WO2020114107A1 - 一种侧扫声呐实时二维成像方法及系统 - Google Patents

一种侧扫声呐实时二维成像方法及系统 Download PDF

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WO2020114107A1
WO2020114107A1 PCT/CN2019/112055 CN2019112055W WO2020114107A1 WO 2020114107 A1 WO2020114107 A1 WO 2020114107A1 CN 2019112055 W CN2019112055 W CN 2019112055W WO 2020114107 A1 WO2020114107 A1 WO 2020114107A1
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data
image
sonar
scan
real
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PCT/CN2019/112055
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French (fr)
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洪晓斌
龚仕枫
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华南理工大学
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/89—Sonar systems specially adapted for specific applications for mapping or imaging

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  • the invention relates to underwater imaging, in particular to a real-time two-dimensional imaging method and system for side-scan sonar.
  • Underwater acoustic imaging is a branch of acoustic imaging. It plays an important role in underwater acoustic detection. It uses the backscattering effect of sound waves by objects to locate underwater and draw images point by point. The use of sound waves for imaging is developed on the basis of sound wave ranging and direction finding. Underwater acoustic wave ranging mainly uses the time difference between the received echo and the transmitted pulse signal to calculate the distance of the target; underwater acoustic wave direction finding mainly uses the sound of the echo to reach the hydrophone system composed of multiple transducers The path difference and phase difference calculate the bearing of the target.
  • acoustic lens technology In underwater acoustic imaging, there are three basic acoustic imaging technologies: acoustic lens technology, beam forming technology, and acoustic holography technology. All three methods of acoustic imaging use the same operations: spatial processing (acquisition of images from the sound field), transduction (conversion of acoustic energy into electrical energy), and detection (conversion of high-frequency signals into observable and nearly DC image signals) , Display (displayed as an image in some form). The difference between these three methods is the sequence of these operations.
  • Acoustic lens technology, beam forming technology, and acoustic holography technology are the main technologies of underwater acoustic imaging in the prior art, but relatively speaking, multi-wave velocity forming technology has the characteristics of high resolution and good imaging continuity for underwater targets. Acoustic imaging technology is more suitable for detection of underwater targets than the other two technologies.
  • the present invention is based on the beamforming technology of underwater acoustic imaging transmission. At the same time, there are still many key technologies for how to effectively achieve double-sided acoustic waves for comprehensive acquisition of underwater target information. There is no complete breakthrough, such as real-time, high efficiency, high resolution, effective acoustic scattering feature extraction and classification, which are also the focus of the current research field of underwater acoustic imaging.
  • the present invention provides a real-time two-dimensional imaging method and system for side-scan sonar.
  • a real-time two-dimensional imaging method for side-scan sonar including
  • a Extract the side-scan sonar reflection wave data unify the format and type of the extracted side-scan data, and obtain a side-scan data format that meets the requirements of two-dimensional imaging;
  • the denoising uses a method based on bilateral filtering.
  • the multi-scale Retinex image enhancement algorithm specifically includes:
  • Wavelet decomposition of the image to obtain high-frequency and low-frequency coefficients of the image
  • the multi-scale Retinex algorithm based on improved bilateral filtering is used to process the low-frequency coefficients of the image
  • the wavelet reconstruction is carried out through the discrete wavelet inverse transform formula to obtain the enhanced spatial image
  • the double-buffer technology After extracting the side-scan sonar reflected wave data, the double-buffer technology is used for data transmission. Specifically, the double-buffer technology opens up a data buffer space and sets two memory spaces, and one storage assumption for reading data is N1, another storage assumption for displaying data is N2;
  • Multi-thread technology is used to read and save.
  • N1 only saves the current latest read data frame, and N2 designs the interface according to the size of the display.
  • the step B also includes a time compensation mechanism, specifically: the currently read data frame, by setting a threshold to determine whether the bright or black dot coordinates are generated due to a mismatch in navigation, block and gray the same position of the new and old multi-frame data Solve the average value of degrees to compensate the gray value of the target.
  • a time compensation mechanism specifically: the currently read data frame, by setting a threshold to determine whether the bright or black dot coordinates are generated due to a mismatch in navigation, block and gray the same position of the new and old multi-frame data Solve the average value of degrees to compensate the gray value of the target.
  • front-end side-scan sonar sensor module Including front-end side-scan sonar sensor module, power supply module, transmission/reception control module and upper computer imaging display module connected in sequence;
  • the front-end side-scan sonar sensor module is used to transmit acoustic waves and receive acoustic echoes, and includes an acoustic sensor array, an acoustic emission/reception circuit, an A/D conversion circuit, and a data interface circuit;
  • the transmitting/receiving control module is used to configure the parameters and receiving data of the front-end side scanning sonar sensor module, including receiving circuit, operating system support circuit, data processing circuit, control circuit and data transmission circuit; the power supply module is the transmitting/receiving control module powered by.
