; Step B3-4: Based on the weighted average algorithm, perform gray value fusion processing on the overlapping region image to obtain the target sonar image.

[0069] Specifically, first, use the RANSAC (Random Sample Consensus) algorithm to remove the incorrect matching points to obtain the target feature matching point pairs.

[0070] Secondly, calculate the transformation matrix H based on the target feature matching point pairs. H is a 3×3 matrix, which contains rotation, translation, and scaling information.

[0071] It can be understood that the transformation matrix H can be a perspective transformation matrix or an affine transformation matrix. The perspective transformation matrix is used to correct the image distortion caused by the angular change in the pitch angle of the sonar between the left and right frame imaging operations. The affine transformation matrix refers to the situation where the sonar only undergoes a left-right angular change between the left and right frame imaging operations (a relatively simpler change compared to the former).

[0072] Thirdly, according to the transformation matrix H, perform a geometric transformation on the second sonar image to align it with the first sonar image to achieve image registration.

[0073] Then, process the gray value fusion of the overlapping region to obtain the target sonar image. Specifically, use the weighted average method: The pixel value P of the overlapping region = w1×P1 + w2×P2, where w1 and w2 are weight coefficients, which are proportional to the distance of the pixel of the sonar image to the boundary.

[0074] Such as Figure 9In the third implementation manner of the present application shown, step 3 specifically includes: Step C1: Obtain the first emission angle information of the first sonar emission device and the second emission angle information of the second sonar emission device. Step C2: Based on the first emission angle information and the second emission angle information, perform perspective correction on the first sonar image and the second sonar image to determine the target sonar image.

[0075] Step C2 specifically includes: Step C2-1: Calculate the emission angle difference information according to the first emission angle information and the second emission angle information; Step C2-2: Rotate and align the second sonar image to the first sonar image according to the emission angle difference information; Step C2-3: Perform image fusion and stitching processing on the first sonar image and the rotated second sonar image to determine the target sonar image.

[0076] This embodiment is applicable to scenarios where the movement of the sonar emission device is mainly horizontal rotation. In this case, the movement of the sonar emission device will cause changes in the overlapping area of the images formed in two directions of the sonar. Therefore, it is necessary to use an attitude sensor to obtain the motion state of the emission device in real time and adjust the image stitching area according to the motion state.

[0077] Specifically, the first sonar emission device and the second sonar emission device are provided with attitude sensors, and through the attitude sensors, the first emission angle information of the first sonar emission device and the second emission angle information of the second sonar emission device can be obtained.

[0078] When the first sonar emission device emits the first sonar signal, record the azimuth angle θ1 of the current sonar array. When the second sonar emission device emits the second sonar signal, record the new azimuth angle θ2, and calculate the angle difference information Δθ = θ2 - θ1 between the two emissions.

[0079] Rotate the second sonar image by the angle difference Δθ to correct the angle of the second sonar image. After completing the angle correction of the second sonar image, the first sonar image and the second sonar image are in the same coordinate system. At this time, the complementary regions of the first sonar image and the second sonar image can be selected for stitching. Then, process the gray value fusion of the overlapping region to obtain the target sonar image. Specifically, use the weighted average method: the pixel value P of the overlapping region = w1×P1 + w2×P2, where w1 and w2 are weight coefficients, which are proportional to the distance of the pixels of the sonar image to the boundary.

[0080] It can be understood that the methods provided in the first embodiment, the second embodiment, and the third embodiment can be flexibly selected according to the actual application scenario, or can be combined to obtain a better stitching effect. For example, in a complex underwater environment, feature point matching and emission angle information correction can be applied simultaneously to improve the accuracy and reliability of stitching.

[0081] It should be noted that the systems, devices or modules illustrated in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer, and the specific form of the computer can be a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email transceiver device, a game console, a tablet computer, a wearable device, or a combination of any several of these devices.

[0082] In a typical configuration, a computer includes one or more processors (CPUs), an input / output interface, a network interface, and a memory.

[0083] The memory may include non-permanent memory in the computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

[0084] Computer-readable media include permanent and non-permanent, removable and non-removable media and can be implemented by any method or technology for storing information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, disk storage, quantum memory, graphene-based storage media or other magnetic storage devices, or any other non-transmission media that can be used to store information accessible by a computing device. As defined herein, computer-readable media do not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0085] The terms and expressions used herein are only for description, and the present application should not be limited to these terms and expressions. Using these terms and expressions does not mean excluding any equivalent features of the illustration and description (or parts thereof), and it should be recognized that various modifications that may exist should also be included within the scope of the claims. Other modifications, variations, and substitutions may also exist. Accordingly, the claims should be regarded as covering all such equivalents.

[0086] Similarly, it should be noted that although this application has been described with reference to current specific embodiments, those of ordinary skill in the art should recognize that the above embodiments are only used to illustrate this application, and various equivalent changes or substitutions can be made without departing from the spirit of the invention. Therefore, as long as the changes and modifications to the above embodiments are within the scope of the spirit of this application, they will fall within the scope of the claims of this application.