  • the upper computer imaging display module is responsible for receiving data from the transmission/reception control module, and performing imaging display and human-computer interaction.
  • the present invention designs a reasonable data extraction format, taking into account subsequent imaging and other functions that may be added in the future, and strictly follows the principle of uniformity to unify and standardize the data format and type; considering the increasing amount of side scan data, data processing It will become cumbersome, set a fixed amount of data into blocks, and take blocks as a unit to simplify the data and facilitate subsequent imaging processing of the host computer;
  • the imaging display rules of the present invention that are easy to observe are based on the characteristics of side-scan sonar linear scanning.
  • the data format is line as a frame, and each frame is connected in a scrolling display mode to achieve dynamic real-time imaging; due to underwater acoustic wave transmission
  • the complexity of the side-scan sonar will carry a lot of noise when receiving the reflected echo.
  • the research uses the advantages of bilateral filtering to perform reasonable image denoising to achieve overall image denoising without losing the target edge information; considering the side scan echo
  • the intensity of the wave is weak, and the overall imaging image is dark.
  • the multi-scale Retinex image enhancement algorithm is used to enhance the image, which increases the brightness of the image and highlights the characteristics of the underwater target.
  • FIG. 1 is a working flowchart of the present invention
  • Figure 2 is a schematic structural view of the present invention
  • 3 is a basic principle diagram of the side-scan sonar of the present invention.
  • a real-time two-dimensional imaging system for side-scan sonar includes a front-end side-scan sonar sensor module, a transmission/reception control module, a power module, and an upper computer imaging display module connected in sequence;
  • the front-end side-scan sonar sensor module is used to transmit acoustic waves and receive acoustic echoes, and includes an acoustic sensor array, an acoustic emission/reception circuit, an A/D conversion circuit, and a data interface circuit;
  • the transmitting/receiving control module is used for configuring the parameters and receiving data of the front-end side scanning sonar sensor module, including receiving circuit, operating system support circuit, data processing circuit, control circuit and data transmission circuit;
  • the power supply module mainly provides stable power supply for the transmission/reception control module, with an output voltage of 9-12V and a current of 2A;
  • the upper computer imaging display module is responsible for receiving data from the transmitting/receiving control module, and performing imaging display and human-computer interaction, such as acoustic emission frequency, sampling number, etc.; each module uses electrical connection with each other.
  • the present invention performs underwater target imaging detection by line scanning.
  • the side-scan sonar sensor module emits sound waves at a certain frequency through the probe, and utilizes the characteristics of small attenuation and strong reflection of sound waves transmitted in water. Reflected acoustic echo; secondly, receive the echo data from the side scan sensor sonar module through the transmit/receive control module, and properly encode and decode the echo, extract and process the required data; finally, image on the host computer
  • the display module receives the data from the transmitting/receiving control module, performs appropriate data conversion and digital image processing, and realizes real-time display of two-dimensional imaging on the host computer system.
  • the pretreatment of underwater sonar mainly includes the enhancement of the contrast of the underwater target, the image smoothing filter to reduce the interference of noise in the image, the enhancement of the target edge contour and the improvement of the sharpness of the target image. It also includes the reading of sonar image data and the establishment of images, sonar image data analysis and image interpolation. In short, the purpose of preprocessing sonar images is to enhance sonar images.
  • the transmitting transducer of underwater acoustic imaging continuously emits an acoustic beam underwater.
  • the acoustic pulse After the acoustic pulse is sent out, it propagates far away in the form of a spherical wave and encounters The back reflected wave or backscattered wave of the object returns to the receiving transducer along the original route, forming a data line in the azimuth direction.
  • the transducer moves along with the platform, it performs transmission and reception operations at a certain time interval, and displays the received data according to distance, thus obtaining a two-dimensional underwater acoustic image.
  • Different objects have different sound reflection characteristics, and the intensity of the echo varies. Therefore, the gray feature in the image contains the attribute information of the target, and the purpose of target imaging can be achieved through image analysis.
  • Sonar images and optical images are essentially energy planes or spatial distribution maps, but sonar images and optical images are essentially different in imaging mechanism.
  • the imaging principle of the optical image is imaged by the photosensitive element by receiving light waves emitted or reflected by the target object.
  • the light wave is a one-way straight line propagation between the photosensitive element and the target object, and air is its propagation medium; while the imaging sonar emits sound waves by emitting transducers.
  • the sound waves When encountering the target object, the sound waves will be reflected and the reflected echoes will be reflected.
  • the echo signal amplitude transformation caused by the difference in the material and distance of the target object is used to generate a sonar image. It is a two-way distance imaging system that propagates between the transducer and the target.
  • the propagation medium has a relatively large impact on the image quality, such as the measurement of the underwater environment, water temperature, water depth, wind speed, noise interference, reverberation interference, unevenness within the ocean, irregularities of the seabed terrain and other uncertain factors All have seriously affected the sonar imaging effect.
  • the underwater noise sources are abundant and the environment is more complicated.
  • the noise sources include marine environmental noise and ship self-noise, etc., which causes the imaging sonar images to be generally polluted, relatively few target object gray levels, and gray levels Relatively rich background noise;
  • the receiving array in the imaging sonar instrument may have certain defects, such as the formation of resolution in only one direction and the unstable movement of the synthetic aperture sonar imaging array carrier, which results in a low resolution of the sonar image;
  • the received acoustic wave signal is weakened and is often incomplete, so that the sonar image does not have detailed, accurate and obvious boundary features like the optical image, and the target object often appears Incomplete, irregular and uncertain borders;
  • the sonar image's clarity is generally low, the detail component is relatively small, and the image is mainly composed of low frequency components;
  • Noise is generally randomly generated, so it has irregularities in size and distribution. Some noise and image information are unrelated and independent of each other, while some are related. Common image noises are multiplicative noise and additive noise. Multiplicative noise is often interwoven with the image, and additive noise often includes Gaussian noise and salt and pepper noise and other typical noises. Therefore, the noise in the sonar image must be filtered out to obtain more and finer original sonar image features.
  • the present invention provides a real-time two-dimensional imaging method of side-scan sonar, which includes the following steps:
  • a Extract the side-scan sonar reflection wave data unify the format and type of the extracted side-scan data, and obtain a side-scan data format that meets the requirements of two-dimensional imaging;
  • the present invention designs a reasonable data extraction format, taking into account the subsequent imaging and other functions that may be added in the future, and strictly follows the principle of uniformity to unify and standardize the data format and type; considering the increasing amount of side scan data, data processing will become Cumbersome, set a fixed amount of data into blocks, and use blocks as units to simplify data and facilitate subsequent imaging processing of the host computer.
  • the present invention adopts the double-buffer technology for data transmission.
  • the double-buffer technology is to open up data buffer space and set two memory spaces, one for reading data is assumed to be N1, and the other is for displaying data.
  • the preservation hypothesis is N2;
  • Multi-thread technology is used to read and save.
  • N1 only saves the current latest read data frame, and N2 designs the interface according to the size of the display.
  • the data format uses lines as one frame, and each frame is connected in a scrolling display mode to achieve dynamic real-time imaging.
  • It also includes a time compensation mechanism, specifically: the currently read data frame, by setting a threshold to determine whether the bright or dark point coordinates are generated due to a mismatch in navigation, block division of the new and old multi-frame data at the same position and the gray average solution To compensate for the gray value of the target.
  • a time compensation mechanism specifically: the currently read data frame, by setting a threshold to determine whether the bright or dark point coordinates are generated due to a mismatch in navigation, block division of the new and old multi-frame data at the same position and the gray average solution To compensate for the gray value of the target.
  • the histogram equalization method can improve the contrast of the side-scan image, but it cannot process the effective information in a targeted manner, it is easy to amplify the noise, and the image distortion is serious.
  • the Retinex algorithm can maintain the object color constancy, but in the case of uneven echo intensity, the image is prone to halo, resulting in blurred images.
  • Bilateral filtering method can better remove image noise caused by small floating objects and bubbles in the water, but at the same time, it will lose a lot of details in the image and is not conducive to feature extraction.
  • the present invention proposes to use a side-scan sonar image enhancement method based on the combination of bilateral filtering and multi-scale Retinex algorithm on the basis of wavelet transform, which overcomes the Retinex algorithm easy to produce halos And the bilateral filtering method is easy to cause the loss of details and other shortcomings.
  • the edge details of the side-scan sonar image are clear, the image contrast is strong and it is easy to identify.
  • the specific steps of the image enhancement method based on bilateral filtering and multi-scale Retinex algorithm are as follows:
  • Multi-scale Retinex algorithm based on bilateral filtering is used to process the low-frequency coefficients of the image.
  • Wavelet transform is an effective tool for time-frequency processing of signals.
  • the image is wavelet decomposed to obtain the low-frequency coefficient of the image and the high-frequency coefficient of different scales.
  • the low-frequency coefficients contain the outline information of the image
  • the high-frequency coefficients contain the information of edges, details and noise in different dimensions of the image.
  • the two-dimensional discrete wavelet decomposition formula is as follows:
  • Is the low-frequency coefficient j 0 is the initial number of layers, m and n are the offset from the (x, y) point; x and y are the spatial coordinates; f (x, y) is the gray value of the image pixel; M and N means that the image consists of M ⁇ N pixels; Is a two-dimensional scaling function; i is the superscript of the assumed values H, V and D, representing the column direction, row direction, diagonal direction; j is the number of wavelet decomposition layers; Is the high frequency coefficient; Wavelet function corresponding to the direction.