Claims

1. A sonar multi-angle amplification method based on image processing, applied to a sonar system, characterized in that: The sonar system comprises: a first sonar transmitting device, a second sonar transmitting device and a sonar receiving device, wherein the transmitting angles of the first sonar transmitting device and the second sonar are complementary, the first sonar transmitting device transmits a first sonar signal, the second sonar transmitting device transmits a second sonar signal, the first sonar signal and the first sonar signal are transmitted in time-sharing, the sonar receiving device is used to receive the first sonar signal and the second sonar signal, and the sonar multi-open angle amplification method comprises: Step 1: Acquire a first sonar image corresponding to the first sonar signal and a second sonar image corresponding to the second sonar signal; Step 2: classifying the first sonar image and the second sonar image according to the image feature information of the first sonar image and the second sonar image, and determining the overall sonar image category of the first sonar image and the second sonar image, wherein the overall sonar image category includes a static sonar image and a dynamic sonar image; Step 3: According to the overall sonar image category, the first sonar image and the second sonar image are stitched together to obtain a target sonar image.

2. The sonar multi-angle amplification method according to claim 1, characterized in that: The image feature information includes at least one of the following: image grayscale contrast feature, image boundary feature and difference feature between consecutive frames of the image.

3. The sonar multi-angle amplification method according to claim 1, characterized in that: The overall sonar image category is the static sonar image, and step 3 specifically includes: Step A1: determining an edge portion of the first sonar image and an edge portion of the second sonar image; Step A2: performing splicing processing on the first sonar image and the second sonar image according to the edge portion of the first sonar image and the edge portion of the second sonar image to obtain the target sonar image.

4. The sonar multi-angle amplification method according to claim 1, characterized in that: The overall sonar image category is the dynamic sonar image, and step 3 specifically includes: Step B1: extracting first feature point information corresponding to the first sonar image and second feature point information corresponding to the second sonar image based on a feature point extraction algorithm; Step B2: matching the first feature point information with the second feature point information to determine an overlapping area image and a non-overlapping area image corresponding to the first sonar image and the second sonar image; Step B3: performing image fusion processing on the overlapping area images and image stitching processing on the non-overlapping area images to obtain the target sonar image.

5. The sonar multi-angle amplification method according to claim 4, characterized in that: The step B2 specifically includes: Step B2-1: Based on the nearest neighbor ratio matching strategy, the first feature point information and the second feature point information are matched to obtain the nearest neighbor distance ratios corresponding to multiple feature matching point pairs; Step B2-2: Determine whether the nearest neighbor distance ratio is greater than a preset distance ratio threshold: If so, determine that the image corresponding to the feature matching point pair is the overlapping area image.

6. The sonar multi-angle amplification method according to claim 5, characterized in that: The step B3 comprises: Step B3-1: Process the feature matching point pairs according to the RANSAC algorithm to calculate and obtain target feature matching point pairs; Step B3-2: Calculate the transformation matrix based on the target feature matching point pairs; Step B3-3: performing image registration on the first sonar image and the second sonar image based on the transformation matrix; Step B3-4: Based on the weighted average algorithm, grayscale value fusion processing is performed on the overlapping area image to obtain the target sonar image.

7. The sonar multi-angle amplification method according to claim 1, characterized in that: The overall sonar image category is the dynamic sonar image, and step 3 specifically includes: Step C1: acquiring first emission angle information of the first sonar transmitting device and second emission angle information of the second sonar transmitting device; Step C2: Based on the first emission angle information and the second emission angle information, the first sonar image and the second sonar image are corrected in perspective to determine the target sonar image.

8. The sonar multi-angle amplification method according to claim 7, characterized in that: The step C2 specifically includes: Step C2-1: Calculate emission angle difference information according to the first emission angle information and the second emission angle information; Step C2-2: rotating and aligning the second sonar image to the first sonar image according to the emission angle difference information; Step C2-3: performing image fusion and stitching processing on the first sonar image and the rotated second sonar image to determine the target sonar image.

9. A sonar multi-angle amplification system, characterized in that: include: a first sonar transmitting device, a second sonar transmitting device, a sonar receiving device and a signal processing device, The emission angles of the first sonar transmitting device and the second sonar are complementary, the first sonar transmitting device transmits a first sonar signal, the second sonar transmitting device transmits a second sonar signal, the first sonar signal and the first sonar signal are transmitted in time-sharing, and the sonar receiving device receives the first sonar signal and the second sonar signal. The signal processing device comprises an acquisition module, a classification module and a processing module. The acquisition module is used to acquire a first sonar image corresponding to the first sonar signal and a second sonar image corresponding to the second sonar signal; The classification module is used to classify the first sonar image and the second sonar image according to the image feature information of the first sonar image and the second sonar image, and determine the overall sonar image category of the first sonar image and the second sonar image, wherein the overall sonar image category includes a static sonar image and a dynamic sonar image; The processing module is used to perform image stitching processing on the first sonar image and the second sonar image according to the overall sonar image category to obtain a target sonar image.

10. A non-volatile readable storage medium storing computer-readable instructions, characterized in that: When the computer-readable instructions are executed by a processor, the processor executes the sonar multi-angle amplification method based on image processing as claimed in claim 1.

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