  • the image is formed by the incident image L(x,y) and the reflected image R(x,y), the incident light illuminates the reflective object, and the reflected light is reflected to the human eye, and the human eye sees the image S(x,
  • the expression of y) is
  • the Retinex algorithm has made many research achievements, from the single-scale Retinex algorithm to the multi-scale weighted average Retinex algorithm (Multi-scale Retinex, MSR), and then to the color restoration multi-scale Retinex algorithm (Multi-scale Retinex with Color Restoration, MSRCR).
  • MSR multi-scale weighted average Retinex
  • MSRCR Color restoration multi-scale Retinex algorithm
  • the MSR algorithm is developed from the SSR algorithm, which can maintain high fidelity of the image and compress the dynamic range.
  • the MSR algorithm is prone to problems such as halo and over-enhancement, and the use of bilateral filtering as the center surround function can effectively improve this situation, and bilateral filtering has good edge retention characteristics, which can enhance image details.
  • Bilateral filtering is widely used. It also considers the difference in pixel spatial intensity, has good edge retention characteristics, and its weight coefficient expression is
  • (x c , y c ) is the position of the center point of the image
  • f(x c , y c ) is the gray value of the pixel at the center point of the image
  • ⁇ s is the standard deviation of the Gaussian function in the spatial domain
  • ⁇ r is the Gaussian function in the range Standard deviation.
  • K is the number of weights
  • ⁇ i is the weight corresponding to the ith scale
  • G i (x, y) is the center surround function using the bilateral filtering algorithm. Carry out the anti-logarithmic transformation of equation (7) to obtain the reflected image R(x, y).
  • Wavelet high-frequency coefficients contain information such as image noise, edges and details. By threshold filtering high-frequency coefficients, noise can be effectively removed.
  • Common threshold filtering methods include hard threshold filtering, soft threshold filtering and half-threshold filtering methods.
  • the hard threshold filtering method maintains the best for edge details, but it is easy to ring, causing visual distortion;
  • the soft threshold filtering method keeps the details relatively smooth, which can improve the distortion phenomenon;
  • the semi-threshold filtering method works best in the detail smoothing, but needs to be determined 2 Thresholds, which requires a large amount of calculation.
  • contrast enhancement is required for the side-scan image.
  • Common processing methods include histogram equalization and local contrast enhancement.
  • the present invention uses a method for automatically adjusting the image contrast according to the change of the local variance.
  • the adaptive contrast adjustment formula is as follows:
  • g(x, y) is the output image intensity
  • k is the number of gain coefficients
  • b(x, y) is the local mean
  • ⁇ is the gain coefficient
  • ⁇ 2 (x) is the local variance.

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • Computer Networks & Wireless Communication (AREA)
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Abstract

一种侧扫声呐实时二维成像方法及系统，包括以线扫描的方式进行水下目标成像检测，前端侧扫声呐传感器模块通过探头以一定的频率发射声波，利用声波在水中传输的衰减小及反射强特性，遇到水底或水下目标会产生反射声回波；其次，通过发射/接收控制模块接收来自侧扫传感器声呐模块的回波数据，且对回波进行适当的编码及解码，提取并处理得到需求的数据；最后，在上位机成像显示模块接收来自发射/接收控制模块的数据进行合适的数据转换及数字图像处理，实现在上位机系统的二维成像实时显示。

Description

一种侧扫声呐实时二维成像方法及系统 技术领域
本发明涉及水下成像，具体涉及一种侧扫声呐实时二维成像方法及系统。
背景技术
水下声成像是声成像的一个分支，在水声探测中有着重要的作用，通过物体对声波的后向散射作用进行水下定位，逐点画图成像。利用声波进行成像，是在声波测距与测向的基础上发展而来的。水下声波测距主要是利用接收回波与发射脉冲信号间的时间差，计算出目标的距离；水下声波测向主要是利用回波到达由多个换能器组成的水听器系统的声程差和相位差，计算出目标的方位。在水下声成像中，基本的声成像技术有三种：声透镜技术、波束形成技术、声全息技术。这三种声成像方法都使用相同的操作：空间处理(从声场中得到图像)、换能(将声能转换成电能)、检波(将高频信号转换成可观测且接近直流的图像信号)、显示(以某种形式显示为图像)。这三种方法的不同之处在于对这些操作进行的先后顺序的不同。
现有技术中采用声透镜技术、波束形成技术、声全息技术是水下声成像主要技术，但相对来说，多波速形成技术以对水下目标高分辨率、成像连续性好的特点，该声成像技术比其他两个技术更适合针对水下目标检测，本发明就是基于波束形成技术的水下声成像发射方式，同时如何有效实现水下目标信息综合获取的双侧声波还存在诸多关键技术没有完全突破，例如实时性、高效、高分辨、有效声散射特征提取及分类等方面，这些也是现在水声成像研究领域重点。因此，研究一种侧扫声呐实时二维成像系统及方法，对加快侧扫声呐系统和侧扫成像方法革命，在水下声学实时成像关键器件与成像算法首先取得突破，形成持续性的自主创新能力和研发积累效应，是从深度和广度两个角度引领产业发展的要义。
发明内容
为了克服现有技术存在的问题，本发明提供一种侧扫声呐实时二维成像方法及系统。
本发明采用如下技术方案：
一种侧扫声呐实时二维成像方法，包括
A提取侧扫声呐反射波数据，将提取的侧扫数据格式及类型进行统一，得到符合二维成像要求的侧扫数据格式；
B将符合侧扫数据格式的反射波数据，以线为一帧，转化为标准化图像；
C对标准化图像进行图像增强及去噪，得到二维成像。
所述去噪采用基于双边滤波的方法。
利用多尺度Retinex图像增强算法进行图像增强。
所述多尺度Retinex图像增强算法，具体为：
将图像进行小波分解，获得图像高频和低频系数；
采用基于双边滤波改进的多尺度Retinex算法对图像低频系数进行处理；
采用软阈值滤波算法对图像高频部分进行处理；
通过离散小波反变换公式进行小波重构，得到增强后的空域图像；
对增强后的空域图像进行局部自适应对比度增强处理。
所述提取侧扫声呐反射波数据后，采用双缓存技术进行数据传输，所述双缓存技术具体是，开辟数据缓存空间，并设定两块内存空间，一块用于读取数据的保存假设为N1，另一块用于显示数据的保存假设为N2；
多线程技术进行读取与保存，N1只保存当前最新读取的数据帧，N2根据显示设计界面的大小。
所述步骤B还包括时间补偿机制，具体为：当前读取的数据帧，通过设置阈值判断是否由于航行不匹配产生亮点或者黑点坐标，对新老多帧数据同一位置进行块分割并进行灰度平均值求解，以补偿目标的灰度值。
一种侧扫声呐实时二维成像的系统，
包括依次连接的前端侧扫声呐传感器模块、电源模块、发射/接收控制模块及上位机成像显示模块；
所述前端侧扫声呐传感器模块用于发射声波和接收声回波，包括声传感器阵列、声发射/接收电路、A/D转换电路及数据接口电路；
所述发射/接收控制模块用于配置前端侧扫声呐传感器模块的参数及接收数据，包括接收电路、操作系统支持电路、数据处理电路、控制电路及数据传输电路；电源模块为发射/接收控制模块供电。
所述上位机成像显示模块负责接收来自发射/接收控制模块的数据，并进行成像显示及人机交互。
本发明的有益效果：
(1)利用双缓存技术搭建数据传输桥梁，合理有效将提取数据放入缓存空间，达到即拿即用的效果；考虑到数据发射与反射回波存在不确定性的时间差，设计合理的数据提取频率及补偿机制，避免数据遗漏；
(2)本发明设计合理的数据提取格式，考虑到后续成像以及未来可能增加其他功能，严格按照统一性原则，将数据格式及类型统一化、标准化；考虑到侧扫数据量不断增加，数据处理将变得繁琐，设置将一定量的数据固定成块，以块为单元，实现数据简单化，便于后续上位机成像处理；
(3)本发明便于观察的成像显示规则，基于侧扫声呐线性扫描的特点，数据格式以线为一帧，设滚动显示的方式将每帧相接以实现动态实时成像；由于水下声波传输的复杂性，侧扫声呐接收反射回波时会携带大量的噪声，研究利用基于双边滤波的优势进行合理的图像去噪，实现图像整体去噪，且不失去目标边缘信息；考虑到侧扫回波的强度较弱，整体成像图像偏暗，利用多尺度Retinex图像增强算法进行图像增强，增加图像亮度的同时，突出水下目标的特征。
附图说明
图1是本发明的工作流程图；
图2是本发明的结构示意图；
图3是本发明的侧扫声呐基本原理图；
图4是本发明的图像增强流程图。
具体实施方式
下面结合实施例及附图，对本发明作进一步地详细说明，但本发明的实施方式不限于此。
实施例
如图1及图2所示，一种侧扫声呐实时二维成像的系统，包括依次连接的前端侧扫声呐传感器模块、发射/接收控制模块、电源模块及上位机成像显示模块；
所述前端侧扫声呐传感器模块用于发射声波和接收声回波，包括声传感器阵列、声发射/接收电路、A/D转换电路及数据接口电路；
所述发射/接收控制模块用于配置前端侧扫声呐传感器模块的参数及接收数据，包括接收电路、操作系统支持电路、数据处理电路、控制电路及数据传输电路；
所述电源模块，主要为发射/接收控制模块进行稳定供电，输出电压为9-12V，电流为2A；
所述上位机成像显示模块负责接收来自发射/接收控制模块的数据，并进行成像显示及人机交互，如声发射频率、采样数等；各模块相互之间使用电气连接。
本发明以线扫描的方式进行水下目标成像检测，侧扫声呐传感器模块通过探头以一定的频率发射声波，利用声波在水中传输的衰减小及反射强特性，遇到水底或水下目标会产生反射声回波；其次，通过发射/接收控制模块接收来自侧扫传感器声呐模块的回波数据，且对回波进行适当的编码及解码，提取并处理得到需求的数据；最后，在上位机成像显示模块接收来自发射/接收控制模块的数据进行合适的数据转换及数字图像处理，实现在上位机系统的二维成像实时显示。
由于水下环境和水声信道复杂多变，以及声波在传播过程中存在衰减、混响、散射、多径现象和旁瓣干扰等，生成的声纳图像干扰严重、分辨率低等。水下声呐的预处理主要包括水下目标对比度的增强、减少图像中噪声的干扰的图像平滑滤波、增强目标边缘轮廓和改善目标图像清晰度图像锐化。另外还包括声呐图像数据的读取与图像的建立、声呐图像的数据分析和图像的插值等。总之，对声呐图像进行预处理的目的就在于对声呐图像进行增强。
如图3侧扫声呐结构示意图所示，水声成像的发射换能器在发射机脉冲的激励下，连续向水下发射声波束，声脉冲发出之后，以球面波方式向远方传播，碰到物体后反射波或反向散射波沿原路线返回到接收换能器，形成方位向的一条数据线。换能器随平台一边运动一边按一定时间间隔进行发射接收操作，并将接收数据按距离显示，就得到了二维水声图像。不同的物体声反射特性不同，回波的强度就大小不一，所以图像中的灰度特征包含了目标的属性信息，通过图像分析可实现目标成像的目的。
声呐图像与光学图像在本质上都是能量平面或者空间分布图，但声呐图像与光学图像在成像机制上有着本质的区别。尽管人工智能学科已经发展比较成熟，但是很多可以用于光学图像处理的技术对声纳图像就不一定可行，特别是有一些前沿的图像处理技术没有在声呐图像处理中得到应用，因此是需要迫切 地对声呐图像处理进行研究的。光学图像的成像原理是由感光元件通过接收目标物体发射或反射的光波而成像的。光波为感光元件和目标物体之间的单程直线传播，空气是其传播介质；而成像声呐则是通过发射换能器来发射声波，当遇到目标物体后，声波会发生反射，反射回波被接收换能器接收后，再利用目标物体材质、距离等不同所引起的回波信号幅度变换来生成声呐图像，是一种在换能器和目标之间双程传播的距离成像系统，其中，传播的介质对图像质量的影响相对较大，比如测量现场的水下环境、水温、水深、风速、噪声干扰、混响干扰、海洋内部的不均匀性、海底地形的不规则性等不确定因素都严重影响了声纳成像效果。
因此，可以总结出声呐图像的主要特征表现为：
(1)水下的噪声源丰富及环境比较复杂，噪声源有海洋环境噪声、舰船自噪声等，从而造成成像声呐图像普遍污染严重，相对较少的目标物体灰度级，和灰度级相对较为丰富背景噪声；
(2)由于成像声呐仪器中接收基阵可能存在着一定的缺陷，例如仅在一个方向上形成分辨率及合成孔径声纳成像基阵载体运动不稳定等，致使得到的声呐图像分辨率低；
(3)由于声波的散射造成声呐图像中存在很多与周围像素灰度值有较大偏差的异常点；
(4)由于复杂的声波传播介质，使得接收到的声波信号被弱化，很多时候都不够完整，以至于声呐图像没有像光学图像那样拥有细致、精确、明显的边界特征，并且目标物体还经常出现边界残缺不全、不规则、不确定等特点；
(5)声呐图像清晰度一般较低，细节分量相对较少，图像主要以低频分量为主；
(6)有些声纳图像目标存在阴影，而有些声纳图像目标则没有阴影，同样使得目标的检测识别难度加大。
由于声纳图像的这些特性，使得对声纳图像的处理方法没有完全可靠的模型方法来进行指导和完善，因此，这些因素在一定程度上阻碍了某些分析、处理和识别技术在声呐领域中的应用和发展。
通过以上声纳图像特征的分析可知，相对于光学图像而言，声呐图像由于水下复杂的环境，使得成像声呐接受到的原始声呐图像数据质量急剧降低，噪声污染普遍严重。因此，对声呐图像的去噪技术进行研究对后序的声呐图像分割与识别都是至关重要的。
噪声一般都是随机产生的，因此都具有大小和分布的不规则性，有些噪声和图像信息互不相关、互相独立，而有些则是相关的。常见的图像噪声有乘性噪声和加性噪声，乘性噪声往往和图像交织在一起，而加性噪声往往又包括高斯噪声和椒盐噪声等典型噪声。因此，必须将声呐图像中的噪声滤除掉，得到更多更精细的原始声纳图像特征。
针对现有技术的情况，本发明提供一种侧扫声呐实时二维成像方法，包括如下步骤：
A提取侧扫声呐反射波数据，将提取的侧扫数据格式及类型进行统一，得到符合二维成像要求的侧扫数据格式；
本发明设计合理的数据提取格式，考虑到后续成像以及未来可能增加其他功能，严格按照统一性原则，将数据格式及类型统一化、标准化；考虑到侧扫数据量不断增加，数据处理将变得繁琐，设置将一定量的数据固定成块，以块为单元，实现数据简单化，便于后续上位机成像处理。
本发明采用双缓存技术进行数据传输，所述双缓存技术具体是，开辟数据缓存空间，并设定两块内存空间，一块用于读取数据的保存假设为N1，另一块用于显示数据的保存假设为N2；
多线程技术进行读取与保存，N1只保存当前最新读取的数据帧，N2根据显示设计界面的大小。
B将符合侧扫数据格式的反射波数据，以线为一帧，转化为标准化图像；
基于侧扫声呐线性扫描的特点，数据格式以线为一帧，设滚动显示的方式将每帧相接以实现动态实时成像。
还包括时间补偿机制，具体为：当前读取的数据帧，通过设置阈值判断是否由于航行不匹配产生亮点或者黑点坐标，对新老多帧数据同一位置进行块分割并进行灰度平均值求解，以补偿目标的灰度值。
C对标准化图像进行图像增强及去噪，得到二维成像。
现有的侧扫声呐图像增强方法主要有3种：一是直方图均衡化方法，直接增强图像对比度；二是基于人体视觉的Retinex算法；三是高斯滤波、双边滤波方法，该方法可以对图像进行滤波去噪。直方图均衡化方法可以提升侧扫图像对比度，但其对有效信息无法做到有针对性的处理，容易放大噪声，使图像失真严重。Retinex算法可以保持物体颜色恒常性，但在回波强度不均匀情况下图像容易出现光晕，导致图像模糊。双边滤波方法可以较好地去除水中细小漂浮物、气泡等导致的图像噪声，但同时会使图像丢失大量细节，不利于特征 提取。
针对上述方法存在的缺点，图4所示，本发明在小波变换基础上，提出利用一种基于双边滤波和多尺度Retinex算法相结合的侧扫声呐图像增强方法，克服了Retinex算法易产生光晕及双边滤波方法易造成细节丢失等缺点，实现侧扫声呐图像边缘细节清晰，图像对比度强且易于辨识。基于双边滤波和多尺度Retinex算法的图像增强方法具体步骤如下：
(1)将图像进行小波分解，获得图像高频和低频系数。
(2)采用基于双边滤波改进的多尺度Retinex算法对图像低频系数进行处理。
(3)采用软阈值滤波算法对图像高频部分进行处理。
(4)通过离散小波反变换公式进行小波重构，得到增强后的空域图像。
(5)对增强后的空域图像进行局部自适应对比度增强处理。
图像增强方法的具体流程如图3所示。
小波变换是对信号进行时频处理的有效工具。依据二维离散小波分解公式对图像进行小波分解，得到图像低频系数和不同尺度的高频系数。低频系数包含图像的轮廓信息，高频系数包含图像不同维度边缘、细节及噪声等信息。
二维离散小波分解公式如下：
Figure PCTCN2019112055-appb-000001
Figure PCTCN2019112055-appb-000002
i＝{H,V,D}
小波重构公式：
Figure PCTCN2019112055-appb-000003
式中：
Figure PCTCN2019112055-appb-000004
为低频系数，j 0为初始层数，m与n为相对(x,y)点的偏移量；x和y为空间坐标；f(x,y)为图像像素的灰度值；M与N表示图像由M×N个像素组成；
Figure PCTCN2019112055-appb-000005
为二维尺度函数；i为假定值H,V和D的上标，代表列方向、行方向、对角线方向；j为小波分解层数；
Figure PCTCN2019112055-appb-000006
为高频系数；
Figure PCTCN2019112055-appb-000007
为对应方向的小波函数。
根据Retinex理论可知，图像由入射图像L(x,y)和反射图像R(x,y) 形成，入射光照到反射物体上，形成反射光反射到人眼，人眼看到的图像S(x,y)的表达式为
S(x,y)＝R(x,y)L(x,y)            (4)
近年来，Retinex算法有了很多研究成果，从单尺度Retinex算法改进成多尺度加权平均的Retinex算法(Multi-scale Retinex，MSR)，再发展成彩色恢复多尺度Retinex算法(Multi-scale Retinex with Color Restoration，MSRCR)。MSR算法是从SSR算法发展而来的，可以保持图像高保真度，压缩动态范围。但采用MSR算法容易出现光晕、过增强等问题，而使用双边滤波作为中心环绕函数可有效改善这种情况，并且双边滤波有良好的边缘保持特性，可增强图像细节。
双边滤波应用十分广泛，它同时考虑了像素空间强度的差异，具有良好的边缘保持特性，其权重系数表达式为
Figure PCTCN2019112055-appb-000008
式中：(x c,y c)为图像中心点位置；f(x c,y c)为图像中心点像素灰度值；σ s为空域高斯函数的标准差；σ r为值域高斯函数的标准差。
使用双边滤波代替高斯滤波作为MSR算法中心环绕函数，可以保持图像边缘特性，消除光晕现象。基于双边滤波理论的多尺度Retinex算法公式为
r(x,y)＝log 2R(x,y)＝log 2S(x,y)-log 2L(x,y)       (6)
Figure PCTCN2019112055-appb-000009
式中：K为权重的个数；ω i为对应第i个尺度的权重；G i(x,y)为采用双边滤波算法的中心环绕函数。对式(7)进行反对数变换，得到反射图像R(x,y)。
小波高频系数包含了图像噪声、边缘及细节等信息，通过对高频系数进行阈值滤波，可有效去除噪声。
常见的阈值滤波方法有硬阈值滤波、软阈值滤波和半阈值滤波方法。硬阈值滤波方法对边缘细节保持最好，但容易振铃，引起视觉失真；软阈值滤波方法细节保持相对平滑，可改善失真现象；半阈值滤波方法在细节平滑处效果最好，但需确定2个阈值，计算量较大。综合考虑，采用软阈值滤波方法，其表达式如下：
Figure PCTCN2019112055-appb-000010
由于侧扫声呐回波强度大量不均匀，所以要对侧扫图像进行对比度增强处理。常见的处理方法有直方图均衡化、局部对比度增强等。但用传统方法进行对比度调整时局部处理效果一般，故本发明利用一种根据局部方差变化自动调整图像对比度的方法。自适应对比度调整公式如下：
Figure PCTCN2019112055-appb-000011
式中：g(x,y)为输出图像强度；k为增益系数的个数；b(x,y)为局部均值；η为增益系数；σ 2(x)为局部方差。
上述实施例为本发明较佳的实施方式，但本发明的实施方式并不受所述实施例的限制，其他的任何未背离本发明的精神实质与原理下所作的改变、修饰、替代、组合、简化，均应为等效的置换方式，都包含在本发明的保护范围之内。

Claims (8)

  1. 一种侧扫声呐实时二维成像方法，其特征在于，包括
    A提取侧扫声呐反射波数据，将提取的侧扫数据格式及类型进行统一，得到符合二维成像要求的侧扫数据格式；
    B将符合侧扫数据格式的反射波数据，以线为一帧，转化为标准化图像；
    C对标准化图像进行图像增强及去噪，得到二维成像。
  2. 根据权利要求1所述的一种侧扫声呐实时二维成像方法，其特征在于，所述去噪采用基于双边滤波的方法。
  3. 根据权利要求1所述的一种侧扫声呐实时二维成像方法，其特征在于，利用多尺度Retinex图像增强算法进行图像增强。
  4. 根据权利要求3所述的一种侧扫声呐实时二维成像方法，其特征在于，所述多尺度Retinex图像增强算法，具体为：
    将图像进行小波分解，获得图像高频和低频系数；
    采用基于双边滤波改进的多尺度Retinex算法对图像低频系数进行处理；
    采用软阈值滤波算法对图像高频部分进行处理；
    通过离散小波反变换公式进行小波重构，得到增强后的空域图像；
    对增强后的空域图像进行局部自适应对比度增强处理。
  5. 根据权利要求1所述的一种侧扫声呐实时二维成像方法，其特征在于，所述提取侧扫声呐反射波数据后，采用双缓存技术进行数据传输，所述双缓存技术具体是，开辟数据缓存空间，并设定两块内存空间，一块用于读取数据的保存假设为N1，另一块用于显示数据的保存假设为N2；
    多线程技术进行读取与保存，N1只保存当前最新读取的数据帧，N2根据显示设计界面的大小。
  6. 根据权利要求1所述的一种侧扫声呐实时二维成像方法，其特征在于，所述步骤B还包括时间补偿机制，具体为：当前读取的数据帧，通过设置阈值判断是否由于航行不匹配产生亮点或者黑点坐标，对新老多帧数据同一位置进行块分割并进行灰度平均值求解，以补偿目标的灰度值。
  7. 一种实现权利要求1-5任一项所述的一种侧扫声呐实时二维成像方法的系统，其特征在于，
    包括依次连接的前端侧扫声呐传感器模块、发射/接收控制模块及上位机成像显示模块；
    所述前端侧扫声呐传感器模块用于发射声波和接收声回波，包括声传感器阵列、声发射/接收电路、A/D转换电路及数据接口电路；
    所述发射/接收控制模块用于配置前端侧扫声呐传感器模块的参数及接收数据，包括接收电路、操作系统支持电路、数据处理电路、控制电路及数据传输电路；
    所述上位机成像显示模块负责接收来自发射/接收控制模块的数据，并进行成像显示及人机交互。
  8. 根据权利要求7所述的系统，其特征在于，还包括电源模块。
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